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Biological Psychology 86 (2011) 254–264
Contents lists available at ScienceDirect
Biological Psychology
journal homepage: www.elsevier.com/locate/biopsycho
Emotionally positive stimuli facilitate lexical decisions—An ERP study
Johanna Kissler ∗ , Susanne Koessler
Department of Psychology, University of Konstanz, Germany
a r t i c l e
i n f o
Article history:
Received 20 October 2009
Accepted 16 December 2010
Available online 22 December 2010
Keywords:
Emotion
ERPs
Lexical decision
Affective priming
International Affective Picture System
a b s t r a c t
The influence of briefly presented positive and negative emotional pictures on lexical decisions on positive, negative and neutral words or pseudowords was investigated. Behavioural reactions were the
fastest following all positive stimuli and most accurate for positive words. Stimulus-locked ERPs revealed
enhanced early posterior and late parietal attention effects following positive pictures. A small neural
affective priming effect was reflected by P3 modulation, indicating more attention allocation to affectively
incongruent prime-target pairs. N400 was insensitive to emotion. Response-locked ERPs revealed an early
fronto-central negativity from 480 ms before reactions to positive words. It was generated in both frontocentral and extra-striate visual areas, demonstrating a contribution of perceptual and, notably, motor
preparation processes. Thus, no behavioural and little neural evidence for congruency-driven affective
priming with emotional pictures was found, but positive stimuli generally facilitated lexical decisions, not
only enhancing perception, but also acting rapidly on response preparation and by-passing full semantic
analysis.
© 2010 Elsevier B.V. All rights reserved.
1. Introduction
Emotions prepare the organism to react rapidly to the environment via two motivational systems, an appetitive system that
responds to positive valence and a defensive system responding to
negative valence. Arousal indicates the degree to which either system is activated. Each system interconnects appropriate episodic
and semantic memory contents, physiological reactions, and action
programs (Lang et al., 1998). Thus, emotions will affect different
stages of information processing, ranging from attentional engagement to action preparation and execution.
Many electrophysiological studies confirm enhanced implicit
attention allocation to various kinds of emotional stimuli reflected
in modulations of early and late attention-related ERPs (Kissler
et al., 2009; Pourtois and Vuilleumier, 2006; Schupp et al., 2006).
Facilitated behavioural responses to emotional stimuli have also
been described in detection (Anderson and Phelps, 2001; Brosch
et al., 2007; Zeelenberg et al., 2006), evaluation (Estes and Verges,
2008), or choice reaction tasks (Estes and Adelman, 2008; Scott
et al., 2009).
Response facilitation by emotional stimuli is uncontroversial,
but it is debated, whether valence or arousal drives this advantage.
∗ Corresponding author at: Department of Psychology, Box D25, University of
Konstanz, 78457 Konstanz, Germany. Tel.: +49 07531 884616;
fax: +49 07531 884601.
E-mail address: [email protected] (J. Kissler).
0301-0511/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.biopsycho.2010.12.006
Whereas some studies reveal faster reactions to arousing stimuli
regardless of valence (Kousta et al., 2009; Larsen et al., 2006), other
studies indicate speeded detection of negative emotional stimuli
(Öhman et al., 2001) and yet others find accelerated responses to
positive stimuli (Leppänen and Hietanen, 2004). Faster responses
to positive stimuli are observed in linguistic tasks, such as color
naming (Mckenna and Sharma, 1995; Williams et al., 1996), word
naming (Algom et al., 2004; Estes and Adelman, 2008), and lexical decision (Estes and Adelman, 2008; Wentura et al., 2000). In
general, faster responses to positive stimuli appear to occur primarily on tasks, where valence is not task-relevant (Estes and Verges,
2008). This has been attributed to slower attentional disengagement from negative stimuli, leading to motor response suppression
(e.g. Estes and Adelman, 2008).
Emotional relevance affects responses not only to current, but
also to subsequent emotional information. This phenomenon is
called affective priming (Fazio et al., 1986): People are generally
faster to judge the affective connotation of a target word (e.g.
“APPEALING”) when it is preceded by a same-valence prime (e.g.
“PARTY”) than by an affectively incongruent prime (e.g. “GUN”).
The affective priming paradigm is well-established with evaluative decision, lexical decision, or naming as target tasks (see
Klauer and Musch, 2003 for an overview). Both spreading activation in semantic networks and priming of response tendencies
have been suggested as underlying mechanisms. Response tendencies are supposed to be primed mainly in evaluative decisions
and semantic memory is thought to be pre-activated in lexical
decisions. However, more recent reports suggest an interaction
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J. Kissler, S. Koessler / Biological Psychology 86 (2011) 254–264
of these processes (Spruyt et al., 2007a,b), response tendencies
also affecting the lexical decision task (see Wentura, 2000). Word
stimuli are most common, but affective priming has also been
reported for emotional faces (Haneda et al., 2003; Murphy and
Zajonc, 1993; Rotteveel et al., 2001; Spruyt et al., 2004), real-life
situations (Spruyt et al., 2007b), black-and-white line drawings
(Giner-Sorolla et al., 1999) or voice–face pairings (Paulmann and
Pell, 2010). Generally, affective priming is most clearly seen with
SOAs shorter than 300 ms, longer SOAs abolish or reverse the effect
(Klauer and Musch, 2003).
