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Biological Psychology 92 (2013) 464– 479

Contents lists available at SciVerse ScienceDirect

Biological Psychology

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motion, Etmnooi, or Emitoon? – Faster lexical access to emotional than toeutral words during reading

ohanna Kisslera,b,∗, Cornelia Herberta,c

Department of Psychology, University of Konstanz, Konstanz, GermanyDepartment of Psychology, University of Bielefeld, Bielefeld, GermanyDepartment of Psychology, University of Würzburg, Würzburg, Germany

r t i c l e i n f o

rticle history:eceived 3 August 2011ccepted 26 September 2012vailable online 8 October 2012

eywords:

a b s t r a c t

Cortical processing of emotional words differs from that of neutral words. Using EEG event-related poten-tials (ERPs), the present study examines the functional stage(s) of this differentiation. Positive, negative,and neutral nouns were randomly mixed with pseudowords and letter strings derived from words withineach valence and presented for reading while participants’ EEG was recorded. Results indicated emotioneffects in the N1 (110–140 ms), early posterior negativity (EPN, 216–320) and late positive potential

motionttentionord processing

exical accessRPsarly posterior negativity

(LPP, 432–500 ms) time windows. Across valence, orthographic word-form effects occurred from about180 ms after stimulus presentation. Crucially, in emotional words, lexicality effects (real words versuspseudowords) were identified from 216 ms, words being more negative over posterior cortex, coincidingwith EPN effects, whereas neutral words differed from pseudowords only after 320 ms. Emotional con-tent affects word processing at pre-lexical, lexical and post-lexical levels, but remarkably lexical accessto emotional words is faster than access to neutral words.

© 2012 Elsevier B.V. All rights reserved.

. Introduction

Visual processing of emotional words differs from visualrocessing of neutral words. Using electroencephalographic event-elated potentials (ERP) emotional–neutral differences have beendentified at various temporal stages following word onset inexical-decision, evaluation, or reading tasks (for review see Kisslert al., 2006). Several ERP studies have described more negative-oing ERPs for emotional words over occipital cortex between 200nd 300 ms (Herbert et al., 2008; Kissler et al., 2007; Kissler et al.,009; Scott et al., 2009) or between 300 and 400 ms (Palazovat al., 2011; Schacht and Sommer, 2009a, 2009b) after word pre-entation. Collectively, these effects are referred to as emotionriven early posterior negativities (EPN). Morphologically analo-ous effects have been reported in emotional face (Schupp et al.,004), scene (Junghofer et al., 2001), or gesture processing (Flaischt al., 2011), and in explicit object-based attention tasks (Hillyardnd Anllo-Vento, 1998; Schoenfeld et al., 2007), implying that early

motion effects in this time window reflect attentional highlightingf emotional stimuli in general (Schupp et al., 2006).

∗ Corresponding author at: Department of Psychology, University of Bielefeld,ostfach 10 01 31, 33501 Bielefeld, Germany.

E-mail address: johanna.kissler@uni-bielefeld.de (J. Kissler).

301-0511/$ – see front matter © 2012 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.biopsycho.2012.09.004

Larger parietal positivities arising around 500 ms after wordonset have also been reported in emotion word processing (Fischlerand Bradley, 2006; Herbert et al., 2006; Schacht and Sommer,2009b), as well as in the processing of emotional scenes, faces,or gestures. Again, parallel effects are found in explicit attentiontasks. Occasionally, effects of emotional content on the N400 com-ponent, a classic index of contextual semantic integration, havebeen found (Herbert et al., 2008; Kiehl et al., 1999), suggesting facil-itated semantic integration of emotional words after a first initialattentional processing stage. Also, emotion effects arising earlierthan 200 ms after word onset have been documented (Begleiter andPlatz, 1969; Hofmann et al., 2009; Ortigue et al., 2004; Skrandies,1998; Skrandies et al., 1998). These very early effects, in particu-lar, support the view that emotional processing can operate evenpre-attentively, outside the boundaries set by other information-processing mechanisms, as proposed by automatic vigilance (Prattoand John, 1991) or automatic evaluation models (Zajonc, 1980). Inthe context of language processing, such very early effects suggestthe possibility of pre-lexical responses to emotional content.

At least under conditions of low to moderate competing cog-nitive load, emotional stimuli, including words, are preferentiallyprocessed. Still, it is debated whether ERP emotion effects are spe-

cific to a particular category or dimension of emotion. Whereasmuch data suggest a major impact of emotional intensity, i.e. stim-ulus arousal, on emotion word processing (Fischler and Bradley,2006; Kissler et al., 2007; Schacht and Sommer, 2009b), some

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J. Kissler, C. Herbert / Biologi

esults indicate specific effects for negative (Bernat et al., 2001)r positive words (Kissler and Koessler, 2011). These discrepan-ies are reflected in different theoretical accounts. According to oneodel, rapid automatic allocation of attention specifically to nega-

ive stimuli is biologically adaptive in facilitating rapid withdrawalrom potentially dangerous environments. Therefore this mech-nism may by-pass other cognitive processes (Pratto and John,991). Alternatively, attentional orienting to emotionally arousingtimuli in general may be needed to mobilize appropriate approachr avoidance behavior (Lang et al., 1997). Finally, appraisal theoryroposes a cascade of processing steps where sequential checks

nfluenced by situational demands determine the patterning ofmotional responses, allowing for more flexibility and perhapseconciling some empirical discrepancies (Grandjean and Scherer,008; Scherer, 2009).

As outlined above, ERP effects of emotion in vision are oftenssumed to reflect spontaneous attentional highlighting of motiva-ionally relevant emotional stimuli. This assumption is supportedy analogous ERP effects in object-based selective attention tasksnd in line with the general concept of emotionally motivatedttention (Lang et al., 1997). Attention and emotion can affect therocessing of perceptual objects, including words, at various tem-oral stages (Luck and Hillyard, 1999; Ruz and Nobre, 2008; Schuppt al., 2007; Vogel et al., 2005; Ziegler et al., 1997). Still, it is contro-ersial, how much perceptual and cognitive processing has to bearried out, before a stimulus’ emotional significance is identifiednd how early in the processing stream emotion effects can occur.n other words, an important question still is: How much, if any,nference do preferences need?

In emotion word processing the question can be put as: Wheno emotion effects occur in relation to different processing stages

n the mental lexicon? To answer this question, emotion effectsan be pitched against a time-line of word recognition derivedrom models of visual word processing. According to classic serialord processing models (e.g. Coltheart et al., 2001; McClelland

nd Rumelhart, 1981), increasingly abstract information, includingrthographic word form and phonological and lexical propertiesf a word, is extracted from the visual percept as activation trav-ls from primary visual to higher order, multimodal, associationreas of the brain, where information is combined to achieve fullomprehension of a word’s meaning (for review see Dien, 2009).

ord-processing stages are assumed to partly overlap and to berganized in an interactive and cascaded fashion, but the extentf parallel processing is a matter of considerable debate (Barbernd Kutas, 2007; Grainger and Holcomb, 2009; Pulvermuller et al.,009). Traditional models agree that some perceptual invarianceas to be extracted from the physical signal, before a word’s mean-

ng can be accessed. It is traditionally assumed that orthographicrocesses take place within the first 250 ms, followed by lexical andemantic access from about 300 ms after stimulus onset, culminat-ng in full semantic contextual integration around 400 ms (Graingernd Holcomb, 2009). However, some models argue for a consider-bly higher speed of word recognition with parallel or near parallelrocessing of different attributes and present evidence for seman-ic processing even within the first 200 ms (e.g. Pulvermuller et al.,009).

