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What could measuring the N400 response to stimuli of inconsistent stereotypes tell us?

What could measuring the N400 response to stimuli of inconsistent stereotypes tell us?


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I'm working on a project proposal for a class on intergroup relations and thought this might be interesting to observe. Participants would be shown consistent stereotypical video clips (e.g. Asian's doing rubics cubes, white girl ordering a psl, etc.), neutral video clips (kid going to school????) and inconsistent (female car mechanic, male nurse). We would then observe the N400 component and recall accuracy after maybe a 48 hour time period.

I am hoping this would give more insight into how well people can retain inconsistent schemas, what the cognitive load of making sense of inconsistent schemas are in relation to other variable types of N400 stimulation (such as language), and how this impacts memory.

I would really appreciate feedback on the design. I honestly really like the idea and I haven't seen anything like it. If you have seen a similar study, or want to point out errors in the experimental design that would be great! Also, comment on study implications you can think of.

If you think it's just altogether a terrible idea, I will not be offended either! That is what scientific communities are for after all.


What could measuring the N400 response to stimuli of inconsistent stereotypes tell us? - Psychology

There is a claim that people can be implicitly (unconsciously) prejudiced. Critically evaluate the evidence for this claim.

Prejudice is a generally negative attitude toward an outgroup (Brendl et al., 2001). It is an unconscious attitude and can develop either through direct experience or by social learning (Dovidio et al., 2001). It influences feelings, thoughts or actions towards social objects by automatically activating evaluations based on past experience that are not consciously remembered (Greenwald & Banaji 1995, p.8). Dovidio et al. (2001) propose four main approaches to the study of implicit prejudice: the aversive racism framework (Gaertner & Dovidio, 1986) the MODE model (Fazio, 1990) the symbolic racism framework (Sears et al., 1997) and the dual attitudes framework (Wilson et al., 2000). Various measures of implicit prejudice have been employed, including response latency, linguistic bias and physiological responses. There have been some criticisms of the existing research but, according to Dovidio et al., ‘compelling evidence has accumulated on the existence of implicit attitudes and beliefs’ (2001, p.192).

The earliest approach to the study of implicit attitudes was the aversive racism framework, proposed by Gaertner and Dovidio (1986, cited in Dovidio et al., 2001). This framework identifies three ‘cells’ of people: 1) non-prejudiced 2) traditional racists 3) aversive racists (Dovidio et al., 2001). It is proposed that most people wish and believe themselves to possess egalitarian attitudes but are nevertheless unconsciously negatively biased against socially disadvantaged groups.

Fazio’s MODE (Motivation and Opportunity as DEterminants of processing) model suggests that behaviour is context dependent (1990, cited in Fazio, 1995). Where there is the opportunity (e.g. time) and the motivation (e.g. social norms) to consider a response, behaviour will be influenced more by explicit than by implicit attitudes. Where there is limited or no opportunity to reflect on behaviour, or little or no motivation to deliberate, behaviour will be spontaneous and, therefore, be determined to a greater extent by implicit attitudes (Dovidio et al., 2001). In keeping with this framework, Dovidio et al. (1997) suggest that the relationship between attitudes and behaviour is dependent on the method of measurement and the type of behaviour. They identify three levels of racial attitude: public (explicit), personal (explicit) and unconscious (implicit) (Dovidio et al., 2001). Dovidio et al. (1997) propose that behaviour will be predicted by public attitudes when social desirability is a factor, personal attitudes when behaviour is private but controlled, and unconscious attitudes when the behaviour is spontaneous.

The symbolic racism framework, suggested by Sears et al. (1997) proposes that prejudice is acquired when young and retained throughout adulthood. With certain primes, prejudice can be activated and expressed in subtle ways while, explicitly, people conform to egalitarian social norms, reflecting moral codes about how they believe they should behave (Sears et al., 1997).

Wilson et al. suggest that people can hold dual attitudes, defined as ‘different evaluations of the same attitude object’ (2000, p.101). Attitudes developed in childhood become implicit when they are overridden (but not overwritten) by new attitudes that are developed later. These implicit attitudes are automatically activated and so have most influence over unconscious behaviours (e.g. body language), or behaviour that a person does not recognise needs to be controlled (Dovidio et al., 2001).

There is much evidence to support the idea that judgements can be implicitly influenced. For example, Dovidio et al. (1986, cited in Dovidio et al., 2001) found evidence for automatic stereotyping using a response-latency task. Participants were presented with either the word ‘white’ or ‘black’ and then given a second word judged to be either a positive or negative stereotypical attribute of the black and white ethnic groups. Participants were asked if the attribute could ever be true or was never true of the group. Reaction times were found to be faster for attributes judged to be stereotypical of that group.

Devine (1989) presented half of her participants with 80 words stereotypically associated with black people and 20 unconnected words. The remaining participants were presented with the reverse. Participants were then shown a fictitious character and asked to rate its various actions. It was found that the participants who had been shown more words stereotyping black people rated the character as being more aggressive. Devine (1989) suggested that activating the stereotype caused participants to project stereotypical attributes of black people onto the character. However, Devine’s (1989) findings have been criticised. For example, many of the participants may have imagined the fictitious character to be white and, therefore, it is possible that the words primed hostility directly, rather than a stereotype of black people, as intended (Greenwald & Banaji, 1995). Many of the words presumed to be stereotypical of black people were generally negative and could have activated aggression directly (Greenwald & Banaji, 1995 Hamilton & Sherman, 1994 cited in Dovidio et al., 2001 and Lepore & Brown, 1997).

Furthermore, the presence of stereotyping does not necessarily indicate prejudice. For example, Devine (1989) distinguished between knowledge of a stereotype and endorsement of a stereotype, with the level of endorsement indicating prejudice. However, in the experiment by Dovidio et al. (1986, cited in Dovidio et al., 2001), it was observed that reaction times were faster for positive attributes paired with ‘white’ than those paired with ‘black’, and for negative attributes paired with ‘black’ than those paired with ‘white’. This finding is confirmed by the study of Greenwald et al. (1998: Experiment 3), where participants were asked to classify black versus white names and pleasant versus unpleasant words. They found that participants responded faster for white-positive pairings than for black-positive pairings. Similarly, negative implicit attitudes of white people towards black people were observed in studies by Ottaway et al. (2001, cited in Dovidio et al., 2001) and Rudman et al., (1999 cited in Dovidio et al., 2001).

Perdue et al. (1990, cited in Dovidio et al., 2001) found that there was automatic bias for one’s ingroup. In this study, participants were subliminally primed with pronouns (e.g. we, us, them) and then presented with a target word that they had to judge as being positive or negative. Reaction times were faster for positive words after ingroup priming (e.g. we, us) than outgroup priming (e.g. them), indicating that participants associated positive words more strongly with their ingroup than with outgroups. Maass et al. (1989, cited in Dovidio et al., 2001) measured linguistic intergroup bias and found that undesirable actions by outgroup members were encoded at a more abstract level than those by ingroup members i.e., a general judgement was made about outgroup members’ characters based on the actions in question. However, desirable actions were encoded at a more concrete level for outgroup relative to ingroup members: i.e., the behaviour was held to be situation specific. This allows inconsistent stereotyping behaviours by outgroup members to be disregarded, protecting more general beliefs held about the outgroup (Dovidio et al., 2001).

Lepore and Brown (1997) state that it is important to distinguish between categories (e.g. ethnic-group labels) and stereotypes (e.g. character traits) when using primes. The level of participants’ prejudice will not affect results when traits are used as primes, as these traits have the effect of priming negative stereotype knowledge, irrespective of attitude. Wittenbrink et al. (1997) found that the level of prejudice does have an effect when ethnic groups are used as primes. They found that negative words were more highly associated with a black person and positive words with a white person and that the effect correlated with the level of participants’ prejudice, as measured by explicit racial-attitude scores. Non-prejudiced people cannot control the automatic activation of stereotyped knowledge, but they will consciously suppress it.

Brendl et al. (2001) found that non-words were judged in a similar way to negative items and suggest that longer response times may be the result of non-familiarity. They reflect the relative ease of retrieving pre-stored evaluations for familiar versus less familiar stimuli. Dasgupta et al. (2000) tested this hypothesis with reference to the relative familiarity of white stereotypes in a white-dominant society (e.g. America). Their findings showed that positive attributes were still more strongly associated with white than black Americans when statistically controlling for differences in the familiarity of stimuli. Ashburn-Nardo et al. (2001) found ingroup bias in their experiments, even though participants had no experience of the ingroup and/or outgroup. They suggest that this bias may reflect ingroup favouritism rather than prejudice against outgroups.

Many studies have investigated the relationship between implicit and explicit prejudice, but there is no clear understanding of what the relationship is (Blair, 2001, cited in Dovidio et al., 2001). Banaji and Greenwald (1995) investigated gender bias in judgements of fame by asking participants to rate the fame of male and female names. They found a bias toward male names, with a lower criteria required in judging familiar male names than required in judging female names.

A meta-analysis by Dovidio et al. (2001) reviewed 27 studies that looked at racial attitudes and found that there was a significant, but weak, correlation between implicit and explicit attitudes across 14 tests using priming measures, three tests using other latency measures (e.g. time spent looking at pictures) and four tests using physiological measures. The correlation was stronger for topics that were not socially sensitive than for those that were. For example, Fazio et al. (1990, cited in Dovidio et al., 2001) found a high correlation for topics such as dentists, but a weak correlation for topics such as pornography. Stacy (1997, cited in Dovidio et al., 2001) found that implicit attitudes predicted marijuana use while explicit attitudes did not, while they both predicted alcohol use, which is less socially stigmatised (Dovidio et al., 2001).

Dovidio et al. found that implicit measures predicted spontaneous but not deliberate behaviours (1997: Experiment 2). They asked participants to interact face-to-face with both black and white partners and to then rate both partners on rating scales. Participants’ rates of blinking and their eye contact with the partners were also measured. It was found that deliberate behaviours (i.e. the ratings) were correlated with explicit measures of self-reported prejudice but not with implicit measures. However, implicit measures predicted participants’ non-verbal behaviour (i.e. blinking and eye contact) negative attitudes predicted more blinking and less eye contact (1997: Experiment 3). Furthermore, a study by Fazio et al. (1995) looking into the Rodney King verdict and perceptions of the black community’s resultant anger showed that explicit measures (i.e. direct ratings of the verdict and the reaction) were correlated with self-reported prejudice. The implicit measures did not correlate with these ratings however they correlated more highly than the explicit measures when participants were asked to rate the relative responsibilities of the white and black communities for the post-verdict reaction. Crosby et al. (1980, cited in Dovidio et al., 1997) suggest that unconscious, nonverbal behaviours may be less subject to social desirability than verbal behaviours. Fazio et al. (1995) suggested that non-verbal behaviours are liable to ‘leakage’ i.e. they occur in spite of conscious efforts to appear non-prejudiced.

One proposed explanation for the weak and variable relationships between implicit and explicit measures is poor reliability of the implicit measures (Kawakami & Dovidio, 2001). However there are many other theories. For example, it may have more to do with the nature of what is being measured (Dovidio et al., 2001). Specifically implicit measures usually require global evaluations (i.e. positive versus negative), while explicit measures can be more complex (e.g. McConahay’s Modern Racism Scale, 1986, cited in Dovidio et al., 2001). Dovidio et al.’s meta-analysis (2001) found a higher relationship between implicit and explicit prejudice for the nine tests requiring general evaluations than for the 18 using more issue-oriented measures.

There is also a theory that implicit and explicit attitudes use different processes and, therefore, would not be expected to show a high correlation (Dovidio et al., 2001 Karpinski & Hilton, 2001). The automatic activation of an evaluation does not necessarily mean that the evaluation will be used (Fiske, 1989 and Gilbert & Hixton 1991, both cited in Dovidio et al., 2001). It has been suggested that response latency tasks measure the time taken to activate evaluations, while self-report tasks measure the use of these evaluations in making judgements (Dovidio et al., 2001). Devine (1989) said that low-prejudiced people will attempt to control the use of these biased evaluations and even prejudiced people may be motivated to conform to egalitarian social norms (Dovidio et al., 2001). For example, Fazio et al. (1990, cited in Dovidio et al., 200) found a weak negative correlation between implicit and explicit attitudes for socially sensitive objects and a high positive correlation for socially non-sensitive objects. Fazio et al. (1995) found a higher correlation between implicit and explicit measures among participants who were less motivated to control their prejudice.

Research to increase the understanding of the psychometric properties of implicit measures may help to account for the variable correlations observed between implicit and explicit attitudes (Fazio et al., 1995). A common measurement technique is the use of response latency tasks combined with priming. In these tasks a social category is primed, often subliminally, and then a target word is presented for participants to judge as either positive or negative. A faster response would demonstrate a stronger association between the two concepts being presented (Dovidio et al., 2001 Karpinski & Hilton, 2001). Specifically, it is expected that participants will respond faster to positive words when their ingroup has been primed than when their outgroup has been primed, and vice versa. The IAT (Implicit Association Test, Greenwald et al. (1998) is a frequently used response latency measure and the ‘best developed measure of implicit evaluations’ (Brendl et al., 2001 p.7600). This test requires participants to judge data presented on the computer’s screen, by classifying it according to evaluative categories (e.g., positive or negative), and social categories (e.g., black or white). Participants use the computer keys to record their responses. It is expected that prejudiced participants will respond faster when, for example, ‘white’ and ‘positive’ share a response key (an ‘evaluatively compatible’ condition) than when ‘white’ and ‘negative’ share a response key (an ‘evaluatively incompatible’ condition). Longer response times indicate greater implicit prejudice as they imply a weaker association between the two concepts (Greenwald et al., 1998 Dovidio et al., 2001). Gawronski, et al. (2007) reviewed three key assumptions about implicit attitudes: that they 1) reflect unconscious representations 2) are less susceptible to social desirability than self-reports 3) reflect older and more stable representations originating in socialisation. Their review found no clear support for these assumptions and led them to propose an alternative model. This model suggests that indirect measures reflect the activation of associations from memory, and that these associations can occur irrespective of whether or not a person considers them to be accurate. In addition, Brendl et al. (2001) state that the IAT may simply measure relative attitudes towards two groups and therefore, it is possible that although one group is preferred to the other, neither group is actually negatively evaluated.

Various studies using the IAT have found negative implicit attitudes held by white people toward black people (e.g. Dasgupta et al., 2000 Greenwald et al., Experiment 3, 1998 Ottaway, Hayden & Oakes, 2001 cited in Dasgupta et al., 2000 Rudman et al., 1999 cited in Dovidio et al., 2001). However, the reliability and validity of the IAT has been called into question, e.g. by Dovidio et al. (2001), who found in their meta-analysis that the test-retest reliability of the IAT was only moderate. Other studies into implicit stereotypes have shown stability over time. For example, Kawakami and Dovidio (2001) found consistently faster response times in their experiments for stereotype-consistent than stereotype-inconsistent trait photographs over periods ranging from one hour to 15 days. Rudman et al. (1999, cited in Dovidio et al., 2001) found reliable racial stereotyping over a nine-week period. Test-retest reliability has also been achieved in studies on racial and gender stereotypes by Kawakami and Dovidio (2001) and on self-regard by Pelham and Hetts (1999, cited in Dovidio et al., 2001).