Several ERP studies have investigated affective priming, and in
line with a spreading activation account many of them focused
on the N400, a sensitive and reliable indicator of semantic relatedness (Holcomb, 1993; see Kutas and Federmeier, 2000 for an
overview; Rösler and Hahne, 1992). N400 amplitude increases with
semantic distance and reflects difficulty of semantic integration
and search processes in the mental lexicon (Kutas and Federmeier,
2000; Rösler and Hahne, 1992; Supp et al., 2004). It is particularly
large for phonotactically legal pseudowords (e.g. Federmeier et al.,
2000; Holcomb, 1993; Supp et al., 2004; Ziegler et al., 1997). The
N400 can be elicited cross-modally, reflecting the degree to which
primes and targets access similar underlying semantic networks,
independent of their physical similarity (for review, see Kutas and
Federmeier, 2009). N400 effects have been obtained with pictorial primes and targets (McPherson and Holcomb, 1999), written
primes and pictorial targets (Federmeier and Kutas, 2002; Wicha
et al., 2003), or picture primes and word targets (Connolly et al.,
1995). N400 is a more sensitive indicator of semantic priming than
reaction time (Heil et al., 2004).
N400 also appears to index affective priming. Schirmer et al.
(2002) reported that at least in females the N400 amplitude elicited
by emotional words in lexical decision is influenced by the prosody
of a preceding sentence. Paulmann and Pell (2010) found N400
modulation by voice prime prosody in a facial affect decision task.
Bostanov and Kotchoubey (2004), presented emotional exclamations (e.g. “Yeah!” and “Oooh!”) after emotion words. This elicited
a larger N400 for contextually inappropriate than to appropriate
emotional exclamations. Affectively congruent music also primes
lexical decisions and modulates the N400 (Steinbeis and Koelsch,
2009). These data indicate a wide replicability of affective priming
and imply spreading activation as an important mechanism.
However, other studies report more variable patterns: investigating how emotional faces prime decisions on subsequent
emotional facial expressions, Werheid and colleagues found ERP
priming effects on early and late attention and emotion ERPs, but
not on the N400 (Werheid et al., 2005a,b). This presumably reflects
perceptual and attentional facilitation, but not spreading activation. Subliminally priming facial affect ratings, Li et al. (2008) also
found effects on the P1 and P3a components, early (Pourtois and
Vuilleumier, 2006) and late (Cuthbert et al., 2000) indicators of
attentional orienting.
Finally, studies examining the effects of pictures from the International Affective Picture System (IAPS, Lang et al., 1999) on the
cortical processing of subsequent emotional information found
no evidence at all for affective priming: Flaisch and colleagues,
paired picture primes with picture targets and found interference of emotional primes with processing of subsequent pictures.
This was evidenced in reduced target-related early posterior negativities (EPNs) and late positive potentials (LPPs), but not in
congruency effects (Flaisch et al., 2008a,b). Zhang et al. (2006) compared affective priming of emotionally congruent and incongruent
word–word and picture–word pairs in an evaluative decision task.
Neural congruency effects were observed only for the word–word
and not for the picture–word pairings. For the word–word, but
not for the picture–word pairs, N400 modulations in the affectively congruent condition were found. Since in the evaluation task
255
spreading activation as reflected in N400 modulations is theoretically not the most prevalent account, the stimulus-locked analysis
may have missed electrocortical indices of response preparation
that could have occurred in this design. On the other hand, two
other studies using emotional pictures as primes also fail to find ERP
evidence of affective priming. Given that these emotional pictures
otherwise very reliably modulate brain responses (e.g. Cuthbert
et al., 2000; for review Schupp et al., 2006), the affective priming
phenomenon may not be as domain general as sometimes assumed.
Thus, many studies find affective priming effects on the N400 and
some report effects on other ERP components, but yet others using
the otherwise so potent IAPS pictures report no priming effects at
all.
Here, we investigate affective priming of lexical decisions by
emotional IAPS pictures, analyzing both stimulus- and responserelated ERPs. Thereby, we address the domain generality of
affective priming and test response facilitation by affective stimuli. ERP studies of affective priming often focus on the N400
implicitly assuming spreading activation as the underlying mechanism. However, other ERP effects have also been found and
the behavioural literature implies that affective priming impacts
also response preparation (Spruyt et al., 2007a,b). Therefore, we
analyze response- as well as target-related ERPs. By examining
response preparation preceding emotional stimuli, facilitation of
motor responses by emotional stimuli can be investigated regardless of affective priming.
Motor preparation is more prominent in the response-locked
than in the stimulus-locked ERP (Nieuwenhuis et al., 2003).