Because models and data differ regarding the speed and stages oford processing itself, identification of the locus of emotion effects

long an empirically determined time-line of word processings needed to inform models of word recognition and emotionalrocessing. From a linguistic perspective, the extent to which emo-ional content can accelerate or by-pass other stages of word

rocessing has implications for models of lexical access. Acceler-tion of word processing by emotion is suggested by consistentvidence of faster lexical decisions to emotional than to neutralords (Kousta et al., 2009; Schacht and Sommer, 2009b), but in

chology 92 (2013) 464– 479 465

lexical-decision emotional response facilitation may also play arole (Kissler and Koessler, 2011). Moreover, models such as the‘automatic vigilance model’, developed from experiments withword stimuli, assume that emotion processing can operate pre-attentively (Pratto and John, 1991), suggesting the existence ofshort-cut routes, by-passing stages of perceptual analysis.

A linguistic challenge is to account for such effects within mod-els of word recognition and to determine whether they are uniqueto emotion words or also occur for other semantic classes, andwhether they could be mimicked by attention manipulations. Fromthe perspective of emotion theory, data will provide informationregarding the temporal evolution of emotion – cognition interac-tions and the direction of emotion effects at distinct processingstages. On-line measures such as ERPs can reveal such sequencesthat might be obscured in lexical-decision reaction times alone,which represent a compound measure, integrating the results ofmany different operations.

So far, two ERP studies investigated the pre-, peri-, or post-lexical status of emotion effects in word processing. Scott et al.(Scott et al., 2009) varied emotional content within high- and low-frequency words in a lexical-decision task. Since frequency effectsin visual word processing are considered indicative of lexical access,word frequency by emotion interactions was identified to deter-mine the functional status of emotion effects. Interactions occurredon the N1 around 150 ms and in the subsequent EPN window(200–300 ms). These N1 and EPN effects were assumed to indi-cate modulations of lexical access by emotional content. An earlierP1 amplitude reduction for negative words was interpreted as apre-lexical perceptual defense mechanism.

Palazova et al. (2011) examined ERP emotion effects inhigh- and low-frequency adjectives, verbs, and nouns, likewiseusing a lexical-decision task. Results confirmed an early fre-quency effect around 100–150 ms which interacted with emotion.Word–pseudoword differences were found between 250 and550 ms. Crucially, main effects of emotion were reflected by an EPNpotential and a centro-parietal positivity (LPP), whose temporalonset largely coincided (EPN) or followed (LPP) word–pseudoworddifferentiation, supporting a lexical or post-lexical status of emo-tion effects.

The present study further investigates the status of emotioneffects along the time-line of word processing using a silent read-ing paradigm: For adults, silent reading is a highly automatic andvery natural process (e.g. Kahneman and Chajczyk, 1983). Simul-taneously measuring on-going brain activity during reading canreveal emotional modulations irrespective of additional effects ofresponse preparation and execution, which may differ from word-processing-related activity itself. Lexical-decision reaction timesare consistently faster for emotion words, with some controversysurrounding the relative role of valence versus arousal (Estes andAdelman, 2008; Kousta et al., 2009). However, in lexical decisionmany different processes could be affected by emotion. Moreover,lexical decision, while highly successful in identifying word–non-word differences, draws explicit attention to a stimulus’ lexicalstatus, thereby potentially affecting lexicality or emotion effects. Infact, Ziegler et al. (1997) demonstrated that the time course of lex-ical and semantic activation in word processing is task-dependent,with faster ERP word–pseudoword differentiation in a semanticcategorization task than during letter search.

Here, emotion effects in reading are investigated in relation toeffects of orthography and lexicality to determine the temporal andfunctional stage(s) of effects. We present positive, negative, andneutral nouns intermixed with letter strings and pseudowords to

identify successively more refined processing stages. Under a serialmodel, differentiation of orthographically legal word forms (wordsor pseudowords) from illegal words forms (letter strings) shouldprecede differentiation of real words (with a corresponding lexical

466 J. Kissler, C. Herbert / Biological Psy

Table 1Means and standard deviations (in brackets) of different stimulus dimensions.

Word stimuli

Positive Neutral Negative

Valence 7.46 (.92) 5.20 (.36) 2.02 (.72)Arousal 5.84 (1.02) 2.18 (.77) 5.72 (.79)

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Concreteness 4.55 (1.16) 4.05 (2.04) 4.20 (1.42)Word Length 7.28 (2.70) 7.13 (1.97) 6.83 (1.95)Word Frequency 107.5 (144.01) 124.57 (20.91) 64.93 (173.05)

ntry) from pseudowords (without lexical entry). Emotion effectsill be assessed along the time-line of such effects. Our previous

tudies have used the rapid serial visual presentation (RSVP) tech-ique to study emotion effects in word processing. Although effectsave been largely replicated in lexical-decision tasks (Hinojosat al., 2010; Palazova et al., 2011; Schacht and Sommer, 2009a,009b; Scott et al., 2009), RSVP with its absence of baseline periodsnd inherent conceptual masking, may create a special experimen-al situation. Here, we examine emotion effects in single wordeading outside RSVP. In particular, we address the timing of emo-ion effects in relation to orthographic word-form analysis andexical access in positive, negative, and neutral words, investigat-ng the possibility that emotional content may accelerate or by-passome of these processes.

. Methods

.1. Participants

Twenty-four native German students (12 women) from the University of Kon-tanz, Germany, took part in the experiment. Mean age was 23.56 (SE = .62) years.ll were right-handed according to the Edinburgh Handedness Inventory (Oldfield,971). They reported no history of neurological or psychiatric disease and theirision was normal or corrected to normal. Subjects signed written informed con-ent forms and received either a financial bonus of 7.50 D (∼12.00 $) or course creditor their participation.

.2. Material

138 German nouns (46 high arousing positive, 46 high arousing negative, 46eutral) were used. From these nouns, for each of the three emotion categories, 46seudowords and 46 letter strings were created by within- and between-word per-utation, resulting in a total of 138 words, 138 pseudowords and 138 letter strings

s experimental stimuli. Positive and negative nouns differed in valence but not inrousal. They differed from neutral nouns in both valence and arousal. Words wereatched across emotion categories for concreteness, length and word frequency

nd did not differ in any of these. Arousal, valence, and concreteness values wereased on self-collected nine-point scale ratings given by 45 students who did notake part in this experiment. Frequency of written words was determined from thetandardized word-database CELEX (Baayen et al., 1995) (see Table 1 for a summaryf stimulus characteristics).

Pseudowords were based on the original words within each emotion categorynd were generated by letter permutations within and between words to precludeimple perceptual repair and at the same time maintain compliance to orthographicnd phonotactic rules of German. Original word length was never altered. Lettertrings were likewise generated by within- and between-word letter permutation,ut now violated German orthographic and phonotactic rules. The words, pseu-owords, and letter strings, used in the experiment are listed in Appendix A.

.3. Procedure

Participants were familiarized with the laboratory, handedness was assessedOldfield, 1971) and they were asked about their past and current health using a stan-ardized questionnaire. They were then seated in an electrically shielded room and aeodesic net containing 256 EEG electrodes was positioned on their head (GSN 2002.0; EGI: Electrical Geodesics, Inc., Eugene, Oregon). Participants were informedhat they were taking part in a word-processing study and that their task was toead a sequence of words and word-like stimuli while their EEG was being recorded.hey were instructed to refrain from head and eye movements during stimulations much as possible and attend to each stimulus for its entire presentation time.

Stimuli were presented for 600 ms, separated by a pseudo-randomly varyingnter-stimulus interval of 900–1200 ms during which a fixation cross was shown.timulus sequence was constrained such that overall transition probability wasqual across stimuli and that no more than three exemplars of the same Stimulusype (word, pseudoword, letter string) appeared in sequence.

chology 92 (2013) 464– 479

2.4. EEG recording and analysis

EEG was recorded from 256 channels using EGI amplifiers and Netstation® soft-ware (GSN 200 v2.0; EGI: Electrical Geodesics, Inc., Eugene, Oregon). Recordingbandwidth was 0.01–100 Hz; sampling rate was 250 Hz. To reduce mains inter-ference, a 50 Hz notch filter was used. Impedance was held beneath 50 k� andCz was used as recording reference. Off-line, data were re-referenced to an aver-age reference and band-pass filtered between 0.1 and 35 Hz. Eye movement andblink artifacts were corrected using the correction algorithm implemented in BESA(Brain Electrical Source Analysis, MEGIS Software GmbH). Remaining artifacts werereduced by individual channel-interpolation or the epochs were rejected (max. 10%).Data were segmented from −100 to 700 ms, baseline corrected using the first 100 ms,and averaged according to condition.