Dovidio et al. (2001) question the internal consistency of the IAT. For example, Dasgupta et al. (2000) found low correlation between implicit racial attitudes when stereotyped white or black names were used and when photographs of white or black people were used (cited in Dovidio et al., 2001). Further, Sherman et al. (1999, cited in Dovidio et al., 2001) reported significantly different correlations between the IAT and a priming measure in two different studies (Dovidio et al., 2001). However, De Houver (1999, cited in Dovidio et al., 2001) states that different measures have fundamentally different structures and call upon different cognitive structures. Therefore, a high correlation between different measures would not be expected (Greenwald et al., 1998 Dovidio et al., 2001) and would, in fact, indicate poor discriminant validity (Campbell & Fiske, 1959 Greenwald et al., 1998).

Reliability and validity are vital if we are to assume that implicit measures represent real attitudes (Robinson et al., 1991 cited in Dovidio et al., 2001). Cameron et al. (2000, cited in Karpinski & Hilton, 2001) were unable to correlate the IAT with various other implicit measures, suggesting that the IAT may, in fact, not be measuring attitudes at all, but merely associations that an individual has been previously exposed to (Karpinski & Hilton, 2001) Therefore, a tendency to associate white more with positive and black more with negative may indicate higher exposure to these associations in the form of cultural stereotypes, rather than higher levels of prejudice (Greenwald et al., 1998: Experiments 2-3 Karpinski & Hilton, 2001). This follows on from the point made by Devine (1989), mentioned earlier, when she distinguished between knowledge of and endorsement of stereotypes. Fiedler, Messner and Bluemke (2006, cited in Dovidio et al., 2001) agree that it is incorrect to assume that recognition of a close association between two concepts equates to an attitude. In addition, they point out that the term ‘black’ is used often as a negative term where race is not involved (e.g. black sheep), and so the word itself may hold negative connotations that have nothing to do with attitudes toward black people. It is necessary to have confidence in the measures employed before they can be used to test relationships (Campbell & Fiske, 1959). Implicit measures require psychometric testing to identify their meaning (Campbell & Fiske, 1959 cited in Dovidio et al., 2001).

In summary, the reliability and validity of the IAT has been found to be moderate. It may be necessary to improve understanding of implicit processes and their relationships with different measurement techniques (Dovidio et al., 2001). This improved understanding of the psychometric properties of implicit measures is necessary if they are to be used for predicting behavior (Fazio et al., 1995).

Further research into the psychometric properties of implicit measures may be necessary it will be important to determine whether implicit measures always succeed in measuring attitudes, rather than simply associations. Implicit and explicit measures of prejudice appear to have only a weak relationship, but this relationship is not fully understood. Generally, research supports the existence of implicit prejudice and indicates that it can predict behaviour, especially that which is spontaneous and independent of explicit attitudes.

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RESULTS

BEHAVIOR

Because our aim was to investigate neural responses based on appearance-behavior congruity, we verified a behavioral congruity effect also existed. We were interested in the relative judgment strength of congruent and incongruent pairs, as prior work identified stronger judgments toward congruent versus incongruent face-behavior pairs (Cassidy & Gutchess, 2014). Approach judgment strength, or the degree of approach motivation relative to average approach motivation, may be of interest in exploring congruity. Although people may approach trustworthy- and untrustworthy-looking people performing positive behaviors, congruity impacts judgment strength.

For each participant, the approach judgment for each pair was subtracted from his or her mean judgment. To compare across congruent (i.e., trustworthy-positive and untrustworthy-negative) and incongruent (i.e., trustworthy-negative and untrustworthy-positive) pairs, we took the absolute values of these subtractions. This accounts for individual differences in scale use and has been used in work considering social judgment and trait attribution strength (Cassidy & Gutchess, 2014 Follett & Hess, 2002). We collapsed across valence because behavioral work has converged on the idea that faces are better distinguished when paired with congruent versus incongruent behaviors (Cassidy & Gutchess, 2014 Rule, Slepian, & Ambady, 2012) and because we did not have a priori predictions regarding valence. 1 We used multi-level modeling (Raudenbush & Bryk, 2002) to examine data where trials were nested within participants. Congruent and neutral-behavior pairs were dummy coded, such that incongruent pairs were an implicit baseline. The equations were as follows:

An effect of congruent face-behaviors emerged (β1 = .54, t(2942) = 12.66, p < .001). Congruent pairs (M = 2.50, SD = .45) received stronger judgments relative to the mean approach tendency than incongruent (M = 1.96, SD = .49). An effect of neutral-behavior pairs also emerged (β2 = -.77, SE = .04, t(2942) = -18.29, p < .001), indicating weaker judgments of neutral-behavior pairs (M = 1.19, SD = 0.38) relative to the mean approach tendency than incongruent. These comparisons implicitly suggest stronger judgments for congruent over neutral-behavior pairs.

MANIPULATION CHECK

We hypothesized that forming impressions from incongruent cues requires more mentalizing than from congruent given the resource demands of inconsistency resolution (e.g., Macrae et al., 1999), with conflict weakening judgments. If this is true, difficulty in making decisions about incongruent versus congruent targets should lead to more disparity between congruent and incongruent targets judgment strength. We calculated disparity for each participant by subtracting the mean judgment strength of incongruent targets from the mean of congruent. We then correlated disparity with self-reported difficulty of making decisions about incongruent over congruent targets. A correlation between disparity and difficulty emerged, r = .70, p < .001. Participants with more disparity between congruent and incongruent target judgment strength reported more difficulty in making decisions about incongruent targets.

IMAGING

We identified regions from the [incongruent > congruent] contrast to assess whether increased mentalizing supported the incongruity’s effect on judgment strength. As hypothesized, greater recruitment of right mPFC existed ( Table 1A , Figure 2A ), consistent with related work (Cloutier et al., 2011 Hehman et al., 2014 Ma et al., 2012 Mende-Siedlecki, Cai, & Todorov, 2013) and supporting the idea that people mentalize more in response to incongruent social cues. Additionally consistent with prior work (Hehman et al., 2014 Ma et al., 2012), a region of left dlPFC emerged ( Table 1A , Figure 2B ). DlPFC engages in tasks requiring cognitive control (Miller & Cohen, 2001). Contrasting [congruent > incongruent] yielded widespread activity in visual processing regions ( Table 1B ), suggesting perhaps more attention to faces for anticipated behaviors.

mPFC (A) and dlPFC (B) activated more for incongruent > congruent targets.

TABLE 1

Brain Regions Responsive to Appearance-Behavior Congruity

A. Incongruent > Congruent
BAIncongruent > Congruentktp-valuexyz
9/46L dorsolateral prefrontal cortex305.54< .001-302637
10R medial prefrontal cortex345.21< .0016501
B. Congruent > Incongruent
BACongruent > Incongruentktp-valuexyz
17R primary visual cortex2447.70< .00115-88-2
18L visual association area1876.01< .001-15-971
18L visual association area 5.47< .001-33-85-11
19L extrastriate cortex 4.61< .001-45-79-5
19R extrastriate cortex494.62< .00142-76-11

Note. Regions listed without cluster sizes are subsumed by the cluster listed above. Regions are listed from highest to lowest t-value.

L = left R = right k = cluster size BA = approximate Brodmann’s area

x, y, and z represent MNI coordinates of the peak voxel within each cluster. Cluster sizes are reported using a voxel-wise threshold of p < .001 and a 19-voxel extent threshold for an experiment-wise threshold of p < .05.

Psychophysiological Interaction (PPI)

PPI identified regions functionally connected with the mPFC seed for incongruent over congruent targets. No activations emerged at p < .001. Activity was coupled with dlPFC (BA 9 k = 9, t = 4.26, p < .001, peak MNI coordinates: 18 44 25) using a more liberal threshold. (p < .005 commonly utilized in related work, see Mende-Siedlecki, Baron, & Todorov, 2013). This suggests mPFC and dlPFC communicate more for incongruent versus congruent targets. mPFC-dlPFC connectivity has been identified during social incongruity during spontaneous, but not intentional, impression formation (Ma et al., 2012). Our effect may be less robust than previous findings because our task involved approach ratings directly related to the intentional formation of impressions.

ROI and Individual Differences

We verified that mPFC response characterized activity related to the inconsistency of appearance-behavior cues using independent region of interest (ROI) analyses. We selected two mPFC regions (MNI coordinates: dorsal mPFC: 4 46 28, ventral mPFC: 6 56 10) identified in related work (Ma et al., 2012) as sensitive to violations in behavior-based trait expectations by opposite valence behaviors. Spherical ROIs of 6mm were defined based on MNI coordinates. At p < .001, activity in the [incongruent > congruent] contrast was identified in the ventral, but not dorsal, mPFC ROI ( Figure 3A ). Thus, our findings complement work on processing inconsistent trait-related information, extending this work to include processing appearance-behavior inconsistencies.

Increased activation to incongruent > congruent targets was evident in an independent ventral mPFC ROI (A). Composite interpersonal enjoyment scores correlated with ventral mPFC engagement to incongruent > congruent targets (B).

Our secondary goal considered individual differences contributing to processing incongruent over congruent appearance-behavior cues. Specifically, we were interested in how differences in introversion and interpersonal ease relate to processing inconsistent person information. Because five post-task questionnaire items (see Methods) related to seeking out interpersonal interactions and had high internal consistency (Cronbach’s alpha = .83), we created a composite interpersonal enjoyment score by averaging these responses for each participant. We correlated [incongruent > congruent] parameter estimates from the ventral mPFC ROI with interpersonal enjoyment scores. A negative relationship emerged, r = -.55, p = .02 ( Figure 3B ). Those with lower interpersonal enjoyment had greater mPFC responses to incongruent over congruent targets. Those with lower interpersonal enjoyment did not, however, exhibit more disparity in judgment strength between congruent and incongruent targets, r = .23, p = .35.


5. General Discussion

In a series of three RSVP reading experiments we tapped comprehender's background knowledge about agent-action-patient contingencies (Experiment 1) and then manipulated linguistic expressions of quantity to be consistent or inconsistent with this knowledge via quantified subject noun phrases, e.g., [ Most / Few ] farmers grow [ crops / worms ] (Experiment 2) and adverbs of quantification, e.g., Farmers [ often / rarely ] grow [ crops / worms ] (Experiment 3). In the latter two experiments we determined comprehender's interpretation of the quantifiers via post-sentence plausibility ratings and compared these offline judgments with the incremental interpretations inferred from on-line ERP measures of processing disruptions at the critical typical or atypical object noun. In Experiment 1, we found the predicted larger N400 amplitude for the atypical in comparison with typical object noun. In Experiment 2 we found small but reliable modulations of the typical object noun N400 amplitude as a function of most- vs. few-type quantified subject noun phrases and a similar pattern of N400 reductions was observed for the adverbs of quantification often vs. rarely in Experiment 3. Lexical factors that modulate N400 amplitude, e.g., length, frequency, and concreteness of the object noun are counterbalanced across quantifiers in this design, as are contextual factors such as lexical associations between the subject noun, main verb, and, object noun. We thus attribute modulation of the typical and atypical object noun N400 amplitudes to the contribution that the different quantifiers make to the evolving semantic context.

We take these N400 amplitude modulations as evidence of incremental quantifier interpretation and inconsistent with any hypothesis according to which the processing of quantifier semantics is entirely deferred or delayed. However, there is also an important dissociation between the patterns of quantifier and typicality effects for the offline and online measures. Whereas the quantifiers (Most vs. Few and often vs. rarely) reverse the offline plausibility judgments for sentences containing typical and atypical object nouns, they do not similarly reverse the N400 amplitudes for the object nouns. So although the ERP data indicate that quantifier meanings are registered in real-time and incrementally incorporated into the evolving representation of semantic context at least to some extent, these initial representations do not appear to be the same, more fully specified interpretations that inform the subsequent offline plausibility judgments. If this is correct, then at least in some respects, the semantic contributions of quantifier expressions to the interpretation of a sentence are processed at a delay and with a time course not yet fully understood.

We note that this interpretation depends essentially on the dissociation between the plausibility judgments and N400 amplitudes. These offline and online measures jointly afford an opportunity to draw sharper inferences than either the end-state sentence comprehension measures or the online ERP measures alone. Whereas the plausibility judgments provide evidence that the quantifiers are (eventually) fully interpreted, it would be a mistake to infer that they are fully interpreted at the time when the critical object noun is encountered. This is not to say that on-line measures are somehow more informative than off-line measures, for it would also be a mistake to conclude from on-line ERP evidence of underspecified quantifier interpretations that the quantifiers were not fully processed by sentence end (or ever). Rather, the conclusion that emerges—quantifiers are processed rapidly and incrementally though not fully when initially encountered, with full interpretations emerging later—is supported precisely by the dissociation between the off-line and on-line measures and cannot be drawn from either alone.

Our findings complement and, importantly, contrast with previous ERP investigations of quantifier interpretation. In a design that probed the resolution of referentially ambiguous quantifier expressions Kaan, et al. (2007) manipulated the cardinality of bare quantifiers and found evidence of processing differences about a second later as a function of the number of objects already introduced into a simple discourse context. Our design does not essentially involve ambiguity resolution or intra-sentential discourse reference but rather examines the contribution of quantifier information to the sentential semantic context that evolves within isolated sentences. In this respect our design has more in common with Kounios & Holcomb (1992). There are a number of differences between their study and ours and perhaps the most salient concerns the results: we observed N400 evidence that the quantified subject noun phrases modulate processing of the object noun whereas Kounios & Holcomb (1992) did not. Our findings thus appear to be inconsistent with the suggestion that N400 primarily reflects aspects of the organization of semantic memory to the exclusion of structural semantic factors.

An unexpected additional finding in these experiments is a prefrontal slow wave positivity for atypical vs. typical object nouns. We found this object noun typicality effect to be most pronounced in the context of the few-type quantifiers (Experiment 2) and adverb rarely (Experiment 3). The time course suggests that these constructions require additional or secondary processing, perhaps related to interpretation (resolving explicit or implicit negatives?) or related to the comparison with background knowledge or decision processes relevant to the plausibility judgment. Positivities evolving after the N400 have been widely observed in ERP sentence comprehension research. Variously termed P600 (Osterhout & Holcomb, 1992) and Syntactic Positive Shift (Hagoort, Brown, & Groothusen, 1993), these effects are often largest over posterior scalp and associated with grammatical disruptions, e.g., words that violate grammatical rules or that are inconsistent with the preferred interpretation of a structural ambiguity. The relation between the frontal positivities observed in our experiments where there is no obvious syntactic ambiguity or anomaly and the many previously reported late posterior positivities is unclear and the relation between semantic and syntactic processing and the negative and positive waveforms that emerge between about 300ms and 1200ms poststimulus is not simple (for reviews and critical discussion see Bornkessel-Schlesewsky & Schlesewsky, 2008 Kolk & Chwilla, 2007 Kuperberg, 2007).

