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A computational analysis of flanker interference in depression

Published online by Cambridge University Press:  02 March 2015

D. G. Dillon
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
T. Wiecki
Affiliation:
Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA
P. Pechtel
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
C. Webb
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
F. Goer
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
L. Murray
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
M. Trivedi
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
M. Fava
Affiliation:
Clinical Research Program, Massachusetts General Hospital, Boston, MA, USA
P. J. McGrath
Affiliation:
New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
M. Weissman
Affiliation:
New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
R. Parsey
Affiliation:
Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, NY, USA
B. Kurian
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
P. Adams
Affiliation:
New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
T. Carmody
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
S. Weyandt
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
K. Shores-Wilson
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
M. Toups
Affiliation:
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
M. McInnis
Affiliation:
Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA
M. A. Oquendo
Affiliation:
New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
C. Cusin
Affiliation:
Clinical Research Program, Massachusetts General Hospital, Boston, MA, USA
P. Deldin
Affiliation:
Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA
G. Bruder
Affiliation:
New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
D. A. Pizzagalli*
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
*
*Address for correspondence: D. A. Pizzagalli, Ph.D., Center for Depression, Anxiety and Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478-9106, USA. (Email: dap@mclean.harvard.edu)

Abstract

Background

Depression is characterized by poor executive function, but – counterintuitively – in some studies, it has been associated with highly accurate performance on certain cognitively demanding tasks. The psychological mechanisms responsible for this paradoxical finding are unclear. To address this issue, we applied a drift diffusion model (DDM) to flanker task data from depressed and healthy adults participating in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study.

Method

One hundred unmedicated, depressed adults and 40 healthy controls completed a flanker task. We investigated the effect of flanker interference on accuracy and response time, and used the DDM to examine group differences in three cognitive processes: prepotent response bias (tendency to respond to the distracting flankers), response inhibition (necessary to resist prepotency), and executive control (required for execution of correct response on incongruent trials).

Results

Consistent with prior reports, depressed participants responded more slowly and accurately than controls on incongruent trials. The DDM indicated that although executive control was sluggish in depressed participants, this was more than offset by decreased prepotent response bias. Among the depressed participants, anhedonia was negatively correlated with a parameter indexing the speed of executive control (r = −0.28, p = 0.007).

Conclusions

Executive control was delayed in depression but this was counterbalanced by reduced prepotent response bias, demonstrating how participants with executive function deficits can nevertheless perform accurately in a cognitive control task. Drawing on data from neural network simulations, we speculate that these results may reflect tonically reduced striatal dopamine in depression.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2015 

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