Response-locked analysis has been used to investigate volitional
motor preparation (Kornhuber and Deecke, 1965), mechanisms
of visual search (Luck and Hillyard, 1990), and action monitoring (for review see Taylor et al., 2007). Early studies suggest that
attention and motivation can affect response reparation (Elbert
et al., 1984, 1985; Kornhuber and Deecke, 1965). More recently,
an emotion effect on action monitoring has been demonstrated
in response locked ERPs (Simon-Thomas and Knight, 2005). Thus,
response facilitation by emotional stimuli in general and in affective priming in particular would suggest that effects may be evident
in pre-response ERPs.
Positive or negative pictures from the International Affective
Picture System (IAPS) are used as primes, and positive, negative,
and neutral adjectives or ‘pseudo-adjectives’ serve as targets in
a lexical decision task. Primes and targets were chosen such that
prime-target pairs matched in emotional content, but differed
semantically to avoid covert semantic priming as a potential source
of effects. For instance, a crime scene could be followed by the German word for ‘narrow-minded’, or a mutilated body was followed
by the word ‘greedy’. Similarly, a sports scene could be followed by
the word ‘erotic’, and a happy family scene by the word ‘successful’.
Reaction time, response accuracy, and stimulus- and responserelated ERPs are assessed. If affective priming is a domain-general
phenomenon behavioural and ERP congruency effects should occur.
ERP effects may become apparent on the N400, if affective priming uses similar mechanisms as semantic priming. If affective
priming affects response preparation, ERP effects should occur in
response-locked ERPs. However, affective priming may also modulate perception- and attention-related ERPs. Finally, IAPS pictures
might not prime lexical decisions after all, in which case emotional
stimuli should still affect behavioural reactions and cortical processing in the absence of congruency effects. Given the evidence for
facilitated reactions to positive stimuli in lexical decisions, accelerated responses to positive stimuli can be expected. Such effects
should be reflected in response-locked ERPs. To address the above
possibilities fully, a data-driven approach to EEG analysis is used to
identify relevant time windows and regions of interest.
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Table 1
Mean pleasure and arousal ratings of picture and word stimuli. Additionally, word
length and word frequency (based on counts for written German language from
the CELEX database) are given for adjectives. The range and direction of the SAM
ratings are as follows: pleasure = 9 (extremely positive) to 1 (extremely negative),
arousal = 9 (extremely arousing) to 1 (not at all arousing). Standard errors are given
in parentheses.
Mean valence and arousal ratings
Adjectives
Valence
Arousal
Word length (letters)
Word frequency (per million)
Pictures
Pleasure
Arousal
Positive
Negative
Neutral
6.70 (0.11) 2.80 (0.07) 4.94 (0.08)
5.34 (0.11) 5.41 (0.13) 3.68 (0.10)
8.21 (0.29) 8.14 (0.28) 7.88 (0.27)
31.50 (7.63) 18.83 (4.19) 24.86 (4.59)
7.17 (0.07)
5.71 (0.08)
2.29 (0.08)
5.79 (0.11)
2. Methods
2.1. Participants
Sixteen native German students (8 women) from the University of Konstanz,
Germany, took part in the experiment. Mean age was 23.56 (SE = .62) years and
all were right-handed according to the Edinburgh Handedness Inventory (Oldfield,
1971). They had no history of neurological or psychiatric disease and their vision
was normal or corrected to normal. Subjects signed written informed consent forms
and received either a financial bonus of 12 D (∼18 $) or course credit for their
participation.
2.2. Material
Primes consisted of 58 positive and 58 negative pictures from the International
Affective Picture System (IAPS, Lang et al., 1999). The pictures were selected on the
basis on their normative Self-Assessment Manikin (SAM, Bradley and Lang, 1994)
ratings of arousal and pleasantness (valence). Selected pictures did not differ in
terms of arousal (F(1,114) < 1) or complexity as measured by JPG size (F(1,14) < 1),
but differed in terms of valence (F(1,114) = 2062.51; p < .0001). Mean SAM ratings of
the selected positive and negative pictures are given in Table 1.
For the lexical decision task 58 positive, 58 negative, and 58 neutral adjectives were chosen from a pool of 500 German adjectives that had also been rated
on the dimensions of arousal and valence using a computerized version of SAM
(Bradley and Lang, 1994) by 45 students. Different subsets from this material have
been used in previous studies (Herbert et al., 2006, 2008; Kissler et al., 2007,
2009). Positive, negative, and neutral adjectives differed significantly from each
other with respect to valence [F(2,171) = 496.25; p < .001; negative vs. positive:
F(1,114) = 908.18; p < .001; positive vs. neutral: F(1,114) = 176.39; p < .001; negative vs. neutral: F(1,114) = 389.32; p < .001]. Positive and negative adjectives were
matched for arousal (F(1,114) < 1), but both differed from neutral adjectives on
that dimension (F(2,171) = 77.09; p < .001; negative vs. neutral: F(1,114) = 115.12;
p < .001; positive vs. neutral: F(1,114) = 128.38; p < .001).
