Abstract
Affective meaning of verbal stimuli was found to influence cognitive control as expressed in the Emotional Stroop Task (EST). Behavioral studies have shown that factors such as valence, arousal, and emotional origin of reaction to stimuli associated with words can lead to lengthening of reaction latencies in EST. Moreover, electrophysiological studies have revealed that affective meaning altered amplitude of some components of evoked potentials recorded during EST, and that this alteration correlated with the performance in EST. The emotional origin was defined as processing based on automatic vs. reflective mechanisms, that underlines formation of emotional reactions to words. The aim of the current study was to investigate, within the framework of EST, correlates of processing of words differing in valence and origin levels, but matched in arousal, concreteness, frequency of appearance and length. We found no behavioral differences in response latencies. When controlling for origin, we found no effects of valence. We found the effect of origin on ERP in two time windows: 290–570 and 570–800 ms. The earlier effect can be attributed to cognitive control while the latter is rather the manifestation of explicit processing of words. In each case, reflective originated stimuli evoked more positive amplitudes compared to automatic originated words.
Emotional stroop task
The Emotional Stroop Task (EST) is a modification of the standard procedure introduced by Stroop (1935), which allows measuring the cognitive control in the case of interference control (Nigg, 2000). Interference in EST is made by the affective content of a word and arises as a result of the competition of two processes (Imbir, ). The first process is an automated reading and understanding of the semantic meaning of words. This captures participants' attention and generates slowdown in the second, controlled process. The second process is related to the task of naming of the font color. In the classical Stroop Test, the interference is caused by the understanding the meaning of words, which are the names of colors. The interference is observed when comparing congruent (e.g., responding “red” to a word “RED” written in red font) and incongruent (responding “red” to word “BLUE” written in red font) trials. The congruent trials are perceived as easier and are performed faster. The EST differs from the classical Stroop Task in the nature of the interference measured (Nigg, 2000; Larsen et al., 2006). In the EST, an incongruent and congruent trials are constructed by carefully choosing words so that they differ only in one affective factor (e.g., valence or arousal), while they are matched in respect of other properties (e.g., frequency, grammatical class, or length). This allows drawing an unambiguous conclusion from collected data. As the incongruent trials, involving the automatic disposition of attention toward a task-irrelevant lure (supposed to be analogical to the classical Strop effect) are treated those with extreme levels of the chosen factor, while congruent are those with moderate or neutral levels of the factor. For example, as far as valence is considered in the EST, trials with positive or negative words are considered incongruent while trials with neutral words are considered congruent (Burt, ; Imbir and Jarymowicz, ).
Factors underlying behavioral effects in EST
The behavioral phenomenon of EST has been discovered in clinical trials. Subjects experiencing particular trauma had longer reaction times for trauma-related words than for other words (Watts et al., 1986; McKenna and Sharma, 1995, 2004). The EST effects were demonstrated also in a clinical and subclinical psychological probes suffering from anxiety disorders (see Williams et al., 1996 for a review). The EST appeared to be a useful tool to detect the source of anxiety, because longer reaction times were observed for words connected in meaning with a particular source of threats. Subsequently, it was reported that EST slowdown could be observed in a normal population with no trauma experience (Nigg, 2000; Larsen et al., 2006; Siakaluk et al., 2014). Valence was shown to influence reaction latencies in cases of words with negative valence (e.g., Williams et al., 1996; McKenna and Sharma, 2004) and also with positive valence (e.g., Pratto and John, 1991; Richards et al., 1992; McKenna and Sharma, 1995). The effect for positive words was usually smaller than for negative words. Also, individual experience with objects or states represented by the words was shown to boost the slowdown (Reiman and McNally, 1995).
Careful inspection of valence effects revealed that other factors, not controlled in advance, could explain the behavioral effects (Burt, ; Larsen et al., 2006). Those factors, identified as far, were arousal load and frequency of appearance in language. It appeared that arousal causes slowdown that is independent from valence (Dresler et al., ; Imbir, ). High arousing words result in a greater slowdown in reaction latencies than low arousing stimuli. Also less frequent words cause higher slowdown than more frequent ones (Burt, ). Some recent results suggest that origin of an affective state may be an another factor responsible for slowdown observed in EST (Imbir and Jarymowicz, ), thus the question concerning factors underlying EST performance is still open. Since the valence effect was shown to be confusing and appeared to be blurred by other factors effects, we decided to ask a question concerning the nature of emotion and its' influence on EST. To find the answer, we have applied the dual-mind theories perspective, especially recently introduced framework concerning emotion and cognition interactions viewed from dual mind perspective (Imbir, ).