2.5. EEG analysis

The Matlab-based EMEGs v2.2 package (Peyk et al., 2011) was used for ERP visu-alization and analysis. To specify time windows and regions of interest, point-wiseANOVAs were conducted across all time-points and sensors. In a first step, differ-ences between positive, negative, and neutral words were determined to replicateprevious effects. Then, effects of Stimulus Type (word, pseudoword, letter string)were examined within each individual valence to assess orthographic and lexicalprocessing stages for each valence, fully controlling for basic perceptual character-istics (note that pseudowords and letter strings were created by permutation withinindividual valence). Separate analyses were conducted to account for the possibilitythat the temporal dynamics of lexical processes differ between neutral, negative,and positive words.

Results were considered meaningful, if effects remained significant at a sig-nificance level of p < .01 for at least 8 sample points (32 ms) and could be seen,without additional spatial or temporal smoothing, in a cluster of at least 10 elec-trodes (Kissler and Koessler, 2011). Main effects were decomposed using linearcontrasts or quadratic trends, depending on the hypothesis to be tested. Statisticalmaps for contrasts were interpreted only in time windows that first revealed sig-nificant topographically overlapping effects in the ANOVA. Such effects are markedwith black boxes in the figures, although the statistical maps for the contrasts areshown across the entire time window to provide full information.

Additionally, based on regions and time windows of interest typically reportedin the literature and identified in the point-wise ANOVAs, effects were confirmedusing ANOVAs assessing the effect of Valence (positive, negative, neutral) in wordsand the effect of Stimulus Type (Words, Pseudowords, Letter strings) within valence.ANOVAs compared mean activity in clusters of sensors covering regions and timewindows of interests and were decomposed using t-test. The same clusters wereused across valences, and sensor clusters were kept constant across effects as muchas possible. Where appropriate according to previous reports, Hemisphere wasincluded as a factor, comparing ERPs at two symmetrical left and right hemisphericelectrode clusters. Sensor clusters are listed in Appendix B.

3. Results

3.1. Emotion in words

3.1.1. Point-wise ANOVAFig. 1 displays p-maps of the time course and topography for the

main effect of Emotion in nouns (Fig. 1a), for the quadratic trendcomparing emotional (positive and negative) with neutral nouns,testing the hypothesis that arousal accounts for emotional – neu-tral differences in reading (Fig. 1b), and the linear contrast testingfor valence-specific differences by comparing positive and nega-tive nouns (Fig. 1c). ERP difference topographies for these effectsare shown in Fig. 2 for negative minus neutral (a) and positiveminus neutral (b) and positive minus negative nouns (c). ANOVArevealed a first significant effect between 108 and 140 ms over leftcentro-occipital scalp. This effect is apparent both in the ANOVA(Fig. 1a) and in the quadratic trend comparing emotional with neu-tral words (Fig. 1 b), but not in the linear contrast between positiveand negative stimuli (Fig. 1c), indicating mainly an arousal effect.Still, the difference topographies show it to be driven mainly bynegative nouns eliciting more negative-going ERPs than neutralnouns between 108 and 140 ms (Fig. 2a).

Further emotion effects evolve from 216 ms after word onset,

extending throughout the entire analysis window (Fig. 1a and b).They start over left lateral scalp for both negative and positivenouns compared to neutral ones and are due to a more pro-nounced posterior negativity and concomitant frontal positivity for

J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479 467

Fig. 1. Probability maps from 0 to 680 ms in steps of 32 ms (on average p < .01 for at least 32 ms) depicting the effects of emotional content on ERPs during reading. (a)P trendc ere sc

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oint-wise ANOVA comparing positive, negative, and neutral words. (b) Quadraticontrasting positive and negative words. Black frames mark time windows that womparison.

motional than for neutral words (Fig. 2a and b). This processirrors the previously described EPN effect for emotional words.irectly comparing ERPs to positive and to negative words (Figs. 1cnd 2c) reveals that from about 400 ms positive words elicit moreight occipito-parietal positivity than negative or neutral words.his replicates the previously documented LPP effect, presentlyestricted to positive content.

.2. Spatio-temporal cluster ANOVA: emotion effect in words

.2.1. 108–140 msEmotion was significant at two bilateral occipito-parietal elec-

rode groups (F(2, 46) = 4.15, p < .05) due to more negative-goingrain potentials for negative than for neutral words (p < .05). Thether categories did not differ and although the effect appearedomewhat left lateralized, the interaction was far from significantF < 1).

.2.2. 216–320 msFurther Emotion effects (F(2, 46) = 4.84, p < .05) arose at two

roups of occipito-parietal electrodes between 216 and 320 ms

ith both positive and negative words differing from neutral ones

ps < .05), but not from each other (F < 1). ERPs were generally moreegative over the left hemisphere (F(1, 23) = 6.53, p < .05), but thisid not interact with valence (F(2, 46) = 1.28, p < .19).

s comparing ERPs elicited by positive and negative with neutral words. (c) t-testsignificant already in the ANOVA and can therefore be interpreted in the post hoc

3.2.3. 324–392 msEmotion further impacted on visual processing between 324 and

392 ms (F(2, 46) = 3.12, p = .05) due to both negative (p < .05) andpositive (p < .05) words differing from neutral words. There wasno effect of Hemisphere or an interaction between Emotion andHemisphere (both p > .2).

3.2.4. 468–608 msA centro-parietal effect of emotion (F(2, 46) = 4.72, p < .05)

emerged between 468 and 608 ms. This was due to more positive-going ERPs for positive than for negative words (p < .05). The effectdiffered between the hemispheres (F(2, 46) = 4.64, p < .05). Overthe left hemisphere, both positive and neutral words had morepositive-going ERPs than negative words (ps < .05), whereas overthe right hemisphere positive words had more positive going ERPsthan both positive and neutral words (ps < .01), the latter also elic-iting more positivity than negative words (p < .05).

3.3. Effects of Stimulus Type: neutral valence

3.3.1. Point-wise ANOVA

To determine the functional stage(s) at which emotion effects

occur in neutral, negative, or positive words, the effect of Stimu-lus Type (Word, Pseudoword, Letter string) was analyzed withineach valence. Fig. 3a displays the result of a point-wise ANOVA

468 J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479

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omparing ERPs elicited by neutral words with pseudowords andetter strings Fig. 3b and c display the p-maps for the linear con-rasts. First effects of Stimulus Type are seen over inferior occipitalcalp between 180 and 248 ms. Further effects arise over rightccipital scalp from 288 ms, extending bilaterally and more supe-ior from 324 ms. Centro-parietal effects of Stimulus Type are seenrom around 432 ms. The underlying difference topographies arehown in Figs. 6a and 7a.

.3.1.1. Pseudowords versus letter strings. Differentiation betweenseudowords and letter strings, reflecting a formal analysis stage,

s first seen between 180 and 249 ms after stimulus onset (Fig. 3c).seudowords elicit more positive-going ERPs over bilateral inferiorccipital scalp (Fig. 7a). A second significant difference betweenseudowords and letter strings arises from 288 ms as a prolongedight occipital negativity for pseudowords compared to lettertrings successively extending over the entire back of the brainFig. 7a). Finally, from 540 ms a left frontal positivity accompanieshe retreating right occipital negativity (Fig. 7a).

