Psychology & Neuroscience Effect of emotionally valenced stimuli on working memory performance

Psychology & Neuroscience

Effect of emotionally valenced stimuli on working memory performance--Manuscript Draft--

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Full Title: Effect of emotionally valenced stimuli on working memory performance

Abstract: Working memory (WM) is the ability to keep information cognitively in course for a briefperiod of time, but with enough duration as to complete a task. Few is known abouthow the different emotional valences of the perceived information provoke effect overWM, since it is known that for WM task performance, motivated behavior receivesimportant emotional influence. Method, a total of 27 subjects university students,randomly selected, participated in the study. Data was acquired from 23 right handedsubjects (20.22 yr mean age, SD = 1.47), 52.2% male (20.09 yr old mean age, SD =1.7), 47.8% female (20.35 yr mean age, SD = 1.3). Instruments and procedure,influence of emotional valence in a WM task was measured using content from theInternational Affective Picture System (IAPS), subjects were asked to remember thefirst image of the pair, compare the second image with it. Accuracy of response (AR)measured by the number of correct responses, and reaction times (RT) weremeasured for each subject. Results show that the RT is shortest for pictures withneutral valence and longest for negative valence, MANOVA statistics showed asignificant main effect of emotional valence. It was found that the AR is highest forpictures with neutral valence and lowest for negative valence. Conclusions, emotionallycharged IAPS pictures were processed worse than neutral ones during workingmemory task performance, there is an effect of emotion valence on RT, and that this ishigher for negative pictures compared with positive ones.

Article Type: Article

Keywords: Working memory, emotional valence, performance.

Corresponding Author: Gilberto GalindoUniversidad Autonoma de Baja CaliforniaMEXICO

Corresponding Author E-Mail: [email protected]

Corresponding Author SecondaryInformation:

Corresponding Author's Institution: Universidad Autonoma de Baja California

Other Authors: Fraga-Vallejo Miguel Angel

Machinskaya Regina

Solovieva Yulia

Peter Mangan

Corresponding Author's SecondaryInstitution:

First Author: Gilberto Galindo

Order of Authors Secondary Information:

Manuscript Region of Origin: MEXICO

Suggested Reviewers: Domagoj SvegarDepartment of Psychology, Faculty of Humanities and Social Sciences, University ofRijeka, [email protected] to his experience in working memory research.

Mara MatherUniversity of Southern [email protected] to her experience in research about emotion and cognition.

Mikels JosephCornell [email protected] to his experience in researching working memory and emotional influence.

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Opposed Reviewers:

Order of Authors: Gilberto Galindo

Fraga-Vallejo Miguel Angel

Machinskaya Regina

Solovieva Yulia

Peter Mangan

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Running head: Effect of Emotional Stimuli on Working Memory

Effect of emotionally valenced stimuli on working memory performance

Galindo-Aldana, G.,1 Fraga-Vallejo, M.,1 Machinskaya, R. I.,2 Solovieva, Y.,3 &

Mangan, P.4

1Autonomous University of Baja California, Neuroscience and Cognition

Laboratory, México.

2Laboratory of Neurophysiology of Cognitive Processes, Institute of Developmental

Physiology, Russian Academy of Education, Moscow, Russia.

3Autonomous University of Puebla, Neuropsychological and Diagnosis Master

Program, Puebla, México.

4Northern Arizona University, Psychology Faculty, Yuma, Arizona, USA.

