Thirty Years and Counting: Finding Meaning in the N400 ...apsychoserver.psychofizz.psych.arizona.edu/JJBA...Thirty Years and Counting: Finding Meaning in the N400 Component of the

PS62C23-Kutas ARI 22 November 2010 8:50

Thirty Years and Counting:Finding Meaning in the N400Component of theEvent-Related BrainPotential (ERP)Marta Kutas1 and Kara D. Federmeier2

1Departments of Cognitive Science and Neurosciences, Center for Research in Language,Kavli Institute for Brain and Mind, University of California, San Diego, California 92093;email: [email protected] of Psychology, Program in Neuroscience, and The Beckman Institutefor Advanced Science and Technology, University of Illinois, Urbana, Illinois 61801;email: [email protected]

Annu. Rev. Psychol. 2011. 62:621–47

First published online as a Review in Advance onAugust 30, 2010

The Annual Review of Psychology is online atpsych.annualreviews.org

This article’s doi:10.1146/annurev.psych.093008.131123

Copyright c© 2011 by Annual Reviews.All rights reserved

0066-4308/11/0110-0621$20.00

Key Words

language, memory, context effects, timing, priming, nonlinguisticstimuli

Abstract

We review the discovery, characterization, and evolving use of theN400, an event-related brain potential response linked to meaning pro-cessing. We describe the elicitation of N400s by an impressive range ofstimulus types—including written, spoken, and signed words or pseu-dowords; drawings, photos, and videos of faces, objects, and actions;sounds; and mathematical symbols—and outline the sensitivity of N400amplitude (as its latency is remarkably constant) to linguistic and non-linguistic manipulations. We emphasize the effectiveness of the N400 asa dependent variable for examining almost every aspect of language pro-cessing and highlight its expanding use to probe semantic memory andto determine how the neurocognitive system dynamically and flexiblyuses bottom-up and top-down information to make sense of the world.We conclude with different theories of the N400’s functional signifi-cance and offer an N400-inspired reconceptualization of how meaningprocessing might unfold.

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ERP: event-relatedbrain potential

ms: millisecond

Contents

INTRODUCTION . . . . . . . . . . . . . . . . . . 622DISCOVERY (1980) . . . . . . . . . . . . . . . . . 622CHARACTERIZING A MEASURE

(1980–1988) . . . . . . . . . . . . . . . . . . . . . . . 623Names and Definitions . . . . . . . . . . . . . 623Functional Sensitivity . . . . . . . . . . . . . . 623Component Characteristics . . . . . . . . . 624

FIRST QUESTIONS ANDDEBATES (1989–1998) . . . . . . . . . . . 625Language . . . . . . . . . . . . . . . . . . . . . . . . . . 625Semantic Memory . . . . . . . . . . . . . . . . . 627Recognition Memory . . . . . . . . . . . . . . 629Debate: Attention and the N400 . . . . 629Special Populations

and Individual Differences . . . . . . . 631NEW AND MATURING

RESEARCH LINES (1999–2009) . . 632Language . . . . . . . . . . . . . . . . . . . . . . . . . . 632Semantic Memory . . . . . . . . . . . . . . . . . 636Recognition Memory . . . . . . . . . . . . . . 637

THEORIES OF THE N400 . . . . . . . . . . 638CONCLUSIONS . . . . . . . . . . . . . . . . . . . . 642

INTRODUCTION

The first report of an N400 response waspublished 30 years ago, in 1980, by Kutas andHillyard. Since its discovery, more than 1,000articles have been written using the N400 as adependent measure, across a wide range of ar-eas, including language processing; object, face,action, and gesture processing; mathematicalcognition; semantic and recognition memory;and a variety of developmental and acquired dis-orders. Across this body of literature, much hasbeen learned about the measure and, in tandem,about human cognitive and neural functioning.Our goal in this review is to recount the N400’shistory, summarizing what we have learnedabout and from this electrophysiological mea-sure and taking the opportunity to reflect onhow discoveries are made, how neurocognitivemeasures are characterized, and how subfieldsof scientific inquiry are born and mature.

DISCOVERY (1980)Soon after the discovery, in the mid-1950s,that it was possible via averaging to extracta time series of changes in electrical brainactivity recorded at the human scalp before,during, and after an event of interest, it wasdemonstrated that measurable parameters ofthese evoked potentials—their amplitudes, la-tencies, and scalp topographies—systematicallyvaried with stimulus or response features (e.g.,pitch, color, intensity). Within five years, thefield of cognitive electrophysiology was bornfrom various demonstrations that scalp event-related brain potential (ERP) waveforms in-dexed not only objective stimulus character-istics (often within the first 200 milliseconds[ms]), but also endogenous influences relatedto people’s reactions or attitudes to the stimuliand experimenters’ instructions (between ∼200and 1500 ms poststimulus onset). By 1978, cog-nitive electrophysiologists had identified ERPmarkers of stimulus evaluation processes dis-tinct from response preparation and execution.In particular, the P300 (P3b) is an endoge-nous, mostly modality-independent responseobserved over central-parietal scalp locationswhose latency (300–800 ms) varies systemati-cally with the duration of stimulus categoriza-tion. P3b amplitudes are inversely correlatedwith the eliciting item’s subjective probabilityof occurrence: the less probable an event, thelarger the P3b elicited (reviewed in Hillyard &Kutas 1983).

Against this backdrop, to investigate the roleof sentence context on word recognition duringreading, Kutas & Hillyard (1980) modified theoddball paradigm, known to elicit large P3b’s,for language materials. Undergraduates readseven-word sentences presented one word persecond; 75% were congruent control sentences(e.g., I shaved off my mustache and beard ), while arandom 25% ended oddly, with an improbableword (experiment 1: He planted string beans in hiscar) or a wholly anomalous one (experiment 2: Itake coffee with cream and dog). Surprisingly, al-though the manipulation modulated the ERP,it did not yield a P3b, but rather a large neg-ativity with a broad (parietally maximal) scalp

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distribution, peaking around 400 ms (largestfor semantic anomalies, but also present for im-probable but sensible endings); it was called theN400.

CHARACTERIZING A MEASURE(1980–1988)

Names and Definitions

The N400 was labeled as such because it wasa relative negativity peaking around 400 ms.More precisely, it is negative-going at partic-ular scalp locations relative to a specific ref-erence derivation (e.g., posterior sites relativeto recordings behind the ears), relative to a100 ms prestimulus baseline. Indeed, the N400to an unexpected item need not be negative inabsolute terms. It is thus typically examinedin cross-condition comparisons and routinelyinstantiated in a difference ERP created viaa point-by-point subtraction of, e.g., a con-gruent ERP from an incongruent one. Thisdifference—or N400 effect—is a monophasicnegativity between 200 and 600 ms, largestover centro-parietal sites, with a slightly right-hemisphere bias (at least for written words insentences).

Although some ERP responses are namedfor their presumed function, the N400 is not,and its functional characterization (like that ofall cognitive measures) is in a continual stateof fine-tuning. Its identity is some function ofits morphology, timing, and behavior undercertain experimental manipulations. Someelectrophysiologists have argued for a preciseneuroanatomical characterization, but that isnot so straightforward in practice, especiallygiven that the same functional operations maybe carried out in different neuroanatomical sub-strates. Accordingly, we do not view the N400as an undifferentiable, localizable (or lesoni-able) neural entity that indexes one particularmental operation. Instead, we use the termN400 as a heuristic label for stimulus-relatedbrain activity in the 200–600 ms poststimulus-onset window with a characteristic morphol-ogy and, critically, a pattern of sensitivity to

Cloze probability(of a word): theproportion ofrespondents supplyingthat particular word asa continuation giventhe preceding contextin an offline normingtask, ranging from 0 to1 in value

Contextualconstraint (e.g., of asentence): the degreeto which the contextestablishes anexpectation for aparticular upcomingword, generallyempirically defined asthe cloze probability ofthe highest probabilitycontinuation, rangingfrom 0 to 1

experimental variables—and hence a com-mon functionality. In the next section, wediscuss what these variables are and howthey impact human brain activity as wellas our comprehension of sensory input(Figure 1).

Functional Sensitivity

Kutas’s mentor Donchin (1984) emphasizedthe importance of carefully characterizing ERPresponses in terms of their functional sensitiv-ity as a prerequisite to using them as markersof specific aspects of information processing.Accordingly, early years of work (reviewed inHillyard & Kutas 1983, Kutas & Van Petten1988) focused on determining what range ofmanipulations the N400 was and was not sensi-tive to (and how) and its relation to behavioralmeasures and other known ERP responses.Using the anomalous sentence paradigmas a starting point, the field asked whetherN400 effects would obtain for any unexpectedmanipulation using words. The answer was aresounding no: there was no observable N400effect to the final word of “I shaved off my mus-tache and BEARD” (a congruent but physicallyunexpected ending) compared to the physicallyexpected congruent ending (beard). Likewise,the N400 also did not obtain in response to justany language-related violation: There wereno N400 effects to simple grammatical (mor-phosyntactic) violations as in “All turtles havefour leg” (versus legs). Other studies confirmedthat the ERPs to all sentence final words-–evencongruent ones—are characterized by some de-gree of N400 activity and further demonstratedthat N400 amplitude is highly correlated(r = 0.9) with an offline measure of the elicit-ing word’s expectancy—i.e., cloze probability,the percentage of individuals who would con-tinue a sentence fragment with that word. Thissensitivity to cloze probability obtains irrespec-tive of contextual constraint (negating a coreprediction of any view that the N400 indexesinhibition, as in Debruille 2007): N400s tothe sensible and equally low cloze probabilitycompletions of strongly constraining sentences

www.annualreviews.org • Thirty Years of N400 Research 623

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RTs: response times

(e.g., The bill was due at the end of the hour)and of weakly constraining sentences (He wassoothed by the gentle wind) were statisticallyindistinguishable and were much larger thanthose to high-cloze-probability endings (Thebill was due at the end of the month).

Indeed, many laboratories demonstratedthat semantic anomalies were neither neces-sary nor sufficient for N400 elicitation and thatN400s did not always pattern with responsetimes (RTs). Fischler and colleagues (1983),for example, found that N400 amplitudes tothe final words in affirmative (e.g., A robinis a bird/vehicle) and negative (A robin is nota bird/vehicle) sentences were determined ex-clusively by the relationship between the firstand the second noun and not by sentencemeaning or truth value (which did, however,affect verification times). Numerous other stud-ies further demonstrated that N400 elicitationdid not require a sentential frame; for exam-ple, N400 effects obtained when the fifth itemof a list mismatched rather than matched theprior four in semantic category membership.N400 effects also were observed in lexical prim-ing paradigms, where a target word was or wasnot somehow related (e.g., identically, associa-tively, semantically, categorically, and perhapsphonologically) to an immediately preceding(prime) word; in all cases, related items showedreduced N400 amplitudes relative to unre-lated items across a number of different tasks(reviewed in Kutas & Van Petten 1988).