.3.1.2. Words versus pseudowords. Linear contrasts reveal a dif-erence between neutral words and pseudowords starting from24 ms (Fig. 3b) as a left occipital negativity and right frontal

ositivity (Fig. 6a). This difference extends until 500 ms (Fig. 3b),volving from a left occipito-temporal negativity into a centralositivity for neutral words, resembling the N400 effect. This pro-ess extends for several hundred milliseconds, retreating over

ntent from 0 to 680 ms in steps of 32 ms. (a) Negative words minus neutral words.frames mark time windows where significant effects were found in the respective

occipital cortex, where it reaches significance again, between 576and 608 ms. Finally, a slightly left frontal negativity develops forwords compared to pseudowords, significant between 648 and680 ms after stimulus onset.

3.4. Spatio-temporal cluster ANOVA: effect of Stimulus Type forneutral valence

To further validate the above effects, a region of interest analy-sis was conducted for individual time windows for the first 500 ms.Figs. 6a and 7a depict the underlying topographical differences.For consistency and because of considerable spatial overlap in theeffects, all posterior effects were analyzed at the same channelgroups as the above emotion effects.

3.4.1. 180–212 msAn effect of Stimulus Type (F(2, 46) = 9.68, p < .01) was identified

at two bilateral inferior-occipital electrode groups. It was due tomore positive-going brain potentials for neutral words and pseu-dowords than for letter strings (p < .01 and p = .01, respectively).Words and pseudowords did not differ (p > .5).

3.4.2. 216–248 msStimulus Type (F(2, 46) = 5.25, p < .01) was significant: Pseu-

dowords, and in tendency also words, were more positive thanletter strings (p < .05 and p = .07, respectively, Fig. 7a).

J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479 469

Fig. 3. Probability maps from 0 to 680 ms in steps of 32 ms (on average p < .01 for at least 32 ms) depicting the effects of Stimulus Type on ERPs during reading of neutralwords, pseudoword, or letter strings derived from neutral words. (a) Point-wise ANOVA comparing words, pseudowords, and letter strings. (b) t-tests comparing wordsa es mai

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.4.3. 252–284 msA significant effect of Hemisphere was due to more negative-

oing potentials over the left hemisphere (F(1, 23) = 5.99, p < .05),ut no effects of Stimulus Type (F < 1) or interactions were foundF < 1).

.4.4. 288–320 msA main effect of Stimulus Type (F(2, 46) = 8.86, p < .01) occurred

ith more negative-going potentials for words than for lettertrings (p < .01). Pseudowords were likewise somewhat more nega-ive than letter strings (p = .08) and did not differ from words (p > .2).RPs were somewhat more negative over the left hemisphere (F(1,3) = 2.82, p = .1), but the interaction was far from significant (F < .1).

.4.5. 324–392 msBetween 324 and 392 ms a further effect of Stimulus Type

merged (F(2,46) = 13.43; p < .01), now differentiating words fromseudowords (Fig. 6a). Words were more negative than both pseu-owords (p < .05) and letter strings (p < .01). The latter did not differ.ffects were somewhat larger over left than over right occipitalreas (F(2, 46) = 2.64, p = .08).

.4.6. 432–500 msFinally, a centro-parietal effect was tested in the typical

400 time range. This yielded a main effect of Stimulus Type

rk time windows that were significant already in the ANOVA and can therefore be

(F(2,46) = 10.12; p < 0.01). Figs. 6a and 7a) reveal that pseudowordswere associated with more negative-going ERPs than both words(p < .01) and letter strings (p < .05). In tendency, letter strings werealso more negative than words (p = .06).

3.5. Effects of Stimulus Type: negative valence

3.5.1. Point-wise ANOVAFig. 4a displays the results of a point-wise ANOVA compar-

ing ERPs for negative words and pseudowords and letter strings.First effects of Stimulus Type are seen over right inferior occipitalscalp from 180 ms. From 216 ms these effect extend over the lefthemisphere, spreading over bilateral occipital and frontal scalp by392 ms. From 396 ms effects are seen fronto-centrally, lasting untilabout 540 ms. Underlying topographical differences are shown inFigs. 6b and 7b.

3.5.1.1. Pseudowords versus letter strings. Pseudowords and letterstrings first differ right-occipitally from 180 after stimulus onset(Fig. 4 c). By 284 ms, more positive going ERPs are elicited by pseu-dowords, primarily over right inferior occipital scalp (Fig. 7 b). From

288 ms a prolonged bilateral occipital negativity for pseudowordscompared to letter strings successively extends over the entire backof the brain (Fig. 7b). Finally, from 540 ms a left frontal positivityaccompanies the retreating right occipital negativity (Fig. 7a).

470 J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479

Fig. 4. Probability maps from 0 to 680 ms in steps of 32 ms (on average p < .01 for at least 32 ms) depicting the effects of Stimulus Type on ERPs during reading of negativew ANOVa es mai

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.5.1.2. Words versus pseudowords. Differentiation between nega-ive words and pseudowords starts from 252 ms (Fig. 4 b) as a leftccipital negativity and left frontal positivity (Fig. 6b) lasting until56 ms. From 360 ms a left frontal positivity develops that gradu-lly extends posterior, spreading over much of the central scalp by32 ms and by 536 ms retreating to left frontal regions. This processesembles the N400 effect.

.6. Spatio-temporal cluster ANOVAs: effect of Stimulus Type foregative valence

To further validate the above effects, a regions of interest analy-is was conducted for the same sensor clusters and time windowss above. Topographical differences underlying these effects arehown in Figs. 6b and 7b.

.6.1. 180–212 msA first effect of Stimulus Type (F(2, 46) = 3.79, p < .05) was due to

omewhat more negative-going brain potentials for letter stringshan for negative words and pseudowords (p < .1 and p < .2, respec-ively). Words and pseudowords did not differ (F < 1).

.6.2. 216–248 msNo clear effects of Stimulus Type (F(2, 46) = 2.18, p = .12) or

emisphere (F(2, 23) = 2.82, p = .11) and no interaction between thewo (F(2, 46) = 1.4, p = .26) were observed.

A comparing words, pseudowords, and letter strings. (b) t-tests comparing wordsrk time windows that were significant already in the ANOVA and can therefore be

3.6.3. 252–284 msA main effect of Stimulus Type (F(2, 46) = 3.93, p < .05) was found,

with more negative-going potentials for words than for pseu-dowords (p < .05). The effect of Hemisphere (F(2, 23) = 2.49, p = .13)or the interaction between Stimulus Type and Hemisphere (F(2,46) = 1.49, p = .23) were not significant.

3.6.4. 288–320 msERPs differed according to Stimulus Type (F(2, 46) = 14.26,

p < .01) with more negative-going potentials for words than forpseudowords (p < .05) and letter strings (p < .01). The effect of Hemi-sphere (F(2, 23) = 2.50, p = .13) or the interaction between StimulusType and Hemisphere (F < 1) were not significant.

3.6.5. 324–392 msStimulus Type was significant (F(2,46) = 18.38; p < .01) due to

words being more negative than both pseudowords (p < .05) andletter strings (p < .01). Pseudowords were also more negative thanletter strings (p < .05). The hemispheres did not differ significantly(F(1, 23) = 2.64, p = .08) and the interaction was far from significant(F < 1).

3.6.6. 432–500 msFinally, a centro-parietal, N400-like effect, was tested. This

yielded a main effect of Stimulus Type (F(2,46) = 5.65; p < 0.01).Pseudowords were associated with more negative-going ERPs than

J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479 471

Fig. 5. Probability maps from 0 to 680 ms in steps of 32 ms (on average p < .01 for at least 32 ms) depicting the effects of Stimulus Type on ERPs during reading of positivew ANOVa es mai

w(

3

3

iadffit6

3pfiono2tl7

ords, pseudoword, or letter strings derived from negative words. (a) Point-wise

nd pseudowords. (c) t-tests contrasting pseudowords and letter strings. Black framnterpreted in the post hoc comparison.

ords (p < .01) and letter strings (p = .01). The latter did not differp > .2).