There are, however, a few reports of late positivities with a predominantly frontal distribution in experimental designs that, like ours, do not involve grammatical or structural disruptions. Moreno, Federmeier, & Kutas, 2002 found that for Spanish-English bilinguals reading English sentences and idioms, a late frontal positivity (650 – 850 ms) was elicited both by unexpected English completions (lexical switches) as well as Spanish translations of the expected English completion (code switches), particularly for the idioms. There is also some preliminary evidence of differential involvement of the cerebral hemispheres. In a study of metaphor comprehension that included literal controls Coulson & Van Petten, 2007 also observed a late anterior positivity (600-900ms) for plausible but unexpected (low cloze) sentence final words in comparison with the expected (high cloze) endings, though only for words presented in the right-hemifield (left hemisphere). Further evidence and, importantly, a clear dissociation between the late positivity and the N400 is reported by Federmeier, Wlotko, De Ochoa-Dewald, & Kutas, 2007. Words may be more or less expected in context with expectancy operationalized via cloze probability, i.e., the probability of production in an offline sentence completion task. Sentence contexts may be more or less constraining where constraint is defined as the highest cloze value of the completions. Replicating Kutas & Hillyard (1984) they found that low cloze sentence final words elicited a larger N400 than high cloze and, furthermore, that for low cloze words, there was no effect of sentential constraint on the N400 amplitude. That is, unexpected words had similar N400s regardless of whether they were unexpected alternatives to a highly expected word or unexpected because the sentential context did not provide enough information to generate strong expectations. However, there was pronounced frontal slow wave positivity when these unexpected words occurred in highly constraining contexts in comparison with weakly constraining contexts. The authors suggest this prefrontal positivity may reflect the appreciation of a mismatch between the expected item and the word presented or the allocation of resources necessary to override or revise a prediction or both.

It is difficult to see how this line of reasoning can be extended to the pattern of data in our Experiment 2 and Experiment 3. Whatever the space of expected continuations might be for the most-type quantifier or often sentence contexts, e.g., most farmers grow ___, in the absence of a supporting discourse context, it is difficult to generate strong expectancies about the continuation of Few farmers grow ___. In our experiment, if anything, those sentences containing the few-type quantifiers and adverb rarely should be less constraining than those sentences with the most-type quantifiers and often. If a prefrontal slow wave positivity is associated with unexpected words in high vs. low constraint contexts we would expect to see the clearest evidence at the atypical object noun worms, in Most farmers grow worms in comparison with Few farmers grow worms (or perhaps in comparison with Few farmers grow crops, the question of which control is appropriate is debatable, though less critical since either choice should be relatively less positive by comparison). Although the prefrontal positivity was indeed greatest for the word worms, it occurred in the less constraining sentential contexts that contained the few-type quantifiers and the adverb rarely. There are many possible explanations for these discrepant findings. It may be that qualitatively similar prefrontal positivities reflect different functional processes in the two experiments. Alternatively, the prefrontal positivity may reflect a process that is common to both, e.g., allocation of processing resources as proposed by Federmeier, et al., 2007 though contra their suggestion, not specifically linked to the revision of a prediction. In addition, plausibility may be playing a different role in the two cases. In our experiment the atypical noun, worms, in the context of the few-type quantifiers although unexpected is, based on the response data, ultimately plausible. Further investigation is needed to determine whether the frontal positivity reflects processing selectively associated with the few- in contrast with most-type quantifiers or some aspect of the plausibility evaluation triggered in this experiment.

Finally, in evaluating the generalizability of our quantifier results we are alive to a potentially instructive parallel with recent research on the real-time comprehension of negation. It is uncontroversial that negation contributes to the overall semantics of a sentence. Although the Fischler, et al. (1983) report that negation did not have a reliable effect on N400 amplitude of the predicate term in simple subject-predicate sentences appears to militate against incremental interpretation of negation (see also Kounios & Holcomb, 1992 Ludtke, Friedrich, De Filippis, & Kaup, 2008), the scope of this result has been sharply circumscribed by recent evidence that negation can be processed incrementally when it is pragmatically licensed by the context. In isolated sentences, explicit denials may provide little useful information, e.g., A robin is not a tree, although true, is uninformative and thus pragmatically infelicitous. However, against the backdrop of appropriate contexts, denials may be highly informative, for example, when a speaker attempts to correct a listener's mistaken belief as in, A robin is not a member of the finch family. In recent work, Staab (2007) and Nieuwland & Kuperberg (2008) independently found that N400 amplitude on critical target words varied in a manner consistent with the incremental interpretation of negation, provided it was pragmatically supported (licensed) by contextual information (c.f., Wason, 1965). Nieuwland & Kuperberg (2008) recorded ERPs in sentences such as, With proper equipment, scuba diving is very [ safe / dangerous ], and found that N400 amplitude for dangerous was greater than for safe and, crucially, also found that this relationship reversed when the copula is was replaced by isn't. This result, in conjunction with their other comparisons was taken as evidence for the incremental interpretation of negation. In our quantifier experiments, we observed N400 amplitude modulation but not reversal at critical target words as a function of quantifier type and are suggesting that this is evidence of incremental construction of partially specified quantifier interpretations. As noted above, our few-type quantifiers are “negative” in the sense that they license negative polarity items. Whether or not the semantics of these quantifier expressions, by analogy with explicit negation markers, might be interpreted incrementally and fully in pragmatically supporting contexts is an open question.


Discussion

Overall Findings

The main purpose of this article was to offer a comprehensive characterization of the N400 for actions by reviewing current findings on this specific domain and to propose a functional neuroanatomical model that is able to integrate the action-related data to current knowledge about the classical N400 elicited by words.

As shown by the reviewed studies, the negative activity elicited by action-related anomalous stimuli begins early, approximately at 250� ms post-stimulus onset perhaps reflecting the rapid access that realistic visual images have to semantic memory networks (West and Holcomb, 2002 Sitnikova et al., 2003, 2008 Mudrik et al., 2010). Nevertheless, other relevant literature, which also includes early components modulation without reporting the N400 (Hauk and Pulvermuller, 2004 Kiefer et al., 2007 Hauk et al., 2008), are out of the scope of this review. Note that in some N400 studies, even earlier modulations -in the 100 to 200 ms window- are observed when dynamic realistic visual images such as videos (Kelly et al., 2004, 2007) or static realistic images such as photographs (Proverbio and Riva, 2009 Proverbio et al., 2010) are used (see Figure 1). Accordingly, these particular temporal dynamics observed when real world features are presented could be reflecting a more direct and rapid mapping to sensorimotor representations.

In addition, the presence of a LPC following the N400 effect was reported in several studies (e.g., Sitnikova et al., 2003, 2008 Wu and Coulson, 2005 Cornejo et al., 2009 Ibanez et al., 2010, 2011a,b). This late effect is assumed to reflect accessing the knowledge of goal-related requirements about real-world actions (Sitnikova et al., 2008), a decision-making related process (Wu and Coulson, 2005), or a continued re-analysis of the inconsistent situation (Munte et al., 1998 Hurtado et al., 2009). Nevertheless, what the presence of this component suggests is that meaning is not computed at once, but rather it is something that emerges through time, with the N400 representing an important aspect of that emergent process, but not, certainly, the final state (Kutas and Federmeier, 2011).

No clear hemispheric dominance is observed across studies. While some studies report a bias over the left hemisphere (Cornejo et al., 2009 Ibanez et al., 2010, 2011a,b), others report that the N400 effect is more prominent over the right hemisphere (West and Holcomb, 2002 Reid and Striano, 2008). Thus, further research is needed to understand the lateralization profiles of different experimental designs and stimuli types.

Finally, the more anterior topographical localization often reported in N400 studies where non-verbal material is used, is also present. In consonance with neural source localization findings discussed in the previous section, this difference has led to the hypothesis that while both negativities could be reflecting similar functional operations instantiated by a common semantic network, these operations could be carried out in non-identical neuroanatomical substrates, with the coupling of motor/premotor regions in the particular case of actions. Although this hypothesis might seem obvious, the claim that meaning is grounded, wholly or in part, in systems for perception and action, is far from being trivial and is currently a debated topic in cognitive neuroscience.

Language and Sensorimotor Processing: Does the N400 for Actions Support a Grounded View of Meaning?

Classical linguistics theories (Collins and Loftus, 1975 Fodor, 1983 Masson and Borowsky, 1998) interpret meaning as the result of the combination of abstract, amodal symbols arbitrarily linked to entities in the real world. In this view, the sensorimotor information derived from our experiences with the world is completely detached from the conceptual knowledge that we have of it. One of the main difficulties derived from these theories, however, is the so-called grounding problem: if we want to know the meaning of an abstract symbol, the symbol has to be grounded in something other than more abstract symbols. The reason is simple: manipulation of abstract symbols merely produces more abstract symbols, not meaning (Glenberg and Robertson, 2000).

An alternative psycholinguistic approach, the embodied semantic theory, gained popularity in the last few years. One of the most radical and controversial claims in this field, suggests that language processing recruits a particular type of neurons that fires both during action execution and during action observation of the same/similar action: the mirror neurons (diPellegrino et al., 1992). In a strict sense, this theory predicts that mirror regions that are activated during action observation and action execution should also be activated during the comprehension of words referring to actions (Gallese and Lakoff, 2005 Pulvermuller et al., 2005 Gallese et al., 2007). Furthermore, these later semantic activations would be distributed in a somatotopically-arranged manner with leg concepts (such as “kicking”) activating the homunculus leg area, mouth concepts (such as �ting”) activating the mouth area and so on.

The embodied framework has triggered intense discussions (Negri et al., 2007 Willems and Hagoort, 2007 Mahon and Caramazza, 2008 Toni et al., 2008 Hickok, 2009), and current neuroscientific research does not necessarily support its radical versions (Arevalo et al., 2012 Ibá༞z et al., 2012a). Recent findings also suggest that the somatotopical activation pattern reported in many of these studies are not exact (Turella et al., 2009 Fernandino and Iacoboni, 2010) and that when the three conditions (observation, execution, and linguistic comprehension) are tested together in the same set of participants, activations elicited by action-associated linguistic stimuli do not match with the activations observed for execution and observation (Postle et al., 2008 de Zubicaray et al., 2010). In other words, “mirror areas” are not sufficient in explaining how our brain processes action meaning and the engagement of other cortical regions is clearly required (Brass et al., 2007).

Accordingly, more lenient versions predicting partially overlapping (but not identical) regions comprising a general motor-language network have been proposed. These interpretations come from studies reporting activity in regions outside the motor/premotor cortices such as the IFG, the temporal cortex, the cerebellum and the inferior/superior parietal lobule (Pobric and Hamilton, 2006 Gazzola and Keysers, 2009 de Zubicaray et al., 2010 Kemmerer and Gonzalez-Castillo, 2010). In consonance with these results, the source localization studies on the N400 for actions reviewed here report similar activations in the aforementioned regions, supporting a “grounded” approximation to meaning construction. Indeed, it has been suggested that the N400 component can be understood within an embodied framework (Chwilla et al., 2007, 2011 Collins et al., 2011 Hald et al., 2011). For instance, Chwilla et al. (2007) reported N400 modulations for novel senseless meanings compared to novel sensible meanings [e.g., “the boys searched for branches/bushes (sensible/senseless) with which they went drumming … ”]. While the first option makes sense, the second one does not. This is because the affordances of bushes do not mesh with the actions required to drum. Moreover, this study shows that participants can establish novel meanings not stored in memory, challenging abstract symbol theories that can only access meaning by consulting stored symbolic knowledge.

Hald et al. (2011) found a frontal N400 response, modulated by the modality switch effect. This effect occurs when a first statement -describing an event grounded in one modality- is followed by a second one in a different modality. For instance, “The cellar is dark” (visual property) followed by 𠇊 mitten is soft” (tactile property). The modality of the previous statement serves as a context and guides predictions. Accordingly, the statement “The cellar is … ” preceded by a tactile context leads to a weaker activation of �rk” than when the preceding context is visual. This is because that, guided by the tactile context, the system is looking for a tactile property of the �llar,” and this will lead to a modality switch negativity. According to the authors these ERP results support an embodied and predictive view of language comprehension. Similarly, Collins et al. (2011) also found that the modality switching effect was associated with increased N400 amplitudes, supporting the claim that perception and action systems help subserve the representation of concepts.

Taken together, these studies are in line with the more lenient versions of the embodied approach and support a “grounded” view of the N400, in the sense that the retrieval of sensory and motor information clearly modulates meaning-related processes indexed by this component. In other words, comprehension has a contextual and situated nature and semantics are grounded in prior experiences with the world.

We believe in a bidirectional cooperative approach in which language and sensorimotor activity can be dissociated (Mahon and Caramazza, 2008), but can also operate together, during meaning construction, in the context of a larger network (Aravena et al., 2010). According to this view, meaning constitutes a polymodal, context-dependent, and constructive representation instantiated by the aforementioned distributed network (Amoruso et al., 2011, 2012 Ibanez and Manes, 2012).

Context Integration: The N400 Action Model

The presentation of incongruent vs. congruent verbal and non-verbal stimuli in different formats, such as environmental sounds, drawings, static, and dynamic pictures, all give rise to a similar N400 effect. Moreover, this effect has been reported at several levels of processing, including semantic, syntactic (Weber and Lavric, 2008 Zhou et al., 2010 Zhang et al., 2011 Morgan-Short et al., 2012), and phonological-orthographical levels (Deacon et al., 2004 Meng et al., 2008). In addition, other complex processes, such as metaphor (Cornejo et al., 2009 Ibanez et al., 2010, 2011a,b), irony (Cornejo et al., 2007), and joke comprehension (Coulson and Wu, 2005), have been shown to modulate the N400 amplitude. In brief, current electrophysiological evidence suggests that the N400 can be elicited by a wide range of stimuli as long as they are potentially meaningful (Kutas and Federmeier, 2011).

One common characteristic reported across studies is that as the target stimulus becomes more expected/congruent with the context, the N400 amplitude is reduced when compared with unexpected/incongruent conditions. This general finding, observed for stimuli across modality, suggests that when the previous context builds up meaning the processing of upcoming information that fits with the current context is facilitated. These effects, sometimes known as 𠇌loze-probability” and “semantic incongruity,” respectively, remain stable across stimulus-modality.

