Literature DB >> 27943159

Conditioned task-set competition: Neural mechanisms of emotional interference in depression.

Aleks Stolicyn1, J Douglas Steele2, Peggy Seriès3.   

Abstract

Depression has been associated with increased response times at the incongruent-, neutral-, and negative-word trials of the classical and emotional Stroop tasks (Epp et al., Clinical Psychology Review, 32, 316-328, 2012). Response-time slowdown effects at incongruent- and negative-word trials of the Stroop tasks were reported to correlate with depressive severity, indicating strong relevance of the effects to the symptomatology. This study proposes a novel integrative computational model of neural mechanisms of both the classical and emotional Stroop effects, drawing on the previous prominent theoretical explanations of performance at the classical Stroop task (Cohen, Dunbar, & McClelland, Psychological Review, 97, 332-361, 1990; Herd, Banich, & O'Reilly, Journal of Cognitive Neuroscience, 18, 22-32, 2006), and in addition suggesting that negative emotional words represent conditioned stimuli for future negative outcomes. The model is shown to explain the classical Stroop effect and the slow (between-trial) emotional Stroop effect with biologically plausible mechanisms, providing an advantage over the previous theoretical accounts (Matthews & Harley, Cognition & Emotion, 10, 561-600, 1996; Wyble, Sharma, & Bowman, Cognition & Emotion, 22, 1019-1051, 2008). Simulation results suggested a candidate mechanism responsible for the pattern of depressive performance at the classical and the emotional Stroop tasks. Hyperactivity of the amygdala, together with increased inhibitory influence of the amygdala over dopaminergic neurotransmission, could be at the origin of the performance deficits.

Entities:  

Keywords:  Amygdala; Computational model; Depression; Dopamine; Emotion; Neural network

Mesh:

Substances:

Year:  2017        PMID: 27943159     DOI: 10.3758/s13415-016-0478-4

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.282


  99 in total

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