Cognition and Emotion

ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20

On the relationship between negative affective priming and prefrontal cognitive control mechanisms Rosalux Falquez, Simone Lang, Ramona Dinu-Biringer, Frauke Nees, Elisabeth Arens, Boris Kotchoubey, Moritz Berger & Sven Barnow To cite this article: Rosalux Falquez, Simone Lang, Ramona Dinu-Biringer, Frauke Nees, Elisabeth Arens, Boris Kotchoubey, Moritz Berger & Sven Barnow (2015): On the relationship between negative affective priming and prefrontal cognitive control mechanisms, Cognition and Emotion, DOI: 10.1080/02699931.2014.994476 To link to this article: http://dx.doi.org/10.1080/02699931.2014.994476

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Date: 25 October 2015, At: 18:35

COGNITION AND EMOTION, 2015 http://dx.doi.org/10.1080/02699931.2014.994476

On the relationship between negative affective priming and prefrontal cognitive control mechanisms Rosalux Falquez1, Simone Lang1, Ramona Dinu-Biringer1,2, Frauke Nees2, Elisabeth Arens1, Boris Kotchoubey3, Moritz Berger4, and Sven Barnow1

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1

Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Heidelberg, Heidelberg, Germany 2 Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany 3 Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Tuebingen, Germany 4 Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany (Received 2 July 2014; accepted 29 November 2014)

Although several studies have examined inhibition of affective stimuli, valence-dependent cognitive control effects remain poorly understood. Behavioural and functional imaging (functional magnetic resonance imaging) data were collected from 17 healthy participants to examine neural correlates of the Negative Affective Priming (NAP) task. We created relative ratio scores considering the reaction times of prime trials in order to assess the amount of interference after the presentation of negative and positive distracter words. Behavioural results showed an attenuated NAP effect for negative distracters compared to neutral stimuli. Furthermore, priming negative distracters generated more interference by reacting to the probe target than positive distracters. Neuroimaging data revealed a stronger prefrontal activation during negative NAP trials compared to positive NAP and neutral control trials, which was reflected in a heightened activation of superior and middle frontal gyrus as well as parietal cortex. The findings show the impact of negative distracters on prefrontal response, contributing to the understanding of NAP effects in healthy subjects. Keywords: Negative affective priming; Selective attention; Facilitation effect; Negativity bias.

In everyday life, the ability to ignore irrelevant, distracting information is decisive for adjustment of behaviour towards current goals (Bunge, Ochsner, Desmond, Glover, & Gabrieli, 2001). Due to survival reasons, emotional stimuli are considered

to be more attention grabbing than neutral information (Bradley, 2009; Ohman, 2007). However, in order to allow goal-directed behaviour, cognitive control is indispensable in situations where emotional information impairs goal

Correspondence should be addressed to: Rosalux Falquez, Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Heidelberg, Hauptstrasse 47-51, 69117 Heidelberg, Germany. E-mail: rosalux.falquez@psychologie. uni-heidelberg.de © 2015 Taylor & Francis

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achievement. In line with these assumptions, previous studies have suggested that an adequate top– down control of irrelevant affective stimuli is associated with mental health (Gotlib, Yue, & Joormann, 2005). Furthermore, failures in ignoring negative distracters have been related to maladaptive emotion regulation strategies such as rumination (Joormann, 2004; Zetsche, D'Avanzato, & Joormann, 2012), which in turn, are strongly linked to psychopathology (Barnow, Aldinger, Ulrich, & Stopsack, 2013; Koole, 2009). With regard to these findings, an understanding of the mechanisms responsible for cognitive control of emotional distracters becomes crucial (Friedman & Miyake, 2004; Juvina & Taatgen, 2009; Yiend, 2010). Cognitive control occurs by means of dynamic processes called executive functions (EFs), which allow the regulation of our behaviour in line with changes in the environment and rely on a number of prefrontal brain regions (Miyake et al., 2000; Suchy, 2009). A crucial factor supporting these functions is working memory, which is a limitedcapacity system that actively holds information in mind. Because of its limited capacity, it is important that selective attention mechanisms are constantly maintaining attentional focus towards relevant stimuli (target selection), while inhibiting competing irrelevant information (distracter inhibition; Hasher, Zacks, & Rahhal, 1999; Joormann & Gotlib, 2010; Milham, Banich, & Barad, 2003). Although several studies have widely examined the impact of emotional distracters on cognitive tasks (Kanske & Kotz, 2011; Kellermann et al., 2012; Okon-Singer, Tzelgov, & Henik, 2007; Padmala, Bauer, & Pessoa, 2011; Van Dillen, Heslenfeld, & Koole, 2009), it has been argued that emotional and cognitive processes are strongly interrelated in the brain, so that strictly examining the influence of emotional cues on cognition might be insufficient (Pessoa, 2008; Pessoa, Padmala, Kenzer, & Bauer, 2012). Recently, only a few studies have begun to focus on the executive control of emotional distracters (Kalanthroff, Cohen, & Henik, 2013). For example, Etkin, Egner, Peraza, Kandel, & Hirsch (2006) presented emotional distracters simultaneously with emotional targets in a Stroop-like task in order to

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investigate the effects of conflict due to different emotional valence within trials. Reaction times (RTs) for incongruent distracter–target pairs (e.g., positive target with negative distracter) were slower than RTs for congruent distracter–target pairs (e.g., positive target with positive distracter). Their results showed that the emotional distraction effects caused by incongruent trials were attenuated during the course of the task. This conflict adaptation effect was linked to a heightened prefrontal activation, which in turn diminished the involvement of the amygdala (Etkin et al., 2006). The authors concluded that this observed neural pattern was due to inhibitory connections from prefrontal regions to subcortical emotional regions such as amygdala, triggered by conflict monitoring and executive processes (e.g., Etkin, Prater, Hoeft, Menon, & Schatzberg, 2010). One important component of executive control is inhibition, which might form the ability to ignore goal-irrelevant information (Verbruggen, Liefooghe, & Vandierendonck, 2004). In a study on the interactions between inhibition control and emotional distraction, Kalanthroff et al. (2013) found that following negative stimuli, inhibitory performance was impaired. Yet, once inhibitory control was active, it decreased interference of negative affective distracters, delineating a regulation effect of inhibitory brain networks on emotional systems, similar to Etkin et al. (2006, 2010). These findings show once more that cognition and emotion are highly interdependent. Unfortunately, this study did not examine the interaction between inhibitory control and positive affective distracters. Another method for investigating the inhibition of irrelevant distracters is the “ignored repetition” version of the classical priming task, namely the RT delays when the target is related to a previously ignored distracter, known as the negative priming (NP) effect. The NP task is an evaluation task, in which two consecutive pairs of trials (prime and probe trials) are presented. In each trial, participants are asked to react to a target cue by simultaneously ignoring a distracter cue. The NP effect comprises the slowing in RT when the distracter in the prime trial is repeated as target in the probe trial. This effect has been observed in