Duality of mind and EST
Recently, the duality of emotion framework was proposed in order to explain diversity of emotions (Jarymowicz and Imbir, ) as well as emotion-cognition interactions (Imbir, ). This proposition is based on duality of mind theories (for broad review see Gawronski and Creighton, ), distinguishing between so-called automatic and controlled processes. There is a huge diversity of dual-mind theories, but all of them highlight the main role of the above-mentioned processing modes. Taking into account Epstein's () proposition of existence of two aspects of mind, namely experiential and rational, we argue that both have their cognitive (c.f. Strack and Deutsch, 2004, 2014; Kahneman, ) manifestations in form of associative (or heuristic) vs. systematic (or rational) processes and emotional (Jarymowicz and Imbir, ) manifestations in form of automatic vs. reflective originated emotional states (c.f. Imbir, ). In the classical view on emotions seen from the dual-mind theory framework, they were thought to be associated only with simplified processing of experiential mind (c.f. Epstein, ; Kahneman, ), but such view was not sufficient to describe more complex, self-conscious emotions (Weiner, 2005). The emotion duality model (Jarymowicz and Imbir, ) states that emotional experiences themselves can originate due to either automatic or reflective evoking mechanisms. This implicates, that affective processes are not necessarily automatic and may be understand as a results of controlled and rational mind processing (c.f. Reykowski, 1989; Strack and Deutsch, 2004, 2014). What is more, according to the classical theories only one of the mind-system could be tested in a given experimental protocol with use of a single task, attention manipulation or stimulus presentation parameters, while the emotional duality model applied to emotional words processing allows to study activation of either of the systems within the same experimental protocol, for the same subject, by treating the ability of evoking automatic or controlled mind processes as inherent property of individual word meanings. This fact address the most important critique addressed to dual-mind perspective (c.f. Ferguson et al., ).
In the case of experiential mind, so-called automatic originated emotions are characteristic for the direct affective responses to environmental stimulation. Such responses do not need language to appear and we assume that they are based on evaluation of criteria of biological value (Damasio, ). Certain objects help in maintaining life and thus are automatically evaluated as pleasant (e.g., fatty and sweet foods), while other things are threats to life and thus are evaluated as unpleasant (e.g., smelly or sour meals). The experiences of automatic originated emotions can be labeled with words (e.g., pain) and thus are widely represented in language (Rolls, 2000). In the case of rational mind, so-called reflective originated emotions are postulated (Jarymowicz and Imbir, ). Their most characteristic feature is that formation of reflective originated emotional states requires language (Reykowski, 1989; Strack and Deutsch, 2004, 2014). The propositional mechanisms in the form of evaluative standards (Reykowski, 1989) serve as a source of reflective emotions. Reflective emotion arises when a situation or behavior is compared to a standard represented in the mind. It is clear that the evaluative standards are both subject dependent and plastic; thus different reflective emotions toward single situation can arise in different subjects, or even in the same subject at different times (Jarymowicz and Imbir, ).
To measure the nature of affective reaction (automatic or reflective), the origin dimension was proposed and used in the case of assessing affective reactions to words (Imbir, , ). On the theoretical level (c.f. Epstein, ; Strack and Deutsch, 2014; Jarymowicz and Imbir, ; Imbir, ) emotional origin is a clearly dichotomic factor, but the direct measurement of the processing style underlying emotion formation is yet not possible, thus we have to base on subjective perception toward the processing mechanisms. Origin dimension is measured on a scale constructed as a type of Self-Assessment Manikin (SAM) scale (Lang, ). This scale allows for non-verbal assessments of feelings connected with presented stimuli (c.f. Figure 1). SAM scale was supplemented with a description of its meaning in order to provide unambiguous interpretation of the “origin” concept. We think that origin is not an intuitive dichotomy when emotions are considered (Jarymowicz and Imbir, ). Origin is rather a hidden underlying mechanism (Russell, 2003); thus we use in creation of SAM scale the heart vs. mind metaphor (c.f. Figure 1 legend), widely represented in culture, as a good exemplification of dual-mind dichotomy of underlying processes (Imbir, ). Heart represents immediate reactions that do not require hesitation, in contrast to mind that represents careful inspection of all opportunities and interpretations of the situation. We argue that some of the emotions are based on non-verbalized criteria of evaluation, as proposed by Damasio's () biological value. Other emotions require cognitive resources and language to interpret and appraise reality. Mechanisms underlying those more cognitive-based emotions are evaluative standards (Reykowski, 1989) or propositional thinking (Strack and Deutsch, 2004) based on processing with the use of sentences and rules of logic. The first case describes so-called automatic emotions and the second case reflective ones. Origin SAM scale allowed for reliable measurement of perception of automatic vs. reflective origins of affective reactions to words (Imbir, , ). Nevertheless, it appeared that not all stimuli had unambiguous associations of their origins. In real world most of states are results of activation of both mental systems (Epstein, ; Kahneman, ; Jarymowicz and Imbir, ). Also this aspect was found in the SAM scale measures collected. Some words received moderate assessments (based on ambiguous interpretations made by different people), thus in fact not allowing for specification of certain origin. We treat those words as stimuli with no specified origins, because no particular and clear associations were drawn (cf. Imbir et al., ). Distinct mechanisms underlying affective processes formation, that are reflected in words connotations defined from a dual-mind perspective, can be compared in a single experiment, due to high level of similarity for materials specific to both mind systems (Imbir, ). In a traditional view on dual-mind systems, there was an expectation to operationalize them as a distinct, especially because experiential system works in visual representations (Epstein, ), while reflective systems is based on verbalizations (Strack and Deutsch, 2004). The lack of possibility to create a single experiment testing consequences of both mind systems was the main weakness raised for dual-mind perspective (Ferguson et al., ). Origin factor, found to be reliably measured for words (Imbir, ), offers an important advantage for understanding the role of dual mind processes in word processing and understanding of affect influence on cognitive control. Figure 1 presents the SAM scale for origin assessments.