Note, however, that unexpected sentence endings have been shown to elicit larger N400 responses, even when endings were semantically congruent (Kutas and Hillyard, 1984). Therefore, it is likely that this component reflects a more general process, than semantic processing per se, in which meaning is shaped by predictions that we create based on current contextual cues and previous experiences. For example, observing someone hammering a nail into a wall with a rolling pin is “weird” to our brain however, it would not be strange if we knew that this person does not have a hammer and they managed to find an alternative solution in order to perform the action. In other words, meaningful actions depend on the circumstances, and a given stimulus can be classified as congruent or incongruent depending on the scenario and the predictions that we make from it.

Current research has shown that the brain is constantly benefiting from context by making predictions about future events (Bar, 2004, 2009). Predictive theories in the domain of perception and action suggest that our brains are good at reducing discrepancies between expectations and current experience. For instance, in the action field, predictive motor theories (Wolpert and Flanagan, 2001 Wolpert et al., 2003 Kilner et al., 2007a,b) assume that analogs models are used to generate predicted sensory consequences of executed actions and to inferred motor commands from observed actions. For example, the predictive coding account (Kilner et al., 2007a,b Kilner, 2011) argues that intentions can be derived through action observation by the generation of an internal model that minimizes the prediction error at different levels of a cortical hierarchy. More specifically, by observing a person performing a specific action, we are able to predict their motor commands and, given these commands, we are able to predict their kinematics, by mapping this information into our own action system. When comparing this information on the multiple levels of the hierarchical model, a prediction error is generated. By minimizing this error at all the levels of action representation, we can infer the most likely cause of an observed action. In neuroanatomical terms, this model is thought of as a double pathway model where action understanding is achieved through interactions between a ventral pathway and a dorsal one (Kilner, 2011). While the ventral pathway links the MTG with the anterior IFG, the dorsal one refers to the action-observation network (AON), including the ventral premotor cortex, the inferior parietal lobule and the STS. The proposal here is that a representation of more abstract features (e.g., the intention and goal of an observed action) is generated by the ventral pathway, through a process of semantic retrieval and selection. This result in the encoding of the representation of the most probable action required to achieve the most probable goal. Once this goal is estimated, then a prediction of the sensory consequences of this action (a more concrete representation of the action) can be generated by the dorsal pathway.

In the perceptual field (Bar, 2004, 2009), object recognition is thought to be mediated by cognitive structures (memory scripts) that integrate information about the identity of the objects that tend to co-occur in a given context with previously learned information about their possible relationships. These structures are thought of as a set of expectations about what is more probable to see or not to see in a given context, enabling us to make predictions and accurately disambiguate incoming information. In this model, frontal areas are involved in updating current contextual information and integrating it with semantic associations stored in temporal regions (e.g., parahippocampal and retrosplenial cortex).

In consonance with the aforementioned accounts, we propose a model for the N400 for actions where frontal areas (e.g., IFG) would update ongoing contextual information in working memory and integrate it with learned target-context associations stored in temporal regions (MTG, STS) in order to get the specific significance of an action event (Amoruso et al., 2011, 2012 Ibanez and Manes, 2012). In addition, the inferior parietal lobe, as a cross-modal area, would mediate the integration of sensory, motor, and conceptual information (Seghier, 2013). Indeed, strategic connections between frontal, temporal, sensorimotor, and parietal regions involved in intentional (Waszak et al., 2012) and conceptual (Opitz, 2010) binding-related processes, such as linking actions to their predicted effects, have been proposed. Based on this account, the N400 can be seen as a neural marker that indexes the integration of current contextual cues. This later process involves: (1) prediction-related activity (frontal regions) and (2) integration with previous experiences (temporal and parietal regions). In addition, the retrieval of modality-specific information (e.g., motor-related information) facilitates the overall process as it becomes well-illustrated in forward models about action.

When we observe another person performing a given action such as grasping a glass of water, we are able to accurately anticipate the future course of the observed action. In other words, current contextual information and previous similar experiences enable as to predict incoming steps and shape meaning construction. These expectations are triggered at different levels, with top𠄽own (e.g., expectations about the intention or the action goal) and bottom–up (kinematics and motor commands) information working together in a mutually constraining manner. Based on this view, our model provides an empirically testable set of hypotheses regarding contextual-based prediction and action meaning comprehension in N400 paradigms. For instance, during tasks using realistic visual images about actions, we expect to observe the engagement of the aforementioned fronto-temporo-parietal network working in concert with motor/premotor areas. In other words, we expect that the semantic processing involved in the N400 effect for action-related material would trigger a sensorimotor resonance in the observer. This prediction is partially confirmed by studies showing that the observation of actions that can be directly mapped onto the observer's motor system report a significant activation of premotor areas (see Van Elk et al., 2008). In temporal terms, we expect that ERP modulations would be observed from its earliest stages, perhaps due to the direct sensorimotor mapping elicited by realistic stimuli. In fact, this is the case in most of the reviewed N400 studies using ecological material (e.g., videos) about everyday actions. Thus, if “grounding” information such as kinematics, body movements, and interactions with artifacts or body/body parts is crucially required by the task (as in most of the designs used in N400 studies for actions) we expect that activity in motor/premotor areas will be enhanced and rapidly observed. In addition, we expect that during the integration of language-related stimuli (e.g., utterances) and action material (e.g., gestures) fronto-temporo-parietal regions as well as motor/premotor regions would be equally activated and maybe a delay in the N400 latency could be reported.

However, it remains an open question if this predictive account for actions could be extended to those tasks where the processing of the incongruence only relies on the use of language-material. While contextual cues clearly serve to pre-activate features of likely upcoming words (e.g., Ibanez et al., 2006, 2011a,b), such that the processing of unexpected stimuli that share semantic features with predicted items is facilitated (Kutas and Federmeier, 2011), it is unclear if a similar predictive error triggered during verbal semantic processing at different levels (e.g., words, sentences, pieces of discourse) can be explained in terms of forwards models. Future studies would benefit the validation and development of the proposed model by defining more detailed and testable predictions including the specific measures of the aforementioned processes.

In particular, our notion of context-dependent construction of meaning based on frontotemporal circuits resembles the view laid out by other colleagues (Kiefer and Pulvermuller, 2012). They suggest that concepts are flexible, distributed and modality-specific sensory and action representations, which depend on previous experience. Kiefer and Pulvermüller also argue that conceptual information proper is stored in sensory and motor areas whereas the anterior temporal lobe serves as a convergence zone for binding the distributed modality-specific representations. In addition, meaning does not necessarily depend only on actions, but also on sensory information from different modalities such as visual form features, motion, sound (Simmons et al., 2007 Hoenig et al., 2008 Kiefer et al., 2008, 2012). This model resembles our bidirectional coupling between motor and language areas. But they differ in the emphasis on modality-specific sensory and action representations and in the somatotopic representations. Strong claims of modality-specific and somatotopic representations have been challenged and recently criticized (see a work summarizing several sources of evidence: Cardona et al., 2013). Moreover, the distributed and extended source of N400 does not fit adequately with a model of somatotopic representations. Our model predicts a coupling, without interpretations about explicit representation coming from discrete areas. Meaning represents an emergent property of such motor-language coupling itself. Thus, in our model meaning is an emergent property of the fronto-temporal network and not only of modality-specific representations.

Recent accounts have proposed the existence, in the anterior temporal lobe (ATL), of a mechanism supporting the interactive activation of semantic representations across modalities (Patterson et al., 2007). According to this position, sensorimotor and language aspects of conceptual knowledge are necessary but not sufficient to build up meaning and an amodal hub region which makes generalizations is required. However, this proposal, mainly derived from anatomo-clinical observations in patients with semantic impairments, is far from being consistent (see Gainotti, 2011). Although many temporal areas are involved in the generation of the action-related N400, the anterior parts of the temporal lobe are not reported when experimental paradigms use current actions or action observation (e.g., Proverbio et al., 2010 Van Elk et al., 2010a,b Ibá༞z et al., 2012a). In fact, the involvement of this cortical area is often seen in N400 tasks requiring only lexical representations (Halgren et al., 2002), suggesting that it might support basic combinatorial operations underling sentence processing (Dronkers et al., 2004 Lau et al., 2008) and syntactic aspects (Noppeney and Price, 2004). In the particular case of the N400 for actions, when determining the incongruence of a given stimulus clearly relays more on a sensorimotor resonance or the re-enactment (Barsalou et al., 2003) of perceptual and action-related states in order to get the meaning of an event, the role of the ATL would be an auxiliary one. Accordingly, its involvement is not expected in these later cases (as supported by source localizations studies on the N400 for actions reviewed in this paper), but it would be indeed expected when the processing or disambiguation of the incongruent incoming information requires more �stract” operations -and this is the case (see N400 studies on word processing reviewed by Lau et al., 2008).

In brief, action N400 supports a fronto-temporo-parietal network (Gainotti, 2011) in which motor and semantic representations would operate together during comprehension of complex situations, predicting effects of semantic processing on the motor system and vice versa. In this view, we avoid predictions derived from radical embodiment (e.g., somatotopic activations) and we only take advantage of the proposal that sensorimotor “grounded” information derived from real-world experiences are necessary during the comprehension of perceived or produced events. Thus, the activation of this network would be modulated depending on stimulus type properties (indexing cortical related activations), previous experiences and learning effects (temporal regions), and current contextual predictions and expectations (IFG and other frontal regions).


Conclusions

It is undeniable that stereotypic behavior is a pervasive and roblematic feature of autism. Furthermore, a substantial body of literature supports the need to modify these behaviors. Fortunately, a variety of effective interventions have been developed to address these problem behaviors. Although traditionally considered to operate under sensory and automatic reinforcement contingencies, research has clarified that repetitive and stereotyped behaviors may also be maintained by social or non-social positive and negative reinforcement. It is important that interventions be applied in line with this evidence. Indeed, it seems most appropriate to describe and categorize stereotypies in terms of their function, rather than their form. In so doing, applied research and clinical applications will not only involve more accurate use of terminology, but also be more likely to influence positive behavior change through effective environmental manipulations. As is the case with many applications of behavioral principles to children with autism, there is no one single effective approach to addressing stereotypy for all children or all stereotypic behaviors. However, a large research base exists to offer practitioners a variety of evidence-based behavioral interventions for stereotypy based on operant function. Although all behavior is lawful, the functional relations are not predetermined. Behavioral treatment and future research should proceed with a functional interpretation of stereotypy in autism that acknowledges its multiple, heterogeneous, and most importantly, modifiable determination.


Appendix A: Stimulus text

So last Thursday I was walking down the steps to the tube and there were these two guys walking up on the other side. Both of them were texting on their phones and joking with each other, and I guess one of them slipped or something ‘cuz all of a sudden he starts falling backwards and throwing his arms in the air. And for like three seconds he was just sort of balanced there, and I thought, you know, he'd pull himself up. But then he tipped even further back and just started tumbling down the stairs and landed on the floor and his head smashed right on the tiles. For a second nothing happened, but then blood started streaming out of his head and it didn't look like he was breathing. And the guy's friend, rather than try to help or anything, just stood there and looked at him. I shouted at him to call an ambulance, and they came pretty soon. The guy turned out to be okay—he just had a nasty gash on the side of his head, but otherwise he was fine.


EXPERIMENT 1

In the first of our two experiments, we examined electrophysiological responses to critical words in underinformative statements versus informative scalar statements, and used this measure to investigate individual differences in pragmatic processing. If scalar pragmatic inferences are generated incrementally during online sentence processing, critical words that render a statement trivial or underinformative should lead to additional semantic processing costs, and should elicit a larger N400 than critical words in informative statements – a pragmatic N400 effect (see also Nieuwland & Kuperberg, 2008). If, on the other hand, pragmatic scalar information is not used incrementally during online processing, the N400 should not be larger to critical words in underinformative statements. In fact, given the closer lexico-semantic associations in underinformative than in informative sentences (people-lungs vs. people-pets), the N400 may even be relatively attenuated in underinformative sentences.

We also hypothesized that there may be individual variation in these patterns of N400 modulation, that may be predicted by variation in participants’ abilities to produce and comprehend pragmatic aspects of language in the real world (e.g., Baron-Cohen, Tager-Flusberg & Cohen, 2000 Happé, 1993 Schindele et al., 2008 Tager-Flusberg, 1981, 1985). We therefore obtained an independent measure of pragmatic language abilities of our participants in everyday life through the Communication subscale of the Autism-Spectrum Quotient questionnaire (the AQ Baron-Cohen, Wheelwright, Skinner, Martin & Clubley, 2001) that quantifies an individual’s pragmatic skills on a continuum from autism to typicality. Of the five AQ subscales, the Communication subscale taps into pragmatic abilities most directly. Some examples of items from this subscale are “Other people frequently tell me that what I’ve said is impolite, even though I think it is polite”, “I find it hard to ‘read between the lines’ when someone is talking to me”, and “I am often the last to understand the point of a joke”.

We predicted that individuals with good pragmatic abilities (as indexed by a low score on the AQ Communication subscale), would be relatively more sensitive to the pragmatic ‘violation’ of underinformativeness and more likely to show a pragmatic N400 effect, as compared to less pragmatically skilled individuals (see Schindele et al., 2008, Pijnacker et al., 2008, for related hypotheses in participants with high-functioning autism or Asperger’s syndrome). This sensitivity may play out in several different ways. For example, individuals with good pragmatic abilities might generate pragmatic inferences more consistently, generate more robust inferences, they might be better at evaluating incoming words for informativeness, or perhaps even have a different task set than people with poor pragmatic skills. In the current study we cannot distinguish between these or other possibilities. Nevertheless, modulation of a pragmatic N400 effect by pragmatic abilities could provide evidence that such everyday communication problems may be, in part, driven by an impaired incremental use of pragmatic knowledge during language processing.

In order to examine the specificity of these potential individual differences, we also included sentences that did not contain scalars, but that contained a word that had a relatively good semantic fit versus relatively poor semantic fit to the preceding sentence context based on real-world knowledge see Table 1 for examples). We predicted that words that were incongruous with real-world knowledge 3 would produce a robust N400 effect compared to words that were congruous with real-world knowledge (e.g., Kutas & Hillyard, 1984) in all individuals, regardless of their AQ-Communication scores. This allowed us to dissociate individual differences in incrementally recruiting pragmatic knowledge from the more general recruitment of real-world knowledge during online processing.

METHODS

Participants

Thirty-one right-handed Tufts students (17 males mean age = 20.2 years) gave written informed consent. All were native English speakers, without neurological or psychiatric disorders.