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several investigations with various types of stimuli (Buchner & Mayr, 2004; Chao & Yeh, 2005; Chawarski & Sternberg, 1993; Daurignac, Houde, & Jouvent, 2006; Fox, 1994). Here, in contrast to Stroop-like cognitive tasks, performance was not analysed by the congruency of distracter–target pairs within trials, but as a function of the congruency between the distracter in the prime trial and the target in the probe trial (Tipper, 1985). For instance, the NP effect has been argued to imply lingered distracter inhibition processes triggered on the prime trial, which then, have to be overcome in the subsequent probe trial (May, Kane, & Hasher, 1995). In other words, Stroop task examines inhibition within trials, whereas NP effects examine lasting inhibition processes in the following probe trial, which strengthens the ecological validity, because we commonly have to inhibit distracters in longer time periods every day. Therefore, the aim of the present study was to investigate the neural correlates of ignoring positive and negative distracters and examine whether there are valence-dependent top–down control mechanisms using the NP task with affective stimuli, which is known as the negative affective priming (NAP) task. The NAP paradigm is an experimental design that has been mainly applied in the context of affective inhibition performance of dysphoric and depressive patients (Eugène, Joormann, Cooney, Atlas, Gotlib, 2010; Joormann, 2004; Leung, Lee, Yip, Li, & Wong, 2009; Wentura, 1999). In each trial, the valence of an affective target word has to be evaluated, whereas a distracter word has to be ignored. The NAP task includes two conditions: a control condition with a neutral distracter in the prime trial (Joormann & Gotlib, 2010) and an NAP condition, which presents valence-related prime distracters and probe targets (e.g., positive distracter in the prime trial, followed by positive target in the probe trial). The NAP effect arises when participants show delayed RT evaluating a probe target that shares the same emotional valence as the distracter in the preceding prime trial, compared to the control probes, where the target is unrelated to the previous prime distracter (Frings, Wentura, & Holtz, 2007; Wentura,

1999). Conversely, if this effect is not shown, it is assumed that prime distracter stimuli could not be inhibited, which is considered in the literature as an attentional bias (e.g., Joormann, 2004). To date, there are only two functional magnetic resonance imaging (fMRI) studies, which have examined neural correlates of the NAP task (Eugène et al., 2010; Leung et al., 2008). In the study by Leung et al. (2008), the NAP effect showed that participants could not ignore the negative distracters successfully, as a significant acceleration of the RT was found. These findings supported the assumption of an attention bias for negative stimuli. This diminished NAP effect for negative distracters was associated with increased activation in the anterior cingulate cortex (ACC) and insula, activations that have been related to the inhibition and response conflict (Braver, Barch, Gray, Molfese, & Snyder, 2001). The failed inhibition effect for negative relative to neutral words was associated with increased activation in the ventrolateral and medial prefrontal cortices, which have been related to detection and evaluation of salient cues (Corbetta & Shulman, 2002; Nakamura et al., 1999). However, the sample size in this study was rather small (n = 8), and NAP effects with positive stimuli were not examined. On the other hand, Eugène et al. (2010) examined the neural correlates of the NAP effect using words with negative and positive valence in depressive and healthy individuals. Although not explicitly mentioned, the NAP effect, i.e., delayed responses to probe targets, was non-significant for negative and positive probe targets in the control group. In healthy participants, the processing of positive distracters, but not negative distracters was associated with increased activation in the rostral ACC, whereas depressed participants showed increased activation in the rostral ACC to negative words (Eugène et al., 2010). Given that the activation of this region was found during conflict triggered when the emotional material has to be ignored (Brassen, Gamer, & Buchel, 2011; Etkin et al., 2006; Haas, Omura, Constable, & Canli, 2006), these findings are in accordance with the attention bias for positive stimuli in healthy persons. One main COGNITION AND EMOTION, 2015

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problem of the latter study is, however, that the control condition contained affective words also. Thus, there was a confounder of the NAP effect with prime distracter valence (e.g., Frings et al., 2007; Joormann, 2004). Thereby, it remains unclear whether the NAP effect is dependent on the valence of the distracter in the control trials. Considering inhibition of negative distracters, findings of experimental studies have been heterogeneous regarding whether healthy participants show an NAP effect. For instance, Gotlib et al. (2005) compared non-dysphoric with dysphoric individuals and found a reduced NAP effect for previously presented negative distracters among non-dysphoric individuals, whereas Joormann (2004) reported a successful inhibition of negative distracters within the non-dysphoric group in relation to dysphoric individuals (Gotlib et al., 2005; Joormann, 2004). The results of Leung et al. (2009) supported the results of Gotlib et al. (2005) by showing that both healthy controls and depressive individuals had difficulties inhibiting negative distracters demonstrated by a reduced NAP effect in both groups (Leung et al., 2009). According to these findings, it seems that for healthy individuals, negative stimuli might be strongly attention grabbing and therefore not easily inhibited. Yet, given that positive or negative distracters in the prime trials can eventually lead to a prolonged RT due to the incongruence to the simultaneously presented emotional target words, as in the case of Stroop-like emotional conflict task (de Fockert, Mizon, & D'Ubaldo, 2010; Etkin et al., 2006), we consider that the RT in the prime trial are also an important information source for the analysis of inhibition performance. Surprisingly, none of the previous studies examining behavioural NAP processing have examined the interference effects of the prime trial distracter, but focused solely on the probe RTs (Eugène et al., 2010; Goeleven, De Raedt, Baert, & Koster, 2006; Goeleven, De Raedt, & Koster, 2007; Joormann & Gotlib, 2010). According to de Fockert et al. (2010), who examined the NP effect with neutral stimuli, the amount of distracter interference is crucial for the interpretation of

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NP, considering that the NP effect depends on the efficiency of distracter rejection (de Fockert et al., 2010). Therefore, we aimed at calculating one more performance score in order to examine the impact of presenting affective distracters previous to a valence-related probe target. The scores were created in accordance to the relative ratios presented by Delaloye and colleagues (de Frias, Dixon, & Strauss, 2006; Delaloye et al., 2009), in order to control for possible overall speed differences between participants: [(Probe Trial (positive/ negative target) – Prime trial (positive/negative target)]/Prime Trial (positive/negative target). Thus, we put probe trials of positive and negative targets (which are presented after a congruently valenced distracter) in relation to identical trials without the previous prime of congruent distracters. By the use of these scores, our goal was to analyse the interference of previously presented affective distracters, which are congruent to the probe target. Note that trials in one score have to show the identical constellation of target–distracter pairs in one trial (e.g., negative target with positive distracter, or positive distracter with negative target). If the resulting scores are bigger than 0, then we assume a higher interference of previous presentation of congruent distracters on the probe. Conversely, if these scores are smaller than 0, then RT by evaluating the targets of identical trials without the previous presentation of valencerelated distracters were in average higher than the RT of the trials with previous presentation of a valence-related distracter, which means that the previous presentation of valence-related distracters had less load on the probe, i.e., there was an attenuated prime interference. Due to the lack of functional imaging investigations of NAP processing and inconsistent findings of valence-dependent inhibition mechanisms, the goal of the present study was to explore the NAP paradigm by investigating its neural correlates in an fMRI study. We followed the procedure of Joormann and Gotlib (2010) and included a category of emotionally neutral stimuli in addition to the two categories of affective stimuli. Furthermore, we calculated the interference indices using

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the aforementioned relative ratios of probe and prime trials besides the standard NAP scores. First, we expected an attenuated classical NAP effect (particularly) for negative affective distracters in relation to neutral distracters, as documented by Leung et al. (2008, 2009), Gotlib et al. (2005) and Eugène et al. (2010). Second, in an attempt to extend the methodology of previous NAP studies, we examined the interference of the previously presented distracters, as the amount of distracter rejection might influence the emergence of NAP (e.g., de Fockert et al., 2010). We hypothesised that negative distracters produce more prime interference than positive distracters (i.e., negative distracter ratio scores are bigger than 0), as negative information is usually more powerful and thoroughly processed than positive information (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Hajcak & Olvet, 2008; Ito, Larsen, Smith, & Cacioppo, 1998). This effect should be associated with prefrontal activation. Third, we assumed that a heightened prefrontal activation during the task would attenuate subcortical emotion-related regions such as amygdala or insula.