Moreover, N400 effects were found togeneralize across input modalities, includingspoken words and American Sign Languagesigns and even language-like nonwords, i.e.,pseudowords (reviewed in Kutas & Van Petten1994). Importantly for functional characteri-zation, N400 effects (albeit with varying am-plitude distributions—topographies—acrossthe scalp) also were routinely seen to line draw-ings, pictures, and faces when primed (versusnot) by single items or sentence contexts.However, N400-like activity was not observedin response to unexpected events in otherstructured domains such as music, be they thefrequency of a note violating a musical scale

sequence or a familiar melody; instead, suchdeviations elicited P3b-like potentials (Besson& Macar 1987). Clearly, the N400 is not a sim-ple signature of the violation of any arbitraryor overlearned pattern. Overall, the early datasuggested that the N400 indexed somethingfundamental about the processing of meaningand hinted that the meaningful/nonmeaningfuldimension may be more important than thelinguistic/nonlinguistic dimension.

We end this section by noting that althoughERP parameters are sensitive to psychologi-cal variables, they are neither generally norreadily reducible to psychological constructs.Ultimately, it is the brain’s “view” of cognitiveprocessing that we seek to characterize. ERPsprovide a particularly apt inroad to this, by be-ing a direct measure of neocortical activity thattracks brain states continuously and instanta-neously. The N400’s relationship to other mea-sures (e.g., RTs) whose functional sensitivitieshad been better mapped out was important as astarting point, but, ultimately, where ERPs aremore direct, selective, and sensitive, the direc-tion of influence must shift. Correspondingly,the field must be willing to rethink the poolof available cognitive constructs it has devel-oped, largely from end-state measures. As weshow, in some cases the questions we ask aboutcognitive processing via the N400 have rela-tively clear answers; in other cases, however,our failures to converge upon an answer afterintensive investigation raises the distinct possi-bility that the question itself may be ill-posed—either insufficiently clear or based on faultyassumptions.

Component Characteristics

As the N400 came to be characterized, itquickly became clear that it was the amplitudeof the response that was most susceptible tomanipulation (becoming smaller when factorsrendered information more expected and thuseasier to process) and most likely to vary withmany of the same factors that influence RTmeasures (see overview in Kutas & Federmeier2009). At a physiological level, amplitude


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reductions might reflect smaller postsynapticpotentials in the same neurons, activation offewer neurons in a population, and/or lesstemporal synchrony among the generating neu-rons. N400 latency, by contrast, was generallyquite stable—a fact whose theoretical signif-icance we are just beginning to appreciate (seeTheories of the N400 section). CharacterizingN400 topography across the scalp has provenmore difficult because a stable distribution wasseen to visual words across manipulations, buttemporally and functionally similar responsesto other stimulus types had overlapping, butdissociable, scalp topographies. Whether thismeans there is more than one N400 is difficultto answer based on surface potentials alonebecause of possible temporal overlap with otherresponses. At a deeper level, the answer dependson what is meant by different, and, as such, istheoretically laden. Early on, when the fieldwas dominated by the information-processingframework, assuming seriality and modularityof processes, topographic differences wereoften regarded as suggestive of different pro-cessors. However, as the field moved towardmore distributed and interactive views, distri-butional differences were likely to be treatedin a graded rather than categorical fashion.

It is also worth noting that in the early daysthere were heated arguments over whether theN400 was, for example, simply a longer-latencymember of the N200 family of responses (typ-ically preceding P3b’s to unexpected events)(e.g., Deacon et al. 1991) or resolution of yetanother component. Linking a newer responsewith a better-characterized one is useful inallowing new predictions and generalizations.Critically, however, such classifications oftenmatter little for how the measure can be used.What is essential whether linking a newly dis-covered response with an older one or splittinga well-studied response into subcomponents isthat the measure be reliably identifiable in dataand its sensitivity to stimulus and task proper-ties mapped out; only then can it be used tomeaningfully answer questions about cognitiveand neural function. By 1988, the N400 hadreached the status of a fairly well-characterized

neural marker (“component”) and began to beusefully applied to a variety of questions, in-cluding those that were difficult or impossibleto test with other metrics, and to challenge coreassumptions about cognitive processing, espe-cially in the domain of language (Kutas & VanPetten 1988, 1994).

FIRST QUESTIONS ANDDEBATES (1989–1998)

Language

Despite evidence to the contrary, the N400 haslong been thought of as a language measure. Aswe hope to make clear, it is much more thanthat—however, it is true that the N400 is a par-ticularly powerful tool for studying language.The N400 opened the door to investigationof the neural bases of language comprehensionin the normal population, not just individualswith aphasia. By neural bases we mean char-acterization of the neural representations andfunctions supporting language processing, notlocalization of those functions. Interest in neu-ral bases aside, the observed systematicity be-tween sensory, conceptual, and linguistic fac-tors and properties of the N400 (together withthose of ERPs more generally) has made itamenable for addressing core psycholinguisticquestions that had proven intractable to mostother dependent measures.

Immediacy and incrementality. A casein point is time. Its critical importance forlanguage processing was never questioned;however, the timing of events—at a granu-larity relevant for psycholinguistics, let aloneneurobiology—was very difficult to measureexcept via unnatural, disruptive probes. RTsare, by their nature, end-state measures, unableto track moment-by-moment processing. In-deed, even online measures, such as self-pacedreading and eye tracking, often showed reliablecontext effects only after several hundreds ofmilliseconds had passed by, in the “spilloverregion,” one or more words beyond the word ofinterest. Psycholinguists thus devised elaborate


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SOAs: stimulus-onsetasynchronies

RSVP: rapid serialvisual presentation

paradigms, based on complex sets of assump-tions, in an attempt to get at temporal aspects oflanguage processing with RT measures; theseincluded presenting stimuli for short durationsor masking them to curtail processing, usingrelatively short stimulus-onset asynchronies(SOAs) to disclose “early” influences of oneword on another (again based on the idea thatprocessing of a stimulus is somehow arrestedwhen a new stimulus is encountered, althoughsee Van Petten 1993) or using response dead-lines. Indeed, these procedures have become somuch the norm that ERP studies are sometimescriticized for drawing conclusions about timingwithout having resorted to any of them, eventhough time is an intrinsic property of theERP. With ERPs, language manipulations canbe tracked through time with millisecond res-olution and without elaborate task conditionsor any added task at all.

One of the first major contributions ofthe N400 to psycholinguistic research wastherefore to show that effects of semantic ma-nipulations could be seen almost immediately:The N400 congruity effect began ∼200 ms(and peaked before 400 ms) into the processingof a critical word—written, spoken, or signed.Furthermore, because ERPs can be examinedin response to every stimulus, not just selectedtargets, they provide an instantaneous and con-tinuous look at language processing. The ERPto every word read one at a time in the center ofthe screen (rapid serial visual presentation, orRSVP) contains N400 activity, which is affectedby context, thereby revealing the inherentlyincremental nature of language processes.Comparing normal English sentences withthose that were syntactically structured but se-mantically anomalous revealed a linear declinein N400 amplitudes of open-class words acrossthe course of congruent sentences (i.e., wordposition effect), which thus seemed to reflectthe incremental build-up of semantic (and notsyntactic) constraints (reviewed in Van Petten1993).

Processing levels. In addition to providingexquisite timing information, ERP measures

provide a means of assessing the qualitative sim-ilarity of two (or more) effects—e.g., at dif-ferent processing levels. N400 studies offeredcritical evidence for both temporal and quali-tative similarity between the effects of a wordprime and those of a sentence context on wordprocessing. Studies showed that the morphol-ogy, timing, and topography of the visual N400semantic priming effect for target words fol-lowing semantically related versus unrelatedprimes were indistinguishable from those forthe visual N400 effect to sentence final wordsof congruent versus anomalous sentences. Thiswas an especially important finding because, onmost accounts, word-level priming was thoughtto be mediated by automatic spreading acti-vation or at least by some process internal tothe mental lexicon, impervious to any externalcontext. Sentence context and other top-downeffects, by contrast, were assumed to exert theirinfluence via qualitatively different controlledprocesses, acting upon the representation ofalready “recognized” words—that is, postlex-ically. Direct, within-subject comparisons oflexical and sentential N400 context effects,however, strongly argued against the possibilitythat they arose from different stages of languageprocessing (Kutas 1993).

Indeed, N400 data provided clear evidencefor interactions of sentence context effectswith word frequency, word-level associations,and word repetition and revealed that whenboth word- and sentence-level informationsources were available, higher-level contexteffects tended to override lower-level ones,contrary to the then-prevailing assumptionsof bottom-up priority for and insularity ofword-level processing (reviewed in Kutas 1993,Van Petten 1993). For example, the semanticconstraints provided by a sentential contextcan supersede lexical frequency effects on theN400. Furthermore, when compared directlywithin the same materials, independent andqualitatively similar effects were obtained forlexical associative priming and sentence-levelcongruity: N400 amplitudes were reduced tolexically associated second words in anomaloussentences as well as to unassociated words


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in congruent sentences, demonstrating thebuild-up of message-level meaning informa-tion over and above word-level associations.When both information sources were present,their influences were additive (with later workshowing that even stronger message-level con-straints override lexical association: Coulsonet al. 2005). These findings helped to establishthat semantic congruity, repetition, and wordfrequency converge to influence a commonstage of word processing. The modularity oflexical processing was irreparably penetratedby incisive N400 results.