Figure 1
EST is a type of task that involves the two types of processes: automated and controlled (Imbir,
Figure 2

Outline of the experimental procedure.
Guided by described above expectations, a behavioral results of early EST study, involving words that differed in levels of origin and valence (Imbir and Jarymowicz,
Using Russell's (2003) concept of bimodal affective space, composed of two orthogonal dimensions of (1) valence, representing pleasantness vs. unpleasantness of an affective state, and (2) arousal, representing the activation underlying an affective state, we decided to check each dimension in the context of duality of emotion framework. In dual mind emotion-cognition relation framework (Imbir,
ERP correlates of word processing and EST performance
Studies conducted so far identified a number of ERP components that are altered by processing of emotional words. These are typically labeled as P1, N1, P2, Early Posterior Negativity (EPN), P3, N450, and Late Positive Complex (LPC) components (Van Hooff et al., 2008; Citron,
The P2 component with maximum amplitude observed at about 200–250 ms (Van Hooff et al., 2008) was found in several studies to be sensitive to the emotional meaning of words. Unfortunately the pattern of results for this component is rather inconsistent. Enlarged amplitudes can be observed for positive words only (Schapkin et al., 2000), negative words only (Huang and Luo,
In the literature examining ERP correlates of cognitive control, the traditional version of Stroop Task is more popular (Duncan-Johnson and Kopell,
The second component found to be influenced by interference control in Stroop Task is P3, sometimes identified with LPC (Sass et al., 2010). The P3 in EST shows centro-posterior localization within 340–600 ms time range. This component was originally detected in the oddball paradigm and was thought to be a manifestation of surprise when less frequent stimuli appear (Luck, 2005), or it can be a manifestation of update of recalled memories content or process of event categorization (Coles et al.,
Aim and hypothesis
The aim of our current study was to check if the factors: valence and emotional origin of stimuli modulate ERP correlates of EST processing. Valence and origin were operationalised with use of SAM scales (c.f. Figure 1 and Imbir,
We intended to search amplitude differences in components typically reported for EST such as P2 and N450, as well as those associated with stimuli meaning connotations and associations processing such as LPC. We expected to find the amplitude differences in P2 component to be related to behavioral differences. This expectation was based on results concerning list of words differing in arousal and subjective significance levels (Imbir et al., submitted). Another previous work indicated that automatic-originated words interfered with task performance on an EST more than reflective-originated words (Imbir and Jarymowicz,
Materials and methods
Participants
The subjects (female = 16, male = 16), aged from 19 to 26 years (M = 21.63, SD = 1.98), were students at different Warsaw colleges and universities. They took part in the experiment voluntarily, for a small reward. All of the participants were right-handed, native Polish language speakers with normal or corrected-to-normal vision. Participants provided their verbal informed consent to participate in the presence of at least two lab members, which was documented in a research diary. We did not collect any personal data from our participants, to assure their anonymity. This procedure was suggested by the bioethical committee. The design, experimental conditions and consent procedure for this study were approved by the bioethical committee of the Maria Grzegorzewska University.
Design
We investigated the behavioral and electrophysiological measures related to the reading of emotional words. We manipulated the factors of valence (3 levels) and origin (3 levels), while controlling the following properties of words: arousal, concreteness, frequency of appearance in language and length. The distribution of variables: response accuracy and number of correct and artifact-free trials was not Gaussian, therefore the significance of effects concerning these variables was assessed by means of the Friedman test for replicated block design. The effects concerning other variables, with approximately normal distribution, were assessed by means of ANOVA with repeated measures.