Further, adjectives were chosen to be comparable in word length (F(2,171) < 1),
number of syllables (F(2,171) < 1) and word frequency (F(2,171) = 1.24; p = .29). Word
frequency data were obtained from the standardized word-database CELEX (Baayen
et al., 1995). See Table 1 for a summary of stimulus characteristics.
Pseudowords were based on the 174 original adjectives and were generated by
letter permutations within and between words to preclude perceptual repair and at
the same time maintain pronounceability. Original word length was never altered.
2.3. Procedure
Participants were familiarized with the laboratory and given general information about the study. Handedness was assessed (Oldfield, 1971) and subjects were
asked about their past and current health using a standardized questionnaire.
Participants were seated in an electrically shielded room and 64 EEG electrodes
were attached to their head. They were informed that they were taking part in a
word processing study and that their task was to indicate by mouse click as quickly
and as accurately as possible if a presented word was a legal German word or a
pseudoword. They were told that pictures would briefly appear before each word
(pseudoword), which they should disregard. Additionally, a written instruction was
presented on the monitor. Assignment of response buttons to the index or middle
finger of the right hand was counter-balanced.
696 picture–word pairs were presented on a computer monitor at a distance of
1.23 m. Presentation was divided into two blocks of 348 trials with a break between
the blocks. In a 2 (pictures valence: positive, negative) × 4 (word type: positive,
neutral, negative, pseudoword) design, positive and negative pictures were followed
by words of each valence or pseudowords. Picture–word pairs had been generated
randomly, but pairings and order of presentation were fixed for all participants.
Immediate repetitions of pictures or words (pseudowords) in two successive trials
and semantic relatedness between picture and word were avoided.
Every trial started with a fixation cross shown for a random interval of
1500–2000 ms, a picture followed for 100 ms and was replaced by a word or pseudoword for another 300 ms. Then, a question mark was shown for 1000 ms which
cued participants to react to the words (pseudowords) as quickly and as accurately
as possible. The experimental setup is depicted in Fig. 1.
2.4. EEG recording
EEG was recorded from 64 channels referenced to Cz, using an EasyCap and NEUROSCAN SynAmps amplifiers and software. Recording bandwith was DC to 70 Hz
and sampling rate was 250 Hz. Recording impedance was held beneath 5 k. Offline, data were re-referenced to an average reference and low-pass filtered at 30 Hz.
For artifact control horizontal and vertical electrooculograms were recorded. Eye
movement artifacts and blinks were corrected using the ocular correction algorithm
implemented in BESA (Brain Electrical Source Analysis, MEGIS Software GmbH).
Gross remaining artifacts were reduced by individual channel-interpolation, individual epochs containing smaller artifacts were rejected (max. 10%).
2.5. Stimulus locked data
For stimulus-locked averaging, filtered data were segmented from 100 ms
before picture onset until 800 ms after target (word-pseudoword) onset and baseline
corrected using 100 ms prime picture onset as baseline.
2.6. Response locked data
For response-locked averaging, filtered data were analyzed from 800 ms before
the motor-response (word–nonword button press decision) to 200 ms after the
response. An epoch of 1600–1500 ms before the response served as the baseline.
3. Data analysis
3.1. Behavioural data – lexical decision performance and
response correctness
Reaction times and correctness of lexical decisions were analyzed with repeated measures ANOVAs with picture type (positive,
negative) and word type (positive, negative, neutral, pseudoword)
Fig. 1. Exemplary depiction of the experimental setup.
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257
Fig. 2. Mean reaction times in the lexical decision task depending on the valence of the preceding prime picture (+1 SE).
as factors. For post-hoc analysis Fisher’s Least Significant Difference
Test was used.
3.2. ERPs
In order to statistically test for priming and response facilitation
effects, a two-stage analysis procedure was applied: First, a pointwise ANOVA including all experimental factors (picture type, word
type), time-points, and EEG sensors was computed. Based on the
results, regions and time-intervals of interest were identified in
which experimental effects could be expected. For the point-wise
ANOVA, a significance criterion of p < .01 was used. Furthermore,
to avoid spurious results, only effects in regions consisting of at
least 8 neighboring electrodes and within time-intervals of at least
28 ms were considered meaningful. In the second step, based on
the results of this exploratory analysis, electrodes belonging to
one region and time window were grouped together and submitted to repeated measure ANOVAs containing the factors picture
type (positive, negative) and word type (positive, negative, neutral, pseudowords). Significant main effects and interactions in
the identified regions of interest were followed up with Fisher’s
Least Significant Difference tests. Statistical analysis of ERPs was
carried out with the MatLab-based open source software EMEGS
(ElectroMagnetic-EncephaloGraphy; www.emegs.org). Because in
total three times as many pseudowords as proper words were presented during the experiment, for each subject only the first 58
pseudowords were averaged and entered into the analysis to obtain
an equal number of averages for each stimulus type. The order of
pseudoword presentations was random for each subject.