Categorization of processes. Over thecourse of determining the functional specificityof the N400, it became clear that whereas sometypes of language manipulations altered theamplitude of the N400, others, including syn-tactic violations, were associated with differenttypes of ERP effects, such as a later positivitycalled the P600 or a temporally coincidentnegativity with a (sometimes left) frontal focuscalled the left anterior negativity (LAN). Afew studies cleverly took advantage of the factthat grammatical violations can have semanticconsequences to study syntactic aspects oflanguage with the N400 (reviewed in Kutas &Kluender 1994, Kutas & Van Petten 1994).More commonly, however, this functionaldissociation was used to determine how thebrain classifies aspects of language about which(psycho)linguists were less certain—e.g., theagreement in gender between a pronoun(her) and its antecedent (the boy), which onsome accounts could be syntactic (constraintsimposed by one’s grammar), or by other ac-counts, semantic (part of each word’s meaningand how it is used in discourse). The ERPresults were clear: Agreement violations didnot modulate N400 activity but elicited a P600(and sometimes LAN) instead, suggestingthe brain treated them as syntactic ratherthan lexico-semantic in nature (Osterhout &Mobley 1995). Similarly, Japanese-languageresearchers used the presence of large N400sto argue for a semantic over a morphosyntacticaccount of the links between nouns and their

ERP effect: a reliabledifference betweenERPs elicited in twoconditions, fromwhich influences ofexperimentalmanipulation(s) can beinferred

Semantic memory:mental storehouse ofwhat we “know” (noawareness implied)about actions, events,people, places, andthings—includingwords—stored in thebrain

classifiers (quantifiers that agree with the typeof entity being counted; Sakai et al. 2006).

Comparisons of auditory and visual lan-guage. The fact that N400s could be observedfor both visual and auditory words affordedcross-modality comparisons that were relativelyless tractable for RT studies. The functionalsimilarity of the N400 generating process inthe two modalities (e.g., sensitivity to semanticrelations, sentential congruity, and relatedanomaly effects—N400 reductions to anoma-lous words semantically related to the highestcloze endings for a sentence frame) was theoret-ically important for psycholinguistics, makingthe occasional differences and interactions allthe more notable. Auditory N400s tended tobegin earlier (although not when speech waspresented at a fixed rate, as in the visual modal-ity, rather than naturally), last longer, and havea slightly more frontal and less right-biasedtopography (reviewed in Kutas & Van Petten1994). Finding different patterns of N400effects (across SOA) when the prime was an au-ditory word and the target a visual word or viceversa, Holcomb & Anderson (1993) argued foran amodal semantic system tapped by modality-specific processes. Importantly, however, themodality-general aspects of the N400 effectsmade it easier to investigate language represen-tations and processes both independent of andas a function of input type, and helped validatethe nonecological RSVP procedure used forreading studies (to avoid contamination ofvisual ERP with eye movements).

Semantic Memory

The N400’s broad sensitivity to meaningfulstimuli and semantic manipulations meant thatit could be used to ask questions about howmeaning-related information is stored in thebrain in what is often called semantic mem-ory (reviewed in Kutas & Federmeier 2000,Kutas & Van Petten 1994). These questionswere examined in studies of typicality and levelof representation, of concreteness, and also ofword type differences (e.g., nouns and verbs:


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LH: left hemisphere

RH: right hemisphere

Gomes et al. 1997). At the most general level,two important findings cut across these stud-ies. One was dissociation between RT andN400 measures, which only sometimes behavedsimilarly. Such dissociations are common tocognitive ERP measures, given that individualcomponents reflect only a subset of the pro-cesses that contribute to RTs and are, in fact, auseful dependent measure specifically for thatreason. The other, perhaps more important,finding was that N400 data often did not fullysupport any of the available theories (even ifERP authors sometimes were compelled tochoose a position), suggesting instead that as-pects of each were correct. Consider, for ex-ample, the N400 work aimed at unearthingwhy people find concrete words easier to pro-cess than abstract words. On a dual-coding ac-count, concrete materials accrue an advantageby virtue of being represented in two seman-tic systems—one verbal, in the left hemisphere(LH), which also represents abstract words, andanother, image-based, in the right hemisphere(RH). By contrast, context-availability theorygrounds concreteness effects in quantitative dif-ferences in semantic richness within a common,amodal semantic system. Across a number ofstudies, N400 results have been systematicallymixed: responses to concrete (versus abstract)words manifest different scalp topography, con-sistent with the dual-coding view. However,such differences are reduced for words com-pleting congruent sentences (Holcomb et al.1999), an interaction that is consistent with thecontext-availability view, albeit not in the pre-cisely predicted form. The N400 data thus callfor a theory that combines elements of bothaccounts.

Words, pictures, and other meaning-ful stimuli. More specifically, one early lineof N400 work tested long-standing ques-tions about whether semantic memory is bestthought of as a single, amodal system (sim-ilarly accessed by stimuli with different sur-face forms, such as pictures and words) or ascomprising a number of distinct (sub)systems(reviewed in Kutas & Federmier 2000). The

answer provided by N400 data—namely, yesand yes—raised serious questions about thevalidity of this debate. For, although therewere broad similarities (in wave shape, timecourse, and functional sensitivity of the N400effect), there were also important differences(especially in terms of scalp topography) inthe response to different types of meaning-ful items. Although much of the debate fo-cused on comparisons of pictures and words, awide range of stimulus types have been investi-gated, including faces, environmental sounds,and even odors. Pictures elicited a similarbut more frontally distributed N400, simi-lar to that for concrete words (Ganis et al.1996). The N400 effects for familiar facescompleted by mismatching versus matchinginternal features had an occipital maximum(Olivares et al. 1999). Within-subject compar-isons of words and meaningful environmen-tal sounds demonstrated N400 effects for each,similar in all but hemispheric laterality, rightdominant for words and left dominant for envi-ronmental sounds (Van Petten & Rheinfelder1995). The weight of these studies pointed to afunctional entity that varies systematically withrelatedness within and across a wide range ofsensory input types, but characterized by to-pographic differences that implicate an assort-ment of at least partially nonoverlapping neu-ral areas in meaning construction. N400s thusare modality sensitive but not modality specific(perhaps marking a unimodal to amodal inter-face; see Theories of the N400 section)—anelectrophysiological marker of processing in adistributed semantic memory system.

Localization/neural source. With the grow-ing sense of the N400 as an index of semanticmemory and the dynamic processing that un-folds within it, it became of interest to local-ize the source(s) of this activity to answer thequestion of not only what brain areas mightbe involved but when and how they mightcontribute (reviewed in Lau et al. 2008, VanPetten & Luka 2006). Some attempts havebeen made to model the scalp-recorded sig-nal, but more exciting developments involved


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the use of intracranial recording techniques,typically in individuals with epilepsy prior tosurgical intervention. Such studies have iden-tified a widely distributed set of brain re-gions coactive with the scalp-recorded N400.These include a source in the anterior me-dial temporal lobe (functionally akin to thescalp N400 with respect to manipulations ofsemantic priming, semantic congruity, repeti-tion, and (verbal) recognition memory), in mid-dle and superior temporal areas, inferior tem-poral areas, and prefrontal areas. Essentially,these same brain areas in both hemispheres (al-though perhaps stronger in the LH) also havebeen identified by other neuroimaging tech-niques such as the magnetic counterpart of theERP—the magnetoencephalogram (MEG)—and the event-related optical signal (Tse et al.2007); both have implicated the superior/middle temporal gyrus, temporal-parietal junc-tion, and medial temporal lobe, and with lessconsistency, the dorsolateral frontal cortex.These brain areas, as we know today, align withthe distributed network presumed integral tosemantic memory storage and processes, as in-dependently identified by hemodynamic imag-ing and neuropsychological studies.

Naturally, there are clear benefits to local-izing the neural generators of any scalp ERPactivity, although more so when there is clearand independent evidence for the generatingarea’s function. As already noted, ERP com-ponents generally, and the N400 in particular,have been used successfully to answer cognitivequestions even as their neural source remainedobscure. Still, it is useful to now know that vari-ous neuroimaging data all point to a multimodalsemantic system and that MEG activity coinci-dent with the scalp N400 suggests that it doesnot reflect activity in a single, static source butrather a wave of activity starting (∼250 ms) inthe posterior half of the left superior temporalgyrus, spreading first forward and ventrally tothe left temporal lobe by 365 ms, and there-after, between 370–500 ms, to the right ante-rior temporal lobe and to both frontal lobes.With such data in hand, the question becomesnot where is the N400 generator localized, or

MEG: magnetoen-cephalogram

ERP components:portions of an ERPwaveform, often a peakor trough, that have acharacteristic shape(morphology), timing,and amplitudedistribution across thescalp (topography) anda well-characterizedpattern of sensitivity toexperimentalmanipulations orneural source, or both

LPC: late positivecomplex

whether there are multiple N400s, but ratherwhat are the functions of the dynamic neuralsystem of which scalp N400s are reflections?

Recognition Memory

The fact that one of the first variables found toclearly modulate N400 amplitude was repeti-tion meant that the N400 could also be used tostudy aspects of recognition memory (reviewedin Friedman & Johnson 2000). N400 patterns inrecognition tasks were similar to those seen forrepetitions, with correctly identified old wordseliciting less negativity in the N400 time win-dow than correctly rejected new words. Disso-ciations of N400 memory-related effects fromthose on later components, such as the late posi-tive complex (LPC), then helped to provide keysupport for multiple process/systems views ofmemory. Smith & Guster (1993), for example,provided early evidence for a dissociation be-tween N400 memory effects and those due torecollection by showing that the magnitude ofthe N400 repetition effect was similar for mem-ory judgments that entailed recollection or onlya feeling of familiarity (whereas LPC modula-tions were yoked to recollection). The N400also played a role in emerging studies usingback-sorting paradigms to examine encoding-related brain activity that predicted later mem-ory performance (a procedure later adoptedby researchers using functional magnetic res-onance imaging, e.g., Jordan et al. 1995). Thisserves as yet another example of the power ofelectrophysiology to get at aspects of cognitionlargely impenetrable with behavioral measures.

