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Motivation and cognitive control in depression

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Abstract
Depression is linked to deficits in cognitive control and a host of other cognitive impairments arise as a consequence of these deficits. Despite of their important role in depression, there are no mechanistic models of cognitive control deficits in depression. In this paper we propose how these deficits can emerge from the interaction between motivational and cognitive processes. We review depression-related impairments in key components of motivation along with new cognitive neuroscience models that focus on the role of motivation in the decision-making about cognitive control allocation. Based on this review we propose a unifying framework which connects motivational and cognitive control deficits in depression. This framework is rooted in computational models of cognitive control and offers a mechanistic understanding of cognitive control deficits in depression.
Keywords
ANTERIOR CINGULATE CORTEX, ALTERED BRAIN ACTIVITY, DECISION-MAKING, LEARNED HELPLESSNESS, STRESSOR CONTROLLABILITY, REMITTED DEPRESSION, ATTENTIONAL CONTROL, SYMPTOM DIMENSIONS, EMOTION REGULATION, NEURAL, MECHANISMS, Depression, Cognitive control, Anhedonia, Motivation, Reward, anticipation, Effort, Controllability of environment

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MLA
Grahek, Ivan, et al. “Motivation and Cognitive Control in Depression.” NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, vol. 102, Pergamon-Elsevier Science, 2019, pp. 371–81.
APA
Grahek, I., Shenhav, A., Musslick, S., Krebs, R., & Koster, E. (2019). Motivation and cognitive control in depression. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 102, 371–381.
Chicago author-date
Grahek, Ivan, Amitai Shenhav, Sebastian Musslick, Ruth Krebs, and Ernst Koster. 2019. “Motivation and Cognitive Control in Depression.” NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 102: 371–81.
Chicago author-date (all authors)
Grahek, Ivan, Amitai Shenhav, Sebastian Musslick, Ruth Krebs, and Ernst Koster. 2019. “Motivation and Cognitive Control in Depression.” NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 102: 371–381.
Vancouver
1.
Grahek I, Shenhav A, Musslick S, Krebs R, Koster E. Motivation and cognitive control in depression. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS. 2019;102:371–81.
IEEE
[1]
I. Grahek, A. Shenhav, S. Musslick, R. Krebs, and E. Koster, “Motivation and cognitive control in depression,” NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, vol. 102, pp. 371–381, 2019.
@article{8637131,
  abstract     = {Depression is linked to deficits in cognitive control and a host of other cognitive impairments arise as a consequence of these deficits. Despite of their important role in depression, there are no mechanistic models of cognitive control deficits in depression. In this paper we propose how these deficits can emerge from the interaction between motivational and cognitive processes. We review depression-related impairments in key components of motivation along with new cognitive neuroscience models that focus on the role of motivation in the decision-making about cognitive control allocation. Based on this review we propose a unifying framework which connects motivational and cognitive control deficits in depression. This framework is rooted in computational models of cognitive control and offers a mechanistic understanding of cognitive control deficits in depression.},
  author       = {Grahek, Ivan and Shenhav, Amitai and Musslick, Sebastian and Krebs, Ruth and Koster, Ernst},
  issn         = {0149-7634},
  journal      = {NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS},
  keywords     = {ANTERIOR CINGULATE CORTEX,ALTERED BRAIN ACTIVITY,DECISION-MAKING,LEARNED HELPLESSNESS,STRESSOR CONTROLLABILITY,REMITTED DEPRESSION,ATTENTIONAL CONTROL,SYMPTOM DIMENSIONS,EMOTION REGULATION,NEURAL,MECHANISMS,Depression,Cognitive control,Anhedonia,Motivation,Reward,anticipation,Effort,Controllability of environment},
  language     = {eng},
  pages        = {371--381},
  publisher    = {Pergamon-Elsevier Science},
  title        = {Motivation and cognitive control in depression},
  url          = {http://dx.doi.org/10.1016/j.neubiorev.2019.04.011},
  volume       = {102},
  year         = {2019},
}

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