4. Results
4.1. Reaction times
Reaction times for the lexical decisions are shown in
Figs. 2 and 3. Subjects responded significantly faster when positive pictures than when negative pictures preceded the words or
pseudo-words (prime picture, F(1,15) = 8.15; p < .05, see Fig. 2). Also,
participants reached their lexical decision soonest, when positive
adjectives were presented and reacted slowest to pseudowords
(target word, F(3,45) = 9.21; p < .0001, see Fig. 3). Post-hoc tests
showed that reaction times to positive words were in tendency
faster than reactions to negative words (p = .06) and significantly
faster than reactions to neutral words (p < .01) and pseudowords
(p < .001). Further, negative words were classified faster than pseudowords (p < .01), but not neutral words. The interaction between
picture type and word type was far from significant (prime × target,
F(3,45) < 1).
Fig. 3. Mean reaction times in the lexical decision task depending on the type of target word (+1 SE).
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Fig. 4. Topographical distribution of p-values from a pointwise ANOVA examining the effects of prime picture (top row), target word (middle row), and their interaction
(bottom row) on ERPs evoked by the target word. Target on-set is at 0 ms. Maps are plotted with a threshold of p < .01 for each sensor and spline-interpolated. Time windows
meeting combined significance criteria (see text) are framed in black.
4.2. Response accuracy
Regarding response accuracy, a main effect of word type
(target word, F(3,45) = 4.72; p < .01) was found. Prime picture
type (F(1,15) < 1) and the interaction between prime and target
(F(3,45) < 1) did not reach significance. Fewer errors were made
when responding to positive adjectives in comparison with neutral adjectives (p < .001), pseudowords (p < .05) and in tendency
also negative adjectives (p < .08). Most errors were made to neutral
adjectives.
5. ERP results
At an occipito-parietal group of 8 electrodes (Oz, O1, O2, O7, O9,
O10, PO9, and PO10), ERPs associated with positive primes were
more negative-going than ERPs associated with negative primes
(F(1,15) = 22.2; p < .001). A complimentary effect was found at 8
frontal sensors (AF3, AF4, AFz, AF7, AF8, FP1, FP2, and FPz), revealing a larger positivity following positive than following negative
pictures (F(1,15) = 13.65). Between 324 and 428 ms, a further effect
of prime type was found at centro-parietal sites, corresponding to
an LPP effect (see Fig. 5). This effect was further analyzed at a group
of 8 parietal electrodes (PO1, PO2, P1, P2, P3, P4, Pz, and CPz), yielding a larger positivity following positive primes (F(1,15) = 21.89,
p < .001). The prime-related ERP effects are visualized in the top
row of Fig. 5.
5.1. Stimulus-locked analysis
5.3. Target type
Fig. 4 displays the temporal evolution and spatial distribution
of significant effects of prime, target and the prime × target interaction in the stimulus-locked analysis. These effects are described
and analyzed in more detail in the following.
5.2. Prime type
Two time-windows where prime valence affected the targetevoked ERP were identified: between 216 and 248 ms after target
on-set an effect of prime type emerged at frontal and left occipitoparietal electrodes corresponding to the often described EPN effect.
As evident from Fig. 4 and the bottom row of Fig. 5, a targetrelated fronto-central effect emerged, starting at 320 ms. This effect
was further analyzed in an early fronto-central and a later centroparietal time window. It corresponded to the frontal and parietal
portions of the N400 effect. Between 320 and 444 ms after word
(pseudoword) onset, the target-evoked early fronto-central N400
effect was analyzed at a cluster of eight fronto-central electrodes
(FZ, FCz, F1, F2, FC3, FC4, F5, and F6). This analysis yielded a significant main effect of Target (F(3,45) = 9.68; p < .001) which was due to
the fact that pseudowords were associated with a larger negativity
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Fig. 5. Difference topographies and ERP waveforms at individual sensors illustrating follow-ups of significant effects in the stimulus-locked analysis. Top left shows the early
effect due to positive prime pictures which led to a relatively more negative waveform and scalp topography between 218 and 248 ms after word on-set. Top right is the late
positivity effect due to positive prime pictures. The bottom row depicts the earlier frontal and later centro-parietal portions of the N400 effect which showed differentiation
between words and pseudowords, but no modulation by emotion. Target on-set is at 0 ms.
than all real words, regardless of word valence (all ps < .001). Word
ERPs did not differ according to valence (all ps > .2).
Between 384 and 572 ms after word (pseudoword) onset, the
later, parietal portions of this process were analyzed at a cluster of eight centro-parietal electrodes (C1, C2, CPz, CP3, CP4, P1,
P2, and Pz). Again, this analysis yielded a main effect of Target
(F(3,45) = 15.42; p < .001) which was due to the fact that pseudowords were associated with a larger negativity than all words,
regardless of word valence (all ps < .001). Words did not differ from
each other according to valence (all ps > .2).