Debate: Attention and the N400

An important early—and now long-standing—debate concerned the role of attention in theelicitation of N400 effects. The prevalent viewat the time divided cognitive processes intothose that required attention (so-called con-trolled processes) and those that proceededwithout attention or awareness (so-called au-tomatic processes). Of interest, in the contextof this debate, was whether the N400 and the


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Prelexical process:hypothesized initial,automatic stage ofword processingduring which the visualor auditory input formis matched to existingword templates in a(hypothesized)structured mentallexicon, leading torecognition and access(activation ofassociated semanticand syntacticinformation)

Postlexical process:hypothesizedattentionallydemanding stage oflanguage processing,occurring only after aword is recognized,during which theaccessed wordinformation iscombined (integrated)with higher-orderlinguistic and/ornonlinguistic contextand backgroundknowledge (semanticmemory) in order toshape the ongoingmessage-levelrepresentation

Integration view:hypothesis thatfacilitatory effects ofcontext arise onlywhen the features of atarget input havealready been accessedthrough bottom-upstimulation and arethus achieved througha greater degree ofmatch and/or easierprocess of linking withprior contextinformation

aspects of semantic processing it seemed to in-dex are controlled or automatic in nature. In thedomain of language, the answer to this ques-tion would help classify the N400 as a prelex-ical process or postlexical process, happeningeither before or after the “magic moment” ofword recognition. At a theoretical level, a lotmight hinge on the answer to this question, asthe sensitivity of the N400 to sentence-levelcontext information would pose problems forcertain theories if the N400 turned out to beprelexical, calling into question claims aboutthe priority, modularity, and insularity of word-level analyses. On the other hand, as it hap-pens, very few of the inferences gleaned fromstudies using the N400 as a dependent measurewould be substantively affected by the outcomeof this debate. The automatic-controlled dis-tinction aside, the data collected in an attemptto resolve this debate address the more gen-eral question of whether word meanings areinvariably activated—irrespective of percepti-bility, attention, awareness, task relevance, andother resource demands—and, in either case,what variables determine what meaning infor-mation is activated, to what extent, and for howlong (reviewed in Deacon & Shelley-Tremblay2000). A corollary of this debate in the N400memory literature centered on whether N400modulations were best thought of as reflectingimplicit or explicit aspects of memory. Initialstudies finding that N400 context effects weresensitive to task demands (Chwilla et al. 1995),selective attention, and pattern masking led tothe view that the N400 was a controlled processand, therefore, on many accounts, postlexical;this was the basis for the contextual integrationview of the N400. Subsequent N400 data, how-ever, called for a more nuanced answer to thisdichotomous choice.

Large N400 sentence context effects areelicited when a participant’s only task is to reador listen, confirming the intuition that semanticprocessing is what humans naturally do withlanguage (i.e., the default). Moreover, similarmagnitude effects were observed even whensome secondary task—semantic, phonological,or graphemic in nature (Connolly et al. 1990)—

was imposed. When single words instead ofsentences served as the prime, task demandshad more of an effect. Although typically largerwhen instructions explicitly called for semanticanalyses, reliable N400 effects (but not neces-sarily concomitant RT priming) were nonethe-less observed in situations where semanticprocessing was not necessary or even benefi-cial. Moreover, N400 amplitude modulationswere clearly seen with experimental manipula-tions aimed at minimizing controlled processes(e.g., of stimulus-onset asynchrony, proportionof related stimuli, level of processing: reviewedin Holcomb 1988). Importantly, then, N400measures revealed ongoing semantic process-ing even when such analysis was orthogonal totask performance and not evidenced in overtbehaviors (e.g., Kuper & Heil 2009). Still, inall these types of studies, participants directedtheir attention to the stimuli (if not to thesemantic level of analysis), and that seems to beimportant for N400 elicitation. This possibilitywas examined in a number of studies crossingpriming with selective attention (reviewed inDeacon & Shelley-Tremblay 2000).

In a selective attention paradigm, partici-pants are asked to respond to target items in-frequently embedded in a stream of nontargetitems in an attended channel as they ignore allthe items in an unattended channel. Nontargetstimuli also may vary on other dimensions—e.g., contain meaning relations between con-secutive items—and the question is the ex-tent to which semantic processing is impactedby where attention is directed. Initial studiesshowed that attentional selection either elim-inates (for selection based on visual location)or severely attenuates (for selection based oncolor) visual and auditory N400 priming effects,perhaps more effectively in the visual modality.McCarthy & Nobre (1993) observed seman-tic and identity priming effects on the N400only for words appearing in the attended spa-tial location, inconsistent with an automaticN400. Subsequent studies factorially combinedsemantic priming with attentional status to cre-ate four conditions: both prime and target at-tended, both unattended, or either the prime or


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the target attended while the other is not. N400repetition and semantic priming effects weremost consistently observed for targets whetheror not they were attended (albeit much atten-uated for unattended targets) as long as theprimes were attended. Observations of seman-tic priming on target N400s by unattendedprimes are more variable, but have on occa-sion revealed some level of semantic process-ing, which importantly can be dissociated frombehavioral priming and recognition effects.

A parallel literature has examined the N400automaticity issue by combining a primingparadigm with visual masking of either theprime or the target. Visual pattern maskingresults when a visual pattern is flashed at thesame spatial location before or after a brief dis-play of the item of interest and has the conse-quence of reducing that item’s conscious per-ceptibility (i.e., reportability). Overall, maskingof primes has been found to attenuate but notto eliminate N400 effects, although Holcomband colleagues convincingly attribute the resid-ual to occasional prime visibility under masking(e.g., Holcomb & Grainger 2009). A similar ac-count, however, cannot explain the presence ofthe small but reliable N400 effect to seman-tically primed versus unprimed masked targetsthat participants could neither categorize muchabove chance nor report (Stenberg et al. 2000).

Other evidence for the presence of N400semantic priming effects under conditions ofreduced awareness comes from the literatureon the attentional blink (AB) phenomenon (re-viewed in Vogel et al. 1998). The attentionalblink is a short refractory period occurringabout 300–600 ms after the detection of a tar-get item (T1) in a stream of rapidly presentedstimuli, during which subsequent targets (T2)are missed. ERP data have bounded the locusof T1-T2 interference as after initial percep-tual processing of T2 (as reflected in normalearly sensory visual potentials) but prior to theencoding of T2 into working memory (as re-flected in elimination of the P3b component).Critically, when semantically related or unre-lated word pairs are embedded in the stimu-lus stream, N400 effects are observed whether

AB: attentional blink

T2 is a target (Vogel et al. 1998) or a prime(Rolke et al. 2001) in the critical AB window.These results from the AB paradigm reveal thatwords that are attended and perceived—but notidentified and encoded into working memory—can nonetheless have undergone some semanticanalysis and, moreover, can influence the se-mantic analysis of upcoming items. Findings ofN400 semantic priming effects during sleep (re-viewed in Ibanez et al. 2008) and N400 memoryeffects in amnesia (Olichney et al. 2000) furthersupport this view.

The N400 thus could not be neatly mappedinto the automatic or controlled category,having characteristics associated with each(being importantly modulated by selectiveattention, and thus not fully automatic, butnot requiring the kind of awareness importantfor controlled processing). This failure in theface of a vast empirical base strongly suggestsproblems with the initial framing of the debate.

Special Populationsand Individual Differences

Once the N400 was characterized as ameasure—and in parallel with its use tobegin to answer basic questions in languageand memory—its power for studying specialpopulations was recognized. In particular,the N400’s functional specificity offered aninroad to questions about the nature of certaindeficits, at least under the right conditions(i.e., using well-tested paradigms that replicatein controls). Moreover, the N400 offered acritical opportunity to measure processing ingroups with more limited abilities to meet thedemands of typical cognitive tasks. Althougha thorough review of the findings from studiesusing the N400 with special populations isbeyond the scope of this article, it is importantto note that the N400 has now been usedin the study of many different conditions,including Alzheimer’s disease, aphasia, autism,cerebral palsy (as a means of measuring vocab-ulary size), closed head injury, dyslexia (andother developmental language disabilities),epilepsy, mood disorders, Parkinson’s disease,


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psychopathy, and schizophrenia (reviewed inKuperberg 2010, Munte et al. 2000). Moregenerally, the N400, often in conjunction withneuropsychological measures, has been used tomeasure individual differences in language andmemory functions in the general population,across the lifespan.

NEW AND MATURINGRESEARCH LINES (1999–2009)

As the field matured, N400 data not only helpedto answer classic, often subdiscipline-specificquestions, but to raise new ones—about the va-lidity of long-standing theoretical dichotomies,the reality of certain core cognitive and lin-guistic constructs, and, indeed, the separabil-ity of the subdisciplines themselves. Accord-ingly, many studies in the literature of thistime are difficult to neatly categorize into broaddomains, as above. Instead, N400 work high-lighted the complex interactions between—andinherent neural inseparability of—perception,attention, memory, language, and meaning.

Language

Discourse processing and world knowl-edge. Expanding on work comparing effectsin word pairs and sentences, researchers beganto look at the comprehension of multisentencetexts (reviewed in Van Berkum 2009). Theyfound that N400 amplitudes were sensitive todiscourse in the same manner and with thesame time course as to word- and (isolated)sentence-level constraints and that the patternof prevalence of higher over lower levels ofanalysis extended to discourse (e.g., discourseconstraints reversing N400 repetition effects:Camblin et al. 2007). For example, simplyadding an informative title to a locally coherentbut globally opaque text passage sufficed toreduce the amplitude of the average N400 to allthe content words in the passage. Further workshowed that N400s to words in identical, com-prehensible sentences were smaller when theywere consistent with the discourse context than

when they were not. Thus, discourse effects un-fold very rapidly—in the case of a spoken word,even before its acoustic realization ends. Giventhe similarity of these N400 discourse effects toother linguistic and even nonlinguistic N400 ef-fects, it would seem unnecessary to resort to anylanguage-specific model to account for them.

Indeed, in many cases, discourse effectswould seem to draw heavily on comprehen-ders’ world knowledge. On some accounts, thistype of knowledge is taken to be distinct fromfacts about words and their meanings and thusshould be processed differently—e.g., lexico-semantic knowledge integrated prior to worldknowledge and pragmatics. N400 data unequiv-ocally show that this type of account is not vi-able (Hagoort et al. 2004): In the context ofa sentence such as “Dutch trains are ____ andvery crowded,” there is no measurable differencebetween the N400 to “sour,” which clearly vio-lates semantic constraints, and that to “white,”which does not but which is at odds with the factof “yellow” Dutch trains (with smallest N400s);similar sensitivity to real-world script knowl-edge can be seen even in word priming (Chwilla& Kolk 2005). Voice-based inferences aboutwho a speaker is (e.g., probable age, gender,and/or social status) and thus what they arelikely to know, believe, or say also modulateN400 activity. Furthermore, what knowledgeis used and how is quite dynamic and flexible.As reviewed in Van Berkum (2009), a prag-matic anomaly out of context (e.g., peanutsfalling in love), associated with large N400 am-plitude, can be attenuated by a context thatidentifies the situation as fictional. Similarly,the insensitivity of the processes indexed by theN400 to negation (discussed above) is amelio-rated when negation is pragmatically licensed(i.e., is being used to reasonable purpose), withequally reduced N400 amplitudes to sentencefinal words in “With proper equipment, scuba div-ing is safe/isn’t dangerous.” N400 data thus attestto the incredible power of the language systemto rapidly access, integrate, and adapt to word,sentence, and discourse information, along withworld knowledge and common ground.