MATERIALS AND METHODS Participants The study sample originally consisted of 23 righthanded volunteers recruited from the Institute of Psychology at the University of Heidelberg and through advertisements posted in newspapers and locations within the community. Volunteers were paid for their participation. Exclusion criteria were any current Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) Axis I or Axis II disorder, history of head trauma, neurological diseases or contraindication to fMRI. The German version of the Structured Clinical Interview for DSM-IV Axis I disorders (SCID) I (Spitzer, Williams, Gibbon, & First, 1992) was used to assess psychiatric diagnosis. Axis II diagnoses were determined using the German version of the SCID II for DSM-IV Axis II disorders (Spitzer, Williams, Gibbon, & First, 1992). One participant could not complete SCID I or II, but was rated as

healthy by two independent clinicians. Handedness was assessed with the Edinburgh Handedness Inventory (Oldfield, 1971). Additionally, verbal IQ scores were measured using the German “Mehrfach-Wortschatz-Intelligenztest” (Lehrl, Triebig, & Fischer, 1995). Data of six participants were dismissed due to high error rates (>10%, n = 5) and personality disorder (n = 1). The final sample consisted of 17 subjects (13 females, mean age 27.00 ± 7.5). The mean crystalline verbal IQ score was 111. 94 (±13.85).

Experimental procedure Blood oxygenation level-dependent (BOLD) signal changes were measured while participants performed the NAP task in the scanner. Stimuli were delivered using Neurobehavioural Systems Presentation Software (www.neurobs.com). We used a modified version of the NAP task by Joormann (Joormann & Gotlib, 2010; Joormann, 2004). Two words were presented on the screen, one above the other; one was written in red letters and the other one in white letters (Figure 1). Participants were instructed to look only at the red target word, ignoring the white distracter word and to rate the valence of the target words (positive or negative). Participants were told to respond as fast and accurately as possible by pressing one of two keys. A typical trial started with a black screen for 1 s, followed by a fixation cross for 500 ms. Then a prime display appeared (Joormann & Gotlib, 2010), and the subject should press a key according to the estimated target valence. This response had to take place within 1000 ms after the stimulus. After the response, the prime display was replaced with the fixation cross for the rest of the 1000-ms interval, after which the next display (probe) was presented. The presentation of the probe display was again followed by a fixation cross. In line with previous studies on NAP (e.g., Joormann & Gotlib, 2010; Joormann, 2004), participants were not aware of the distinction between prime and probe trials while performing the task. In order to avoid position effects, the COGNITION AND EMOTION, 2015

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Figure 1. The NAP task (modified from Joormann, 2004).

spatial position of the target and distracter words (upper or lower position) was randomly assigned on each trial. In the NAP condition, the distracter word in the prime display and the target word in the probe display shared the same valence (either negative or positive), whereas in the control condition trials (CT) the distracter in the prime display was a neutral word (Table 1). Note, that the NAP effect

occurs when the previous to-be-ignored distracter in the prime leads to a slowing of the response on the to-be-attended probe target, given that both share the same valence, which had to be ignored in the previous prime trial (Wentura, 1999). After five practice trials, participants completed 208 trials, arranged in four conditions (NAP with positive words, NAP with negative words, CT with positive words, CT with negative words).

Table 1. Condition characteristics of prime and probe trials

Prime trial

NAP condition Positive target in probe trial Negative target in probe trial Control condition Positive target in probe trial Negative target in probe trial

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Probe trial

Distracter

Target

Distracter

Target

Positive Negative

Negative Positive

Negative Positive

Positive Negative

Neutral Neutral

Negative Positive

Negative Positive

Positive Negative

NEGATIVE AFFECTIVE PRIMING

Each condition consisted of 52 prime and probe trials. The sequence of trials was randomised for each participant.

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Stimulus material The stimulus set (adjectives or nouns) was selected from the Berlin Affective Word List Reloaded (Vo et al., 2009). Here, a rating list of word stimuli for arousal and valence is presented. Valence was rated using a 7-point scale ranging from −3 (very negative) to +3 (very positive). Arousal is rated on a 5-point scale ranging from 1 (low arousal) to 5 (high arousal). Words with a valence rating of less than −1 are classified as “negative”, words ranging from −1 to 1 are classified as “neutral” and words ranging from more than 1 to 3 are classified as “positive”. The final stimulus set consisted of 182 affective negative words (valence: −1.83, standard deviation [SD] = 0.44; arousal: 3.69, SD = 0.5), 182 affective positive words (valence: 1.78, SD = 0.37; arousal: 2.54, SD = 0.66) and 52 neutral words (valence: M = 0.12, SD = 0.3; arousal: M = 2.33, SD = 0.53). The word length of each word category (negative, positive, neutral), word frequency, valence and imaginability were matched between conditions. Positive and negative words differed significantly in arousal ratings within conditions (p < .001). That is, negative words were rated as more arousing than the positive words in both priming and control conditions. Taking only affective words in the analysis, arousal ratings of the NAP (n = 208) and control conditions (n = 156; NAP arousal: 3.26, SD = 0.86; CT arousal: 2.92, SD = 0.74) also differed significantly from each other (p < .001). Ratings of emotional valence (p = .83), world length (p = .65) and imaginability (p = .73) were not significantly different between conditions.

Statistical analysis of valence-dependent NAP effects According to previous NAP studies (Goeleven et al., 2007; Joormann, 2010), we used the difference between the RT to the correctly answered probe trials of NAP and control conditions (RT NAP probe – RT CT probe), for positive and negative valence, respectively. A positive value

means that the response in the NAP probe trials is delayed (NAP effect). By contrast, a negative value reflects an attenuation of the NAP effect. These values were included as dependent variables in repeated-measures analysis of variance (ANOVA) with the within-factor of valence (positive, negative) as independent variables.

Statistical analysis of interference indices for positive and negative distracters To analyse whether NAP probe responses require a heightened inhibition effort compared to prime responses, we created an interference index score based on a previous study by Delaloye et al. (2009). The index is a difference between RT to NAP probes and NAP primes of the same valence, divided by the RT to NAP prime. The index is calculated separately for negative and positive targets, i.e., [(RT NAP probe negative target – RT NAP prime negative target)/RT NAP prime negative target], in the priming conditions only. This index was used to control for possible overall speed differences between participants (de Frias et al., 2006; Delaloye et al., 2009). We further analysed interference index score differences by running repeated-measures ANOVA comparing the NAP positive versus NAP negative interference indices, i.e., the inhibition effort of priming negative or positive distracter words.