5.4. Prime × target interaction
A spatially and temporally restricted prime × target interaction
emerged in a centro-parietal region between 320 and 352 ms after
target on-set. It was further analyzed at a group of eight centroparietal electrodes (CP3, CP4, CP5, CP6, CPz, P1, P2, and Pz). The
prime × target interaction (F(3,45) = 6.04; p < .01) was due to less
positive ERPs to affectively congruent, than affectively incongruent prime-target pairs. Positive–positive pairings differed from
positive–negative ones (p < .01) as well as from negative–positive
ones (p < .05). Negative–negative pairings were associated with a
smaller positive potential than positive–negative pairings (p < .01)
and in tendency also smaller than negative–positive pairings
(p < .06). This effect is visualized in Fig. 6.
5.5. Response-locked analysis
Fig. 7 displays the temporal evolution and spatial distribution of significant effects of prime, target and the prime × target
interaction in the response-locked analysis. No clear spatially or
temporally stable prime × target interactions were found in the
response-locked analysis. However, as evident from Fig. 7, an
effect of prime emerged between 320 and 292 ms before the
response. Target-related effects emerged in the response locked
data between 480 and 388 ms before the response and from 288 to
68 ms pre-response. These effects were further analyzed as detailed
in the following.
5.6. Prime
Between 320 and 290 ms pre-response a main effect of prime
valence (F(1,15) = 8.56,; p = .01) was identified at a group of nine
parietal sensors (PO1, PO2, P1, P2, P3, P4, P7, P8, and Pz). The effect
was due to the fact that in parietal regions positive primes were
associated with more positive going ERPs than negative primes.
This effect likely resembles the above described prime-related parietal positivity.
5.7. Target
Between 480 and 388 ms before the response a main effect of
target type was identified (F(3,45) = 6.72, p < .01), which was veri-
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Fig. 6. Interaction of prime and target valence between 320 and 352 ms after target on-set at parietal scalp sites. The difference topography is shown on the left, the time
course of the activity is illustrated at centro-parietal sensor CPz.
fied at a group of eight fronto-central electrodes (F1, F2, FC3, FC4,
FCz, C1, C2, and Cz). It turned out to be due to the fact that positive
targets were associated with more negative brain potentials than
pseudoword targets (p < .01) and in tendency also negative targets
(p < .1).
Finally, between 288 and 96 ms pre-response a last effect of
target type emerged. The nature of this effect was evaluated at
a slightly left-lateralized group of eight parietal electrodes (CP3,
CP5, P1, P2, P3, Pz, PO1, and PO2). Pre-response ERPs differed
depending on the target type (target, F(3,45) = 10.33; p < .001). This
was due to more positivity preceding responses to words, regardless of their valence, than to pseudowords (all ps < .05). The effect
of Prime (F(1,15) = .16; p = .7) and the target × prime interaction
(F(3,45) = .65; p = .59) were not significant.
In order to facilitate interpretation of these response-locked
effects as due to response preparation or perceptual target processing, the sources of the effects were approximated using the
L2-Minimum-Norm-Pseudoinverse method (L2-MNP, Hamalainen
and Ilmoniemi, 1994). L2-MNP is an inverse modeling technique
applied to reconstruct the topography of the primary current
underlying the electric current distribution. The L2-MNP allows
the estimation of distributed neural network activity without a priori assumptions regarding the location and/or number of current
sources (Hamalainen and Ilmoniemi, 1994). In addition, of all possible generator sources only those exclusively determined by the
measured electric current are considered. Four concentric spher-
ical shells with evenly distributed 3 (azimuthal, polar, and radial
direction) × 360 dipoles were used as source model. A Tikhonov
regularization parameter k of 0.02 was applied. For visualization
purposes, the estimated sources were projected onto the surface
of an averaged brain (Montreal Brain, Montreal Neurological Institute) as implemented in EMEGS.
Fig. 8 shows the ERP time course at selected sensors, the topographical differences, and the source localizations for the early
(480–388 ms pre-response, top row) and the later pre-response
target effect (288–96 ms pre-response, bottom row). The results
suggest that both effects are attributable to enhanced activity in
perception and attention, but notably also motor systems, contributing to motor-response preparation.
6. Discussion
This study investigated accuracy, reaction times, and stimulus and response-locked ERPs in a picture–word affective priming
experiment using the lexical decision task. Behaviourally, we
observed no congruency effects indicative of affective priming.
Instead, facilitation for positive stimuli was found. First, presentation of positive pictures accelerated subjects’ reactions in the
subsequent lexical decision. Second, subjects’ lexical decisions
were fastest in response to positive words. Both positive and
negative emotional adjectives were responded to faster than pseudowords, but the advantage was largest for positive adjectives.
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J. Kissler, S. Koessler / Biological Psychology 86 (2011) 254–264
261
Fig. 7. Topographical distribution of p-values from a pointwise ANOVA examining the effects of prime picture (top row), target word (middle row), and their interaction
(bottom row) on pre-response ERPs. Response on-set is at 0 ms. Maps are plotted with a threshold of p < .01 for each sensor and spline-interpolated. Time windows meeting
combined significance criteria (see text) are framed in black.