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Nonliteral language. In addition to com-pelling the retrieval of facts, language sup-ports abstraction and flights of fancy, not in-frequently expressed via figurative language.Studies of nonliteral language processing havecapitalized on the temporal precision of ERPsto test hypotheses about when and how (fromwhat information) nonliteral meaning is con-structed, and whether the processing of literaland nonliteral language differs in quantitativeand/or qualitative ways. Irony and sarcasm havereceived some inquiry, but the primary focushas been on joke and metaphor comprehen-sion (reviewed by Coulson 2011). Overall, theprocesses indexed by the N400 seem to unfoldin a similar manner with the same timing forfigurative as for literal language, contrary tothe view that meaning processing for nonlit-eral language is inherently slower. For instance,whereas N400s are larger for metaphors (“Heknows that power is a strong intoxicant”) thanfor nonmetaphorical controls (“He knows thatwhisky is a strong intoxicant”), they are of inter-mediate amplitude for literal sentences that re-quire explicit mappings between objects and thedomains in which they commonly occur (“Heused cough syrup as an intoxicant”). N400 effectsthus suggest quantitative rather than qualita-tive differences between literal and figurativelanguage, with metaphors often taxing mappingand conceptual integration processes more thanliteral sentences. At the same time, however,some aspects of joke comprehension seem eas-ier for the RH than LH, as inferred from dif-ferential N400 attenuations to probe words fol-lowing one-line jokes.

Plausibility. Although the N400 is broadlysensitive to factors related to semantic fit, somesurprises have been encountered, especiallythe finding that thematic role (verb argument)violations, which a priori were thought to besemantic in nature and certainly have strongsemantic implications, did not necessarily mod-ulate N400 amplitudes (reviewed in Kuperberg2007). For example, N400s were not differentto “eat” in “For breakfast the boys would onlyeat. . .” than in the thematically incongruent

“For breakfast the eggs would only eat. . .” Instead,this comparison yielded a P600-like positivity.Importantly, such findings, like those for nega-tion, constraint, and related anomalies, serve toemphasize that the N400 is not simply an indexof semantic plausibility. Instead, it seems clearthat plausibility judgments are some functionof a number of processes that differ in the timecourse of their availability, and are usuallyevaluated as a nonspeeded, end-state response.In contrast, the N400 occupies a temporallydelimited place within an incremental system(see discussion in Federmeier & Laszlo 2009).Thus, in some cases (e.g., negation in theabsence of pragmatic licensing), informationthat ultimately impacts plausibility judgmentsis not active in time to modulate N400 activity.In other cases, information associated withimplausible stimuli has, at least temporarily,been activated—e.g., because incoming wordsshare features with contextually inducedpredictions or are related to or associated withother words or concepts in the sentence ordiscourse—creating what Kuperberg (2007)calls a “temporary semantic illusion.” Notably,in this context, it is important to distinguishbetween a lack of an N400 effect and a lackof an N400 component, because failure tofind an N400 difference across conditions(because both are facilitated relative to a whollyunexpected baseline condition or becauseneither is) cannot be used to conclude thatthe operations indexed by the N400 have beensuspended or blocked (Bornkessel-Schlesewsky& Schlesewsky 2008, Kolk & Chwilla 2007).In these cases there are N400 responses, justnot differential levels of activity in the semanticsystem across two inputs that ultimately yielddifferent plausibility judgments. Similar con-siderations apply to the literature employingdouble-violation paradigms (in which a givenword violates constraints at multiple levels ofanalysis) to ask how different aspects of lan-guage (especially semantic and syntactic ones,but also prosodic) may interact (Gunter et al.2000, Hagoort 2003). These studies have re-vealed complex interactions between meaningand form-based analyses, but more generally


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serve to highlight the utility of the multidimen-sional nature of the ERP signal, which allowsdifferent types of language-related effects tobe examined in parallel, on the same word,without obfuscating their separate influences.

Predictive processing. With accumulatingdata attesting to the prevalent role of sentenceand discourse context information in shapinglanguage comprehension, a key question forthe field became when and how context affectsthe processing of an incoming word. Answersto these questions would help adjudicatebetween bottom-up processing models andinteractive ones, in which top-down informa-tion and bottom-up information are assumedto be processed in parallel and in a mutuallyconstraining manner. ERP work in this timeperiod provided some of the earliest andmost powerful evidence showing that contextshapes word processing from its earliest stages.Indeed, it became clear that, at least for youngadult comprehenders, context informationactually serves to preactivate features of likelyupcoming words, such that the processing ofunexpected stimuli that share semantic (Kutas& Federmeier 2000) or even orthographic(Laszlo & Federmeier 2009) features with pre-dicted items is facilitated. Strong evidence forpredictive processing in language came fromERP studies that examined responses to wordspreceding a predicted target—for example,function words or adjectives that, althoughperfectly compatible with the accrued contextinformation, matched or mismatched in gender(e.g., van Berkum et al. 2005, Wicha et al. 2003)or form (e.g., English “a” versus “an”: DeLonget al. 2005) with a predicted (but not yet pre-sented) upcoming word [e.g., “On windy days,the boy liked to go outside and fly a/an . . .” (wherekite is predicted)]. Because, in the absence ofprediction, these modifying words constituteequally good fits to the accrued contextualinformation, N400 reductions when the wordsmatched as opposed to mismatched the pre-dicted target showed clearly that informationabout likely upcoming words has shaped thesystem in advance. Furthermore, at least in the

auditory modality where information about aword accrues over time, N400 data (Van Pettenet al. 1999) made clear that the processing ofpredictable and unpredictable words divergesprior to a word’s recognition point—essentiallyas soon as the system detects contextually mis-matching perceptual information. ERP datahave also suggested, however, a shift towardmore passive, bottom-up processing strategiesin many (although not all) healthy, agingindividuals (Wlotko et al. 2010).

There are thus multiple routes to successfulcomprehension, and studies combining ERPmeasures with visual half-field presentationmethods, used to bias processing toward thecontralateral hemisphere, have made clear thatit would be an error to conceive of compre-hension as unfolding along a single processingstream, even within a given individual of aparticular age (for reviews, see Federmeier2007, Federmeier et al. 2008). Such data revealboth important contributions to meaning com-prehension from RH processing as well as im-portant hemispheric differences, including theextent to which processing in each hemisphereis sensitive to prediction-based influences.Federmeier (2007) has hypothesized that animportant source for such asymmetries may bemore efficacious top-down connections in theLH, supported by LH-dominant language pro-duction mechanisms. Regardless of the precisenature and source of the differences, however,ERP data make clear that any complete theoryof language processing will have to acknowl-edge the separate contributions of these twoprocessing streams and explain how they cometogether to serve comprehension goals.

Word recognition. Collectively, N400 sen-tence-processing data point to a language com-prehension system that makes use of all the in-formation it can as soon as it can in order todeal with a rapid, noisy input stream. Such datahelped to compel a shift away from models thattreat word recognition as a relatively isolated,data-driven process and also led to a reconsid-eration of the postlexical view of the N400.With that came a surge of interest in using


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the measure to examine aspects of word recog-nition, including the nature and influence oforthographic and phonological levels of struc-ture and the representation and processing ofmorphology. The results lined up well withinteractive views, revealing highly intertwinedand sometimes multiple effects of many lexicalvariables (reviewed in Barber & Kutas 2007).Furthermore, the fact that not only words butalso pseudowords (e.g., GORP) and even illegalstrings (e.g., NKL) were subject to the process-ing reflected in the N400 (Laszlo & Federmeier2009) and were similarly sensitive to language-relevant variables (such as orthographic neigh-borhood size) suggests that the process of cate-gorizing inputs as lexically represented or evenorthographically regular occurs in parallel withattempts at meaning access.

ERP evidence thus suggests that the wordrecognition process is extended over time, withcritical aspects only beginning to take placearound 200 ms after word onset; N400 datahave mapped out a very similar time course forface recognition (reviewed by Schweinberger &Burton 2003). Although this accords with moregeneral views of the time course of processingin the brain, as well as with what is known aboutthe nature and neural source of componentspreceding the N400, it has sparked some con-troversy. In particular, the time course of pro-cessing suggested by ERPs is striking given thateye movements during natural reading tend tobe fast and that some models of eye movementcontrol assume that word recognition drives(and hence precedes) saccades (Reichle et al.2003). Thus, N400 data place important con-straints on our understanding of when and howwords are recognized and linked to meaning,with implications not only for psycholinguistictheories but also for, e.g., models of eye move-ment control.

Language learning and bilingualism. In par-allel with studies of the factors affecting adultword recognition is a growing literature har-nessing the power of ERPs to study languagelearning and development. The neural archi-

Orthographicneighborhood: anitem that shares all butone letter in commonwith a particular wordis its orthographicneighbor

tecture necessary to support N400 processingseems to be available quite early, as N400 ef-fects have been reported in children as young as9 months viewing unexpected events in actionsequences (Reid et al. 2009). In the domain oflanguage, picture/word congruity N400 effectshave been seen by 12 to 14 months of age andvary with (productive) vocabulary (Friedrich &Friederici 2010). Semantic congruity effects insentences have been reported by 19 months andare predictive of language skill at 30 months(Friedrich & Friederici 2006).

ERPs have also been used to address a num-ber of important issues in the area of bilin-gual language processing, including questionsabout critical periods, effects of language pro-ficiency and dominance, relationships betweena bilingual’s two languages, and effects of code-switching, among others (reviewed in Kutaset al. 2009). N400 semantic priming and sen-tence congruity effects have been reported formore than a dozen languages in both mono-linguals and bilinguals, with no evidence thatN400s differ in their timing or topography asa function of specific language characteristicsor writing systems. N400 parameters, however,are sensitive to an individual’s proficiency witha language, even if they know only one, makingthem an excellent tool for investigating com-petence in adult second language acquisition.McLaughlin et al. (2004), for instance, showedthat N400 amplitude reductions could distin-guish words from pseudowords with only 14hours of classroom instruction in a second lan-guage, and semantically related words from un-related ones with as little as 63 hours. Thesereliable N400 effects were accompanied bychance-level overt word and relatedness judg-ments, highlighting the sensitivity of ERP mea-sures to early, implicit aspects of learning. Moretypical bilinguals show N400 priming and se-mantic congruity effects in both of their lan-guages, with the timing (and to a lesser extentthe amplitude) of these effects a function oflanguage proficiency and age of acquisition—being later and smaller for less well-learnedlanguages.