Linguistic materials
Linguistic materials were chosen from an Affective Norms for Polish Words Reload (ANPW_R: Imbir,
Table 1
| M | (SD) | M | (SD) | M | (SD) | Origin category | M | (SD) | |
|---|---|---|---|---|---|---|---|---|---|
| Valence | 3.50 | (0.36) | 5.02 | (0.56) | 6.71 | (0.35) | Automatic | 5.07 | (1.39) |
| Origin | 4.45 | (0.53) | 4.58 | (0.37) | 4.33 | (0.70) | 4.45 | (0.55) | |
| Arousal | 4.37 | (0.49) | 4.15 | (0.55) | 4.28 | (0.80) | 4.27 | (0.62) | |
| Concreteness | 4.31 | (1.15) | 3.95 | (0.74) | 4.48 | (1.20) | 4.24 | (1.05) | |
| NoL | 7.20 | (2.65) | 7.47 | (1.96) | 7.40 | (2.41) | 7.36 | (2.31) | |
| Ln_freq | 5.21 | (1.91) | 5.65 | (2.03) | 5.73 | (2.28) | 5.53 | (2.04) | |
| Valence | 3.37 | (0.36) | 5.19 | (0.54) | 6.38 | (0.32) | Control (0) | 4.98 | (1.32) |
| Origin | 5.41 | (0.31) | 5.49 | (0.30) | 5.36 | (0.35) | 5.42 | (0.32) | |
| Arousal | 4.15 | (0.23) | 4.12 | (0.67) | 4.04 | (0.51) | 4.11 | (0.49) | |
| Concreteness | 4.05 | (1.12) | 3.96 | (1.32) | 4.17 | (0.74) | 4.06 | (1.06) | |
| NoL | 6.47 | (2.03) | 5.27 | (1.33) | 6.93 | (2.02) | 6.22 | (1.92) | |
| Ln_freq | 5.48 | (2.28) | 5.97 | (1.27) | 6.61 | (2.02) | 6.02 | (1.92) | |
| Valence | 3.66 | (0.35) | 5.30 | (0.39) | 6.49 | (0.40) | Reflective | 5.15 | (1.23) |
| Origin | 6.46 | (0.30) | 6.63 | (0.41) | 6.63 | (0.56) | 6.57 | (0.43) | |
| Arousal | 4.32 | (0.49) | 3.93 | (0.47) | 4.03 | (0.36) | 4.10 | (0.46) | |
| Concreteness | 4.17 | (1.13) | 4.09 | (1.17) | 4.41 | (1.07) | 4.22 | (1.11) | |
| NoL | 7.07 | (1.75) | 6.27 | (1.62) | 7.20 | (2.27) | 6.84 | (1.91) | |
| Ln_freq | 5.42 | (1.37) | 6.53 | (1.79) | 6.01 | (1.22) | 5.99 | (1.52) | |
| Valence category | Negative | Neutral | Positive | Total | |||||
| Valence | 3.51 | (0.37) | 5.17 | (0.50) | 6.53 | (0.38) | Total | 5.07 | (1.31) |
| Origin | 5.44 | (0.92) | 5.57 | (0.92) | 5.44 | (1.09) | 5.48 | (0.97) | |
| arousal | 4.28 | (0.42) | 4.07 | (0.56) | 4.12 | (0.58) | 4.16 | (0.53) | |
| concreteness | 4.18 | (1.11) | 4.00 | (1.08) | 4.35 | (1.01) | 4.18 | (1.07) | |
| NoL | 6.91 | (2.15) | 6.33 | (1.86) | 7.18 | (2.20) | 6.81 | (2.09) | |
| Ln_freq | 5.37 | (1.85) | 6.05 | (1.72) | 6.12 | (1.89) | 5.85 | (1.84) | |
Descriptive statistics (M, SD) for groups of words used in factorial manipulation (Source: Imbir et al.,
Table 2
| Valence category | |||||||
|---|---|---|---|---|---|---|---|
| Negative | Neutral | Positive | |||||
| Origin Category | |||||||
| Automatic | czkawka szloch łzy uszczypnięcie pijak naiwniak słabeusz zmęczenie hałas plotka grymas gafa usidlenie smarkacz zaślepienie | hiccup sob tears pinch drunk sucker weakling fatigue noise rumor grimace blunder ensnaring stripling infatuation | procesja kościół kuksaniec tarot loteria westchnienie jałmużna błazen mrowienie pragnienie obrzęd wróżka młodzież łasuch burza | procession church nudge tarot lottery sigh alms clown tingling desire rite fairy youth gourmand storm | zakochanie passa toast powitanie zapach słodycz pomoc niemowlak flirt potomstwo pozdrowienie skarb walentynka podarunek ferie | infatuation streak toast welcome fragrance sweetness help infant flirt offspring greeting treasure valentine gift holiday | |
| Control (0) | wina ciemnota truchło dół ochłap breja paszkwil kuternoga reumatyzm biedak śpiączka obtarcie błąd łachmany wada | fault unacquaintance carcass pit offal slush libel lame rheumatism wretch coma sore error rags drawback | doping chór kłębek telewizja guru wódka unik czara smok blef żargon głębia farsa grono pisarz | cheering choir hank television guru vodka dodge goblet dragon bluff jargon depth farce bunch writer | przyjęcie rejs powiew promocja klimat gość brawa kreskówka melodia wydarzenie smak południe malarstwo wyzwanie obrońca | party cruise waft promotion climate guest applause cartoon melody event taste south painting challenge defender | |