.7. Effects of Stimulus Type: positive valence

.7.1. Point-wise ANOVAFig. 5a displays the result of a point-wise ANOVA compar-

ng the cortical processing of positive words and pseudowordsnd letter strings. Fig. 6b illustrates the underlying topographicifferences. Initial effects of Stimulus Type are seen over rightrontal scalp from 216 ms. From 252 ms additional effects areound over left occipital and right parietal scalp, gradually extend-ng in frontal and parietal regions until 356 ms. In the followingime windows, effects gradually diminish and finally disappear by12 ms.

.7.1.1. Pseudowords versus Letter strings. Differentiation betweenseudowords and letter strings, reflecting a formal analysis stage,rst starts right-frontally from 216 ms (Fig. 5c). Although theccipital negativity for letter strings observed for the neutral andegative valences is likewise visible (Fig. 7c), here it falls shortf significance. Instead, a left frontal negativity is significant until

84 ms. Subsequently, an initially right dominant posterior nega-ivity for pseudowords appears (288–320 ms) gradually becomingeft-dominant, and moving more anterior by 500 ms (Figs. 5c andc).

A comparing words, pseudowords, and letter strings. (b) t-tests comparing wordsrk time windows that were significant already in the ANOVA and can therefore be

3.7.1.2. Words versus pseudowords. Linear contrasts reveal that thedifferentiation between positive words and pseudowords startsfrom 216 ms (Fig. 5 b). It is first significant as a frontal positivity(Fig. 6 b). The concomitant left occipital negativity is visible in thistime window, but only reaches significance from 252 ms, lastinguntil 392 ms (Fig. 6b). From 432 ms the frontal positivity starts toextend centrally, reverting to frontal regions by 572 ms, this processreflecting the N400 effect. An additional brief occipital positivity isseen between 576 and 608 ms.

3.8. Spatio-temporal cluster ANOVA: effect of Stimulus Type forpositive valence

To further validate the above effects, the same regions-of-interest analysis as above was conducted. Topographicaldifferences underlying the reported effects are shown in Figs. 6cand 7c.

3.8.1. 180−248 msAlthough over the right hemisphere words and pseudowords

were somewhat more positive-going than letter strings, neithera clear effect of Stimulus Type (F(2, 46) = 1.7, p < .2), nor of Hemi-sphere (p > .4) or an interaction (F(2, 46) = 2.13, p < .2) were found.

3.8.2. 216–248 msNo effects of Stimulus Type (F(2, 46) = 1.42, p < .2) or Hemisphere

(F(2, 23) = 1.81, p = .19) were found, but an interaction between

472 J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479

F s in dm nus psi

Scpwpos

3

m(pfi4tth

3

m(peH

ig. 6. Topographic difference maps of ERPs elicited by words versus pseudowordinus pseudowords. (b) Negative words minus pseudowords. (c) Positive words mi

n the respective statistical comparisons.

timulus Type X Hemisphere (F(2, 46) = 5.1, p = .01 emerged. It indi-ated that over the left hemisphere words were more negative thanseudowords (p < .01), whereas over the right hemisphere wordsere more positive than letter strings (p < .05), not differing fromseudowords. Words were also more negative over the left thanver the right hemisphere (p < .01), whereas pseudowords or lettertrings showed no asymmetry.

.8.3. 252–284 msA main effect of Stimulus Type (F(2, 46) = 4.86, p = .01), with

ore negative-going potentials for words than for pseudowordsp < .05), as well as a significant effect of Hemisphere (F(1, 23) = 6.93,

< .05), with more negativity over the left hemisphere, were identi-ed. The interaction between Stimulus Type and Hemisphere (F(2,6) = 6.07, p < .01) indicated more negative-going potentials overhe left hemisphere elicited by words than by pseudowords or let-er strings (p < .01). No such difference was observed over the rightemisphere (p > .2).

.8.4. 288–320 msA main effect of Stimulus Type (F(2, 46) = 16.93, p < .01) with

ore negative-going potentials for words than for pseudowords

p = .05) and letter strings (p < .01) as well as more negative-goingotentials for pseudowords than for words (p < .05) were found. Theffect of Hemisphere or the interaction between Stimulus Type andemisphere were not significant (F < 1).

ifferent emotion categories from 0 to 680 ms in steps of 32 ms. (a) Neutral wordseudowords. Black frames mark time windows where significant effects were found

3.8.5. 324–392 msERPs differed depending on Stimulus Types (F(2,46) = 16.48;

p < .01), words being more negative than both pseudowords(p < .01) and letter strings (p < .01). The latter were not significantlydifferent. The hemispheres did not differ (F(1, 23) = 1.60, p > .2) andthe interaction was far from significant (F < 1).

3.8.6. 432–500 msFinally, a centro-parietal N400-like effect yielded a main effect

of Stimulus Type (F(2,46) = 4.52; p < 0.05). Pseudowords were asso-ciated with more negative-going ERPs than words (p < .05). Letterstrings fell between words and pseudowords but did not differsignificantly from either (both p > .1).

4. Discussion

The present study investigated the time course and topogra-phy of emotion and lexicality effects in silent reading. It replicatesand extends several findings about neural mechanisms of wordprocessing, in general, and emotion word processing in particular.But in combination of the two, the study yields a remarkable newfinding: Word–pseudoword differentiation is faster for emotionalthan for neutral words, indicating faster lexical access to emotional

than to neutral words.

Replicating previous research, an EPN to emotional comparedto neutral words was found between 200 and 300 ms after stimu-lus onset (Herbert et al., 2008; Hinojosa et al., 2010; Kissler et al.,

J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479 473

F stringP tter stp nd in

2wo2o

cfcwtPpag(nrp(

plfwnf

ig. 7. Topographic difference maps of ERPs elicited by pseudowords versus letter

seudowords and letter strings derived from neutral words. (b) Pseudowords and leositive words. Black frames mark time windows where significant effects were fou

007; Scott et al., 2009). Also, a second posterior emotion effectas identified between 300 and 400 ms, similar to the effects previ-

usly reported by Schacht and her colleagues (Schacht and Sommer,009a, 2009b). Perhaps, this later part of the effect is attenuated andbscured in RSVP designs.

Regarding the time-line of reading, an occipital positivity and aoncomitant left frontal negativity were found for pseudowordsrom about 180 ms after stimulus onset, reflecting orthographi-al word-form processing. Orthographical word-form processingas assessed comparing pseudowords with letter strings so as not

o confound it further with emotion effects carried by the words.seudoword–letter string differentiation occurred as a bilateralosterior negativity for pseudowords by about 200 ms lasting untilbout 500 ms. There was some variation in the onset of the ortho-raphical differentiation in that the effect became significant laterfrom 216 ms) for stimuli derived from positive words than fromegative or neutral words (from 180 ms). The reason for this is cur-ently unclear, but because the topographic differences betweenseudowords and letter strings were similar for all three valencesFig. 7), it could be due to random noise effects.

Crucially, however, the differentiation between words andseudowords, that is, between word forms that possess an actual

exical entry, and word forms that do not, was found to dif-

er according to emotional content, occurring in the early EPNindow (216–300 ms) for emotional words, but only later foreutral words. In detail, in neutral words, word–pseudoword dif-

erentiation occurred as a left occipito-temporal negativity from

s derived from different emotion categories from 0 to 680 ms in steps of 32 ms. (a)rings derived from negative words. (c) Pseudowords and letter strings derived from

the respective statistical comparisons.