Image acquisition BOLD images were obtained on a 3-Tesla MRI scanner system (TRIO, Siemens Medical Systems, Erlangen, Germany) equipped with a 32-channel head coil. Changes in BOLD T2*-weighted MR signal were measured using a gradient echo-planar imaging sequence (repetition time [TR] = 2380 ms, echo time [TE] = 25 ms, field of view [FoV] = 210 mm, flip angle = 90°, 64 × 64 matrix, 40 slices covering the whole brain, slice thickness 3 mm, no gap, voxel size 3 × 3 × 3 mm). A T1-weighted anatomical image was additionally acquired for each subject to allow anatomical localisation (TR = 2300 ms, TE = 2.98 ms, 160 slices, voxel size 1.0 × 1.0 × 1.1 mm). COGNITION AND EMOTION, 2015

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Image processing and statistical analysis Image processing and statistical analysis were conducted with Statistical Parameter Mapping (Friston et al., 1994) version 8 (Wellcome Department of Cognitive Neurology, London UK; http://www.fil.ion.ucl.ac.uk/spm). Pre-processing included realignment, co-registration, segmentation and spatial normalisation (template of Montreal Neurological Institute, MNI). Then, a Gaussian filter of 8-mm full-width at halfmaximum was applied to smooth the data spatially. Due to the short inter-trial intervals, the NAP task was closer to a block design than to an eventrelated design. However, for the statistical analysis of regional differences in brain activation, individual onsets of priming and control trials for positive and negative words (mean time frame = 3.66 ± 0.45; range = 3–4.51) were put into the event-related general linear model design at the subject level (Josephs & Henson, 1999). Contrasts between different conditions (NAP Positive [PP] vs. Control Positive [CP], and NAP Negative [PN] vs. Control Negative [CN]) were computed for each subject. In the second-level analysis, onesample t-tests for the contrasts for each condition were used to obtain activation patterns for each condition. In the next step, we ran paired t-test with the same contrasts (see above) as paired variable, which were entered for each subject, to compare the activation during priming trials with positive and negative words compared to the equivalent control conditions (positive vs. neutral, negative vs. neutral). The probability threshold of the whole-brain analyses was set at p < .001 uncorrected. The minimum cluster extent (K) was set at 10 contiguous voxels. For a priori defined regions, which are implicated in NP, the

dorsolateral prefrotal cortex, inferior frontal cortex, parietal cortex (Egner & Hirsch, 2005; Ungar, Nestor, Niznikiewicz, Wible, & Kubicki, 2010), a small volume correction was used with p < .05 (family-wise-error-corrected). The regions were derived from the anatomical labelling atlas (aal) toolbox from the PickAtlas. Using the publically available SPM8 tool MarsBar (http://marsbar. sourceforge.net/), we built post hoc region-ofinterests (ROI) of activated regions in prefrontal cortex (PFC), and then extracted the mean peak values of every ROI. Afterwards, we correlated the extracted data with inhibition effort and NAP scores, in order to investigate potential relationships.

RESULTS Behavioural data The mean RT and SD of each condition are presented in Table 2. Following standard procedures, outlying RT scores below 500 and above 3000 ms were eliminated from the analyses (0.62% of the data), and only correct responses (94.6% of all trials) were analysed. The Kolmogorov–Smirnov test was used for testing the distribution of raw data. Because the test was not significant for any variable (all p > .1), normal distribution was assumed.

Negative affective priming effect The average RT for each probe condition is presented in Figure 2. A repeated-measures ANOVA of NAP difference scores showed a main effect of valence [F(1,16) = 9.02, p = .008], which indicated that the probe RT was significantly accelerated for negative probe targets [F(1,16) = 5.24, p = .036], reflecting an attenuation of the

Table 2. Mean RTs of each condition in ms (N = 17)

Positive target in probe trials (PP and CP)

NAP trials Control trials

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Negative target in probe trials (PN and CN)

Prime

Probe

Prime

Probe

1004.69 ± 204.89 1157.52 ± 292.13

1002.63 ± 219.98 1001.84 ± 224.63

1016.49 ± 221.15 1100.34 ± 241.65

1052.54 ± 234.65 1095.69 ± 248.59

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valence [F(1,16) = 5.46, p = .033], revealing a significantly higher impact of negative NAP prime trials compared to positive NAP prime trials. This might reflect a stronger interference of the negative distracter words compared to the positive distracter words in the prime (Figure 3).

Imaging results

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Figure 2. Average RT to probe trials in each condition. *p < .05.

NAP effect for the negative distracter words. There was no significant difference for the probe RTs of the positive target probes (p = .96).

Interference indices The statistical analysis of the prime trial interference index showed a significant main effect of

Brain regions demonstrating increased BOLD signal during the NAP task are summarised in Table 3. In the PP vs. CP condition, subjects showed enhanced activation in the right middle (BA19) and inferior (BA37) temporal gyrus, right middle cingulate gyrus (BA31), bilateral precuneus (BA7) and other regions of multisensory integration as the left superior occipital (BA31) and right superior parietal cortex (BA7). In contrast to this, a decrease of BOLD signal was observed in the left inferior frontal gyrus (BA9), the left insula (BA13) and medial regions of the left superior frontal gyrus (SFG; BA9).

Figure 3. NAP and CT indices computed by the ratio [(RT probe negative target – RT prime negative target)/RT prime negative target] for affectie and neutral prime distractors of both conditions. COGNITION AND EMOTION, 2015

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Table 3. Brain activation for each contrast

MNI coordinates One-sample t-tests PP > CP R middle temporal gyrus (BA19) R inferior temporal gyrus (BA37) R middle cingulate gyrus (BA31) L/R precuneus (BA7)

k

x

y

z

T

75

45 60 12 12 −12 12 −12 −21 18 −39 −33 −6 −15 −6

−52 −61 −37 −61 −64 −70 −67 −70 −70 17 23 29 32 20

−2 −5 43 31 34 34 25 25 52 25 −2 37 43 49

5.88* 3.88* 5.48 5.40* 4.92* 5.02* 4.90* 5.24* 4.16 −8.52* −6* −6.34* −5.33* −5.40*

60 57 48 −24 −9 6 −6 −27 −57 −51

−43 −46 −49 53 −61 −52 −37 20 17 26

13 28 31 −5 31 37 46 −5 4 −8

6.03* 5.14* 5.30* 4.90 5.35* 4.84* 5.20* −7.85* −5.07* −4.73*

−12 −27 51

35 20 −55

40 46 28

5.25 4.97 4.92*

42 77 74

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L/R cuneus (BA31) L superior occipital cortex (BA31) R superior parietal cortex (BA7) L inferior frontal gyrus (BA9) L insula (BA13) L SFG (BA9)

74 19 507 189

L supplementary motor area (BA8) PN > CN R superior temporal gyrus (BA40) R supramarginal gyrus (BA40) R angular gyrus L SFG (BA10) L/R precuneus (31) L middle cingulate gyrus (BA7) L insula (BA13) L inferior frontal gyrus (BA45)

284 20 160 139

Paired t-test (PN > CN) > (PP > CP) L SFG (BA8) L middle frontal gyrus (BA8) R angular gyrus (BA40)

37 17 45

Notes: Voxel threshold p < .001. Uncorrected, extend threshold. MNI = Montreal Neurological Institute; K = cluster size in voxel; BA = Brodmann area; L = Left; R = Right. *p < .05, FWE-corrected (ROI analysis).

In the PN vs. CN contrast, participants showed a significant BOLD signal increase in the right superior temporal (BA40), supramarginal (BA40) as well as in the angular gyrus, the orbital part of left SFG (BA10), bilateral precuneus (BA31), and the left middle cingulate gyrus (BA7). Meanwhile, a decrease of BOLD activity was found in the left insula (BA13) and the left inferior frontal gyrus (BA45) (Figure 4).

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Comparison between negative and positive trials Comparison between PN > CN and PP > CP revealed a stronger activation in the left (dorsolateral) superior and middle frontal gyrus (BA8), as well as in the right angular gyrus (BA40) for negative versus positive NAP trials (Figure 5).

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Figure 4. Neural correlates of ignoring (a) positive (positive target in probe trials) and (b) negative stimuli (negative target in probe trials) related to inhibition of neutral stimuli (control conditions). The colour bar indicates t-values. The display threshold is p < .001 (FWE-uncorrected).