Materials

We constructed 70 sentence pairs such that the underinformative and informative versions of each sentence pair were identical except for the critical word. Each sentence consisted of two clauses, and the first clause (the quantifier clause) always started with the quantifier ‘some’ and always ended with a comma after the critical word. We selected critical words so that replacing ‘some’ by the quantifier 𠆊ll’ would yield a true statement in the underinformative condition (e.g., 𠇊ll people have lungs”), but a false statement in the informative condition (e.g., 𠇊ll people have pets”). The second clause always contained at least three words and provided additional information about the critical word, the main NP in the scalar clause (e.g., ‘people’) or the scalar clause as a whole, and was created so that the complete sentence constituted a logically true statement in each condition. Critical words in the two conditions were approximately matched for average length in number of letters (underinformative, informative, M = 6.7/7.0, SD = 1.8/2.0) and log frequency (Francis & Kucera, 1976 underinformative, informative, M = 1.73/1.91, SD = 2.29/2.03). Semantic similarity values were calculated for the critical words within the underinformative and informative sentences using Latent Semantic Analysis (Landauer & Dumais, 1997 Landauer, Foltz, & Laham, 1998 available on the Internet at http://lsa.colorado.edu). As expected, underinformative words yielded a higher LSA value than informative words (underinformative, informative M =.33/.17, SD =.23/.18 t(138) = 4.58, p < .001). As noted in the Introduction, higher LSA values are generally associated with smaller N400 amplitudes compared to lower LSA values, because the LSA values reflect in part the amount of lexico-semantic priming a word receives from the preceding context.

For the semantic fit manipulation, we constructed another 70 sentence pairs that were identical except for the critical word. Critical words were selected that were relatively congruous or incongruous to the sentence with regard to world knowledge (see Table 1 for examples). Critical words in the two conditions were matched for average length in letters (congruous, incongruous, M = 6.4/6.3, SD = 2.1/1.7) and log frequency (Francis & Kucera, 1982 congruous, incongruous, M = 1.46/1.50, SD = 1.74/1.88). Semantic similarity values were calculated for the congruous, incongruous words using Latent Semantic Analysis. Good semantic fit words yielded a higher LSA value than poor semantic fit words (congruous, incongruous, M =.22/.14, SD =.11/.08 t(138) = 5.31, p < .001). At least two words followed the critical words before the sentence ended.

We also created 35 filler sentences that each had a similar sentence structure as the scalar sentences but that always started with the quantifier ‘many’, and involved a simple and true statement (e.g., “Many vegetarians eat bean curd, which is rich in protein.”).

We created two counterbalanced lists so that each sentence appeared in only one condition per list, but in all conditions equally often across lists. Within each list, items were pseudorandomly mixed with the 70 sentences containing a semantic fit manipulation (35 containing a relatively good fitting critical word, 35 containing a relatively poor fitting critical word) and the 35 filler sentences to limit the succession of identical sentence types, while matching trial-types on average list position.

The Autism-Spectrum Quotient

The AQ (Baron-Cohen et al., 2001) is a self-administered questionnaire that is designed to measure the extent to which adults with normal intelligence possess traits associated with Autism Spectrum Disorder (ASD). Although this scale is not a diagnostic measure, its discriminative validity as a screening tool has been clinically tested (Woodbury-Smith, Robinson, Wheelwright, & Baron-Cohen, 2005). The test consists of 50 items, made up of 10 questions assessing five subscales: Social Skill (e.g., “I would rather go to a library than a party”), Communication (e.g., “I frequently find that I don’t know how to keep a conversation going”), Imagination (e.g., “When I’m reading a story, I find it difficult to work out the characters’ intentions”), Attention To Detail (e.g., “I usually notice car number plates or similar strings of information”), and Attention-Switching (e.g., “I frequently get so absorbed in one thing that I lose sight of other things”). Half the questions are worded to elicit an 𠆊gree’ response and the other half a 𠆍isagree’ response, addressing demonstrated areas of cognitive characteristics in ASD (DSM-IV, 1994 Baron-Cohen et al., 2001). Higher scores on the AQ indicate stronger presence of traits associated with ASD. A score of 32+ appears to be a useful cutoff for distinguishing individuals who have clinically significant levels of autistic traits (Baron-Cohen et al., 2001 the maximum score of the participants in our study was 30). Such a high score on the AQ however does not mean that an individual has autism, because a diagnosis is only merited, based on diagnostic measures such as the DSM-IV (1994), ADI-R (Lord, Rutter & Couteur, 1994) or ADOS-G (Lord et al., 2000), if the individual is suffering a clinical level of distress as a result of their autistic traits. In the current study, the AQ was administered in a quiet room subsequently to the ERP experiment, and took each participant about 10 minutes.

Procedure

Participants silently read sentences, presented word-by-word and centered on a computer monitor, while minimizing eye-movements and blinks. There was no task other than reading for comprehension. To parallel natural reading times (Legge, Ahn, Klitz & Luebker, 1997), all words were presented using a variable presentation procedure (Otten & Van Berkum, 2008 see also Nieuwland & Kuperberg, 2008). Word duration in ms was computed as ((number of letters × 27) + 187), with a 10 letter maximum. Also, to mimic natural reading times at clause boundaries (e.g., Hirotani, Frazier & Rayner, 2006 Legge et al., 1997 Rayner, Kambe & Duffy, 2000), critical words (which were followed by a comma) were presented for an additional 227 ms, and sentence-final words for an additional 500 ms. All inter-word-intervals were 121 ms. Following sentence-final words, a blank screen was presented for 500 ms, followed by a fixation mark at which subjects could blink and self-pace on to the next sentence by a right-hand button press. Participants were given six short breaks. Total time-on-task was approximately 40 minutes. After the ERP experiment, each subject was allowed a short break to wash up and was then administered a brief exit-interview, followed by the Autism-Spectrum Quotient questionnaire.

In the exit-interview, participants received a booklet that contained 6 pages and were instructed to answer the question from the booklet page-by-page without looking at the subsequent pages. On page 1, subjects were asked to report whether they noticed anything about the sentences they read and what research question(s) they thought the experiment was about. On page 2, an example of an informative scalar sentence was given, and participants reported whether they thought that sentences starting with ‘Some’ stood out, what they thought the purpose of these sentences was, and what research question these sentences involved. On page 3, subjects reported whether they thought that some of the sentences in the experiment sounded odd and provided a brief explanation why they thought this. On pages 4 and 5, subjects were presented with 10 different scalar statements, including informative and underinformative scalar sentences truncated after the CW as well as longer sentences that contained locally informative or under informative phrases. Subjects were asked to rate whether each sentence was true (1=false, 5=true) and how normal they would find it if somebody said this (1=odd, 5=normal). On page 6, subjects were informed that a sentences like “Some people have lungs” could be rated as false (because the sentence implies that most people do not have lungs) or true (because there are at least some people in the world that do have lungs). The subjects were asked to report whether they thought during the experiment about whether these sentences were true or false, whether they during the experiment ‘treated’ these sentences as true or false, and how consistently they did this (1=very inconsistently, 5=very consistently).

EEG Recording

The electroencephalogram (EEG) was recorded from 29 tin electrodes held in place on the scalp by an elastic cap (Electro-Cap International, Inc., Eaton, OH, USA). Electrode locations included Fz, Cz, Pz, Oz, Fp1/2, F3/4, F7/8, FC1/2, FC5/6, C3/4, T3/4, T5/6, CP1/2, CP5/6, P3/4, P7/8, O1/2, and 2 additional EOG electrodes all were referenced to the left mastoid). The EEG recordings were amplified (band-pass filtered at 0.01 Hz� Hz) and digitized at 200 Hz. Impedance was kept below 5 kOhm for EEG electrodes. Prior to off-line averaging, single-trial waveforms were automatically screened for amplifier blocking and muscle/blink/eye-movement artifacts over 850 ms epochs (starting 100 ms before CW onset). Two participants were excluded due to excessive artifacts (mean trial loss > 50%). For the remaining 29 participants, average ERPs (normalized by subtraction to a 100 ms pre-stimulus baseline) were computed over artifact-free trials for CWs in all conditions (mean trial loss across conditions 11%, range 0�%, without substantial differences in mean trial loss across conditions).

Statistical analysis

For all analyses reported below, the Greenhouse/Geisser correction was applied to F tests with more than one degree of freedom in the numerator. Note that due to the large number of trials needed for averaging in ERPs (which reduces the probability that the results hinge on just a few odd items), statistics are only reported for by subjects analyses, and analyses by items are not included.

RESULTS

Main effect of informativeness

Critical words elicited very similar N400 responses in the underinformative and the informative statements (see Figure 1 , left panel). Because modulation of the N400 ERP is generally maximal at posterior electrodes (e.g., Kutas et al., 2006), we divided all electrodes into anterior electrodes (F3/4, F7/8, F9/10, FC1/2, FC5/6, FP1/2, FPz, Fz) and posterior electrodes (Pz, Oz, CP1/2, CP5/6, P3/4, P7/8, O1/2) for subsequent analyses. Using mean amplitude in the 350 to 450 ms time window, a 2 (informativeness: informative, underinformative) × 2 (AP distribution: anterior, posterior) repeated measures analysis of variance (ANOVA) revealed that there was no statistically significant difference between the ERP responses to informative and underinformative statements, and no interaction effect between informativeness and AP distribution.

Left panel: Grand-average event-related potential (ERP) waveforms elicited by critical words in underinformative (dotted lines) and informative (solid lines) statements from Experiment 1, shown at electrode locations Cz, Pz, and Oz. In this and all following figures, negativity is plotted upwards. Middle panel: Grand average ERPs elicited by critical words in underinformative and informative statements per AQ Communication group in Experiment 1, and corresponding scalp distributions of the mean difference effect (underinformative minus informative sentences) in the 350- to 450 ms analysis window. Right panel: Correlation between N400 effect and AQ Communication score.

AQ-Comm score and ERP responses to informativeness

AQ scores ranged from 9 to 30 (M=21, SD=7.04). To explore the role of pragmatic abilities, we first grouped the participants into low AQ-Comm (N=15) and high AQ-Comm (N=14) groups based on the median split of scores on the Communication subscale. AQ-Comm score for the low AQ-Comm group ranged from 0 to 5 (M=2.33, SD=.51 7 males and 8 females, mean age 20.9 years, mean total AQ score 15.8), and from 6 to 9 for the high AQ-Comm group (M=7.2, SD=.28 8 males and 6 females, mean age 19.3 years, mean total AQ score 26.5). The two AQ-Comm groups showed statistically significant differences in AQ-Comm score (t(27)=8.34, p<.001) and in total AQ score (t(27)=6.24, p<.001), as well as in age (t(27)=2.49, p<.05 when entered into the subsequent analyses as a covariate, the factor age, however, did not change the patterns of results.

Grand average ERPs for the two groups are displayed in Figure 1 (middle panel). Using mean amplitude in the 350 to 450 ms time window, the overall ANOVA revealed a significant 2 (informativeness: informative, underinformative) × 2 (AQ-Comm Group: low AQ-Comm, high AQ-Comm) interaction effect when using all electrodes (F(1,27)=9.45, p=.005). There was no significant 3-way interaction with AP distribution (F(1,27)=2.19, p=.15), but the Informativeness by AQ-Comm group interaction effect was statistically significant when using only posterior electrodes (F(1,27)=11.54, p=.002), but only marginally significant when using anterior electrodes (F(1,27)=3.3, p=.07). This predominantly posterior distribution of N400 modulation is consistent with the N400 literature (e.g., Kutas et al., 2006).

Simple main-effect analysis for the groups separately, using posterior electrodes only, showed that underinformative statements elicited larger N400 responses than informative statements in the low AQ-Comm group (F(1,14)=5.57, p=.033, CI −.82 ± .75), whereas informative statements elicited larger N400 responses than underinformative statements in the high AQ-Comm group (F(1,13)=6.12, p=.028, CI 𢄡.38 ± 1.2). There was no statistically significant effect of informativeness in the two AQ-Comm groups separately when taking into account anterior electrodes only (Fsρ, n.s.).

As can be seen from Figure 1 , there appeared to be differential effects of informativeness for the two groups before the 350� ms time window. We therefore performed additional 2 (informativeness: informative, underinformative) × 2 (AQ-Comm Group: low AQ-Comm, high AQ-Comm) ANOVAs for the 50�, 150� and 250� time windows. These revealed some significant effects within early time windows (50� ms in the low AQ-Comm group, 150� ms in the high AQ-Comm group see Appendix A for full report, which can be found at http://www.nmr.mgh.harvard.edu/kuperberglab/materials.htm). We were concerned that these early effects of informativeness reflected an artefactual side effect of dividing subjects on the basis of their AQ-Comm score. It is well-known that with limited numbers of EEG trials going into the average of a single subject, single-subject ERPs constitute unknown mixtures of critical ERP effects and residual EEG background noise which could, in principle, explain the early onset ERP differences. We therefore repeated analyses using a longer, 500 ms pre-CW baseline thus reducing noise in the baseline time window (and consequently, in the post-baseline ERP signal). ERP difference effects that truly are the result of the experimental manipulation should survive this longer baseline analysis. The corresponding figures for these analyses can be found at the website as referenced above. After rebaselining, the early effects in the 50� and 150� ms windows disappeared but left the main pattern of results in the 250� and 350� ms windows unchanged (see Appendix A). Additional analyses for the post-450 ms time windows using the original baseline as well as the new baseline can also be found on our website.

Correlation analysis for AQ-Comm scores and ERP responses to informativeness

We also performed a correlation analysis that took into account the full range in individual AQ-Comm scores, and revealed a negative correlation between AQ-Comm score and the mean ERP difference score calculated as underinformative minus informative in the 350� ms time window at posterior electrodes (Pearson’s r = −.53, p=.003 see Figure 1 , right panel). This correlation effect was also present for total AQ score (r = −.55, p=.002), the Social Skill subscale score (r = −.45, p=.014) and Attention-Switching subscale score (r = −.55, p=.002), but was not significant for scores on the subscales Imagination (r = −.21, p=.29) and Attention To Detail (r =.17, p=.39). We should note that the Attention-Switching subscale and the Communication subscale were also the strongest interrelated subscales, so the effects of these subscales are hard to tease apart.

ERP responses to informativeness and the role of LSA

As mentioned in the Introduction, the content words in underinformative statements co-occur in language relatively more frequently than those in the informative statements, as reflected by their differences in LSA values. However, not each underinformative statement from each sentence pair had a larger LSA value than its informative counterpart. This allowed us to separate our items into one set that had a relatively small LSA difference between informative and underinformative sentences (LSA(underinformative-informative), M = 𢄠.02, SD = 0.12), and one set that had a relatively large LSA difference across conditions (M =0.34, SD =0.18). By computing ERPs separately for these two sets for each group, we investigated the effect of informativeness while controlling for lexical-semantic factors.