Positive, but not negative adjectives, were responded to faster
than neutral ones and in tendency positive adjectives were also
responded to faster than negative ones. Third, participants made
fewest errors when responding to positive adjectives. In lexical
decision, a number of previous studies found faster reactions to positive words (Estes and Adelman, 2008; Kiehl et al., 1999; Wentura
et al., 2000), which has been theoretically ascribed to delayed disengagement from and motor suppression by negative stimuli. While
the present results confirm fastest lexical decisions following positive stimuli, they are not in line with a motor suppression account.
Motor suppression suggests a ‘freezing-like’ response which would
predict slowed reactions to negative in comparison to neutral stimuli, but the present pattern of results suggests specific facilitation
for positive stimuli compared to neutral ones. Responses to negative and neutral words did not differ significantly, but numerically
responses to negative words were faster.
Accelerated responses to positive stimuli may be contributed
to by the response movement required. Neumann and Strack
(2000) investigated the interaction between emotional content and
approach or avoidance movements across several tasks including lexical decision and found response facilitation in particular
when subjects had the impression of approaching a positive
word. Button-press as an approach-movement may thus promote
response facilitation for positive stimuli. The independent effect of
prime picture valence may likewise be due to accelerated responses
to positive stimuli on tasks where valence is not task relevant. Out-
side lexical decision, a response advantage for positive stimuli has
for instance been found in face or picture recognition (Kissler and
Hauswald, 2008; Leppänen and Hietanen, 2004)
The neurophysiological data largely parallel the behavioural
pattern. In the stimulus-locked data, enhanced processing of
positive stimuli was found, but only little evidence for congruency effects indicative of affective priming emerged. Positive
prime pictures had numerically relatively small, but quite consistent and significant effects on the processing of all types
of target stimuli around 220 ms and between about 320 and
420 after target on-set. Regarding timing and topography the
effects resemble the previously described early posterior negativity and the late positive potential, respectively. In passive
picture viewing, both these components are usually considerably larger for emotionally arousing in comparison to neutral
stimuli, regardless of valence. However, often the advantage is
somewhat greater for positive than for negative pictures, even
when these are matched for arousal (Cuthbert et al., 2000;
Flaisch et al., 2008b; Kissler and Hauswald, 2008; Palomba et al.,
1997; Schupp et al., 2003). The current task may have accentuated this advantage for positive stimuli. This is open to future
research.
ERPs have been shown to be more sensitive measures of priming
than reaction times (Heil et al., 2004) and indeed, a small congruency effect was found over parietal brain areas. However, this
effect was not reflected in overt behaviour. Based on the timing,
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J. Kissler, S. Koessler / Biological Psychology 86 (2011) 254–264
Fig. 8. Top row: early pre-response effect of target valence. A more pronounced fronto-central pre-target negativity is illustrated at representative sensor Cz (left). The
difference topography is shown in the mid-panel and the source localization of the difference potential is shown on the right. The bottom row shows a late pre-response
effect of target type (words vs. pseudowords). It is illustrated at a left centro-parietal sensor (far left) and the spatial extent of the difference is shown in the middle. The right
panel depicts the source localization of the difference potential.
topography and direction of ERP amplitudes, it seems that in a
small and restricted time window, processing of affectively congruent prime-target pairs consumed less attentional resources than
affectively incongruent prime-target pairs as reflected in a smaller
parietal positivity perhaps resembling the P3a. For facial expressions, a P3a priming effect has been reported by Li et al. (2008).
On the N400, which under a spreading activation account should
have been particularly sensitive to affective priming, the wellknown pseudoword effect was predominant. Although the N400
could be clearly identified in the data (see Figs. 4 and 5), no modulation by either prime or target valence, or an interaction thereof,
appeared. Two different sub-processes of N400 were identified, a
frontal and a centro-parietal one, which did not differ functionally.
Although early studies characterized the N400 as having primarily a
centro-parietal distribution, later studies showed that, although the
distribution is generally broad, it is often more frontal for concrete
words and pictures (Ganis and Kutas, 2003; Kounios and Holcomb,
1994) as well as in single word presentations (Herbert et al., 2008).
This pattern has been only recently validated directly (Voss and
Federmeier, 2010). Whereas some authors suggest that frontal
N400 potentials specifically reflect familiarity effects in recognition memory rather than priming (Nyhus and Curran, 2009), in line
with the present data, Voss and Federmeier (2010) in a direct com-
parison found no functional differences between the frontal and
the centro-parietal N400.
The response-locked ERPs also revealed specific effects for positive stimuli. A small effect of positive primes, based on its timing
and topography, probably mirrored the prime-induced late positive
potential already evident in the stimulus-locked data. Of note, in the
pre-response data, a fronto-central negativity was larger preceding
reactions to positive words than to pseudowords, and in tendency
also negative words. This effect occurred between 480 and 380 ms
before the response was made (i.e. starting about 150 ms after target onset) and was later followed by a general response facilitation
effect for words compared to pseudowords which activated similar brain areas. The topography and generator distribution of the
earlier effect suggest that it reflects perceptual and attentional
enhancement, but, notably also response facilitation. Early perceptual and attentional enhancement effects of emotional content
in word processing have been reported (Hofmann et al., 2009;
Kissler et al., 2007, 2009; Ortigue et al., 2004; Scott et al., 2009).