| Reflective | egzaminy ignorancja krata minus szpieg koszty podwładny podatek alimenty odsetki rząd przemyt recesja bezrobocie heretyk | exams ignorance grating minus spy costs subordinate tax alimony interest government smuggling recession unemployment heretic | szlachta etykieta sułtan zadatki prawo prasa stawka raport wojsko interes dyscyplina wynik weto hodowla kurs | nobility label sultan makings right press bid report army business discipline result veto breeding course | miliard tolerancja mistrz patent dobytek absolwent uczony stypendium szczyt równowaga oszczędności płaca satyra lider zysk | billion tolerance master patent property graduate scholar scholarship peak balance savings wages satire leader profit | |
Full list of stimuli used in each category of experimental manipulation.
The properties of construction of the manipulation were assessed by means of 3 (valence levels) × 3 (origin levels) ANOVA analyses for each dimension measured. In the case of manipulated variables we have found for valence ratings significant differences for valence levels: F(2, 126) = 607.44, p < 0.001, η2 = 0.91, but not for origin levels: F(2, 126) = 1.88, p = 0.16, η2 = 0.03, nor for interaction between valence and origin levels: F(4, 126) = 2.09, p = 0.086, η2 = 0.062. For origin ratings we have found significant differences for origin levels: F(2, 126) = 254.55, p < 0.001, η2 = 0.80, but not for valence levels: F(2, 126) = 1.27, p = 0.28, η2 = 0.02, nor for interaction between valence and origin levels: F(4, 126) = 0.5, p = 0.74, η2 = 0.016.
In the case of controlled variables no statistically significant effects were found for three dimensions. Arousal ratings: no statistically significant effects were found [statistics summary: between valence levels: F(2, 126) = 1.98, p = 0.14, η2 = 0.02, origin levels: F(2, 126) = 1.44, p = 0.24, η2 = 0.02, interaction between valence and origin levels: F(4, 126) = 0.5, p = 0.72, η2 = 0.016]. Concreteness ratings: no statistically significant effects were found [statistics summary: for valence levels: F(2, 126) = 1.19, p = 0.31, η2 = 0.02, for origin levels: F(2, 126) = 0.4, p = 0.67, η2 = 0.006, for interaction between valence and origin levels: F(4, 126) = 0.12, p = 0.98, η2 = 0.004]. Frequency of the words' appearance in the Polish language (after logarithm transformation, with data taken from Kazojć,
Procedure
Subjects were seated in a comfortable chair. The words were displayed on a 15.6-inch LCD screen at a distance of ~1 m from the subjects' eyes. The font was Helvetica 50 point size. Simultaneously with the target word cues indicating initial letters of Polish names of possible colors: P—orange (pomarańczowy), C—red (czerwony), Z—green (zielony), N—blue (niebieski), was displayed at the bottom of the screen. Each participant performed a training session to learn what the task was and how to perform it correctly. The training consisted of 20 initial trials (naming color squares displayed in one of the four target colors, reading color-meaning words) followed by 60 standard Stroop Tests (Stroop, 1935) i.e., naming the font color—both congruent and incongruent presented in random order. After those trial sessions, the main experiment was introduced, based on EST with use of emotional words selected. Each time participants were encouraged to respond as quickly and as accurately as possible. The subject's task in the main part of the experiment was to indicate the font color of the emotional words by pressing a response key labeled by the one of the letters P, C, Z, N. The experimental protocol is depicted in Figure 2.