Running head: Effect of emotional stimuli on working memory

Psychology & Neuroscience, xxx

DOI: xxx

Galindo-Aldana, G. and Fraga-Vallejo, M., Autonomous University of Baja California, Neuroscience and Cognition Laboratory, México. Machinskaya, R. I., Laboratory of Neurophysiology of Cognitive Processes, Institute of Developmental Physiology, Russian Academy of Education, Moscow, Russia. Solovieva, Y.,

Autonomous University of Puebla, Neuropsychological and Diagnosis Master Program, Puebla, México. Mangan, P., Northern Arizona University, Psychology Faculty, Yuma, Arizona, USA. Correspondence regarding this article should be directed to: Gilberto Galindo Aldana, Av. Colombia, 802, Col. Compuertas, 21218, Mexicali, Mexico. E-mail: [email protected]

Title page with All Author Information

mailto:[email protected]


INTRODUCTION

Working memory (WM) is defined as the ability to keep cognitive information

available for a brief period of time but long enough to use that information to

complete a task (Baddeley, 2003). It is an executive function (Elliott, 2003), in which

an individual makes a decision using information that is no longer present but can be

retrieved from short- or long-term memory with the objective of achieving a goal

(Baddeley, 2002; Baddeley, 1974; Baddeley, Jarrold, & Vargha-Khadem, 2011).

Working memory is a complex psychological function that is greatly affected by the

individual’s emotional state and behavioral goals (Damasio, 1994; Davidson, 2000).

In recent years, research on WM has produced well-validated methods for

measuring the influence of emotions on WM (Alvarez & Cavanagh, 2004; Chan,

Shum, Toulopoulou, & Chen, 2008; Svegar, 2011), supported by evidence of brain

organization using neuroimaging and electrophysiological techniques (Fusar-Poli et

al., 2009; Jurado & Rosselli, 2007; Pessoa, 2008; Zikopoulos & Barbas, 2012). Thus,

goal-oriented behavior depends to a great extent on the mechanisms of WM and

maintenance of goal and context information in WM.

Working memory capacity is correlated with higher-order behavioral control,

such as attention, and social and moral decision making. For example, deficits in

WM interfere with the ability to direct behavior and, more importantly, keep a

behavior “in mind” (Gazzaley, 2011). One of the important features of WM is the

number of situations in which an automated behavior needs to be inhibited and a

different behavior is executed in response to a particular cue (Hikosaka & Isoda,

2010). The ability to maintain the necessary information to complete a task permits

an individual to plan and organize higher-order behaviors, instead of only responding

to immediate changes in the environment. Without WM, an individual’s behavior

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would be controlled by environmental stimuli that are present. This would contribute

to executive control dysfunction, resulting in an inability to inhibit impulsive

behaviors.

Although WM is a critical skill for many related functions and predicts

performance on a wide variety of cognitive tasks, only a few studies have

investigated the specific manner in which emotional information influences WM

performance. Little is known about how different emotional valences of currently

available information affect WM performance. With regard to successful performance

on WM tasks, emotions have an important influence on goal-directed behavior

(Damasio, 1994; Davidson, 2000; Davidson & Irwin, 1999) that can be hindered or

enhanced by the level of arousal that is produced by stimuli (Sommer, Glascher,

Moritz, & Buchel, 2008). In a previous study on emotions and WM, adult participants

were asked to detect a whether a series of new facial expressions were the same or

different from six previously seen facial expressions. A mean number of three

emotional facial expressions were retained in WM (Svegar, 2011). However, in this

study, WM capacity was measured for facial expressions in which only facial

features were visible and other features (e.g., hair, ears, etc.) were obscured,

instead of showing the totality of emotional facial expressions of individuals in a

natural setting.

Behavioral WM has been reported to consist of segregated cognitive

subsystems (Darling, Della Sala, & Logie, 2007). With regard to social interactions,

other studies (Lo Presti, Schon, Tricarico, Swisher, Celone, & Stern, 2008) proposed

a perceptual cerebral system within temporal and occipital cortices that separately

process and identity facial emotional expressions, with the interconnected

involvement of the orbitofrontal cortex, amygdala, and hippocampus (Banks,


Kamryn, Angstadt, Pradeep, & Phan, 2007) in information processing in visual WM

paradigms.

As mentioned previously, attention plays an important role in WM and other

cognitive abilities (Cowan et al., 2005). Cowan et al. (2005) proposed an attention-

WM relationship that suggests that the term attention refers to selective attention.