324 ms after stimulus onset. By contrast, in negative words a leftoccipito-temporal negativity significantly differentiated word frompseudowords from 252 ms. In positive words the effect was signif-icant already from 216 ms. Since pseudowords and letter stringswere derived from the words within one valence, an influenceof simple perceptual features is unlikely, since physical contentdid not vary between stimulus types (words, pseudowords, let-ter strings) within one valence. Thus, lexical access in reading wasfound to be faster in emotional than in neutral words. The timingand topography of this effect suggests that, at least in silent reading,a timing-difference in lexical access between emotional and neu-tral stimuli drives at least the early (200–300 ms) emotion-wordEPN effect. In other words, emotional content accelerates lexicalaccess. This acceleration may contribute to the faster lexical deci-sions for emotional words seen in lexical-decision tasks (Koustaet al., 2009; Schacht and Sommer, 2009b). Whether the difference inonset between positive and negative words is meaningful and repli-cable is open to future research. While valence-dependent effectsare sometimes found in lexical decisions, occasionally also withfaster reaction times for positive words (e.g. Kissler and Koessler,2011), arousal-dependent effects with acceleration for both pos-itive and negative valence are more typical (Kousta et al., 2009).In any case, comparing the topographies of the effects, the dif-

ferences between positive and negative words and pseudowordsare clearly more similar regarding timing and topography than thedifference between neutral words and pseudowords. Fig. 8 illus-trates this major result of this experiment as ERP time course at

474 J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479

F blue)o ional ww

sw

owTfelramlitaaewi(

nwtf

ig. 8. ERP time course at selected sensors for emotional words (red), neutral words (f major effects, ERPs are collapsed across valence (positive and negative) for emotords.

ix representative sensors, collapsing across negative and positiveords.

Pre- and post-lexical effects of emotional content were alsobserved: A posterior negativity driven primarily by negativeords was observed already from about 110 ms after word onset.

his early emotion effect may replicate the posterior N1 effector negative words reported by Scott et al. (2009). N1 emotionffects are reported less consistently than later effects but are inine with findings of a negativity bias towards high arousing mate-ial (Cacioppo, 2004; Ito and Cacioppo, 2000). This negativity bias islso compatible with Pratto and John’s (1991) automatic vigilanceodel. From an emotion-theory perspective, it would support the

ong-held view that emotional responses or ‘preferences’, need nonferences (Zajonc, 1980), or at least fewer inferences than otherypes of processing, suggesting that emotional processing can oper-te outside the boundaries of cognitive information-processing. Atny rate, recent work by Schacht and her group actually providevidence that very early, presumably pre-lexical, emotion effects inord processing can be induced by associating a previously mean-

ngless symbol with reward value in an operant learning procedureSchacht et al., 2012).

However, since the negative words have somewhat, although

ot significantly, lower frequencies than positive and neutralords, a covert frequency effect also needs to be considered. In

his regard, Scott et al. (2009) report stronger P1 and N1 effectsor high frequency than for low frequency words, suggesting that

, pseudowords (black solid), and letter strings (black dashed). To facilitate inspectionords. Pseudowords and letter strings are collapsed across valences of the original

subtle differences in word frequency, with somewhat less frequentnegative words should have attenuated, rather than accentuatedthese effects.

Consistent with previous literature, emotion effects were alsofound in a later time window, the LPP window, and in the present,as well as in some previous studies (Herbert et al., 2008; Kissleret al., 2009), the more pronounced posterior-parietal positivitywas restricted to positive contents. Again, the possibility of sub-tle imbalances in non-emotional stimulus properties needs to beconsidered, precluding firm conclusions. However the entire tim-ing pattern of effects lends itself to an interpretation in terms ofa plausible adaptive processing sequence, perhaps most consis-tent with appraisal theory (Grandjean and Scherer, 2008): It maybe advantageous to initially (even pre-lexically) rapidly and selec-tively process negative stimuli. At a mid-latency stage, which herehas been shown to coincide with lexical access to emotional words(EPN), the organism may process arousing stimuli regardless ofvalence. Finally, at a post-lexical stage, pleasant stimuli may enjoyan advantage. Whereas rapid processing of negative contents maybe survival critical, later extended evaluation of pleasurable mate-rial may be important for subjective well being.

The most important finding of the present study is that lex-

ical access for emotional words is faster than lexical access forneutral words. This merits further discussion in the context ofthe word-processing literature in general. There is wide agree-ment about the existence of distinct orthographic, lexical, and

cal Psy

svtcpiasavpWfieaSvqaiaecl2ewdarawssisasiwibicf1bf

pwpseelfis

trorpao

J. Kissler, C. Herbert / Biologi

emantic processing levels, presently modeled by pseudowordersus letter string, word versus pseudoword, and emotional con-ent manipulations, respectively. Considerable debate, however,oncerns the timing of different processing steps in visual wordrocessing and the degree to which these steps occur in sequence,

n parallel, or in interaction. Perhaps the most influential viewssumes interactive and cascaded processing, allowing for botherial processing steps and their interaction via feedback mech-nisms (Coltheart et al., 2001). Empirically, some data supportery rapid initial activation of the mental lexicon, chiefly sup-orted by eye-movement and ERP evidence from lexical decision.ord frequency effects around 150 ms are taken as perhaps the

rst indicators of lexical access (Sereno and Rayner, 2003; Serenot al., 1998). Early word frequency by emotion interactions havelso been reported in two previous studies (Palazova et al., 2011;cott et al., 2009), but the present study did not manipulate thisariable. Although the mental lexicon clearly uses perceptual fre-uency as an organizational principle to access its content, this is

rather low-level principle that may not be specific to words. Fornstance, orthographic typicality effects are highly similar for wordsnd pseudowords and can also been found around 100 ms (Haukt al., 2006). Using other experimental manipulations, magnetoen-ephalography (MEG) data indicate lexical processing considerablyater, only around 350 ms after word onset (Pylkkanen and Marantz,003; Pylkkanen et al., 2002). The present results found lexicalityffects as reflected by word–pseudoword differentiation for neutralords from about 324 ms onwards, similar to the above MEG evi-ence. However, effects occurred for negative words from 252 msnd for positive words already from 216 ms. Palazova et al. (2011)eport word–pseudoword differentiation for nouns from 270 ms in

lexical-decision task, but included the emotional words in theirord–pseudoword comparison. If averaged across valence, both

tudies would yield a similar timing of lexical access. Present resultsuggest that part of the variability of reports on the timing of lex-cal access may be due to differential lexical access for differentemantic classes. It is open to future research, whether such effectsre restricted to emotional content or might also occur for otheremantic classes, if these are explicitly attended to. Future stud-es will also elucidate, whether faster lexical access for emotional

ords is specific to reading designs. There is the possibility thatntrinsically motivated attention to emotion speeds up processing,ut that this acceleration disappears when attention is explic-

tly drawn to the lexicality dimension, as in lexical-decision tasks,onsistent with evidence that the timing of word–pseudoword dif-erentiation in the ERP can vary with the task at hand (Ziegler et al.,997). Alternatively, faster lexical access to emotional words maye a fairly general phenomenon that at least partly accounts foraster lexical-decision times for emotional words.

The present results support, at least during initial processinghases, sequentially initiated, partly overlapping processing stagesith an initial orthographic (from 180 ms) and a later lexicalhase (from about 220 ms, depending on valence). A similarequence was described across various tasks by Bentin et al. (Bentint al., 1999). They found in early time windows major differ-nces between words and pseudowords on the one hand andetter strings on the other hand and only comparatively late identi-ed word–pseudoword differences, peaking around 400 ms, whenemantic integration is also assumed to occur.

Previous reports have linked the emotion-word EPN effecto semantic processing and indeed, the time window that car-ies the lexicality effect in emotional words also, and by virtuef this, comprises an emotion-neutral differentiation. Indeed,

esponses to stimulus semantics could in general coincide with orrecede other forms of lexical analysis or task requirements mightlter the time course and perhaps also the general occurrencef attribute-specific activations in word processing. On the one

chology 92 (2013) 464– 479 475

hand, distinct responses to words of different semantic cate-gories have been reported between 200 and 300 ms after wordonset (Dehaene, 1995; Hauk et al., 2008; Hinojosa et al., 2004).On the other hand, under certain experimental manipulationsthat limit attentional resources even a total absence of semanticprocessing, which is otherwise assumed to be automatic duringreading, has been observed (Smith et al., 2001). Because at leastin non-competitive situations all kinds of emotional stimuli attractattention, and because emotional stimuli often signal the need forrapid action, they may result in differential brain responses evenin situations where otherwise apparently very little higher levelanalysis occurs early on. Experimental test should demonstratewhether the EPN effect represents early semantic analysis anddetermine the degree to which it depends on attentional engage-ment and current motivational demands. Demands imposed bythe experimenter, for instance in the form of attention to a spe-cific semantic category, might be able to mimic effects currentlyfound for emotional words that possess an intrinsic attentionaland motivational relevance. Still, present results demonstratethat emotional content accelerates lexical access in silent readingtasks.