Figure 5. Comparisons during negative target in probe trials related to positive target in probe trials (PN > CN) > (PP > CP) presented at p < .001 level, FWE-uncorrected. L = left; R = right. COGNITION AND EMOTION, 2015

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Correlations between mean peak values and behavioural data In order to minimise the effect of extreme scores in the activation data, we calculated Spearman correlation coefficients. Results showed that bilateral SFG activation correlated significantly with interference scores of negative NAP conditions, rs = .59, p = .01 (Figure 6). However, the interference scores did not significantly predict bilateral SFG activation β = 0.36, R2 = 0.13, p = .16. In addition, the activation of left insula correlated positively with the amount of interference, rs = .57, p = .02, as well as with the bilateral SFG activation, rs = .54, p = .03. A linear regression showed that interference scores significantly predicted the amount of activation in the left insula, β = 0.51, R2 = 0.26, p = .04.

DISCUSSION The present study aimed at exploring behavioural data and neural activations related to NAP effects and valence-dependent prime interference mechanisms in healthy subjects. In summary, our results show an inverse NAP effect for negative distracter words, which means that these distracters were poorly ignored and therefore produced a

Figure 6. Scatter-plot displaying the correlation of bilateral SFG activation (mean peak values) and interference scores of negative NAP conditions.

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facilitation effect for the evaluation of subsequent probe targets. A higher interference effect of previously presented prime trials in the negative distracter condition (PN) supported this finding, reflected by the delayed interference indices for probes after presenting negative distracter primes. In addition, regions in the left SFG were activated during the PN conditions compared to the CT conditions, whereas a deactivation of the same regions were found in the PP conditions compared to the CT conditions with neutral distracters. The inversed NAP effect for negative distracter words, reflected in an accelerated RT to the probe condition compared to neutral distracter words, demonstrates that the compromised rejection of negative affective distracter words in the prime lead to a facilitation effect (inversed NAP effect) when identifying negative affective targets in the probe. No significant difference was found for positive compared to neutral distracters. The accelerated response times to negative probe targets did not confirm the NAP effect with emotionally negative stimuli and thus contradicts the results of Joormann (2004, 2010). However, the findings agree with other NAP studies, which did not find an NAP effect with negative stimulus material in healthy individuals as well (Dai & Feng, 2011; Goeleven et al., 2006; Leung et al., 2009). The absence of inhibition of negative affective distracters supports the assumption of an automatic attention bias for negative cues in healthy subjects (Pratto & John, 1991). In the positive distracter NAP condition, no significant facilitation effect was observed. Furthermore, previously presented negative prime distracters produced more interference than the previous presentation of positive distracter words as shown by the interference indices. That is, negative distracters in the previous prime trial occasioned a delay on the consequently shown trials and therefore were poorly ignored compared to the positive distracters. This assumption is supported by several behavioural studies demonstrating that negative information is more salient than positive or neutral information (Baumeister et al., 2001; Compton et al., 2003). Moreover, the current findings support a recent study demonstrating that

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the attentional capture of negative words occurs quicker than the attentional capture of neutral or positive words (Sutton & Altarriba, 2011), being in line with the “automatic vigilance hypothesis”, which assumes that negative stimuli can impact and moderate attention (Pratto & John, 1991).

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Neural correlates of top–down control ignoring negative distracter stimuli Moreover, the fMRI data corroborated the behavioural findings suggesting that the processing of negative affective distracters elicited increased activation in orbital regions of the left SFG (BA10), the right parietal cortex, the right superior temporal gyrus and the bilateral precuneus. However, positive distracter condition elicited BOLD activation in parietal, temporal and occipital regions, but a deactivation of frontal, cognitive regions. Both conditions showed deactivation of left insula and inferior frontal gyrus, while solely the positive condition showed a deactivation of left SFG. These results lead to the assumption that ignoring negative distracters produced more prefrontal activation, followed by the neutral distracters, which in turn incited more prefrontal activation than the positive distracters. The enhanced activity in the left SFG during the processing of negative distracters compared to neutral distracters might represent the involvement of stronger valuation processes (Cunningham, Kesek, & Mowrer, 2009; Walton, Behrens, Noonan, & Rushworth, 2011), while the right temporoparietal junction (TPJ) activation is especially important for orienting towards sensory relevant stimuli (Corbetta, Kincade, & Shulman, 2002; Corbetta & Shulman, 2002). Furthermore, our findings show a deactivation of prefrontal cortex areas while ignoring positive distracters, whereas during the presentation of negative distracters, a heightened prefrontal activation is observed. That is, the enhanced prefrontal activation might reflect the behaviourally observed interference of negative distracters. We further found a heightened orbital SFG processing by attempting to ignore negative distracter words, as well as attenuated insula activation. However,

during the presentation of positive distracter words, a deactivation of the insula and medial SFG was observed. On the other hand, our findings demonstrate a positive relationship between the activation of prefrontal areas and insula, which might contradict the findings of Van Dillen et al. (2009) by demonstrating that prefrontal areas “turned off” emotional brain areas after inducing negative affective states (Van Dillen et al., 2009). The right TPJ (BA40), which might be related to reorienting of attention to survival-related cues (Chang et al., 2013; Corbetta & Shulman, 2002; Krall et al., 2014), was involved in the processing of negative affective distracter primes compared to control conditions. In addition, several studies demonstrated the existence of both structural and functional connectivity between prefrontal and parietal cortex (e.g., Cabeza et al., 1997; Cavada & Goldman-Rakic, 1989; Mitchell et al., 2008; Morecraft, Geula, & Mesulam, 1993), suggesting a possible interdependence of these regions in implementing an attentional set. The right precuneus, however, responded to both affective distracter conditions compared to control conditions (Table 3). Interestingly, this region has been associated with self-referential thought, mental imagery, episodic memory retrieval and other higher order cognitive functions also related to emotional processing (Barrett, Mesquita, Ochsner, & Gross, 2007; Cavanna & Trimble, 2006). Therefore, we assume that affective words must have caused more imagery than neutral words. Moreover, we found the involvement of middle cingulate gyrus in both affective distracter conditions, a highly connected area of emotional processing integration, which has been related to emotional processing and moral judgement in previous studies (Hartwell et al., 2011; Hayashi et al., 2014; Lu et al., 2013). Additionally, the activation of the insula was surprisingly attenuated not only on the negative distracter condition but also in the positive distracter condition compared to the control condition. This finding contradicts our expectations, as there was no heightened prefrontal activation in the PP > CT condition, so that the prefrontal COGNITION AND EMOTION, 2015

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activation could not have attenuated the activation of the insula. Furthermore, insula involvement correlated positively with the interference score of negative distracter primes, i.e., the more interference, the more insula activation. Similarly, Levens and Phelps (2010) accounted that the left insula is involved in interference resolution of affective stimuli (Levens & Phelps, 2010). However, regions in the left insula were deactivated during positive and negative distracter conditions. This pattern indicates either that the interference level of negative distracters was probably not high enough to involve insula activation ( neutral > positive), demonstrating that ignoring negative distracters requires more cognitive control resources than processing neutral or positive distracters. The insula might have been involved in interference resolution of negative distracter words. Acknowledgements We thank all the subjects who participated in this present research. We also thank Dirk Wentura, Adelheid Fuxa and Moritz Riese for their assistance with several aspects of this study.

Disclosure statement No potential conflict of interest was reported by the authors.