This implies that some information is selected for more concentrated processing at

the expense of information that is perceived as less relevant. Therefore, analyses of

WM performance should focus on the scope of attention and the control of attention.

In an emotional situation, the ability to regulate, inhibit, enhance, maintain, and

modulate emotional arousal is necessary to accomplish a goal (Hinnant & O'Brien,

2007) that involves responding to relevant information.

Emotional regulation is a crucial skill for other higher complex functions, such

as empathy (Hinnant & O'Brien, 2007) and affect and behavior prediction (Storbeck,

Davidson, Dahl, Blass, & Yung, 2015). However, explanations for this relationship

and developmental descriptions are still lacking. Presuming that this function evolves

during development, differences could be expected in the influence of emotion on

WM in different age groups (Mammarella, Borella, Carretti, Leonardi, & Fairfield,

2013). Psychopathology has examined whether higher levels of anhedonia are

associated with a diminished impact of emotion and related to WM performance.

One experiment (Becerril & Barch, 2011) presented neutral and emotional facial

expressions to two different groups, and both of them exhibited higher accuracy but

slower reaction times (RTs) for negative stimuli compared with neutral stimuli. The

study found alterations in activity of the prefrontal cortex and hippocampus while

participants performed an emotionally loaded WM task, suggesting that disturbances

in emotional processing in schizophrenia are related to alterations in emotion-


cognition interactions rather than perception and subjective experiences. Functional

magnetic resonance imaging (fMRI) findings in patients with posttraumatic stress

disorder revealed higher activation in regions related to the processing of emotions,

including the amygdala, precuneus, and fusiform gyrus, and lower activation in the

inferior frontal cortex, insula, and left supramarginal gyrus compared with controls

(Zhang et al., 2013).

Previous research on the influence of emotionally valenced stimuli on WM

proposed that affective information that depends on the lexical content of emotionally

valenced words is another area that needs to be investigated (Fairfield, Mammarella,

Di Domenico, & Palumbo, 2015). Additionally, highly complex reciprocal connections

between prefrontal structures and the subcortical limbic system could elucidate

interactions between emotional processing and decision making on WM tasks. The

aim of the present study was to determine the possible effects of different

emotionally valenced visual stimuli (i.e., pictures of scenes or facial expressions) on

decision making in a working memory task in young adults.

METHODS

Participants

A total of 27 university students were randomly selected to participate in the

study. The inclusion criteria were the following: no psychological, neurological, or

psychiatric clinical history or recent emotional disturbances, including eating

disorders. Two of the students were excluded from the sample because of missing

data, and two others correctly answered less than 50% in the experimental probes.

Their poor performance was considered to be the result of their failure to understand

the instructions. The data were obtained from 23 right-handed subjects (mean age =


20.22 years, standard deviation [SD] = 1.47 years), 52.2% male (mean age = 20.09

years, SD = 1.7 years) and 47.8% female (mean age = 20.35 years, SD = 1.3 years).

All of the participants had normal vision. All of the subjects were assessed with the

Montreal Cognitive Assessment (Rojo-Mota, Pedrero-Pérez, Ruiz-Sánchez de León,

Llanero-Luque, & Puerta-García, 2013) to identify possible cognitive impairments. All

of the participants scored 24.22 or higher, indicating a lack of cognitive impairments.

Instruments and procedure

This study was conducted in accordance with the determinations of the

Helsinki Accord. Prior to the experimental probes, informed consent was provided by

each participant. All of the task procedures were explained, and the subjects

participated voluntarily.