They have been found from about 100 ms after word presentation, mostly over bilateral occipito-temporal areas, and the current
source analysis indicates that the present effects are partly due
to such early perceptual processing. However, superior parietal
and fronto-central sources contribute to the effect, implying that
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J. Kissler, S. Koessler / Biological Psychology 86 (2011) 254–264
mechanisms of response preparation act already very early in the
processing stream. This would suggest that initial response facilitation by affective targets can pre-cede full semantic analysis, a
notion also implied by behavioural literature on affective priming
(Klauer and Musch, 2003). Such effects may be mediated at least
in part by a fast subcortical visual pathway (LeDoux, 2000) which
also appears to rapidly modulate the reflexive behavioural response
system (Lang and Davis, 2006) and early visual processes (Liddell
et al., 2005). Whereas very rapid activations have been reported
more often for negative stimuli, invasive recordings in humans
show that they in principle also exist for positive stimuli (Kawasaki
et al., 2005). Regarding emotional words, a recent study showed
particularly pronounced amygdala responses to positive adjectives
similar to the ones used in the present study (Herbert et al., 2009).
Together with the above described observations, this supports the
possibility of rapid activation of motor-related regions via a subcortical visual pathway. Lexical decisions may be especially conducive
to facilitation for positive stimuli.
While still tentative, this present observation is interesting and
important and calls for future ERP research into response preparation in choice reaction tasks with emotional stimuli as well as in
affective priming. The results support stronger response facilitation
for positive stimuli, but not as a consequence of motor suppression by negative stimuli. If this had been the case, the event-related
potentials preceding negative targets should have been reduced in
comparison to neutral targets. This was not the case.
A number of factors may be responsible for our failure to obtain
affective priming in a picture–word lexical decision task. Since
three other previous studies also failed to observe clear neural
effects of affective priming using IAPS picture stimuli (Flaisch et al.,
2008a,b; Zhang et al., 2006) the present pattern may be specific
to this particular prime-target combination and point to a limit
in affective priming. In line with this, de Gelder et al. (2002) found
more immediate electrocortical priming effects for face-voice, than
for picture-voice pairs. Cross-modal affective priming has been
reported for voice–face pairs (Paulmann and Pell), and music–word
pairs (Steinbeis and Koelsch, 2009), perhaps rendering pictures
special in this respect. N400 semantic priming effects have been
obtained with pictures and words as well as other stimulus combinations (Kutas and Federmeier, 2009), but specifically creating
picture prime and word target pairs that were not semantically
related may have counteracted spreading activation processes and
affective priming. In this respect, the present finding may only
reflect the tip of the iceberg of a more general problem in affective priming research: Conceivably, some of the previous studies
reporting ‘affective priming’ partly measured semantic priming.
Storbeck and Robinson (2004) directly compared semantic and
affective priming across a variety of experimental situations: They
found that semantic priming was a much more robust phenomenon
than affective priming, particularly in lexical decision tasks. It is
difficult to completely orthogonalize semantic and affective relatedness, especially with word stimuli (see Storbeck and Robinson,
2004, for a discussion). Even if semantic relatedness has been
successfully controlled in previous studies, many studies of affective priming used comparatively small prime-target sets (about 10
pairs) that were repeated numerous times in the exact same pairing. Thus, it is possible that previously obtained affective priming
effects were at least partly due to the effect of covert associative
learning. Under the label of ‘affective’ priming subjects may have
acquired semantic relatedness plus the appropriate response. The
affective nature of the prime may have facilitated associative learning for congruent pairs, causing them to have a net advantage over
incongruent pairs. Such a mechanism could not have come into play
in our experiment since we used a large variety of complex slides as
primes and adjectives as targets, which were not repeated within
a particular condition (say positive–positive). Indeed, at least with
263
the naming task which, just like the lexical decision task, is thought
to rely heavily on spreading activation processes, affective priming
has only been obtained in studies that used multiple stimulus repetitions and not with single presentation sets (so-called ‘infinite
sets’, see Spruyt et al., 2007a,b).
In sum, using a typical affective priming set-up in a lexical
decision task with emotional pictures as primes and emotional
adjectives as targets, we found facilitation effects of positive primes
and targets, both on a behavioural and a cortical level, but no
behavioural and only very small neural congruency effects indicative of affective priming. We also found effects of positive emotional
content on stimulus processing and in particular a surprisingly
early impact of positive content on response preparation. The latter
effect may be indicative of a direct, pre-lexical, influence of affective word content on behaviour preparation which may by-pass
semantic analysis. This phenomenon, in particular, merits further
examination.
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