The corresponding figures for these analyses can be found at (http://www.nmr.mgh.harvard.edu/kuperberglab/materials.htm). These plots reveal clear differences between the low and high AQ-Comm groups in N400 modulation by LSA and informativeness. Analyses focusing on N400 peak amplitude modulations across posterior electrodes in the 350� ms time window showed that the informativeness by LSA difference interaction effect was significant in the high AQ-Comm group (F(1,13)=5.38, p=.037), but not in the low AQ-Comm group (F(1,14)=.02, p=.90). Follow-ups showed that, in the low AQ-Comm group, critical words in underinformative statements elicited a larger N400 than those in informative statements, both when there was a relatively small and a relatively large LSA difference between conditions (small difference, F(1,14)=2.37, p=.043, CI −.84 ± .76 large difference, F(1,14)=2.19, p=.052, CI −.80 ± .77). In the high AQ-Comm group, however, underinformative statements elicited a lower N400 than informative statements only when there was a relatively large LSA difference (F(1,13) =4.01, p= 0.001, CI 𢄢.25 ± 1.21), but not when there was a relatively small LSA difference (F(1,13) =.21, p= 0.834, CI −.17 ± 1.76).

In sum, whereas we found a typical modulation of LSA in the high AQ-Comm group, the pragmatic N400 effect in the low AQ-Comm group was insensitive to LSA.

Group differences in ERP responses to sentence-final words

We also examined the ERP responses to sentence-final words in underinformative and informative statements between the two AQ-Comm groups (see Figure 2 ). Statistical analyses were carried out using mean amplitude in the 300 to 500 ms. The sentence-final words involved different word categories, and there may have been differences in naturalness of the second clauses following informative versus underinformative statement. Our main interest in this comparison was therefore not the main effects of informativeness (positive ERPs to sentence-final words of underinformative than informative sentences across both groups, F(1,27)=20.28, p<.001, CI .96 ± .46), but rather the differences between the two AQ-Comm groups to the same set of stimuli. As shown in Figure 2 , there was a clear differential ERP effect on the sentence-final words in underinformative and informative statements in the low AQ-Comm group, but less so in the high AQ-Comm group. This differential ERP effect appeared to have a slightly frontal distribution (i.e., inconsistent with an N400 effect scalp distribution), and may reflect additional sentence wrap-up processing. Across all electrodes, the overall ANOVA revealed a marginally significant informativeness by AQ-Comm group interaction effect (F(1,27)=3.88, p=.059) and follow-ups showed that the modulation by informativeness was significant in the low AQ-Comm group (F(1,27)=17.56, p=.001, CI 1.36 ± .70), but only marginally significant in the high AQ-Comm group (F(1,27)=3.64, p=.079, CI .54 ± . 60). A 2 (informativeness: informative, underinformative) × 2 (AP distribution: anterior, posterior) ANOVA revealed no interaction effect of informativeness with anterior-posterior distribution (Fρ), and there was no significant interaction between informativeness, AQ-Comm group and distribution (Fρ). Because the effect was prolonged, we repeated the above analyses in the 500� ms window and this yielded the same pattern of results.

Grand average ERPs elicited by sentence-final words in underinformative (dotted lines) and informative (solid lines) statements per AQ Communication group in Experiment 1, shown at electrode locations FPz, Cz, and Oz, and corresponding scalp distributions of the mean difference effect (underinformative minus informative sentences) in the 300- to 500 ms and the 500- to 700 ms analysis window.

Group differences in ERP responses to real-world congruous versus incongruous sentences

To determine the specificity of the group differences in ERP responses to underinformativeness, we also examined whether the groups differed in their N400 modulation to words that were congruous versus incongruous with real-world knowledge. We compared the modulation of the N400 by words with a relatively poor versus good fit based on real-world knowledge across the two groups. As can be seen from Figure 3 , the modulation of the N400 was quite similar across the two groups. Using mean amplitude at posterior electrodes in the 350 to 450 ms time window, the overall 2 (Real world congruity: congruous, incongruous) × 2 (AQ-Comm Group: low AQ-Comm, high AQ-Comm) ANOVA revealed that the incongruous words evoked a larger amplitude N400 than congruous words (F(1,27)=19.28, p<.001, CI 𢄡.35 ± .64) However, no Real world congruity by AQ-Comm Group interaction was observed (F(1,27)=1.77, p=.19). There was also no significant Real world congruity by AQ-Comm Group interaction in the adjoining 250� and 450� time windows (all Fs < 2, ns.). Consistent with the absence of this interaction, there was also no significant correlation between the N400 difference effect in the 350� ms time window and AQ-Comm score (Pearson’s r = −.29, p=.13).

Left panel: Grand average ERPs elicited by words that had a relatively poor (dotted lines) and relatively good (solid lines) semantic fit per AQ Communication group in Experiment 1, and corresponding scalp distributions. Right panel: Correlation between N400 effect and AQ Communication score.

Exploratory analyses of ERP responses to the scalar quantifiers

Although our experiment was not specifically designed to examine ERP responses to the scalar quantifiers, we performed an exploratory analysis to investigate whether there were differences between the two AQ-Comm groups in ERP responses to the sentence-initial scalar quantifiers ‘Some’ (the sentence-initial word of the experimental sentences) and ‘Many’ (the sentence-initial word in 35 filler sentences). The reasoning behind this analysis was that if the quantifiers themselves evoke differential pragmatic processing, then the differences in pragmatic abilities between the groups may already become apparent at the quantifier. We note that the quantifier ‘many’ can elicit a “not all” implicature as can ‘some’, so this comparison is not optimal for examining differences in pragmatic processing. However, because these quantifiers can be arranged on a scale of informativeness where ‘many’ is stronger than ‘some’, the ‘some’ implicature would include “not many” as well as “not all”. In this sense, and particularly in an experimental context in which both are repeatedly presented, one could argue that these scalar quantifiers are associated with implicatures that are of different strength.

The figures corresponding to this analysis can be accessed at http://www.nmr.mgh.harvard.edu/kuperberglab/materials.htm. In the high AQ-Comm group, ‘Many’, relative to ‘Some’ appeared to evoke a slightly more negative right-lateralized waveform at about 300� ms and a more positive frontally-distributed waveform at about 650� ms. There appeared to be no such effect in the low AQ group. We performed a series of repeated measures ANOVAs to test for the 2 (quantifier: some, many) by 2 (AQ-Comm group: low AQ-Comm, high AQ-Comm) interaction, in adjoining 50 ms time windows between 100 and 800 ms after quantifier onset, using all electrodes or only anterior or posterior electrodes. The only (marginally) significant interaction effect was found in the 650� ms window using anterior electrodes (F(1,27)=3.77, p=.063). Follow-up analyses confirmed that ‘many’ elicited more positive ERPs than ‘some’ in the high AQ-Comm group (F(1,13)=14.70, p=.002, CI 𢄢.04 ± 1.15), but there was no difference between the two quantifiers in the low AQ-Comm group (F(1,14)=.07, p=.80, CI −.21 ± 1.68). In addition, this frontal positivity effect showed a marginally significant correlation with AQ-Comm score (Pearson’s r = .34, p=.073). There was also a marginally significant correlation between the frontal positivity effect and the differential ERP effect at the critical words, suggesting that participants who showed a larger frontal positive effect were less likely to show a pragmatic N400 effect later in the sentence (r = −.35, p=.06). The frontal positivity, however, did not predict the N400 modulation by real-world congruity (Pearson’s r = −.15, p=.46).

Exit interview

We examined whether the AQ-Comm groups differed in their exit-interview ratings for truth-value and naturalness. A 2 (AQ-Comm group: low AQ-Comm, high AQ-Comm) by 2 (informativeness: informative, underinformative) ANOVA revealed no group differences in the truth-value ratings and the naturalness ratings (all Fsς). In addition, underinformative and informative statements received similar truth-value ratings (tρ) but different naturalness ratings (t(1,28)= 15.98, p < .001).

DISCUSSION

Across all participants, underinformative statements elicited N400 responses that were similar to those elicited by informative statements. However, there was marked heterogeneity across individuals in N400 modulation, with some individuals showing a larger N400 to critical words in underinformative than in informative statements, and others showing the opposite pattern of modulation (i.e., a larger N400 to critical words in informative than underinformative statements). Most importantly, these individual differences could be explained by taking into account individual variability in real-world pragmatic language ability. Individuals with few pragmatic language difficulties (as indexed by a low score on the AQ Communication subscale) were more sensitive to the pragmatic ‘violation’ of underinformativeness. This opposite pattern of activity was clear both in a median split analysis that dichotomized the two groups and in a correlation analysis that took into account the full range in individual AQ-Comm scores. Importantly, this N400 modulation by AQ-Comm score did not extend to the N400 responses to words with a relatively poor fit with respect to world knowledge, suggesting that AQ-Comm score was fairly specific in explaining the pattern of N400 modulation to the pragmatic violations. In addition, the two groups were differentially sensitive to lexical-semantic co-occurrence: whereas the low AQ-Comm group showed a pragmatic N400 effect independently of whether the underinformative and informative sentences were matched for LSA, the high AQ-Comm group’s ERP responses were modulated by LSA. Finally, we also explored ERP responses to the scalar quantifier ‘some’ versus’ many’. Although these quantifiers could be argued to evoke related (although not identical) pragmatic processes, rendering this comparison suboptimal for examining potential differences in pragmatic processing, we did find some preliminary evidence that pragmatic abilities influenced processing at the scalars themselves.

If one considers only the pragmatically skilled participants, our results show that pragmatically underinformative statements are associated with early semantic processing costs (see also Nieuwland & Kuperberg, 2008). This result suggests that the pragmatic meaning of a scalar quantifier can, in principle, be rapidly and incrementally incorporated during sentence comprehension, a finding that is consistent with models of language processing that incorporate an incremental contribution of pragmatic factors (Crain & Steedman, 1985 Altmann & Steedman, 1988 Tanenhaus & Trueswell, 1995) and with the results of studies from the visual world paradigm (Grodner et al., 2010).

In contrast to the more pragmatically skilled participants, however, the less pragmatically skilled participants showed no pragmatic N400 effect. Their processing was rather driven primarily by the relatively closer lexical-semantic relationships between individual words in these statements which overrode pragmatic factors. One possible interpretation of these results is that these individuals, who report difficulties with pragmatic abilities in everyday life, were simply incapable of generating scalar inferences. One could argue that this conclusion is in line with the notion from Relevance Theory that scalar inferences are not obligatory (see also Bott & Noveck, 2004 Noveck & Posada, 2003) but depend on constraints from the context and possibly from neuropsychological factors (see also Happé, 1993).

However, if one takes into account the ERP patterns elicited by sentence-initial scalars, a more complicated picture emerges. The exploratory analyses of ERP responses elicited by the sentence-initial scalar quantifiers suggest that pragmatic abilities influenced scalar statement processing already at the scalar quantifier. Perhaps counterintuitively, differential processing of the two different scalar quantifiers was most pronounced in the pragmatically less skilled participants. We will provide more in-depth discussion of these issues in the general discussion, but what these results suggest is that pragmatically less skilled participants may have been able to temporarily ignore or inhibit their pragmatic knowledge during the processing of the critical words (see Feeney et al., 2004 Handley & Feeney, in press), instead of being insensitive to pragmatic constraints (e.g., Schindele et al., 2008).

In sum, our results suggest that pragmatic constraints can have rapid effects during on-line sentence comprehension. When pragmatic constraints are taken into account, as in low AQ-Comm people, they may guide expectations about upcoming words through the pragmatic presumption of informativeness. But when these constraints cannot be used or they are ignored, as in the high AQ-Comm group, the effects of other constraints may surface, such as the effect of lexical-semantic relationships. In our second experiment, we examined the incremental processing of weak scalar quantifiers further by modulating the effect of pragmatic constraints through linguistic focus.


Empathy predicts false belief reasoning ability: evidence from the N400

Interpreting others’ actions relies on an understanding of their current mental state. Emerging research has begun to identify a number of factors that give rise to individual differences in this ability. We report an event-related brain potential study where participants (N = 28) read contexts that described a character having a true belief (TB) or false belief (FB) about an object’s location. A second sentence described where that character would look for the object. Critically, this sentence included a sentence-final noun that was either consistent or inconsistent with the character’s belief. Participants also completed the Empathy Quotient questionnaire. Analysis of the N400 revealed that when the character held a TB about the object’s location, the N400 waveform was more negative-going for belief inconsistent vs belief consistent critical words. However, when the character held an FB about the object’s location the opposite pattern was found. Intriguingly, correlations between the N400 inconsistency effect and individuals’ empathy scores showed a significant correlation for FB but not TB. This suggests that people who are high in empathy can successfully interpret events according to the character’s FB, while low empathizers bias their interpretation of events to their own egocentric view.