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Semantic Memory

Scenes, actions, and gestures. N400 studiesexpanded into much richer nonlinguisticcontexts (reviewed in Sitnikova et al. 2008),looking at congruency effects within picturesequences conveying a story, photos of objectsin a visual scene (roll of toilet paper versussoccer ball in a soccer game), and short videosof everyday events (razor versus rolling pinused as a razor in a clip of a person shaving).The N400 effects elicited in these paradigmsresemble lexico-semantic N400s in morphol-ogy and timing, with some differences in scalptopography (more frontal than those seen forwritten abstract words), although temporaloverlap with an earlier, frontally distributednegativity (N300) observed in such paradigmscomplicates topographic assessments. Willemset al. (2008) directly compared speech andpicture N400 effects as individuals listened tosentences in which a critical word, a coincidentdepicted object, or both could be contextuallycongruent or incongruent. Relative to thewholly congruent condition, all mismatchconditions yielded larger fronto-central N400sindistinguishable in amplitude, latency, orscalp topography. Such data argue againstany view of sense-making in which linguisticinformation is treated differently (in time ornature) than nonlinguistic (objects, scenes)information. Indeed, even for linguistic stimuli,emerging N400 data made clear that manydifferent kinds of features, including sharedphysical shape (e.g., between coin and button:Kellenbach et al. 2000) and emotional valence(Schirmer & Kotz 2003), contribute to seman-tic analysis. The view of the N400 as a markerof language processing is thus shifting towarda view of the N400 as reflecting meaningprocessing more broadly. Correspondingly,the N400 is increasingly appreciated as a toolfor examining object and face recognition aswell as action and gesture processing.

Relative to typical actions, actions that arepurposeless, inappropriate, and/or impossiblealong various dimensions (e.g., cutting jewelryon a plate with a knife and fork, cutting bread

with a saw, standing on one foot in the mid-dle of a desert) elicit N400 effects, suggestingfunctional similarity in comprehending every-day scenes and linguistic expressions of such(e.g., Proverbio & Riva 2009). Critically, boththe appropriateness of the object used in an ac-tion (e.g., inserting screwdriver versus key intoa keyhole) and the appropriateness of featuresof the motor act itself (e.g., orientation of theobject with respect to the keyhole) individuallyand jointly modulate N400 amplitudes (Bachet al. 2009), although topographic and dura-tional differences implicate partially nonover-lapping neural systems. Other N400 data haveshown that the relationship between hand shapeand the shape of an object to be grasped is usedby observers to make sense of the details and co-operativeness of interpersonal actions (Shibataet al. 2009). This emerging line of N400 workthus shows that motor and object features makeearly, parallel contributions to how an action isunderstood. Moreover, preparation to executea meaningful (but not meaningless) action in-fluences the N400 to a word (related or not tothe action’s goal) presented prior to action exe-cution, indicating that semantic activation maybe inherent in action preparation (van Elk et al.2008). Clearly, actions can serve as a semanticcontext for words, and the N400 as a means ofassessing how and when conceptual knowledge,language, and action converge.

The relationship between motor activityand language has been further explored in thedomain of gesture, with N400 data providingstrong evidence that gestures are analyzed andused semantically in real time. N400 effectshave been reported for gestures that mismatcha prior spoken word with respect to an objectproperty and those that mismatch an action ina preceding cartoon sequence or spoken sen-tence (Kelly et al. 2004, Wu & Coulson 2005).Moreover, when either of a co-occurringgesture and spoken word was semanticallyanomalous (versus congruent) with an ongoingspoken sentence context, the resulting N400effect had the same time course (Ozyurek et al.2007). N400 data thus have demonstratedthat body movements can influence ongoing


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language comprehension almost immediatelyand in a manner functionally indistinguishablefrom linguistic inputs.

Math. Mathematics is another domain, usuallyconsidered quite distinct from language, thathas shown canonical N400 effects. Whether us-ing an arithmetic verification task or a more im-plicit probe task (Galfano et al. 2004), responsesto incorrect (versus correct) solutions are char-acterized by centro-parietal negativity, whichwithin-subjects comparisons indicate is virtu-ally identical to that for semantically incon-gruous words in written sentences (Niedeggenet al. 1999). Perhaps even more importantly,the arithmetic N400 effect shows a remarkablefunctional similarity to lexico-semantic ones: Itsamplitude is similarly sensitive to relations be-tween items in long-term memory and is disso-ciable from concomitant RT measures. For ex-ample, Nieddegen & Roesler (1999) recordedERPs and RTs for multiplication facts (5 ×8) that were either correct (40) or incorrect,and, when incorrect, varied in numerical dis-tance from the correct product and were ei-ther related (32, 24, 16) or unrelated (34, 26,18) to the operands. Both these factors influ-enced RTs additively. N400s, however, weresmall to correct solutions, equally large to allunrelated solutions and to distant related solu-tions, and intermediate in size to incorrect so-lutions that were both close and related. Thus,although the neural systems need not be iden-tical, it certainly seems that similar functionalprinciples are at work during the processing ofsemantic/linguistic and arithmetic knowledge.

Recognition Memory

For a time, memory research parted wayswith the rest of the N400 literature, in largepart because the N400-like response studiedin the context of recognition memory cameto be regarded as a separable component—the“FN400” (frontal N400)—based on its appar-ently different scalp topography and purportedlink with explicit familiarity signals. In a piv-otal study, Curran (2000) investigated FN400

FN400: frontal N400

effects using a plurality reversal manipulationshown to reduce recollection but to have lit-tle effect on familiarity. This manipulation hadno effect on FN400 repetition effects, but itdid influence ERPs associated with recollec-tion [late positive complexes (LPCs)], support-ing an association between FN400 and famil-iarity. Many studies followed that used similartechniques to associate FN400s with familiarityand LPCs with recollection, thereby support-ing dual-process memory models that posit aqualitative distinction between the brain areasand processing involved in feelings of familiar-ity from those involved in conscious recollec-tion (reviewed in Rugg & Curran 2007).

However, more recently, some have ques-tioned the distinction between the N400 andFN400. Topographical differences (which aredifficult to interpret given the possibility ofcomponent overlap) and paradigmatic differ-ences notwithstanding, no study has actuallydissociated the N400 from the FN400. Indeed,some evidence indicates their functional simi-larity. For instance, like the N400, the FN400does not vary in latency as a result of multipleencounters with the same stimulus ( Johnsonet al. 1998). Moreover, Paller and colleagues(2007) have argued that empirical evidenceshowing the FN400 is not sensitive to consciousrecollection does not necessarily warrant theconclusion that it must be related to familiarity.

Thus, some recent research has endeavoredto reconnect the two literatures by positing thatin the context of memory, the FN400 is actuallya marker of facilitated conceptual processingdue to repetition, or conceptual priming, and isnot directly related to feelings of familiarity. Onthis view, then, the FN400 is an N400, elicitedby meaningful stimuli in recognition tasks andmodulated in amplitude when prior exposurerenders semantic processing easier. To dissoci-ate conceptual priming from familiarity, thesestudies have measured both in highly similarcircumstances in order to identify ERPs thatvary with one versus the other. Voss & Paller(2006), for instance, found that priming con-ceptual information associated with celebrityfaces led to FN400 effects that covaried with


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the magnitude of priming, but, critically, notwith familiarity for the same faces. Anotherline of research used abstract geometric shapes,which vary in their meaningfulness to individ-ual participants and thus in the extent to whichthey can support conceptual priming with rep-etition, but which can be made more familiarby repetition, independent of meaningfulness(Voss & Paller 2007). Only meaningful shapesproduced FN400 effects, indicating that it is thepotential for conceptual priming, not familiar-ity, that drives FN400 modulations. Such stud-ies collectively provide strong evidence againstpurported functional distinctions between theFN400 and the N400, indicating instead thatthe processing responsible for the N400 is alsoactive during recognition memory tasks.

THEORIES OF THE N400

With the rapid growth of the literature havecome attempts to develop theories of the N400.Some of these are anchored at the neurobi-ological level, seeking to delineate the brainnetwork(s) responsible for the N400 (Lauet al. 2008) and linking the component tospecific neural functions, such as binding(Federmeier & Laszlo 2009). Others areframed at a functional level, mapping theN400 onto particular cognitive operation(s),such as orthographic/phonological analysis(Deacon et al. 2004), semantic memory access(Kutas & Federmeier 2000, van Berkum 2009),or semantic/conceptual unification (Hagoortet al. 2009). Many of these functional viewsare based on the underlying assumption thatcomprehension involves a feedforward seriesof processes in which words are analyzed firstas perceptual objects and then as linguisticobjects (lexical processing), culminating in thematch between a phonological or orthographicinput and a representation in the mentallexicon—i.e., in word recognition. Critically,upon recognition, semantic (among other typesof) information becomes available and can thenbe integrated with the current mental model ofthe unfolding sentence or discourse. A similarstream of increasingly complex perceptual

analyses leading to recognition, which then af-fords semantic access, also has been posited forface and object processing. On such a view, theN400 might be functionally characterized asarising from one (or more) of these processingsteps, and, indeed, which one(s) of these pro-cesses the N400 reflects is what distinguishesmost of the currently competing theories.

On one end of the spectrum are views(Brown & Hagoort 1993, Hagoort et al. 2009)that position the N400 relatively late (postitem recognition) in this processing stream,associating the N400 to processes linkingup (integrating) the semantic informationaccessed from the current word with meaninginformation encompassing multiple words(e.g., sentence or discourse message-levelrepresentations, presumably held in workingmemory). In particular, Hagoort et al. (2009)identify the N400 with semantic “unification”processes, defined as “the integration oflexically retrieved information into a represen-tation of multi-word utterances, as well as theintegration of meaning extracted from nonlin-guistic modalities,” placing special emphasis onthe constructive nature of the meaning integra-tion (“a semantic representation is constructedthat is not already available in memory”).Views of this type that associate the N400 withpostlexical aspects of semantic analysis canreadily account for the multimodal and cross-modal nature of the N400, on the assumptionthat the various meaning-laden stimulus typesultimately converge on shared (or at leastpartially overlapping) conceptual-level repre-sentations. They can also easily explain thesensitivity of N400 amplitude to pragmatic anddiscourse-level manipulations, and the relativeprecedence, in many cases, of such high-levelfactors over lower-level ones. However, chal-lenges for such late-stage accounts include thepresence of N400s to stimuli that are not rep-resented in the mental lexicon (pseudowordsand even illegal strings) and the emergence ofN400 effects to lexically represented stimuliprior to their recognition point (i.e., beforea listener knows which word s/he is hearing).Furthermore, for all of these stimulus types,


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N400 amplitude is sensitive to a whole hostof factors whose sole or primary influence ispresumed to be at earlier (prelexical or lexical)processing stages, such as orthographic neigh-borhood size and neighbor frequency, lexical(and subpart) frequency, orthographic andphonological similarity, and repetition. Finally,integration/unification processes have beenlinked to top-down control mechanisms,yet N400 effects have been observed underconditions in which such control seems un-likely, as for semantic priming effects underthe attentional blink or repetition effects inamnesic patients.