The influence of emotional valence in the WM task was measured using facial

images, objects, and scenes that had one of three different emotional valences. The

pictures were retrieved from the International Affective Picture System (IAPS; Lang,

Bradley, & Cuthbert, 2008). A total of 240 pictures were selected and divided into

three groups: 80 pictures of positive emotional states, 80 pictures of negative

emotional states, and 80 pictures of neutral situations. The images were presented

in pairs with a 4 s delay between the first and second pictures. The pairs of images

could be the same (meaning that the second picture could be the same as the first

one) or different (meaning that the picture could have one or more features that were

different from the first picture). Of the pictures that were presented, 50% were the

same, and 50% were different. Each of the pairs of pictures differed from other pairs

in the emotional valence that was shown, in addition to being the same or different,

and were presented in a pseudorandom order (Figure 1). The participants were


asked to maintain in memory the first image of the pair and compare the second

image with the stored image. They were asked to press the lower button on a

Logitech joystick if the pictures were the same and the higher button if the pictures

were different. The participants were given 10 s to respond. If no response was

emitted during that time, the next pair of pictures was presented. Each participant

underwent 120 trials (40 with positive valence, 40 with negative valence, and 40 with

neutral valence). The accuracy of responding (AR) was measured as the number of

correct responses. Reaction times were recorded in milliseconds for each participant

using EEGxProc software. Each participant was tested individually in a quiet room

where the visual stimuli were shown on a 19-inch color monitor at a distance of 40

cm from the participant’s face.

—Figure 1—

RESULTS

The influence of the emotional valence of visual stimuli in the WM task was

analyzed using two parameters, RT and AR (calculated as a percentage of correct

responses). Both parameters were statistically analyzed using the General Linear

Model at three levels according to the type of emotional valence stimuli that were

presented (positive, negative, and neutral).

The multivariate analysis of variance (MANOVA) revealed a significant main

effect of emotional valence (F2,21 = 20.136, p < .0001). The RT was shortest for

pictures with neutral valence and longest for pictures with negative valence.

Comparisons of the main effect that was adjusted for multiple comparisons using

Bonferroni correction revealed significant pairwise differences in RT between


positive and negative pictures (p = .019), positive and neutral pictures (p = .005), and

negative and neutral pictures (p < .0001; Figure 2).

—Figure 2—

For measuring the AR, trials in which no responses were emitted were

considered inaccurate responses. The AR was highest for pictures with neutral

valence and lowest for pictures with negative valence. The MANOVA revealed a

significant main effect of emotional valence (F2,21 = 28.015, p < .0001). The

comparison of the main effect that was adjusted for multiple comparisons with

Bonferroni correction revealed significant pairwise differences in the AR between

neutral and positive pictures (p < .0001) and neutral and negative pictures (p <

.0001) but no significant differences between negative and positive pictures (Figure

3).

—Figure 3—

DISCUSSION

The present study found two effects that were influenced by the emotional

valence of visual stimuli in a WM task. First, the effect of emotional stimuli on the AR

was greatest when the emotional valence of the stimuli was negative, reflected by a

lower percentage of correct responses compared with stimuli with neutral valence.

Second, RTs were longer when the emotional valence of the stimuli was negative

compared with stimuli with neutral or positive valence. Similar results were found in

children aged 9-12 years, who exhibited impairment in WM performance when the


emotional expressions were negative (Augusti, Torheim, & Melinder, 2014). Similar

performance was reported in older children and adults, in which responses to faces

with emotional expressions were slower for fearful and happy faces compared with

non-emotional faces (Barnes, Kaplan, & Vaidya, 2007).

Another study (Rozovskaya, Mershina, & Pechenkova, 2014) used similar

images and also found that emotionally neutral images resulted in better task

performance compared with negative visual stimuli in 30-year-old participants. The

authors analyzed fMRI and behavioral data together and suggested that the

processing of negative emotional expressions in WM results in different brain activity

compared with neutral expressions, and this activity appears to be less efficient in

this type of cognitive task.