The N400 as an index of racial stereotype accessibility

doi:10.1093/scan/nst018 SCAN (2014) 9, 544 ^552 1 2 3 Eric Hehman, Hannah I. Volpert, and Robert F. Simons 1 2 Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA, Department of Psychological Sciences, University of Missouri, Columbia, MO 65211, USA, and Department of Psychology, University of Delaware, Newark, DE 19716, USA The current research examined the viability of the N400, an event-related potential (ERP) related to the detection of semantic incongruity, as an index of both stereotype accessibility and interracial prejudice. Participants EEG was recorded while they completed a sequential priming task, in which negative or positive, stereotypically black (African American) or white (Caucasian American) traits followed the presentation of either a black or white face acting as a prime. ERP examination focused on the N400, but additionally examined N100 and P200 reactivity. Replicating and extending previous N400 stereotype research, results indicated that the N400 can indeed function as an index of stereotype accessibility in an interracial domain, as greater N400 reactivity was elicited by trials in which the face prime was incongruent with the target trait than when primes and traits matched. Furthermore, N400 activity was moderated by participants self-reported explicit bias. More explicitly biased participants demonstrated greater N400 reactivity to stereotypically white traits following black faces than black traits following black faces. P200 activity was additionally associated with participants implicit biases, as more implicitly biased participants similarly demonstrated greater P200 reactivity to stereotypically white traits following black faces than black traits following black faces. Keywords: N400 stereotyping prejudice P200 intergroup dynamics INTRODUCTION The N400 has only recently been explored as a method of assessing stereotype accessibility. Individuals who associate certain groups with The complexities of human society necessitate the usage of stereotypes particular characteristics should demonstrate larger N400s when pre- as cognitive shortcuts to sort social information. These shortcuts in- sented with characteristics incongruent with those groups because they fluence decision making regarding the targets of stereotypes (Cuddy are less associated in memory, compared with congruent, more easily et al., 2007), sometimes indirectly contributing to intergroup prejudice accessible stereotypes. Some evidence indicates that this is the case. For and discrimination. Recent work has turned to event-related potentials example, in research examining gender stereotypes, pairing &lsquowomen&rsquo (ERPs) to study and measure the accessibility of stereotypes (White with stereotypically male traits elicited greater N400 reactivity than et al., 2009 Wang et al., 2011), circumventing the limitations of the when &lsquowomen&rsquo and stereotypically female traits were paired (White self-report and behavioral paradigms of previous work by examining et al., 2009). Other work has claimed that N400 variation can function underlying processes with greater temporal sensitivity. This research to index prejudice, as shown by larger N400s exhibited by urban has specifically focused on a negative-going ERP occurring 400 ms Chinese when positive adjectives were paired with disparaged rural after stimulus onset (the N400) due to its well-understood association outgroup migrant workers relative to when these adjectives were with the ease of integrating a semantic stimulus with its current con- paired with the ingroup (Wang et al., 2011). text (Kutas and Hillyard, 1984 Kutas and Federmeier, 2000). The primary goal of this study was to replicate and extend this research by examining N400 responses to negative and positive stereotypes in Stereotypes and prejudice an intergroup context. In addition, a secondary goal was to explore The conclusion that the N400 can function as an index of prejudice possible links between neural responses to congruent and incongruent should be made tentatively, however, due to how stereotypes and stereotypes with participants&rsquo implicit and explicit racial bias. prejudice are traditionally conceptualized. Stereotypes and prejudice are separate constructs, the former referring to associations between a The N400 specific group and meaningful behaviors or concepts, whereas the Theoretically rooted in conceptual priming and spreading activation, latter refers to evaluative biases regarding a group, typically negative larger N400 reactivity reflects the difficulty of accessing information in nature (Dovidio et al., 1986). Awareness of stereotypes does not stored in semantic memory associated with a meaningful stimulus necessitate biased thoughts or behavior. Indeed, a growing literature (Kutas and Federmeier, 2000). For example, the sentence &lsquoJordan was suggests that each may depend on separate neural processes and pre- eaten by a DOORWAY&rsquo would elicit a larger N400 than &lsquoJordan was eaten dict different forms of discriminatory behavior (Dovidio et al., 2002 by a DINOSAUR&rsquo, as dinosaurs and eating are more semantically asso- Amodio and Devine, 2006 Amodio, 2008). Should N400 activity be ciated than doorways and eating. Although initially discovered examin- driven only by the difficulty of accessing information stored in seman- ing incongruent words in sentences, research has since demonstrated tic memory, then it may be better characterized as indexing stereotype that the N400 is elicited by incongruent word pairings (Bentin et al., accessibility, rather than negative or positive evaluations of an out- 1985), words incongruent with music (Daltrozzo and Schoen, 2008) and group (i.e. prejudice). incongruent words and images (Nigam et al., 1992). This activity likely Recent research contrasting sequential with evaluative priming is originates in the middle superior temporal lobes, associated with the consistent with this interpretation. Sequential priming is used to representation of semantic information (Lau et al., 2008). investigate how concepts may be associated in memory (Bargh and Chartrand, 2000) and involves a prime quickly followed by a target. Received 10 September 2012 Accepted 27 January 2013 Participants make non-evaluative decisions about each target, such as Advance Access publication 5 February 2013 whether it is a word or non-word (Neely, 1991). Participants are typ- The first two authors contributed equally to this work. ically faster and more accurate in identifying target words primed by Correspondence should be addressed to Eric Hehman, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA. E-mail: [email protected] related than unrelated words. Evaluative priming, on the other hand, The Author (2013). Published by Oxford University Press. For Permissions, please email: [email protected] N400 SCAN (2014) 545 occurs when negatively or positively valenced primes facilitate evalu- to test this possibility in a semantic priming paradigm, while simul- ative responses to targets congruent in valence. Thus, semantic priming taneously replicating the limited research examining the N400 and occurs when the meaning of a prime and target are associated, whereas stereotype accessibility. Specifically, we examined ERPs following evaluative priming is evident when the prime and target share a both negative and positive, stereotypically in- and outgroup traits in valence, but not necessarily a meaning. Although seemingly similar, an inter-racial context. unique neural responses to each paradigm indicate the processes EEG was recorded while participants completed a semantic priming involved may be distinct evaluative priming solely influenced the task, seeing first a black or white face prime, followed by negative and magnitude of the late positive potential (LPP), and not the N400 positive words stereotypically characteristic of blacks and whites. ERP (Herring et al., 2011). This finding indicates that semantic and evalu- analysis focused on the N400, but additionally examined the N100, ative priming may be driven by separable neural mechanisms and that associated with early attentional processes (Hillyard and Mu ¨ nte, 1984), the N400 may not be elicited by the negative and positive evaluations and the P200, associated with greater attention to negative, threatening required for prejudice, thus being indicative solely of stereotype stimuli (Bartholow et al., 2003) and implicated in implicit bias (Correll accessibility. et al., 2006 Payne, 2006 He et al., 2009). ERP components were then examined for relationships with both implicit bias, collected during separate experimental sessions using the Implicit Association Test N400 and prejudice (IAT Greenwald et al., 2003) and self-reported explicit bias, as mea- Despite evidence that evaluative biases may not be involved in the sured by the Attitudes Toward Blacks (ATB) scale (Brigham, 1993). N400 directly, the possibility remains that this component can be utilized as an indirect measure of prejudice. Both positively and nega- METHOD tively valenced stereotypes exist for many groups, are learned and sub- Participants and design ject to reinforcement in memory (Gaertner and McLaughlin, 1983). Thus, an individual who strongly associates a group with negative Participants included 32 white, right-handed undergraduates (14 male) stereotypes might demonstrate a large N400 to positive associations who participated for partial course credit in a 2(Prime: Black, with that group. A disparity in N400s elicited by negative and positive White) 2(Valence: Negative, Positive) 2(Congruence: Congruent, traits might be indirectly associated with participant behavior, just as Incongruent) repeated measures design. stereotypes exert an influence on behavior (Cuddy et al., 2007). A physiological indicator of stereotype accessibility or prejudice would Stimuli be extremely valuable due to the social desirability difficulties inherent Face primes for the sequential priming task were color photos of 36 in conscious or self-reported measures of bias (Dienstbier, 1970 Plant whites and 36 blacks with neutral expressions. Negative and positive, and Devine, 1998). stereotypically black and white traits were selected from previous re- Indeed, some research has attempted to examine the link between search on stereotype content (Kawakami and Dovidio, 2001 Madon N400 reactivity and prejudice (Wang et al., 2011). However, the con- et al., 2001) and included based on pilot testing during which 35 par- founding of the valence and stereotypicality of the target traits utilized ticipants evaluated 95 traits first on a stereotypically black¼1to in this research limit the conclusions that can be drawn regarding white¼ 7 and then a positive¼ 1 to negative¼ 7 continuum. Nine stereotype accessibility. For instance, &lsquoclean&rsquo, although positively traits evaluated as most black/positive (e.g. athletic), black/negative valenced, is more stereotypically associated with urban Chinese than (e.g. hostile), white/positive (e.g. educated) and white/negative (e.g. rural migrant workers, as the latter group performs hard labor in &lsquodis- spoiled) were selected, resulting in a total of 36 traits. Across race, tasteful jobs that the city residents are unwilling to do&rsquo (Wang et al., traits were rated as equally negative and positive, F(1, 34)¼ 0.26, 2011, p. 104). Should more controlled, negative and positive, stereo- P¼ 0.612 and did not vary in length by race F(1,32)¼ 0.00, typically ingroup and outgroup traits be utilized, the role of negatively P¼ 1.000 or valence condition F(1,32)¼ 0.51, P¼ 0.482 (Table 1). or positively valenced incongruities in driving N400 variation might be explored. Building on the above framework, our secondary goal was to explore links between ERPs and measures of implicit and explicit Table 1 Target traits and mean evaluations of negative to positive valence from pilot racial bias. Interpreting brain activity as a psychological phenomenon Black positive Mean White positive Mean can be misleading absent corroboration with other measures (Guglielmi, 1999 Amodio, 2008). This issue is particularly problematic Athletic 6.29 Educated 6.46 for existing N400 research on stereotyping, as N400 activity has not Cultural 5.86 Industrious 5.21 yet been linked to more traditional, implicit and explicit measures of Humorous 6.29 Managerial 6.35 Masculine 6.14 Rich 6.04 bias. Explicit biases are consciously endorsed beliefs and judgments Muscular 5.71 Smart 6.56 (Mitchell et al., 2005) predicting consciously controlled behaviors Rhythmic 5.71 Trusting 6.17 such as verbal bias during intergroup interactions (Dovidio et al., Strong 5.86 Wealthy 5.83 2002) or decreased political support for President Obama (Hehman Well-built 6.29 Well-traveled 5.00 et al., 2010). Implicit biases, on the other hand, generally manifest without an individual&rsquos awareness (Greenwald and Banaji, 1995) and Black negative Mean White negative Mean predict unconscious behavior, such as negative non-verbal gestures or facial expressions during interracial interactions (Dovidio et al., Armed 2.67 Boring 2.78 Delinquent 1.43 Greedy 2.08 2002), or seating distance from an outgroup member (Amodio and Hostile 1.71 Pasty 2.67 Devine, 2006). On welfare 1.14 Prejudiced 2.04 Poor 1.29 Pretentious 2.50 Quick tempered 2.00 Shallow 2.28 The current research Unemployed 1.29 Spoiled 2.12 In summary, the question of whether the N400 can be utilized as an Violent 1.14 Whiny 2.28 index of prejudice is currently unresolved. The current research sought 546 SCAN (2014) E. Hehman et al. Procedure (e.g. joy), and six &lsquobad&rsquo adjectives (e.g. cancer) that were evaluative in nature. Categories were paired creating either congruent (African Electroencephalography collection American and Bad, European American and Good) or incongruent Participants received a general description of the experiment while (African American and Good, European American and Bad) associ- being fitted with an electrode cap and then completed the sequential ations. Faces and adjectives presented in the IAT were different from priming task. The task was presented on a 17 inch CRT monitor using those presented during the sequential priming task. Participants Presentation (Neurobehavioral Systems). For each trial, the participant categorized each stimulus via response pad. Order of presentation would see either a black or white face, followed by a negative or posi- was counterbalanced. Higher values indicate greater ingroup evaluative tive trait that was either stereotypically congruent (e.g. a black stereo- bias. Participants were compensated in the form of $5 or course credit. type following a black face) or incongruent (e.g. a white stereotype As expected, implicit (IAT D: M¼ 0.37, s.d.¼ 0.35) and explicit bias following a black face) with the face prime. As explicit tasks increase (M¼ 5.14, s.d.¼ 1.00) were not correlated (r¼0.033, P¼ 0.867). the magnitude of the N400 (Chwilla et al., 2000), participants rated the traits as negative or positive by response pad, using their left and right index fingers, the assignment of which was counterbalanced across Data acquisition and reduction participants. After a 5-trial practice block, participants completed EEG data were collected from 32 Ag/AgCl electrodes embedded in an 4 blocks of 72 trials each, for a total of 288 trials. Condition was electrode cap. During recording, all activity was average referenced, randomized within block. On each trial, a fixation cross appeared while AFz served as the ground site. Electrode impedances were kept for 500 ms. Facial primes were then presented for 500 ms, followed below 20 K. Advanced Neuro Technology (ANT) acquisition hard- by a 500 ms blank screen before the target trait was presented for ware (Advanced Neuro Technology, Enschede, The Netherlands) was 1000 ms. A 1000 ms blank screen followed, after which the program used to amplify, digitize (512 Hz) and filter (bandpass 0.1&ndash30 Hz) the proceeded to the next trial regardless of response. EEG signal. The EEG was corrected for eyeblinks using Advance Source Analysis software from ANT. Trials exceeding 75 mV were rejected Implicit and explicit bias measures before signal averaging. Participants were pretested before the experimental session to assess To create ERPs, EEG was digitally re-referenced offline to the aver- their explicit attitudes regarding blacks on the ATB (Brigham, 1993 age of the mastoids. As the stimulus-onset asynchrony (SOA) was ¼ 0.81). Higher values indicate more positive feelings toward blacks, 1000 ms, epochs associated with each face&ndashtrait pair were time or less explicit bias. Following EEG collection (M¼ 2.6 days, s.d.