The timing of a single trial in the main part of experiment was the following: a fixation cross was displayed for 700 ms; next a word was presented for as long as it took the subject to read and respond to it (no timeout was implemented, the exceptionally long responses were excluded from the offline analysis); after detecting the response the screen went blank for 300–400 ms. The trials were grouped, so that 15 words of homogeneous properties (i.e., the same level of valence and origin) were presented consecutively. We decided on a block design because EST effects are more pronounced in this type of presentation, in fact larger behavioral effects were found for block design in comparison to fully random presentation of words (c.f. Bar-Haim et al.,
The whole experiment was composed of three repetitions of 2 distinct lists of words. First list (described above) was designed to measure valence-origin factors influence on EST. Second list was designed to operationalize factorial manipulation of arousal and subjective significance, the two activational factors postulated in dual-mind model of Emotion-Cognition interactions (Imbir,
EEG material
Apparatus
Stimuli were displayed on a 15.6-inch LCD display controlled by a PC. A second PC was used for recording EEG data. Stimuli and EEG data were synchronized using a custom-made hardware trigger. The trigger consisted of a light sensor measuring the brightness of a small rectangular portion of the screen, which was covered by the sensor. Brightness of that part of the screen was modulated simultaneously with the stimulus presentation. The signal from the sensor was recorded, together with the EEG signal, on an auxiliary input of the amplifier. This auxiliary signal was later used to align trials. EEG activity was recorded from 19 derivations of 10–20 system: Fz, Cz, Pz, Fp1/2, F7/8, F3/4, T3/4, C3/4, T5/6, P3/4, O1/2, referenced to linked earlobes, grounded on the clavicle. The impedances of electrodes were below 5 kΩ. The signal was acquired using a Porti7 (TMSI) amplifier at 256 Hz sampling frequency.
Offline EEG signal processing
The offline processing of the signal was performed in Matlab® with the EEGLAB (Delorme and Makeig,
The statistical tests were implemented using the appropriate R procedures (R Development Core Team, 2008, available from http://www.R-project.org). Trials with erroneous responses, or corrupted with artifacts (e.g., eye blinks or muscle activity), or with extremely short (shorter than 2.5 percentile of the distribution of all response latencies), or long (longer than 97.5 percentile of the distribution) response latencies were excluded from the ERP analysis. The mean number of trials remaining in each of the 9 manipulation condition (from the initial 45) was M = 37 (SEM = 0.3). The Friedman test for replicated block design did not indicate significant differences in the average number of trials per condition for the origin groups with valence as a blocking variable [ = 3.4, p = 0.2], nor for the valence groups with origin as a blocking variable [ = 0.46, p = 0.8].
Results
Behavioral measures
The mean response accuracy was M = 90% (SEM = 0.4). The Friedman test for replicated block design did not indicate significant differences in the average accuracy per condition for the valence groups with origin as a blocking variable [χ(2) = 1.08, p = 0.58], or for the origin groups with valence as a blocking variable [χ(2) = 5.88, p = 0.053]. The response latency was analyzed for the trials that were accepted for ERP analysis (i.e., artifact free, correct responses, without the 5% most extreme RT values). Analysis by means of 3(valence levels) × 3(origin levels) ANOVA with repeated measures applied to log transformed reaction latencies did not reveal any significant effects [factor valence: F(2, 62) = 0.84, p = 0.44; factor origin: F(2, 62) = 0.65, p = 0.53; valence × origin interaction: F(4, 124) = 2.0, p = 0.1]. The average response latency was M = 820 (SEM = 8.6) ms.
Electrophysiological data
Selection of time windows and regions of interest
The following time windows were selected for evaluation of ERP effects: 50–150, 150–290, 290–570, 570–800 ms. This selection is based on the global field power curve GFP (Figure 3). The GFP is evaluated as spatial standard deviation. It quantifies the sum of electrical activity over all electrodes at a given time point. The latencies of GFP maxima may be interpreted as the latencies of evoked potential components (Lehmann and Skrandies, 1980; Skrandies, 1990). Since we do not expect lateralization effects, three regions of interest (ROI) were selected as follows: frontal (F) (electrodes: F3, Fz, F4), central (C) (electrodes: C3, Cz, C4), and parietal (P) (electrodes: P3, Pz, P4). A similar approach can be found in the other studies focusing on neural correlates of EST task (e.g., Schirmer and Kotz, 2003; Thomas et al., 2007; Taake et al., 2009) and gives us a chance to investigate a distribution of effects in a front-to-back dimension.
Figure 3

Global field power with the selected time-windows marked by vertical lines. Below–average amplitude topographies for each of the windows.