The processing of emotional information can affect WM performance and

processes related to cognitive control. Nonetheless, previous experiments reported

contradictory results with regard to whether emotions have a facilitatory or

detrimental effect on performance (Lindström & Bohlin, 2011), which contrasts with

the present study that used similar stimuli from the same picture system (IAPS; Lang

et al., 2008), the authors reported that emotionally loaded visual stimuli facilitated

WM performance (reflected by the number of correct hits), eliciting higher

discriminability and lower RTs than neutral items. Both positively valenced and

negatively valenced stimuli were associated with this facilitatory effect. In the study

by Lindström and Bohlin (2001), shorter RTs in response to emotional stimuli were

explained by enhanced response selection relative to neutral stimuli. Other authors

found that the maintained feeling of the subject and valence effects depended on a

memory delay, suggesting that the WM system may include domain-specific

components (Mikels, Reuter-Lorenz, Beyer, & Fredrickson, 2008).


Emotions have also been reported to be closely linked to memory (Justel,

Psyrdellis, & Ruetti, 2013). Within this framework, the present results suggest that

the visual information that is observed is influenced by its emotional content.

However, when a WM task must be performed, informational details can be missed,

thus compromising performance in accurately identifying the features of the stimuli.

An explanation for the differences between the present study and Justel et al. (2013)

could be the type of memory that is being measured. Impairments in WM that are

associated with emotional state has also been studied by means of determining

whereas the emotional arousal can impair its feature binding (Mather & Nesmith,

2008). Mather (2008) reported that participants presented poorer short-term memory

of the location of highly arousing pictures compared with pictures that were less

arousing, suggesting that emotional arousal can disrupt the encoding of visual

information. These authors further performed fMRI and found that emotionally

arousing pictures elicited more attention, in which subjects exhibited more activation

in visual areas.

The present study evaluated the effects of emotional valence on WM

performance, in which aversive (negative) stimuli significantly reduced the

percentage of correct responses, and stimuli with less emotional valence were

associated with improvements in WM accuracy. The longer RTs may suggest that

aversive information interferes with the detection of differences in the pictures. In

psychophysiology, at least two motivational systems have been proposed: aversive

and attractive (Bradley & Lang, 2006). Both systems can be activated by different

unconditioned stimuli, and they have reciprocal inhibitory connections that modulate

behavior.


The present study suggests that performance in a WM task with more

complex visual stimuli (including faces with emotional expressions but not isolated

expressions) presents emotion-dependent differences in the AR and RT. One of the

main functions of humans is making predictions about future events (Brown & Brüne,

2012). Working memory is a basic executive function that is necessary to keep

ongoing information available to be able to make such predictions as accurately and

congruently as possible based on self-goals and intentions. Thus, emotionally

valenced information that is perceived in the social environment can lead to

important variations in self-control, behavior, and social success.

Some of the contradictory results that were found in the present study

compared with previous studies suggest the need for further investigations by

considering differences in the models that are used to study the influence of

emotional information on WM.

CONCLUSIONS

The main finding of the present study was that emotionally charged IAPS

images were processed worse than neutral pictures during the WM task. We also

observed an effect of emotional valence on RT, which was longer for negative

pictures than for positive pictures.

Acknowledgements

We thanks the undergraduate psychology students who contributed to this

experimental series of studies: Sheyla Amor Guillén, Adriana Chávez, and Marisol

López. We also thank the volunteers who participated in this study. The authors


declar no conflicts of interest, and no specific grant to report is related to this

research.

REFERENCES

Alvarez, G. & Cavanagh, P. (2004). The capacity of visual short-term memory is set

both by visual information load and by number of objects. Psychological

Science, 15(2), 106-111.

Augusti, E. M., Torheim, H. K., & Melinder, A. (2014). The effect of emotional facial

expressions on children's working memory: associations with age and

behavior. Child Neuropsychology, 20(1), 86-105.

Baddeley, A. (1974). The episodic buffer: a new component of working memory?

Trends in Cognitive Sciences, 4(11), 417-423.

Baddeley, A. (2002). Is working memory still working? European Psychologist, 7(2),

85-97.

Baddeley, A. (2003). Working memory: looking back and looking forward. Nature

Reviews Neuroscience, 4(10), 829-839.