Several later effects of both stimulus type and emotional contentalso appeared, again replicating and extending previous findings.Regarding stimulus type, from about 360 to 500 ms after stimu-lus presentation, more negative-going centro-parietal ERPs wereobserved for pseudowords, essentially replicating the well-knownN400 effect, presumably indicating extended lexical search pro-cesses for word-like stimuli for which no lexical entry has yetbeen found. Finally, although not the focus of the present analy-ses, around 600 ms post stimulus, words elicited relatively morepositivity over the left hemisphere than letter strings and pseu-dowords which appears consistent with a P600 effect in wordreading. Although the P600 is mostly seen in syntactic tasks, ageneral attentional interpretation of late positive potentials wouldsuggest that words, because they contain more information thanpseudowords and letter strings attract more attentional resources,resulting in a larger P600. Also, effects of semantics on the P600have been observed (van Herten et al., 2005).

In parallel with the later effects of stimulus type, further effectsof emotional content were also observed. A second posterior neg-ativity for emotional words appeared between 320 and 420 ms. Itshowed a similar topography as the previous EPN and was likewisedriven by arousal, differentiating between positive and negativewords on the one hand and neutral words on the other hand.Regarding its timing and topography, this effect may resemblethe EPN effect described by Schacht and colleagues who describeda posterior negativity for emotional words emerging in lexical-decision or evaluation tasks, similar to the EPN (Palazova et al.,2011; Schacht and Sommer, 2009a, 2009b). Perhaps this effect isobscured in the RSVP designs that we have previously used. At anyrate, this second EPN effect parallels word–pseudoword differen-tiation. Finally, a right-lateralized late positive potential revealedan emotion effect around 500 ms. Replicating previous research(Herbert et al., 2008; Herbert et al., 2006; Kissler et al., 2009;Schapkin et al., 2000), this positivity was more pronounced for pos-itive words and differentiated them from both neutral and negativeones. In this time window a frontal positivity was also identified,being larger for emotionally arousing than for neutral words. Theeffect, which to our knowledge has not been described before, mayreflect the frontal cortex’s well-documented role in the evaluationof emotional stimuli (for review, see Etkin et al., 2011). Its identi-fication may be due to the higher spatial sampling of the present

compared to previous studies.

In sum, the present emotion effects replicate previous reportsof N1, EPN and LPP modulations in single word reading outsidethe RSVP design. Remarkably, against a time-line of structural and

4 cal Psy

lpe

gFacnmtiststansvgaamitpwnpeoaphs1khcpmbbedic

76 J. Kissler, C. Herbert / Biologi

exical differentiation, the present data show faster word–seudoword differentiation, indicating faster lexical access, tomotional than to neutral words.

The present findings also fit into a larger context of threeeneral questions about the mechanisms of emotional attention.irstly, a pertinent question in the entire emotional attention liter-ture is whether or how brain mechanisms of emotional attentionan be dissociated from brain systems involved in the control ofon-emotional attention. Regarding the present results, experi-ental manipulations that would test ‘how special’ emotion in

he present context really is have been indicated above. If exper-mental situations can be created, where explicit attention can behown to have, say ERP effects, different from the effects of emo-ional attention, or more precisely from the effects of emotionaltimuli, this would be grounds to argue for separate neural sys-ems. However, even if in ERP scalp potentials effects of explicitttention and implicit or stimulus-driven emotional attention can-ot be dissociated, there may still be differences in the drivingtructures that may be invisible to EEG. Here, a combination ofery high spatial sampling from the scalp to distinguish topo-raphical differences, use of advanced source analysis methods, andnalyses that allow examine directionality in inter-regional inter-ctions may help. Finally, the complimentary use of methods thateasure and visualize sub-cortical structures provides valuable

nformation. With regard to emotional attention these often regardhe relative effects of the amygdala and the striatum versus thearietal and prefrontal cortices. Specifically, regarding emotionalord processing an important issue is whether the emotional sig-ificance is computed on-line, potentially involving amplificationrocesses from other structures, perhaps the amygdala or whethermotional significance is somehow pre-stored in the lexicon. A sec-nd cluster of issues in emotional attention research regards clinicalspects. As in much of emotion research, also data from word-rocessing studies in clinical or highly anxious populations showeightened and in the EEG often also earlier effects than in typicalamples, in particular for disorder-relevant material (e.g., Flor et al.,997; Knost et al., 1997; Pauli et al., 2005; Weinstein, 1995). Basicnowledge about the generation and reversibility of such effects inealthy samples should of course aid better intervention design. Aritical question is to what extent emotion effects in clinical sam-les are accessible to awareness and to what extent they can beodified by overt control or verbalization strategies, verbalization

eing a prominent interventional strategy for psychological distur-ances. Experimental evidence shows that verbalization can reducemotional responses even without explicit intention to control or

own-regulate emotion (Lieberman et al., 2007). Likewise, there

s evidence that self-reference (i.e. the extent to which a word’sontent describes one’s own emotions and feelings) modulates

Negative word Pseudoword Letter string

Krieg Greik Rgkie

Folter Tofler Tlrfeo

Alptraum Patrumla Tpuaamlr

Schmerz Schrenz Zshrecm

Selbstmord Blemsdrost Trlsbeodsm

Panik Kawin Iakpn

Brutalität Bitturätal Rbtuaitltä

Schlägerei Eischrage Gshäeiclre

Eifersucht Seierfucht Uchsrtfiee

Katastrophe Phatakroste Khrpteatsao

Geisel Seleig Gsliee

Lawine Wilane Iaelwn

Diktator Rottadek Ttikrdoa

Wahnsinn Winnsat Iwnnhnas

Eiter Riete Rtiee

Kälte Tälke Tlkäe

Schlange Langsche Ehscglna

chology 92 (2013) 464– 479

emotional word processing at various processing stages (e.g. Lewiset al., 2007) even in the absence of explicit appraisal instructions(Herbert et al., 2011a,b). Apparently, paradigms based on languagecontent do provide suitable tools to study the neural correlatesof emotional self-awareness (Herbert et al., 2011b). Explicit emo-tion control is currently a very active field of research, but it isunclear to what extent appeal to overt regulation strategies canreally normalize emotional responding in anxiety patients (but seeKircanski et al., 2012). A notoriously successful technique lend-ing itself to validation by neuroscientific methods is exposure andhabituation. Here, it may be particularly instructive to use methodswith high temporal resolution that allow to examine which com-ponents of processing habituate and which do not. Finally, someless conventional pharmacological intervention, such as the use oflow-dose cortisone or beta blockers may reduce emotional reac-tivity without the adverse effects of common tranquilizers. Theeffects of cortisone and beta blockers on emotional responding canbe tested relatively easily in both healthy and clinical populations. Athird general question regarding mechanisms of emotional atten-tion regards the continuity of mechanisms across species: Whileit seems relatively unproblematic to fruitfully apply knowledgefrom basic emotion research to clinical populations, even with thegoal of testing and optimizing the outcome of interventions, it ismuch more of a challenge to theoretically integrate data across allmethodological levels and across human and animal research withthe goal of a grand theory. With our own research field in mind,we can easily dismiss it as at present simply impossible: Humansare a symbolic species and use language; rats and monkeys are notand do not. But even outside the specific field of emotional lan-guage, it currently seems that a model that will really integrateacross all methodological approaches and levels of analyses wouldbe so general that it would not be testable. Integrating the varioustypes of human behavioral and neuroscience data, aiming for clin-ical applications, currently seems enough of a challenge. Althoughmuch of what we know about affective conditioning comes fromrats and much of what we know about visual perception and atten-tion comes from monkeys, one should be careful not to take toobig logical leaps across levels of analyses. Therefore, we currentlyprefer to remain agnostic with regard to this ultimate challenge ofour field and say, regarding the specific topic of this paper as well ason the way towards the grand theory: Further research is needed.