On the other end of the processing contin-uum, the fact that, e.g., N400 repetition ef-fects are seen even for pseudowords with lit-tle resemblance to known words—i.e., stimulithat are not represented in the mental lexi-con and thus presumably cannot have associatedsemantics—has led others to postulate that theN400 reflects processing stages prior to wordrecognition and semantic access, such as ortho-graphic and/or phonological analysis (Deaconet al. 2004). The strengths and weaknesses ofthis pre-recognition view are a mirror image ofthe integration view: This framework providesa straightforward explanation for basic lexical-level influences on the N400 but no obviousaccount of discourse effects and their prece-dence in shaping N400 patterns. Moreover, be-cause this account is word specific, N400 ef-fects to nonlinguistic stimuli must be assumedto arise from functionally similar—but never-theless distinct—neural activity.

The broad sensitivity of the N400 to bothlower-level and higher-level factors that impactmeaning processing has spawned a number ofaccounts that position the N400 at the junc-tion where these processes intersect—namely,at the level of semantic access itself (Kutas &Federmeier 2000; see also Lau et al. 2009,van Berkum 2009). However, even this “mid-dle ground” approach cannot explain the fullrange of N400 data if the assumptions of thetraditional processing model are maintained.For example, on the assumption that a wordmust be recognized before its meaning can be

accessed, N400 effects for nonlexically repre-sented stimuli remain inexplicable. Similarly,on the assumption that processing is wholly orlargely feedforward, it becomes difficult to rec-oncile the immediate and often dominant influ-ences of more global aspects of context on initialsemantic access.

Given that the N400 does not readily maponto specific subprocesses posited in traditionalframeworks, which have been built largely frombehavioral and linguistic evidence, it may provemore fruitful to use what has been learned aboutthe N400 to reshape the underlying concep-tualizations of how comprehension unfolds, inways that are more constrained by our under-standing of neural processing. In the context ofthe typical stream of brain activity triggered byan incoming stimulus, the N400 can be char-acterized as a temporal interval in which uni-modal sensory analysis gives way to multimodalassociations in a manner that makes use of—and has consequences for—long-term memory.Processing in the first 200 or so milliseconds af-ter the onset of a potentially meaningful stimu-lus is dominated by brain activity related to per-ceptual analysis, which differs across modalityin its spatial and temporal characteristics as wellas in its sensitivity to factors like attention. Withthe N400, then, these different input streamsconverge—temporally, spatially, and function-ally. Given notable variability across stimuli infactors such as familiarity and perceptual com-plexity, it would seem that the time neededto settle into a final, stable state of perceptualanalysis (i.e., recognition) must necessarily dif-fer for different types of input (and, likely, alsoas a function of task and context). Indeed, be-havioral and other electrophysiological indices(such as the P3b) change their latency relativeto the stimulus of interest in ways that are sys-tematically related to these factors (e.g., Kutaset al. 1977). Yet, such variables routinely affectthe amplitude—but usually not the timing—of the N400 (see review in Federmeier &Laszlo 2009). This implies that initial accessto long-term multimodal (semantic) memory,as indexed by the N400, occurs at differentpoints along the apprehension-to-recognition


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continuum for different stimuli and under dif-ferent conditions: some stimuli may be “rec-ognized” before access, but for others, accessmay be initiated before recognition is complete.In other words, access to item-associated infor-mation in long-term memory (LTM) may bedecoupled from recognition.

Because the transition from unimodal tomultimodal processing (e.g., from word formto the concept that word brings to mind)is neither dependent upon nor driven by aparticular functional outcome of perceptualanalysis, all types of stimuli, from the highlypracticed to the completely novel, would beexpected to elicit N400 activity to some degree,with the amount and nature of that activity afunction of the stimulus-induced state of theperceptual system at the time that semanticaccess is initiated. For example, to the extentthat neural representations are distributedand/or the activation of stimulus features isnoisy (e.g., that the visual input C-A-B acti-vates not only “CAB” but also, to some extent,“DAB,” “CUB,” and “CAR”), semantic infor-mation associated with all of these coactivatedrepresentations will come online together,with a strength proportional to the strengthof the eliciting perceptual signal. Rather thanreflecting the activation of “a word’s meaning,”then, the N400 region of the ERP is moreaccurately described as reflecting the activity ina multimodal long-term memory system thatis induced by a given input stimulus during adelimited time window as meaning is dynam-ically constructed (see discussion in Laszlo &Federmeier 2010). Such activity is observed fornonwords as well as for words, rendering thesystem more robust to input noise and provid-ing a mechanism for implicit conceptual-levellearning of novel stimuli (Gratton et al. 2009).Baseline activity levels, however, will be higherfor some stimuli than for others because theyare similar to or associated with many otherthings stored in memory (e.g., have high or-thographic neighborhood sizes, large cohorts,or many lexical associates) and/or because theyare linked to more meaning features (e.g., areambiguous, more polysemous, or concrete as

opposed to abstract). Given evidence that thesemantic feature information being accessed iswidely distributed across the neural network,it also follows that different stimuli and typesof stimuli (e.g., words and pictures) elicitfunctionally similar but spatially different ac-tivity patterns across this distributed network,resulting in the observed differences in thetopography of scalp-recorded N400s.

Although the N400 reflects stimulus-induced semantic activity in LTM, it does notnecessarily follow that the activation states ofthe semantic memory system as a whole arestrictly a function of the current input (elicit-ing stimulus) or, indeed, even of feedforwardstimulation in general. There is presumably al-ways activity in the semantic system, and thatactivity is in constant flux in response to bothexternal and internal events and states. For ex-ample, information that is encountered moreoften may tend to have higher baseline states ofactivity, and information that has been accessedrecently—due to stimulus repetition or featu-ral overlap—also will tend to be more active.Furthermore, activation states can be modu-lated by internally generated events, such as re-calling a stimulus or predicting an upcomingone. Finally, a wide variety of state and trait-based factors—e.g., mood (Federmeier et al.2001) and schizotypy (Kiang & Kutas 2005)—as well as task demands and goals may changeactivity levels in semantic memory, at the globalor more local levels, if not both. In all of thesecases, to the extent that some information rep-resented in LTM is already partially or whollyactive by the time semantic access for a giveninput stimulus is initiated, that information willnot need to become active in response to the in-put. Thus, preactivation of semantic informa-tion, by any means, will tend to reduce baselineN400s to a stimulus that would normally acti-vate that information. As a consequence, in anexperimental context, the N400 response to agiven input can be used as a tool to assess seman-tic memory states, with the amount of N400reduction (relative to a control condition) re-vealing how much of the information normallyelicited by that stimulus is already active.


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The N400 window thus provides a tem-porally delimited electrical snapshot of theintersection of a feedforward flow of stimulus-driven activity with a state of the distributed,dynamically active neural landscape that issemantic memory. As such, N400 activity canbe modulated by factors that affect either theinput stream or the configuration of activity insemantic memory. Manipulations of attention,for instance, may affect either or both ofthese levels. Attentional manipulations mayserve to preactivate information in semanticmemory by rendering some information moreimportant and/or more predictable underone task condition than another, and/or bymodulating the strategies that participantschoose to or can use—for example, what kindof controlled processes are brought to bear inorder to remember, integrate, or disambiguateinputs—with consequences for the state ofsemantic memory then encountered by subse-quent stimuli. Such manipulations might thusaffect the size of N400 effects observed. VanBerkum (2009) also emphasizes that semanticretrieval can be intensified by attention. Onthe view we are building here, one way that thiscould happen is by effects of selective attentionon the sensory input. Much ERP work detailshow selective attention to space, objects, andvarious perceptual features of objects canmodulate the amount of feedforward activityelicited by an incoming stimulus (Luck et al.2000). To the extent that the N400 is part ofthis feedforward stream, selective attentionwould be expected to correspondingly modu-late even baseline N400 amplitudes. However,just as selective attention generally does noteradicate sensory ERP components, it wouldseem unlikely to eliminate all signs of N400 ac-tivity and, since the nature of attentional effectsdiffers across modalities, N400 modulations byattention would likely as well. We suggest thatattention can thus serve to alter the balancebetween the contributions of feedforward andtopdown activity to the processing of meaning.That balance also seems to be importantlydifferent between the two cerebral hemispheres

(Federmeier 2007), with concomitant impacton the N400 seen when processing is bi-ased toward the LH and RH (which haveseparable feedforward perceptual streams,each capable of triggering and modulating anN400).

In sum, the N400 arises from a time pe-riod in which stimulus-driven activity entersinto temporal synchrony with a broad, mul-timodal neural network, whose current stateshave been shaped by recent and long-term ex-perience of a wide range of types (e.g., basedon world experience, long-standing and recentlinguistic and nonlinguistic inputs, attentionalstates, and affect/mood). Federmeier & Laszlo(2009) have hypothesized that this temporalsynchrony effects a binding, creating a multi-modal conceptual representation. Notably, onthis view, conceptual representations are notlooked up in memory but rather are dynami-cally created and highly context dependent: Be-cause semantic memory states are continuouslychanging, the meaning of a given stimulus, de-fined as the configuration of neural activity thatis bound together in response to that stimu-lus, will be somewhat different across people,time, contexts, and processing circumstances.The binding that occurs during the N400 isimplicit and transient—although the activityelicited by a given input will have an influencefor a short time (e.g., in the form of repetition orconceptual priming effects), even when explicitmemory systems are compromised (as in am-nesics, for example). Furthermore, given thatthe N400, and effects on it, can be obtained un-der conditions of reduced awareness, it seemsunlikely that N400 activity is directly respon-sible for the conscious experience of meaning(although the presence of N400 activity maybe a useful marker of whether neural systemshave the properties and/or integrity to supportsuch awareness: Schoenle & Witzke 2004). Ini-tial conceptual representations may thus be lost,or may enter into consciousness, be stored inworking memory, and/or (assuming an intacthippocampus) come to be stored in long-termmemory.