Baddeley, A., Jarrold, C., & Vargha-Khadem, F. (2011). Working memory and the

hippocampus. Journal of Cognitive Neuroscience, 23(12), 3855-3861.

Banks, S. J., Eddy, K. T., Angstadt, M., Nathan, P. J., & Phan, L. (2007). Amygdala-

frontal connectivity during emotion regulation. Social and Cognitive Affective

Neuroscience, 2, 303-312.

Barnes, K. A., Kaplan, L. A., & Vaidya, C. J. (2007). Developmental differences in

cognitive control of socio-affective processing. Developmental

Neuropsychology, 32(3), 787-807.


Becerril, K. & Barch, D. (2011). Influence of emotional processing on working

memory in schizophrenia. Schizophrenia Bulletin, 37(5), 1027-1038.

Bradley, M. & Lang, P. (2006). Emotion and motivation. In J.T. Cacioppo, L.G.

Tassinary, & G. Bernston (Eds.), Handbook of psychophysiology (pp. 582).

New York: Cambridge University Press.

Brown, E. C. & Brüne, M. (2012). The role of prediction in social neuroscience.

Frontiers in Human Neuroscience, 6, 147.

Cowan, N., Elliott, E. M., Saults, J. S., Morey, C. C., Mattox, S., Hismjatullina, A., &

Conway, A. R. (2005). On the capacity of attention: its estimation and its role

in working memory and cognitive aptitudes. Cognitive Psychology, 51(1), 42-

100.

Chan, R. C. K., Shum, D., Toulopoulou, T., & Chen, E. Y. H. (2008). Assessment of

executive functions: review of instruments and identification of critical issues.

Archives of Clinical Neuropsychology, 23, 201-216.

Damasio, A. (1994). Descartes' error: emotion, reason, and the human brain: New

York: Penguin Books.

Darling, S., Della Sala, S., & Logie, R. H. (2007). Behavioural evidence for

separating components within visuo-spatial working memory. Cognitive

Processing, 8(3), 175-181.

Davidson, R. J. (2000). Affective neuroscience and psychophysiology: toward a

synthesis. Psychophysiology, 40, 655-665.

Davidson, R. J. & Irwin, W. (1999). The functional neuroanatomy of emotion and

affective style. Trends in Cognitive Sciences, 3(1), 11-21.

Elliott, R. (2003). Executive functions and their disorders. British Medical Bulletin, 65,

49-59.


Fairfield, B., Mammarella, N., Di Domenico, A., & Palumbo, R. (2015). Running with

emotion: when affective content hampers working memory performance.

International Journal of Psychophysiology, 50, 161-164.

Fusar-Poli, P., Placentino, A., Carletti, F., Landi, P., Allen, P., Surguladze, S.,

Benedetti, F., Abbamonte, M., Gasparotti, R., Barale, F., Perez, J., McGuire,

P., & Politi, P. (2009). Functional atlas of emotional faces processing: a voxel-

based meta-analysis of 105 functional magnetic resonance imaging studies.

Journal of Psychiatry and Neuroscience, 34(6), 418-432.

Gazzaley, A. (2011). Influence of early attentional modulation on working memory.

Neuropsychologia, 49(6), 1410-1424.

Hikosaka, O. & Isoda, M. (2010). Switching from automatic to controlled behavior:

cortico-basal ganglia mechanisms. Trends in Cognitive Sciences, 14(4), 154-

161.

Hinnant, J. B. & O'Brien, M. (2007). Cognitive and emotional control and perspective

taking and their relations to empathy in 5-year-old children. Journal of Genetic

Psychology, 168(3), 301-322.

Jurado, M. B. & Rosselli, M. (2007). The elusive nature of executive functions: a

review of our current understanding. Neuropsychology Review, 17(3), 213-

233.