REFERENCES Barnow, S., Aldinger, M., Ulrich, I., & Stopsack, M. (2013). Emotionsregulation bei Depression Ein multimethodaler Überblick [Emotion regulation in depression: An overview of results using various methods]. Psychologische Rundschau, 64, 235–243. doi:10.1026/0033-3042/A000172 Barrett, L. F., Mesquita, B., Ochsner, K. N., & Gross, J. J. (2007). The experience of emotion. Annual Review of Psychology, 58, 373–403. doi:10.1146/ annurev.psych.58.110405.085709 Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology, 5, 323–370. doi:10. 1037/1089-2680.5.4.323 Becker, M. W., & Leinenger, M. (2011). Attentional selection is biased toward mood-congruent stimuli. Emotion, 11, 1248–1254. doi:10.1037/A0023524 Biss, R. K., & Hasher, L. (2011). Delighted and distracted: Positive affect increases priming for irrelevant information. Emotion, 11, 1474–1478. doi:10. 1037/a0023855

COGNITION AND EMOTION, 2015

15

Downloaded by [Gazi University] at 18:35 25 October 2015

FALQUEZ ET AL.

Bradley, M. M. (2009). Natural selective attention: Orienting and emotion. Psychophysiology, 46(1), 1–11. doi:10.1111/j.1469-8986.2008.00702.x Brassen, S., Gamer, M., & Büchel, C. (2011). Anterior cingulate activation is related to a positivity bias and emotional stability in successful aging. Biological Psychiatry, 70(2), 131–137. doi: 10.1016/j.biopsych. 2010.10.013 Braver, T. S., Barch, D. M., Gray, J. R., Molfese, D. L., & Snyder, A. (2001). Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cerebral Cortex, 11, 825–836. doi:10.1093/ cercor/11.9.825 Broadbent, D. E., & Gregory, M. (1967). Perception of emotionally toned words. Nature, 215, 581–584. doi:10.1038/215581a0 Buchner, A., & Mayr, S. (2004). Auditory negative priming in younger and older adults. The Quarterly Journal of Experimental Psychology, 57, 769–787. doi:10.1080/02724980343000431 Bunge, S. A., Ochsner, K. N., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (2001). Prefrontal regions involved in keeping information in and out of mind. Brain, 124, 2074–2086. doi:10.1093/brain/124. 10.2074 Cabeza, R., Mangels, J., Nyberg, L., Habib, R., Houle, S., McIntosh, A. R., & Tulving, E. (1997). Brain regions differentially involved in remembering what and when: a PET study. Neuron, 19, 863–870. doi:10.1016/S0896-6273(00)80967-8 Cavada, C., & Goldman-Rakic, P. S. (1989). Posterior parietal cortex in rhesus monkey: II. Evidence for segregated corticocortical networks linking sensory and limbic areas with the frontal lobe. Journal of Computational Neurology, 287, 422–445. doi:10. 1002/cne.902870403 Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: A review of its functional anatomy and behavioural correlates. Brain, 129, 564–583. doi:10. 1093/brain/awl004 Chang, C. F., Hsu, T. Y., Tseng, P., Liang, W. K., Tzeng, O. J., Hung, D. L., & Juan, C. H. (2013). Right temporoparietal junction and attentional reorienting. Human Brain Mapping, 34, 869–877. doi:10.1002/hbm.21476 Chao, H.-F., & Yeh, Y.-Y. (2005). Location negative priming in identity discrimination relies on location repetition. Perception and Psychophysics, 67, 789–801. doi:10.3758/BF03193533 Chawarski, M. C., & Sternberg, R. J. (1993). Negative priming in word recognition: A context effect.

16

COGNITION AND EMOTION, 2015

Journal of Experimental Psychology: General, 122, 195–206. doi:10.1037/0096-3445.122.2.195 Compton, R. J. (2003). The interface between emotion and attention: A review of evidence from psychology and neuroscience. Behavioral and Cognitive Neuroscience Reviews, 2(2), 115–129. doi:10.1177/1534 582303255278 Compton, R. J., Banich, M. T., Mohanty, A., Milham, M. P., Herrington, J., Miller, … Heller, W. (2003). Paying attention to emotion: An fMRI investigation of cognitive and emotional Stroop tasks. Cognitive, Affective, and Behavioral Neuroscience, 3(2), 81–96. doi:10.3758/CABN.3.2.81 Corbetta, M., Kincade, J. M., & Shulman, G. L. (2002). Neural systems for visual orienting and their relationships to spatial working memory. Journal of Cognitive Neuroscience, 14, 508–523. doi:10.1162/ 089892902317362029 Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. doi:10.1038/nrn755 Cunningham, W. A., Kesek, A., & Mowrer, S. M. (2009). Distinct orbitofrontal regions encode stimulus and choice valuation. Journal of Cognitive Neuroscience, 21, 1956–1966. doi:10.1162/jocn.2008. 21148 Cutini, S., Scatturin, P., Menon, E., Bisiacchi, P. S., Gamberini, L., Zorzi, M., & Dell'Acqua, R. (2008). Selective activation of the superior frontal gyrus in task-switching: An event-related fNIRS study. Neuroimage, 42, 945–955. doi:10.1016/j.neuroimage. 2008.05.013 Dai, Q., & Feng, Z. Z. (2011). Deficient interference inhibition for negative stimuli in depression: An event-related potential study. Clinical Neurophysiology, 122(1), 52–61. doi:10.1016/j.clinph.2010. 05.025 Daurignac, E., Houde, O., & Jouvent, R. (2006). Negative priming in a numerical Piaget-like task as evidenced by ERP. Journal of Cognitive Neuroscience, 18, 730–736. doi:10.1162/jocn.2006.18.5.730 de Fockert, J. W., Mizon, G. A., & D'Ubaldo, M. (2010). No negative priming without cognitive control. Journal of Experimental Psychology: Human Perception and Performance, 36, 1333–1341. doi:10. 1037/a0020404 de Frias, C. M., Dixon, R. A., & Strauss, E. (2006). Structure of four executive functioning tests in healthy older adults. Neuropsychology, 20, 206–214. doi:10.1037/0894-4105.20.2.206

Downloaded by [Gazi University] at 18:35 25 October 2015

NEGATIVE AFFECTIVE PRIMING

Delaloye, C., Moy, G., Baudois, S., De Bilbao, F., Dubois Remund, C., Hofer, F., … Giannakopoulos, P. (2009). The contribution of aging to the understanding of the dimensionality of executive functions. Archives of Gerontology and Geriatrics, 49(1), e51–e59. doi:10.1016/j.archger.2008.08.011 du Boisgueheneuc, F., Levy, R., Volle, E., Seassau, M., Duffau, H., Kinkingnehun, S.,... Dubois, B. (2006). Functions of the left superior frontal gyrus in humans: a lesion study. Brain, 129, 3315–3328. doi:10.1093/brain/awl244 Egner, T., & Hirsch, J. (2005). Where memory meets attention: Neural substrates of negative priming. Journal of Cognitive Neuroscience, 17, 1774–1784. doi:10.1162/089892905774589226 Etkin, A., Egner, T., Peraza, D. M., Kandel, E. R., & Hirsch, J. (2006). Resolving emotional conflict: A role for the rostral anterior cingulate cortex in modulating activity in the amygdala. Neuron, 51, 871–882. doi:10.1016/j.neuron.2006.07.029 Etkin, A., Prater, K. E., Hoeft, F., Menon, V., & Schatzberg, A. F. (2010). Failure of anterior cingulate activation and connectivity with the amygdala during implicit regulation of emotional processing in generalized anxiety disorder. American Journal of Psychiatry, 167, 545–554. doi:10.1176/appi.ajp.2009.09070931 Eugène, F., Joormann, J., Cooney, R. E., Atlas, L. Y., & Gotlib, I. H. (2010). Neural correlates of inhibitory deficits in depression. Psychiatry Research: Neuroimaging, 181(1), 30–35. doi:10.1016/j.pscy chresns.2009.07.010 Fales, C. L., Barch, D. M., Rundle, M. M., Mintun, M. A., Mathews, J., Snyder, A. Z., & Sheline, Y. I. (2009). Antidepressant treatment normalizes hypoactivity in dorsolateral prefrontal cortex during emotional interference processing in major depression. Journal of Affective Disorder, 112, 206–211. doi:10.1016/j.jad. 2008.04.027 Fales, C. L., Barch, D. M., Rundle, M. M., Mintun, M. A., Snyder, A. Z., Cohen, J. D., … Sheline, Y. I. (2008). Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biological Psychiatry, 63, 377–384. doi:10.1016/j.biopsych.2007.06.012 Fox, E. (1994). Interference and negative priming from ignored distractors: The role of selection difficulty. Perception and Psychophysics, 56, 565–574. doi:10. 3758/BF03206952 Friedman, N. P., & Miyake, A. (2004). The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental

Psychology: General, 133(1), 101–135. doi:10.1037/ 0096-3445.133.1.101 Frings, C., Wentura, D., & Holtz, M. (2007). Dysphorics cannot ignore unpleasant information. Cognition & Emotion, 21, 1525–1534. doi:10.1080/ 02699930601054042 Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J.-B., Frith, C. D., & Frackowiak, R. S. J. (1994). Statistical parametric maps in functional imaging: A general linear approach. Human Brain Mapping, 2, 189–210. doi:10.1002/hbm.460020402 Goeleven, E., De Raedt, R., Baert, S., & Koster, E. H. W. (2006). Deficient inhibition of emotional information in depression. Journal of Affective Disorders, 93(1–3), 149–157. doi:10.1016/j.jad.2006.03.007 Goeleven, E., De Raedt, R., & Koster, E. H. W. (2007). The influence of induced mood on the inhibition of emotional information. Motivation and Emotion, 31, 208–218. doi:10.1007/s11031-0079064-y Gotlib, I. H., Yue, D. N., & Joormann, J. (2005). Selective attention in dysphoric individuals: The role of affective interference and inhibition. Cognitive Therapy and Research, 29, 417–432. doi:10.1007/ s10608-005-5753-6 Grimshaw, G. M., & Carmel, D. (2014). An asymmetric inhibition model of hemispheric differences in emotional processing. Frontiers in Psychology, 5, 489. doi:10.3389/fpsyg.2014.00489 Haas, B. W., Omura, K., Constable, R. T., & Canli, T. (2006). Interference produced by emotional conflict associated with anterior cingulate activation. Cognitive, Affective, and Behavioral Neuroscience, 6, 152– 156. doi:10.3758/CABN.6.2.152 Hajcak, G., & Olvet, D. M. (2008). The persistence of attention to emotion: Brain potentials during and after picture presentation. Emotion, 8, 250–255. doi:10.1037/1528-3542.8.2.250 Hartwell, K. J., Johnson, K. A., Li, X. B., Myrick, H., LeMatty, T., George, M. S., & Brady, K. T. (2011). Neural correlates of craving and resisting craving for tobacco in nicotine dependent smokers. Addiction Biology, 16, 654–666. doi:10.1111/j.13691600.2011.00340.x Hasher, L., Zacks, R. T., & Rahhal, T. A. (1999). Timing, instructions, and inhibitory control: Some missing factors in the age and memory debate. Gerontology, 45, 355–357. doi:10.1159/000022121 Hayashi, A., Abe, N., Fujii, T., Ito, A., Ueno, A., Koseki, Y., … Mori, E. (2014). Dissociable neural systems for moral judgment of anti- and pro-social COGNITION AND EMOTION, 2015

17

Downloaded by [Gazi University] at 18:35 25 October 2015

FALQUEZ ET AL.

lying. Brain Research, 1556, 46–56. doi:10.1016/j. brainres.2014.02.011 Herrington, J. D., Heller, W., Mohanty, A., Engels, A. S., Banich, M. T., Webb, A. G., & Miller, G. A. (2010). Localization of asymmetric brain function in emotion and depression. Psychophysiology, 47, 442– 454. doi:10.1111/j.1469-8986.2009.00958.x Ito, T. A., Larsen, J. T., Smith, N. K., & Cacioppo, J. T. (1998). Negative information weighs more heavily on the brain: The negativity bias in evaluative categorizations. Journal of Personality and Social Psychology, 75, 887–900. doi:10.1037/0022-3514.75.4.887 Joormann, J. (2004). Attentional bias in dysphoria: The role of inhibitory processes. Cognition & Emotion, 18(1), 125–147. doi:10.1080/02699930244000480 Joormann, J. (2010). Cognitive inhibition and emotion regulation in depression. Current Directions in Psychological Science, 19, 161–166. doi:10.1177/0963721 410370293 Joormann, J., & Gotlib, I. H. (2010). Emotion regulation in depression: relation to cognitive inhibition. Cognition & Emotion, 24(2), 281–298. doi:10.1080/ 02699930903407948 Josephs, O., & Henson, R. N. (1999). Event-related functional magnetic resonance imaging: Modelling, inference and optimization. Philosophical Transactions of the Royal Society of London: Part B Biological Sciences, 354, 1215–1228. doi:10.1098/rstb.1999.0475 Juvina, I., & Taatgen, N. A. (2009). A repetitionsuppression account of between-trial effects in a modified Stroop paradigm. Acta Psychologica (Amsterdam), 131(1), 72–84. doi:10.1016/j.actpsy.2009. 03.002 Kalanthroff, E., Cohen, N., & Henik, A. (2013). Stop feeling: Inhibition of emotional interference following stop-signal trials. Frontiers in Human Neuroscience, 7, 78. doi:10.3389/fnhum.2013.00078 Kanske, P., & Kotz, S. A. (2011). Conflict processing is modulated by positive emotion: ERP data from a flanker task. Behavioural Brain Research, 219, 382– 386. doi:10.1016/j.bbr.2011.01.043 Kellermann, T. S., Sternkopf, M. A., Schneider, F., Habel, U., Turetsky, B. I., Zilles, K., & Eickhoff, S. B. (2012). Modulating the processing of emotional stimuli by cognitive demand. Social Cognitive and Affective Neuroscience, 7, 263–273. doi:10.1093/scan/ nsq104 Klauer, K. C., Mierke, J., & Musch, J. (2003). The positivity proportion effect: A list context effect in masked affective priming. Memory & Cognition, 31, 953–967. doi:10.3758/BF03196448