Analysis of ERP effects
The analysis was performed by applying a three-factor repeated measure analysis of variance (origin × valence × ROI) to the mean amplitude from each subject, in each of the time windows. For each of the time windows there was a significant main effect of ROI but this finding is not interesting and will not be discussed further. There were no significant interaction between ROI and the other two variables in any of the time windows, therefore further on the amplitudes averaged across ROIs were analyzed. No statistically significant effects were observed for time windows 50–150, 150–290 ms. No effects were obtained for valence levels in any time window (Figure 4A). But for two time windows there were significant effects for origin levels. Namely, in time window 290–570 ms a main effect of origin [F(2, 62) = 5.078, p < 0.01] was obtained. The amplitude was less negative for stimuli with reflective origin (M = −0.27, SEM = 0.33) than for those with automatic origin (M = −0.72, SEM = 0.30), and with no specific origin (M = −0.81, SEM = 0.30); corresponding t-test results [t(31) = 2.37, p < 0.05; t(31) = 2.83, p < 0.02]. In the time window 570–800 ms a main effect of origin [F(2, 62) = 4.78, p < 0.016] was obtained too, but the pattern of differences was slightly different. Only the amplitude for reflective stimuli (M = 0.56, SEM = 0.27) was more positive than for automatic origin (M = 0.13, SEM = 0.26); corresponding t-test result [t(31) = 2.92, p < 0.02]. No statistically significant effects of interaction between valence and origin were observed in these time windows [290–570 ms:F(4, 124) = 1.37, p = 0.25; 570–800 ms:F(4, 124) = 0.46, p = 0.77]. The time course of the ERPs, which illustrate the results, is shown in Figure 4B. Since no significant interactions between origin levels and ROI were observed, the curves in Figure 4 are the amplitudes of ERP averaged across all three ROIs.
Figure 4

Grand mean ERPs for the three levels of: (A) valence dimesion, (B) origin dimension, averaged across the three ROIs. The thick gray horizontal lines indicate the time-windows with significant differences between the origin levels. Signal from each electrode included in ROIs is presented respectively below: (C) for valence and (D) origin. The symbols in legend are the labels of valence levels (Pos, positive; Neu, neutral; Neg, negative), and origin levels (Refl, reflective; Zero, of no specific origin; Auto, automatic). Horizontal axis–time in ms, vertical axis–amplitude in μV. Vertical gray lines mark the edges of the selected time-windows.
Discussion
This study was focused on investigating the role of origin and valence of emotional words in the processing of EST and involuntary word processing. We hoped to find electrophysiological correlates of underlying mechanisms, even when the behavioral outcomes of the task are not visible (c.f. Thomas et al., 2007). Result confirmed that there are no differences in response latencies; meanwhile ERP amplitude differs between levels of origin of emotion included in word meaning, but not between valence levels. The differences appeared in time windows characteristic to components thought to be manifestations of cognitive control (N450: 290–570 ms) and involuntary word processing including more controlled and explicit cognitive processing of words meaning (LPC: 570–800 ms). Surprisingly, electrophysiological results were not localized at a particular site, but rather generally distributed over all the ROIs analyzed.
Behavioral results
As expected, we did not find behavioral differences in reaction latencies due to the type of word processed in EST. Those results are coherent with our other unpublished negative results concerning behavioral-only measures for the same list of words as used now. This lack of difference is also consistent with EEG measures in the P2 component, found in our earlier study (Imbir et al., submitted) to be a strict correlate of behavioral differences. Lack of behavioral differences related to variations of valence dimension can be attributed to the role of another dimensions found to be more crucial (c.f. Burt,
In this study, we did not find the results for the origin of the affective state, reported in our earlier studies involving EST (c.f. Imbir and Jarymowicz,
ERP results
Electrophysiological correlates of EST allowed us to inspect the stages of task processing and the role of valence and origin dimensions of words used in this process. What is the most interesting is that we found no effects of valence during the whole time course analyzed. It seems that if the origin of an affective state is controlled and aligned in all valence conditions, the traditional effects may disappear (Imbir and Jarymowicz,
The lack of amplitude differences in P2 time range observed in this study corresponds with the lack of behavioral differences in response latencies. Previously mentioned second list used in this experimental protocol [contrasting 3 levels of arousal and 3 levels of subjective significance (Imbir et al., submitted)] resulted in both reaction latencies differences due to both factors as well as amplitude differences in P2 (150–290 ms) component closely resembled the pattern of behavioral results (longer reaction times ~ more positive amplitude). Thomas et al. (2007) suggested that P2 amplitude might be a more sensitive measure of inhibitory control than behavioral responses. Valence and origin list of words results reported in current paper supports this claim, the same as result for arousal and significance list of words (Imbir et al., submitted).