¼ 4.11 locked to the presentation of the trait stimulus, rather than facial days, range¼ 13 days), participants completed an evaluative IAT prime. Trials with too many artifacts or with a participant response (Gaertner and McLaughlin, 1983) in a different location as part of that did not match the predetermined valence of the trait presented a presumably unrelated experiment, scored as recommended by were excluded from further analysis. Subjects with fewer than 20 usable Greenwald et al. (2003). Participants were randomly presented with trials in any of the 8 conditions were removed from analysis (n¼ 7). stimuli consisting of 6 white faces, six black faces, six &lsquogood&rsquo adjectives Two additional participants were removed for failure to follow Fig. 1 Virtual electrode clusters extracted from the spatial PCA. N400 SCAN (2014) 547 Fig. 2 ERP at virtual electrode 1 (A) compared with temporal PCA loadings (B) used to identify the N100 (Component 6), the P200 (Component 3) and N400 (Component 1). directions, resulting in 23 participants (7 male) suitable for data ana- RESULTS lysis. Each average was baseline corrected by subtracting the average We first present preliminary analysis regarding behavioral response voltage occurring during the 200 ms before stimulus onset from the latencies during the task. We then examine the primary hypotheses entire average. regarding N400 variance across conditions, before additionally inves- To reduce the dimensionality of the data, a spatial principle com- tigating N100 and P200 variation. Finally, we move on to exploring ponents analysis (PCA) was conducted on individual averages of each our secondary hypotheses regarding the relationships between ERP condition. The spatial PCA identifies and forms virtual electrodes from components and measures of implicit and explicit bias. We observed clusters of highly correlated electrodes and captures the variance no effects of gender, and the analyses reported below collapse across uniquely associated with the scalp distribution of the ERPs (Spencer this dimension. et al., 2001). Four virtual electrode clusters emerged from the spatial PCA accounting for 85.2% of the variance (Figure 1 Cluster 4 was Statistical approach excluded as it closely related to activity at the two mastoids). Next, Our primary hypotheses were tested by subjecting response latencies virtual ERPs were derived from the &lsquofactor scores&rsquo for each participant, and ERP components to a 2(Prime: Black, White) 2(Valence of condition and virtual electrode at all time points. Virtual ERPs were target: Negative, Positive) 2(Congruence: Congruent, Incongruent) then submitted to a temporal PCA, analyzing the covariance among repeated measures analysis of variance (ANOVA). time points for the 4 spatial factors, 8 experimental conditions and 23 A different approach was utilized to examine our secondary hypoth- participants to identify distinct components across time. Six temporal eses relating ERP components and prejudice measures. ERP difference components from the PCA were extracted that accounted for 92% of scores were created to examine the effect of congruence, initially col- the variance before varimax rotation. The temporal components were lapsing across valence, for each ERP component. These difference visually examined in conjunction with the virtual ERPs (Figure 2) to scores were created by subtracting ERP activity for incongruent identify three temporal components of interest: N100 (Component 6), conditions from congruent conditions, separately across race: (black P200 (Component 3) and N400 (Component 1). We statistically ana- lyzed all three temporal components at Virtual Electrode 1, where the congruent black incongruent) and (white congruent white incon- amplitude for each was maximal. Components 2 and 4 were not ana- gruent]. In other words, an average of the ERPs elicited in trials where lyzed because they reflected variance prior and subsequent to the epoch black faces were followed by words stereotypically associated with containing the ERP, and Component 5 was not analyzed as it did not whites were subtracted from an average of the ERPs elicited in trials reflect activity associated with Virtual Electrode 1. where black faces were followed by words stereotypically associated 548 SCAN (2014) E. Hehman et al. with blacks. The same was done for trials with white primes. In sep- P200 arate analyses, implicit and explicit bias scores were then regressed on A main effect of valence was evident, with greater P200 activity to both (black congruent black incongruent) and (white congru- negative traits, F(1, 22)¼ 6.69, P¼ 0.017,  ¼ 0.23, qualified by a ent white incongruent] difference scores simultaneously. Significant three-way Prime Valence Congruence interaction, F(1, 22)¼ prediction of these difference scores is analogous to within-subject 9.31, P¼ 0.006,  ¼ 0.30 (Figure 4). Simple effects revealed that fol- moderation (Judd et al., 2001). Because these initial difference scores lowing black face primes, incongruent negative traits elicited greater collapsed across the valence of trait to examine the effects of incon- P200 reactivity than incongruent positive traits, F(1, 22)¼ 9.17, gruence, additional difference scores were created for select follow-up P¼ 0.006,  ¼ 0.29. An opposite effect occurred following white analyses to explore the role of trait valence in eliciting responses. face primes, as congruent negative traits elicited greater P200 reactivity than congruent positive traits, F(1, 22)¼ 6.12, P¼ 0.022,  ¼ 0.22. Response latencies Greater P200 amplitudes to negative vs positive stimuli is consistent with previous research (Bartholow et al., 2003), although the differen- The ANOVA revealed two main effects of response latencies. tial elicitation of the P200 by incongruent traits following a black Participants responded more quickly both to traits primed by black prime and congruent traits following a white prime is novel. We faces, F(1, 22)¼ 6.16, P¼ 0.021,  ¼ 0.22, and to negatively valenced return to interpreting this result in the Discussion. traits, F(1, 22)¼ 5.33, P¼ 0.031,  ¼ 0.20. No other effects or inter- actions were present. Response latencies were not correlated with ERP activity. Relationships with implicit and explicit bias We next examined our secondary hypotheses regarding how differen- ERP reactivity across conditions tial N400 reactivity might correlate with more traditional measures of N400 implicit and explicit bias. Each ERP component was examined, but N100 activity was not moderated by implicit or explicit biases. The ANOVA examining N400 reactivity revealed a main effect of con- gruence, F(1, 22)¼ 4.88, P¼ 0.038,  ¼ 0.18. Larger negative deflec- tions were demonstrated in response to incongruent (M¼0.808, N400 s.d.¼ 0.80) than congruent face-trait pairings (M¼0.720, s.d.¼ As the N400 is a negative-going deflection, a difference score with a 0.80), indicating that counter-stereotypical traits were more difficult positive value indicates a larger N400 to incongruent compared with to access (see Figure 3 for raw ERPs). This result conceptually repli- congruent face&ndashtrait pairings. We first examined whether more expli- cates and extends previous research finding greater N400 reactivity for citly biased participants would demonstrate greater N400 reactivity incongruent gender stereotypes (White et al., 2009) by demonstrating than low-bias participants. ATB scores were regressed upon both the effect with a different task, SOA and stereotype group. Importantly, black and white congruence difference scores simultaneously. neither the prime valence congruence interaction, F(1, 22)¼ 1.63, Explicitly biased participants exhibited larger differences than low-bias P¼ 0.215, nor the two-way interactions predicting N400 reactivity participants in N400 activity between black congruent and incongruent were significant. Together, these results indicate that across all partici- trials (¼0.598, P¼ 0.003) (Figure 5), but not on white trials pants, stereotypes incongruent with blacks or whites, or stereotypes (¼0.038, P¼ 0.837). In other words, the more explicitly biased negative or positive in nature, did not differentially or multiplicatively the participant, the greater the N400 displayed to stereotypically elicit N400 activity. Rather, consistent with a non-evaluative interpret- white traits following a black face (compared with stereotypically ation of N400 reactivity, only congruence influenced N400 responses. black traits following a black face). The above analysis collapsed across stereotype valence. Thus, to N100 explore whether the effect was particularly driven by N400 reactivity A main effect of race of face prime emerged, F(1, 22)¼ 6.48, P¼ 0.018, to negative or positive stereotypes, two additional difference scores ¼ 0.23. Larger N100s were elicited by traits following black than contrasting N400 reactivity elicited by negative or positive stereotypes white faces. were simultaneously regressed on ATB scores. Again, the more Fig. 3 Raw ERPs for electrodes comprising virtual electrode 1 by condition. N400 SCAN (2014) 549 Fig. 4 P200 factor scores by condition. Fig. 5 (A and B) ERPs at virtual electrode 1. Black congruent conditions contrasted with black incongruent conditions for both low (A bottom half) and high (B upper half) explicitly biased participants. (C) Correlation between difference in black congruent vs black incongruent conditions and ATB scores across all participants. explicitly biased the participant, the greater the N400 demonstrated to persisted for an additional 250 ms, indicating that individuals with stereotypically white traits following a black face. Results indicated that greater explicit bias engaged in more prolonged processing. We N400s elicited by both incongruent positive (¼0.436, P¼ 0.031) return to this unexpected result in the Discussion. and incongruent negative traits (¼0.692, P¼ 0.001) were contri- Differential N400 reactivity between congruent and incongruent buting uniquely to the relationship with explicit bias, although the conditions following black primes robustly explained 42% of the effect was larger regarding negative traits. variance in ATB scores (R ¼ 0.417). No other effects regarding ATB Consistent with these results, N400 morphology varied between low scores were evident. As the N400 indexes the difficulty in accessing and high explicitly biased participants (Figure 5). For participants associated information (Nigam et al., 1992), this result indicates that lower in explicit bias, N400 activity was evident for approximately more explicitly biased participants may have struggled to incorporate 300 ms, but for participants higher in explicit bias, N400 activity both negative and positive stereotypically white traits with the context 550 SCAN (2014) E. Hehman et al. Fig. 6 Correlation between difference in black congruent vs black incongruent conditions and IAT scores across all participants. of black faces. Implicit bias was not related to N400 activity in any were not explicitly associating targets and primes hints at the condition. automatic nature of the association, supporting a spreading activation interpretation of the N400 (Franklin et al., 2007). However, the racial element of this task may have been apparent to participants, P200 and therefore, although it is clear that this task was less explicit than An analysis identical to that conducted with the N400 was conducted previous research, conclusive inferences regarding automaticity cannot regarding variation on the P200. Implicit and explicit bias scores were be made. regressed on the same series of condition-based difference scores. Furthermore, N400 reactivity was demonstrated with a task includ- Unlike N400 reactivity, explicit bias did not predict differential P200 ing a 1000 ms SOA. Research indicates that evaluative priming does activity between any conditions. not occur with SOAs of greater than 300 ms (Hermans et al., 2001, Implicit bias, on the other hand, did predict differential P200 2003 Gawronski et al., 2005 Castner et al., 2007). Thus, the present reactivity between conditions. Individuals with greater implicit bias result reinforces the semantic, rather than evaluative, nature of our demonstrated greater P200 reactivity differences between congruent paradigm, as well as indicating that separable neural systems may be and incongruent trials primed by black faces (¼0.560, involved with evaluative and semantic priming effects. The current P¼ 0.014), but not trials primed by white faces (¼0.245, P¼ 0.247), than low bias participants. Thus, the more implicitly research did not find differing response latencies for congruent and biased the participant, the greater the P200 elicited by stereotypically incongruent trials typically obtained in the above stereotype and evalu- White traits following a black face (compared with stereotypically ative priming research. However, given that the SOAs used in the black traits following a black face) (Figure 6). current paradigm (1000 ms) were longer than is typical in this type We again simultaneously regressed the difference scores examining of research, this absence may be unsurprising. Regardless, researchers the effect of negative or positive valence on IAT scores. Neither rela- interested in response latencies should note this difference. tionship was significant (ps > 0.1), indicating that stereotype valence In addition, the race-based stereotypes in the current work were was not contributing uniquely. Congruence alone drove the effect. sociopolitically charged, and participants would likely have been reluc- Differential P200 reactivity between congruent and incongruent con- tant or unable to explicitly acknowledge the strength of their associ- ditions following black primes explained 28% of the variance in the ations. The current results theoretically extend previous work by IAT (R ¼ 0.284). No other relationships with IAT scores were present. demonstrating that the N400 can be used as a metric of stereotype accessibility even in domains where social desirability is a salient issue. DISCUSSION This result highlights the utility of the N400 for researchers interested in examining stereotype-accessibility in various domains. The current research examined the viability of assessing N400 reactivity The secondary goal of this study was to examine whether N400 to congruent and incongruent associations as an index of both stereo- reactivity could be extended to examine individual prejudices by con- type accessibility and interracial prejudice. The current findings repli- trasting N400 reactivity to both positively and negatively valenced cate previous research demonstrating greater N400 reactivity to stereotypes. Our approach was to correlate differences in individuals&rsquo stereotype&ndashincongruent than to congruent associations, but with im- responses to valenced conditions with more traditional and validated portant methodological and theoretical differences. First, results were measures of interracial prejudice: self-report measures and the IAT. obtained regarding black and white stereotypes, instead of gendered Indeed, a strong relationship was evident between N400 activity and stereotypes (White et al., 2009). In addition, the results demonstrate self-reported explicit racial bias, as racially biased participants demon- that the N400 effect manifests even when stereotypes were unrelated to the task (evaluating words as negative or positive). In previous strated particularly strong reactivity to stereotypically white words fol- work, participants explicitly indicated whether target words matched lowing black faces. Interestingly, both negatively and positively the primes. That N400 reactivity was elicited even when participants valenced stereotypes were independently involved in self-reported bias. N400 SCAN (2014) 551 There was a striking difference in N400 morphology related to alternative method would have been to contrast conditions where the the explicit bias of the participant. In biased individuals, the N400 trait was held constant while varying the race of face prime (e.g. Black elicited by incongruent stereotypes endured for an additional 250 ms Congruent White Incongruent). This alternative method of incon- (Figure 5). To our knowledge, the only other research documenting gruence was in fact examined, but no relationships with ERPs were such an effect was found comparing N400s elicited by incongruent evident. Increased vigilance and attention following black primes may words appearing as pairs or within a sentence (Van Petten, 1993). be responsible for this pattern of effects. Supportive of this possibility, Van Petten found more enduring N400 activity (200 ms longer) faster response latencies and larger N100s were elicited by traits fol- when incongruencies were located within sentences, compared with lowing black than white primes. Previous work has demonstrated that N400 activity following an incongruent word pair, concluding that the N100 is sensitive to task factors (Hillyard and Mu ¨ nte, 1984) such as the longer duration reflected the associated semantic detail retrieved whether targets are armed in a shooter paradigm (Correll et al., 2006), for the word that elicited the N400. In the current research, a similar indicating that participants may have believed that traits following interpretation suggests that individuals with greater explicit bias might Black faces were more relevant to the task, or that assessments of preju- have engaged in longer and more complex analysis when stereotypic- dice were being made on those trials and thus commanding attention. ally white words were primed with black faces, compared with their We had no a priori hypotheses about which contrasts might best pre- less biased peers. Thus, white words associated with black faces may be dict bias, however, and future work should examine exactly why these incongruent only for individuals with greater explicit bias, while less particular comparisons were linked with bias. This result highlights the biased individuals exhibit an N400 more typical of semantic processing importance of corroborating neurological measures with other, better (Kutas and Hillyard, 1984 Nigam et al., 1992 Van Petten, 1993). This understood assessments of behavior (Guglielmi, 1999). novel, although unexpected, result is consistent with the original A limitation of the current work involves the selected stereotypical hypotheses. The results of our secondary hypotheses should be traits. Specifically, negative black stereotypes were evaluated as more viewed with some care, given our moderate sample size and the some- negative than negative white stereotypes. This result is likely due to the times ephemeral nature of individual differences. That said, we note physical danger connotations of the negative black stereotypes. the robust relationship between N400 reactivity and self-reported bias We selected the most negatively or positively valenced traits in each (R ¼ 0.417) and believe that future work should examine the link category to maximize participant responsiveness, but more equally between N400 reactivity and individual biases more closely. matched comparisons would have been preferable. However, it is crit- Regarding effects involving other ERPs, participants demonstrated ical to note that this difference in valence regarding negative stimuli larger P200s to negative than positive traits in general, consistent with does not account for any of the current effects. Participants generally previous characterizations of P200 activity as primarily demonstrating responded to these different categories of stimuli equally and indeed vigilance to threat (Bartholow et al., 2003). In addition, the P200 was sometimes demonstrated greater reactivity to negative white stereo- sensitive to the race of prime, valence and congruence of trait simul- types (e.g. P200). Nonetheless, future research should ensure stimuli taneously as demonstrated by the three-way interaction (Figure 4). are equated on all dimensions. This pattern of activity might be explained as an overall reaction to In summary, the current research extends previous work finding negative White traits. Participants might have found negative ingroup that the N400 can act as a viable index of stereotype accessibility in traits more threatening than positive ingroup traits. In turn, these interracial domains. In addition, we provide preliminary evidence that negative ingroup traits may have been particularly threatening when differential N400 and P200 reactivity to negatively and positively explicitly associated with the ingroup by the face prime. valenced stereotypes may provide a window into individual biases. An alternative to this explanation is that larger P200s were simply These results warrant future attention regarding neurological indica- elicited by negative, stereotypically white words. We favor the incon- tors of prejudice and stereotype endorsement. Further research may be gruency explanation, however, given our care in selecting target traits. able to use such components to shed further light on the neurological Negative stereotypically white words were not (i) more stereotypical or roots of intergroup conflict. (ii) longer than any other trait categories and were not (iii) more negative in valence than negative black stereotypes. Future research REFERENCES may examine whether these traits varied on other dimensions, and Amodio, D.M. (2008). The social neuroscience of intergroup relations. European Review of how that might account for the current results. Nonetheless, the cur- Social Psychology, 19,1&ndash54. rent results indicate that the P200 may be more sensitive to multiple Amodio, D.M., Devine, P.G. (2006). Stereotyping and evaluation in implicit race bias: evidence for independent constructs and unique effects on behavior. Journal of dimensions than previously believed. Personality and Social Psychology, 91, 652&ndash61. In addition, differential P200 reactivity predicted individuals&rsquo impli- Bartholow, B.D., Pearson, M.A., Gratton, G., Fabiani, M. (2003). Effects of alcohol on cit bias. This relationship was evident only when contrasting congruent person perception: a social cognitive neuroscience approach. Journal of Personality and incongruent conditions following black faces. 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Social Cognitive and Affective Neuroscience &ndash Oxford University Press


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