18

COGNITION AND EMOTION, 2015

Koole, S. L. (2009). The psychology of emotion regulation: An integrative review. Cognition & Emotion, 23(1), 4–41. doi:10.1080/02699930802619031 Krall, S. C., Rottschy, C., Oberwelland, E., Bzdok, D., Fox, P. T., Eickhoff, S. B., … Konrad, K. (2014). The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis. Brain Structure & Function, 1–18. doi:10.1007/s00429-014-0803-z Lehrl, S., Triebig, G., & Fischer, B. (1995). Multiple choice vocabulary test MWT as a valid and short test to estimate premorbid intelligence. Acta Neurologica Scandinavica, 91, 335–345. doi:10.1111/j.16000404.1995.tb07018.x Leung, K.-K., Lee, T. M. C., Xiao, Z., Wang, Z., Zhang, J. X. X., Yip, P. S. F., & Li, L. S. W. (2008). Neural activities for negative priming with affective stimuli: An fMRI study. Neuroscience Letters, 433, 194–198. doi:10.1016/j.neulet.2008.01.011 Leung, K.-K., Lee, T. M. C., Yip, P., Li, L. S. W., & Wong, M. M. C. (2009). Selective attention biases of people with depression: Positive and negative priming of depression-related information. Psychiatry Research, 165, 241–251. doi:10.1016/j.psychres.2007. 10.022 Levens, S. M., & Phelps, E. A. (2010). Insula and orbital frontal cortex activity underlying emotion interference resolution in working memory. Journal of Cognitive Neuroscience, 22, 2790–2803. doi:10. 1162/jocn.2010.21428 Lu, S. J., Gao, W. J., Wei, Z. G., Wu, W. W., Liao, M., Ding, Y. Q., … Li, L. J. (2013). Reduced cingulate gyrus volume associated with enhanced cortisol awakening response in young healthy adults reporting childhood trauma. PLoS One, 8(7). doi:10.1371/journal.pone.0069350 May, C. P., Kane, M. J., & Hasher, L. (1995). Determinants of negative priming. Psychological Bulletin, 118(1), 35–54. doi:10.1037/0033-2909.118.1.35 Milham, M. P., Banich, M. T., & Barad, V. (2003). Competition for priority in processing increases prefrontal cortex’s involvement in top-down control: An event-related fMRI study of the Stroop task. Brain Research and Cognitive Brain Research, 17, 212–222. doi:10.1016/S0926-6410(03)00108-3 Mitchell, D. G. V., Luo, Q., Mondillo, K., Vythilingam, M., Finger, E. C., & Blair, R. J. R. (2008). The interference of operant task performance by emotional distracters: An antagonistic relationship between the amygdala and frontoparietal cortices. Neuroimage, 40, 859–868. doi:10.1016/j.neuroimage.2007.08.002

Downloaded by [Gazi University] at 18:35 25 October 2015

NEGATIVE AFFECTIVE PRIMING

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “Frontal Lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100. doi:10.1006/cogp.1999.0734 Morecraft, R. J., Geula, C., & Mesulam, M.-M. (1993). Architecture of connectivity within a cingulo-fronto-parietal neurocognitive network for directed attention. Archives of Neurology, 50, 279– 284. doi:10.1001/archneur.1993.00540030045013 Nakamura, K., Kawashima, R., Ito, K., Sugiura, M., Kato, T., Nakamura, A., … Kojima, S. (1999). Activation of the right inferior frontal cortex during assessment of facial emotion. Journal of Neurophysiology, 82, 1610–1614. Ohman, A. (2007). Has evolution primed humans to “beware the beast”? Proceedings of the National Academy of Sciences USA, 104, 16396–16397. doi:10.1073/pnas.0707885104 Okon-Singer, H., Tzelgov, J., & Henik, A. (2007). Distinguishing between automaticity and attention in the processing of emotionally significant stimuli. Emotion, 7(1), 147–157. doi:10.1037/1528-3542.7. 1.147 Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97–113. doi:10.1016/0028-3932(71)90067-4 Padmala, S., Bauer, A., & Pessoa, L. (2011). Negative emotion impairs conflict-driven executive control. Frontiers in Psychology, 2, 192. doi:10.3389/fpsyg. 2011.00192 Pessoa, L. (2008). On the relationship between emotion and cognition. Nature Reviews in Neuroscience, 9(2), 148–158. doi:10.1038/nrn2317 Pessoa, L., Padmala, S., Kenzer, A., & Bauer, A. (2012). Interactions between cognition and emotion during response inhibition. Emotion, 12, 192–197. doi:10.1037/A0024109 Pratto, F., & John, O. P. (1991). Automatic vigilance: The attention-grabbing power of negative social information. Journal of Personality and Social Psychology, 61, 380–391. doi:10.1037/0022-3514.61.3.380 Siegle, G. J., Thompson, W., Carter, C. S., Steinhauer, S. R., & Thase, M. E. (2007). Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: Related and independent features. Biological Psychiatry, 61, 198–209. doi:10.1016/j.biopsych.2006.05.048 Spitzer, R. L., Williams, J. B. W., Gibbon, M., & First, M. B. (1992). The Structured Clinical Interview for

DSM-III-R (SCID) 1. History, rationale, and description. Archives of General Psychiatry, 49, 624– 629. doi:10.1001/archpsyc.1992.01820080032005 Suchy, Y. (2009). Executive functioning: Overview, assessment, and research issues for non-neuropsychologists. Annals of Behavioural Medicine, 37(2), 106–116. doi:10.1007/s12160-009-9097-4 Sutton, T. M., & Altarriba, J. (2011). The automatic activation and perception of emotion in word processing: Evidence from a modified dot probe paradigm. Journal of Cognitive Psychology, 23, 736– 747. doi:10.1080/20445911.2011.554392 Tipper, S. P. (1985). The negative priming effect: Inhibitory priming by ignored objects. The Quarterly Journal of Experimental Psychology, 37, 571–590. doi:10.1080/14640748508400920 Ungar, L., Nestor, P. G., Niznikiewicz, M. A., Wible, C. G., & Kubicki, M. (2010). Color Stroop and negative priming in schizophrenia: An fMRI study. Psychiatry Research: Neuroimaging, 181(1), 24–29. doi:10.1016/j.pscychresns.2009.07.005 Van Dillen, L. F., Heslenfeld, D. J., & Koole, S. L. (2009). Tuning down the emotional brain: An fMRI study of the effects of cognitive load on the processing of affective images. Neuroimage, 45, 1212–1219. doi:10.1016/j.neuroimage.2009.01.016 Verbruggen, F., Liefooghe, B., & Vandierendonck, A. (2004). The interaction between stop signal inhibition and distractor interference in the flanker and Stroop task. Acta Psychologica (Amsterdam), 116(1), 21–37. doi:10.1016/j.actpsy.2003.12.011 Viviani, R., Lo, H., Sim, E. J., Beschoner, P., Stingl, J. C., & Horn, A. B. (2010). The neural substrate of positive bias in spontaneous emotional processing. PLoS One, 5(11), e15454. doi:10.1371/journal.pone. 0015454 Vo, M. L., Conrad, M., Kuchinke, L., Urton, K., Hofmann, M. J., & Jacobs, A. M. (2009). The Berlin affective word list reloaded (BAWL-R). Behavior Research Methods, 41, 534–538. doi:10.3758/ BRM.41.2.534 Wager, T. D., & Smith, E. E. (2003). Neuroimaging studies of working memory:. Cognitive, Affective, and Behavioral Neuroscience, 3, 255–274. doi:10.3758/ CABN.3.4.255 Walton, M. E., Behrens, T. E., Noonan, M. P., & Rushworth, M. F. (2011). Giving credit where credit is due: Orbitofrontal cortex and valuation in an uncertain world. Annals of the New York Academy of Science, 1239, 14–24. doi:10.1111/j.1749-6632.2011. 06257.x COGNITION AND EMOTION, 2015

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FALQUEZ ET AL.

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Wentura, D. (1999). Activation and inhibition of affective information: for negative priming in the evaluation task. Cognition & Emotion, 13(1), 65–91. doi:10.1080/026999399379375 Yiend, J. (2010). The effects of emotion on attention: A review of attentional processing of emotional information. Cognition & Emotion, 24(1), 3–47. doi:10.1080/02699930903205698 Zetsche, U., D’Avanzato, C., & Joormann, J. (2012). Depression and rumination: Relation to components

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COGNITION AND EMOTION, 2015

of inhibition. Cognition and Emotion, 26, 758–767. doi:10.1080/02699931.2011.613919 Zetsche, U., & Joormann, J. (2011). Components of interference control predict depressive symptoms and rumination cross-sectionally and at six months follow-up. Journal of Behavior Therapy and Experimental Psychiatry, 42(1), 65–73. doi:10.1016/j.jbtep.2010. 06.001