The results concerning origin of emotional state consequences for EST processing (c.f. Figure 4B) are interesting. We found global effects in two time ranges that can be attributed to the N450 and LPC components. The first component, peaking at about 350–500 ms after stimulus onset, called N450 (c.f. West and Alain, 2000) is frequently reported (Van Hooff et al., 2008; Taake et al., 2009) in studies with EST paradigm. The N450 is located in the frontal regions of a head (Sass et al., 2010). Although no interaction with ROI was found for amplitudes in this study, the topography of the average amplitude distribution for this time window (c.f. Figure 3, bottom graphs) suggest that the most intensive negativity is indeed located in the frontal regions of the head. The amplitude of the N450 component was found to be more negative for incongruent than congruent trials (West, 2003; West et al., 2004). The underlying mechanism is possibly associated with conflict detection (West, 2003; West et al., 2004) or selection of competing responses (West and Alain, 1999). In ERP waveform we can see the N450 component (c.f. Figure 4B, 290–570 ms). The reflective originated conditions generated less negative amplitude than automatic originated and control words. This mean, that less incongruent were the reflective originated stimuli presentation conditions, thus one may expect that indeed the rational mind reduces interference of automated reading and meaning of stimuli understanding, even without behavioral outcomes in response latencies. The lack of correspondence with behavioral results may suggest, that decision concerning the type of answer is made earlier (in P2 time range), while N450 in this study reflect rather the conflict cost appearing after decision was made. Alternatively, they may be interpreted in the context of involuntary processing of a meaning of words included in manipulations (see below).
The last component, the LPC, is a manifestation of explicit and controlled cognitive activation of the content and connotations of a word, but rather made without explicit instruction in the context of current experiment. This is a late word-processing related activity rather than a cognitive control manifestation, especially we may assume that this a kind of post-semantic processing (Jończyk,
It is worth highlighting that results of our study were not localized in a specific site or ROI. This is a different result to other studies showing localized effects. It may be partially due to the half-exploratory analytical strategy chosen in this study. When ANOVA showed no significant interaction between one of the main factors and the ROI factor, we simply resigned from further investigation inside ROIs, despite the fact, that average amplitude distribution showed some topographical variations (c.f. Figure 3). In fact, effects found are distributed in the same way all over the head. This strategy allows us not to miss potentially important findings connected with new proposed origin dimension. Although some results with origin exist so far (c.f. Imbir et al.,
It is worth to compare the results of current study to the results of study with use of LDT paradigm applied for the same list of stimuli (c.f. Imbir et al.,
Finally we would like to note, that in current study we have used a relatively low number of stimuli repeated three times. This is a result of a compromise between careful selection of stimuli and balancing them in all controlled dimensions, and the need to have enough events for averaging ERPs. In fact, the repetition of stimuli may potentially lead to attenuation of behavioral and ERP effects. Lack of valence related differences observed in results might be therefore attributed to this methodological issue. However, the fact that in these circumstances we observe an effect of origin supports the postulated higher importance of origin dimension even stronger.
Conclusion
Results of this study showed that despite the lack of behavioral results, the processing of EST causes differences in electrophysiological correlates of this task. We have demonstrated that there were no differences in the P2 component, found in another study (Imbir et al., submitted) to be a strict manifestation of behavioral differences. We also found only origin, but not valence, shaped cortical responses of the brain while processing words in EST. It is possible that without including origin factor in experimental schema valence differences can be detected. When origin is controlled, the differences in amplitudes for negative as well as positive words can disappear.
Authors contributions
All authors contributed to final version of the manuscript. Theoretical proposition: KI; Design: KI, JŻ Method (words): KI; Method (EEG measures) JŻ, TS; Experimental procedure programming: TS, JŻ Experiment execution: TS, JŻ Statistical analyses: JŻ, KI, TS, JD, GB; Results description: JŻ, JD; Results discussion: KI; Figures: JŻ, TS, KI, JD, GB.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Statements
Funding
The project was funded by the National Science Center on the basis of decision: DEC-2013/09/B/HS6/00303. KI was supported by the foundation for Polish Science (FNP).
Acknowledgments
We would like to express our thanks to Alicja Brzozowska for participation in data collection and technical assistance. We would also like to thank the reviewers for their insightful comments and recommendations for manuscript improvements.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00880/full#supplementary-material
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Summary
Keywords
duality of emotions, emotional stroop task, mechanisms of cognitive control, ERP, emotional words
Citation
Imbir KK, Spustek T, Duda J, Bernatowicz G and Żygierewicz J (2017) N450 and LPC Event-Related Potential Correlates of an Emotional Stroop Task with Words Differing in Valence and Emotional Origin. Front. Psychol. 8:880. doi: 10.3389/fpsyg.2017.00880
Received
17 February 2016
Accepted
15 May 2017
Published
30 May 2017
Volume
8 - 2017
Edited by
Cornelia Herbert, University of Ulm, Germany
Reviewed by
Jianfeng Yang, Shaanxi Normal University, China; Nathaniel Delaney-Busch, Tufts University, United States
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© 2017 Imbir, Spustek, Duda, Bernatowicz and Żygierewicz.
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*Correspondence: Kamil K. Imbir kamil.imbir@gmail.com
This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology
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