Acknowledgement

We thank Christina Herold for help with data collection andprocessing. Research was supported by the Deutsche Forschungs-gemeinschaft (KI1286/4-1).

Appendix A. Experimental material.

Word Pseudoword Letter String

Opfer Pfore EofrSpinne Pinnes SnpnieSeuche Echase CshueeElend Endle DlneeExplosion Soponixel NlpesxiooWunde Dunpe UdwneSünde Dünes NsdeüHabgier Heilbarg HbgreaiRevolver Verrovel LvrroeevBastard Darbsahn DbartsaGeschwür Schürweg WhcsrgeüAas Asa Saa

Spionage Pioganse GpnsioeaKot Tok TkoLügner Nagrül NgüelrZahnarzt Zarthans AzrthznaSpritze Zetpris Zzieprt

A

A

J. Kissler, C. Herbert / Biological Psychology 92 (2013) 464– 479 477

ppendix A (Continued )Negative word Pseudoword Letter string Word Pseudoword Letter String

Wahn Ahni Nwha Heroin Hirone HoienrGestank Kesgunt Kgtsnea Kerker Kerek KrrkeeLepra Peral Ealpr Beklemmung Memklebung KbeeugnmmlSchock Coschk Kccohs Durchfall Dallfurch LlduafrhcNarbe Barne Nrbea Isolation Olwosatin SnltooaiiNarkose Koscharne Kbeeugnmml Bestie Eisbit Btsiee

Neutral word Pseudoword Letter String Word Pseudoword Letter String

Gebäude Begedäu Ugdbeäa Symbol Mybols YomlsbBügeleisen Siegelüben Bnsüieeegl Akustik Kusikat TkskuiaAktentasche Teschakiten Hetkaaencts Siedlung Glodneis UildsngeAutomat Totauma Tmtuaao Getreide Diegeret DtrgeeieDing Gind Ignd Flasche Felscha LfeahcsMetall Ratell Eatllm Merkmal Kerlamm KmmealrAutobus Sugobau Uouatsb Möbel Löbem LmbeöGabel Batel Lbgae Sicht Achest IcthsDetail Ledial Tdliea Geschirr Gischer ErhcsigrBewohner Wehoreb Rbhnweeo Haussschuhe Saghusche ShcueahsuhPapier Paripe Aieprp Quadrat Quardta TqrduaaInhalt Talkhin Iatlhn Person Punser OensrpFlugzeug Geulfzug Gzlfgeuu Kaufhaus Haufsauk UaakfshuApparat Wappatar Aaaprtp Hammer Remmat MhmearBleistift Liebstfit Btieitstlt Maschine Nimasche HmecsniaArm Marn Rmaa Eigenschaft Egonscheift NgfthsceeiaReflex Fexmel Xrfeel Stirn Rinst RstniVerhalten Venerhalt Vhteealnrl Mikroskop Pikomser KskpmroioGelenk Gekel Neekgl Gedanke Kagonde GkeeadnOrientierung Rienoetung Oieegnrnrtiu Insekt Tiksen KtsnieObjekt Jekbot Jbktoe Beruf Ferüb RbfueAktenordner Ratenkorden Ktdernneaor Computer Tupercom UprctmeoBüro Rubo Oürb Begriff Fifberg Iefgfrb

Positive word Pseudoword Letter string Word Pseudoword Letter String

Liebe Abeil Ieebl Sex Xeis SxeOrgasmus Semusorg Roaussgm Reise Siere EeisrBeischlaf Fabsichel Aehflbcis Zungenkuss Gusskunzel UeusgskznnZärtlichkeit Kicherzättin Zchäikiettlr Party Tarpy AytrpEkstase Essfeka Sktaees Liebelei Leibeile LbleeiieVerführung Führunger Üfrhgnrvue Vergnügen Hugenrüven ÜgeevgnnFrühling Ginflühr Rfhgnlüi Umarmung Ammurung MgnmruuaLeidenschaft Deischenlaft Leetfdhcsain Fete Neet EetfÜberraschung Archenbürung Rhcsüeangubr Hochzeit Zohteich HhzctoieAbenteuer Stenebreu Ebnrtuaee Baby Byba YbbaErregung Urrengeng Rrggnuee Mut Tum MtuKuss Sukos Ssku Geschenk Kelschgen HcseekgnLiebschaft Battscheil Letfhcsiab Liebhaber Leibherab IbhbreaelUrlaub Laurub Rlbuua Held Dehl LhdeFerien Neifer Nrfeei Heiterkeit Kitterheife IeikheettFreude Deufer Ueedfr Geburtstag Sattbervug TgbgtsaeuSafari Faraus Rfsiaa Lob Bol LboDuft Hisfurdt Fdtu Spass Sasp SpssaSport Torps Osrtp Spassvogel Plagsavoses VlgoaesspsFreundschaft Rumedschaft Hsftafrdcnue Tänzer Zänter RztnäeBelohnung Ohnlebung Glbhoeunn Rose Sore OesrNobelpreis Pronsebeil Lsnpeieobr Wärme Märweg RwmeäVerlobung Gliebvorn Rnbuoelvg Euphorie Repheu Hpruieoe

ppendix B. EGI 256 channel Geodesic Net Sensor Groups used for statistical analysis.

Emotion108–140 msLeft occipital: 84, 85, 86, 94, 95, 96, 97, 105, 106, 107, 114, 115, 116, 123, 124, 153,Right occipital: 154, 159, 160, 161, 162, 163, 168, 169, 170, 171, 172, 177, 178, 179216–284 msLeft: 103, 104, 105, 106, 113, 114, 115, 116, 122, 123, 124, 125, 135, 136, 137Right: 149, 150, 158, 159, 160, 167, 168, 169, 170, 176, 177, 178, 189, 190, 201324–420 ms

Left: 103, 104, 105, 106, 113, 114, 115, 116, 122, 123, 124, 125, 135, 136, 137Right: 149, 150, 158, 159, 160, 167, 168, 169, 170, 176, 177, 178, 189, 190, 201468–608 msLeft parietal: 128, 129, 130, 131, 139, 140, 141, 142, 143, 144, 151, 152, 153, 154, 155, 161,162, 163, 164Right parietal: 76, 77, 78, 85, 86, 87, 88, 96, 97, 98, 99, 107, 108, 109, 110, 117, 118, 119, 126

4 cal Psychology 92 (2013) 464– 479

A

35, 136,9, 190, 200

, 1370, 201

132, 1

R

B

B

B

B

B

C

C

D

D

E

E

F

F

F

G

G

H

H

H

H

H

H

H

H

H

78 J. Kissler, C. Herbert / Biologi

ppendix B (Continued )

Stimulus Type184–248 msLeft occipital: 95, 104, 105, 106, 107, 113, 114, 115, 116, 121, 112, 122, 123, 124, 1Right occipital: 158, 159, 160, 161, 167, 168, 169, 170, 171, 176, 177, 178, 188, 18216–392 msLeft occipital: 103, 104, 105, 106, 113, 114, 115, 116, 122, 123, 124, 125, 135, 136Right occipital: 149, 150, 158, 159, 160, 167, 168, 169, 170, 176, 177, 178, 189, 19432–500 msCentro-parietal: 59, 64, 65, 70, 71, 75, 76, 80, 84, 95, 106, 115, 116, 124, 125, 131,

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