Justel, N., Psyrdellis, M., & Ruetti, E. (2013). Modulation of emotional memory, a

revision of the main factors which influence memories. Suma Psicológica,

20(2), 163-174.

Lang, P., Bradley, M., & Cuthbert, B. (2008). International Affective Picture System

(IAPS): affective ratings of pictures and instruction manual. Gainesville:

University of Florida.


Lindström, B. & Bohlin, G. (2011). Emotion processing facilitates working memory

performance. Cognition and Emotion, 25(7), 1196-1204.

Lo Presti, M. L., Schon, K., Tricarico, M. D., Swisher, J. D., Celone, K. A., & Stern, C.

E. (2008). Working memory for social cues recruits orbitofrontal cortex and

amygdala: a functional magnetic resonance imaging study of delayed

matching to sample for emotional expressions. Journal of Neuroscience,

28(14), 3718-3728.

Mammarella, N., Borella, E., Carretti, B., Leonardi, G., & Fairfield, B. (2013).

Examining an emotion enhancement effect in working memory: evidence from

age-related differences. Neuropsychological Rehabilitation, 23(3), 416-428.

Mather, M. & Nesmith, K. (2008). Arousal-enhanced location memory for pictures.

Journal of Memory and Language, 58(2), 449-464.

Mikels, J. A., Reuter-Lorenz, P. A., Beyer, J. A., & Fredrickson, B. L. (2008). Emotion

and working memory: evidence for domain-specific processes for affective

maintenance. Emotion, 8(2), 256-266.

Pessoa, L. (2008). On the relationship between emotion and cognition. Nature, 9,

148-158.

Rojo-Mota, G., Pedrero-Pérez, E. J., Ruiz-Sánchez de León, J. M., Llanero-Luque,

M., & Puerta-García, C. (2013). Cribado neurocognitivo en adictos a

sustancias: la evaluación cognitiva de Montreal [Neurocognitive screening in

substance addicts: the Montreal Cognitive Assessment]. Revista de

Neurologia, 56(3), 129-136.

Rozovskaya, R., Mershina, E., & Pechenkova, E. (2014). How working memory is

influenced by processing of emotional information: an event-related fMRI


study. Paper presented at the The Sixth International Conference on

Cognitive Science.

Sommer, T., Glascher, J., Moritz, S., & Buchel, C. (2008). Emotional enhancement

effect of memory: removing the influence of cognitive factors. Learning and

Memory, 15(8), 569-573.

Storbeck, J., Davidson, N. A., Dahl, C. F., Blass, S., & Yung, E. (2015). Emotion,

working memory task demands and individual differences predict behavior,

cognitive effort and negative affect. Cognition and Emotion, 29(1), 95-117.

Svegar, D. (2011). Visual working memory capacity for emotional facial expressions.

Psihologijske Teme, 20(3), 489-502.

Zhang, J. N., Xiong, K. L., Qiu, M. G., Zhang, Y., Xie, B., Wang, J., Li, M., Chen, H.,

Zhang, Y., & Zhang, J. J. (2013). Negative emotional distraction on neural

circuits for working memory in patients with posttraumatic stress disorder.

Brain Research, 1531, 94-101.

Zikopoulos, B. & Barbas, H. (2012). Pathways for emotions and attention converge

on the thalamic reticular nucleus in primates. Journal of Neuroscience, 32(15),

5338-5350.


Figure 1. Sequence of visual stimulus admiration.

Wait subject’s

Response, SAME-

DIFFERENT, and RT

4000 ms Blank

interval

Attention

1st Vis. Stim.

2nd Vis. Stim.

Wait experimenter’s

start

4000 ms

+


Figure 2. Mean (± SEM) RT (in milliseconds) in the working memory task, presenting

the effect of emotional valence of the visual stimuli.


Figure 3. Mean (± SEM) accuracy (%correct answers) in working memory task,

presenting the effect of emotional valence of the visual stimuli.

Psychology & Neuroscience Effect of emotionally valenced stimuli on working memory performance

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