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More generally, this highlights the fact thatthe meaning of a stimulus is not computed at asingle point in time, but rather is something thatemerges through time, with the activity mea-sured in the N400 representing an importantaspect of that emergent process, but not, cer-tainly, the final state. Indeed, at the time of theN400, meaning states may still be incoherent,either because a given stimulus elicits more thanone disparate meaning (i.e., is ambiguous or,as in the case of unfamiliar nonwords, broadlyelicits activity associated with similar inputs) orbecause context information has induced onestate and the incoming stimulus a different one(e.g., in the case of semantic anomalies, but alsomore generally when unexpected words are en-countered or contextually induced predictionsare disconfirmed). Thus, initial conceptual rep-resentations, as reflected in the N400, will oftenneed to be refined with time, either throughcontinued interactions within semantic mem-ory or via the application of later-occurring pro-cesses that serve to select meaning features, re-vise initial interpretations, or otherwise updatemeaning representations (for example, adding

information that might not have become avail-able by the time the N400 was triggered; seediscussion in Federmeier & Laszlo 2009).

CONCLUSIONS

Although an emerging theory of the neural andfunctional nature of the N400 may help to or-ganize the growing literature and spark novelpredictions, the outcome of current theoreti-cal debates would have remarkably little impacton the contributions of the great majority ofthe work highlighted throughout this reviewusing the N400 as a dependent measure. Im-pressive gains have been made across a wholehost of cognitive domains, and, perhaps mostcritically, the N400 has been instrumental inbreaking down barriers between those domains.The N400 literature, taken as a whole, providesa compelling picture of how perception, atten-tion, memory, and language jointly participatein the neural events responsible for the N400and thus together contribute to the amazingability of the human brain to infuse its worldwith meaning.

SUMMARY POINTS

1. ERPs provide temporally exquisite brain measures that have proven especially powerfultools for getting at aspects of cognition largely impenetrable with behavioral measures—for distinguishing among qualitatively different processes and tracking their time courses,often without any overt task and sometimes even in the absence of awareness.

2. ERP data in general—and the N400 in particular—underscore the crucial role for time(and timing) in comprehension (as in cognition more generally).

3. Furthermore, N400 data:(a) point to a distributed, multimodal, bihemispheric comprehension system that is si-multaneously open to linguistic and nonlinguistic influences, which often interact;(b) suggest that access to meaning is a natural part of the stimulus-elicited processingstream, not dependent on an information state such as “recognition,” and thus open toall stimuli in all task conditions (unless the feedforward stream has been suppressed byselective attention);(c) have shown that comprehension is largely nonserial, at least partially incremental,predictive, flexible, and context-dependent; and(d ) have been instrumental in blurring the line between long-honored dichotomies suchas prelexical versus postlexical, automatic versus controlled, and literal versus nonliteralprocessing, among others.


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FUTURE DIRECTIONS

1. The conceptual system immediately integrates new information into its emergingrepresentation-–except when it doesn’t. What information is immediately processed (towhat analytic depth, determined by what factors) and incrementally updated? Why is theappreciation of some types of information (thematic role, negation) often delayed?

2. Similarly, the system can be predictive-–but under what circumstances is it predictive?What determines whether or not it functions predictively?

3. Given sensitivity of the processes indexed by the N400 to a wide range of stimulus typesacross modality, how are these different information types-–which make different kindsof information available and with different time courses—integrated as the brain makessense of current sensory-cognitive input?

4. When and how is information from two hemispheres brought together for normal com-prehension?

5. Which brain activity (if any) is common across all types of N400 effects and which brainactivity is specific to particular modalities and/or stimulus types and/or manipulations?

6. What controls the timing of the N400?

7. What is the relationship (associations and dissociations) between N400 measures andreaction time measures and eye movement measures?

8. Are there N400-like potentials in other species? If so, how is the processing of meaningsimilar or different across species? If not, what does this tell us about how other species“view” the world and make connections across sensory modalities?

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings thatmight be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

M. Kutas, K. Federmeier, and much of the work cited herein were supported by grants HD022614and AG83013 to MK and AG26308 to KF. We gratefully thank G. Dell, V. Ferreira, S. Laszlo,C. Lee, T. Munte, T. Urbach, J. Voss, and E. Wlotko for their comments on a previous version ofthis article. There would be little to review had it not been for the hundreds of studies and reportsby scientists worldwide. We wish we had the space to cite each and every one of the articles thatshaped our writings; instead, due to space constraints, we primarily cite reviews for all but therecent years. We thank you all.

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www.annualreviews.org • Thirty Years of N400 Research C-1

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←−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−Figure 1Over-sentence average ERP to words in written text, including large N400 effect to a semanticallyanomalous word. Above, on left, is canonical visual ERP comparison of congruent versus anomaloussentence final words, on a 3-microvolt scale (which applies to all but two waveforms, with 5-microvolt scalesinstead); above, on right, is a topographic map of the ERP difference (anomalous minus congruent, N400effect) from 300–500 ms postfinal word onset. (Row 1) All data sets from central midline site. Sentence Final:N400 to semantic anomaly and other sentence endings as function of average cloze probability (Kutas et al.1984); Sentence Medial: sentence medial noun at three levels of cloze probability; N400 x Cloze: correlationbetween mean N400 (300–500 ms) amplitude and cloze probability (DeLong et al. 2005). (Row 2) SentenceReading: midline parietal ERPs to expected or best completion (BC) ending given sentence context, low clozeprobability endings that were and were not related to the BC (Kutas 1993); Categorical Relations: ERPs tosentence final word that is an expected category exemplar or an unexpected, implausible exemplar from thesame category as the expected one (related anomalous) or from a different category (unrelated anomalous);Visual Hemifield: at right medial central site in response to final word briefly flashed in left visual field(LVF)—i.e., initially to the right hemisphere—or right visual field (RVF); Speech: at frontal midline site inresponse to naturally speech (see Federmeier 2007). (Row 3 ) Word Association: ERPs to second word of aword pair, strongly related, moderately related, or unrelated to the first word from same participants asSentence Reading above (Kutas 1993); Neighborhood Size: midline parietal ERP to letter strings includingwords, pseudowords, and acronyms in a list as a function of orthographic neighborhood size (Laszlo &Federmeier 2010); Word Repetition: ERPs to just the words upon initial presentation and their repetition,from these same experimental runs and participants. (Row 4) Math: midline central ERPs to correct equationsolutions and errors that were or were not related to the solution (Nieddegen et al. 1999); Video: midlinefrontal ERPs to last video frame, congruent or anomalous with prior video context (Sitnikova et al. 2008);Sentence Repetition: midline central ERP to congruent or anomalous sentence final words on initialpresentation and one repetition.

C-2 Kutas · Federmeier

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PS62-FrontMatter ARI 15 November 2010 17:50

Annual Review ofPsychology

Volume 62, 2011 Contents

Prefatory

The Development of Problem Solving in Young Children:A Critical Cognitive SkillRachel Keen � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1

Decision Making

The Neuroscience of Social Decision-MakingJames K. Rilling and Alan G. Sanfey � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �23

Speech Perception

Speech PerceptionArthur G. Samuel � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �49

Attention and Performance

A Taxonomy of External and Internal AttentionMarvin M. Chun, Julie D. Golomb, and Nicholas B. Turk-Browne � � � � � � � � � � � � � � � � � � � � � �73

Language Processing

The Neural Bases of Social Cognition and Story ComprehensionRaymond A. Mar � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 103

Reasoning and Problem Solving

Causal Learning and Inference as a Rational Process:The New SynthesisKeith J. Holyoak and Patricia W. Cheng � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 135

Emotional, Social, and Personality Development

Development in the Early Years: Socialization, Motor Development,and ConsciousnessClaire B. Kopp � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 165

Peer Contagion in Child and Adolescent Socialand Emotional DevelopmentThomas J. Dishion and Jessica M. Tipsord � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 189

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Adulthood and Aging

Psychological Wisdom Research: Commonalities and Differences in aGrowing FieldUrsula M. Staudinger and Judith Gluck � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 215

Development in the Family

Socialization Processes in the Family: Social andEmotional DevelopmentJoan E. Grusec � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 243

Psychopathology

Delusional BeliefMax Coltheart, Robyn Langdon, and Ryan McKay � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 271

Therapy for Specific Problems

Long-Term Impact of Prevention Programs to Promote EffectiveParenting: Lasting Effects but Uncertain ProcessesIrwin N. Sandler, Erin N. Schoenfelder, Sharlene A. Wolchik,

and David P. MacKinnon � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 299

Self and Identity

Do Conscious Thoughts Cause Behavior?Roy F. Baumeister, E.J. Masicampo, and Kathleen D. Vohs � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 331

Neuroscience of Self and Self-RegulationTodd F. Heatherton � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 363

Attitude Change and Persuasion

Attitudes and Attitude ChangeGerd Bohner and Nina Dickel � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 391

Cross-Country or Regional Comparisons

Culture, Mind, and the Brain: Current Evidence and Future DirectionsShinobu Kitayama and Ayse K. Uskul � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 419

Cognition in Organizations

Heuristic Decision MakingGerd Gigerenzer and Wolfgang Gaissmaier � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 451

Structures and Goals of Educational Settings

Early Care, Education, and Child DevelopmentDeborah A. Phillips and Amy E. Lowenstein � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 483

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Psychophysiological Disorders and Psychological Dimensionson Medical Disorders

Psychological Perspectives on Pathways Linking Socioeconomic Statusand Physical HealthKaren A. Matthews and Linda C. Gallo � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 501

Psychological Science on Pregnancy: Stress Processes, BiopsychosocialModels, and Emerging Research IssuesChristine Dunkel Schetter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 531

Research Methodology

The Development of Autobiographical MemoryRobyn Fivush � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 559

The Disaggregation of Within-Person and Between-Person Effects inLongitudinal Models of ChangePatrick J. Curran and Daniel J. Bauer � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 583

Thirty Years and Counting: Finding Meaning in the N400Component of the Event-Related Brain Potential (ERP)Marta Kutas and Kara D. Federmeier � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 621

Indexes

Cumulative Index of Contributing Authors, Volumes 52–62 � � � � � � � � � � � � � � � � � � � � � � � � � � � 000

Cumulative Index of Chapter Titles, Volumes 52–62 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 000

Errata

An online log of corrections to Annual Review of Psychology articles may be found athttp://psych.AnnualReviews.org/errata.shtml

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Documents

Thirty Years and Counting: Finding Meaning in the N400 ...apsychoserver.psychofizz.psych.arizona.edu/JJBA...Thirty Years and Counting: Finding Meaning in the N400 Component of the