» Articles » PMID: 25923684

Neural Loss Aversion Differences Between Depression Patients and Healthy Individuals: A Functional MRI Investigation

Overview
Journal Neuroradiol J
Publisher Sage Publications
Specialties Neurology
Radiology
Date 2015 Apr 30
PMID 25923684
Citations 21
Authors
Affiliations
Soon will be listed here.
Abstract

Neuroeconomics employs neuroscience techniques to explain decision-making behaviours. Prospect theory, a prominent model of decision-making, features a value function with parameters for risk and loss aversion. Recent work with normal participants identified activation related to loss aversion in brain regions including the amygdala, ventral striatum, and ventromedial prefrontal cortex. However, the brain network for loss aversion in pathologies such as depression has yet to be identified. The aim of the current study is to employ the value function from prospect theory to examine behavioural and neural manifestations of loss aversion in depressed and healthy individuals to identify the neurobiological markers of loss aversion in economic behaviour. We acquired behavioural data and fMRI scans while healthy controls and patients with depression performed an economic decision-making task. Behavioural loss aversion was higher in patients with depression than in healthy controls. fMRI results revealed that the two groups shared a brain network for value function including right ventral striatum, ventromedial prefrontal cortex, and right amygdala. However, the neural loss aversion results revealed greater activations in the right dorsal striatum and the right anterior insula for controls compared with patients with depression, and higher activations in the midbrain region ventral tegmental area for patients with depression compared with controls. These results suggest that while the brain network for loss aversion is shared between depressed and healthy individuals, some differences exist with respect to differential activation of additional areas. Our findings are relevant to identifying neurobiological markers for altered decision-making in the depressed.

Citing Articles

Decomposing loss aversion from a single neural signal.

Wang R, Wang X, Platt M, Sheng F iScience. 2024; 27(7):110153.

PMID: 39006480 PMC: 11245989. DOI: 10.1016/j.isci.2024.110153.


An ecological assessment of decision-making under risk and ambiguity through the virtual serious game Kalliste Decision Task.

Molins F, Gil-Gomez J, Serrano M, Mesa-Gresa P Sci Rep. 2024; 14(1):13144.

PMID: 38849446 PMC: 11161587. DOI: 10.1038/s41598-024-63752-y.


Economic Decisions with Ambiguous Outcome Magnitudes Vary with Low and High Stakes but Not Trait Anxiety or Depression.

Zbozinek T, Charpentier C, Qi S, Mobbs D Comput Psychiatr. 2024; 5(1):119-139.

PMID: 38773996 PMC: 11104296. DOI: 10.5334/cpsy.79.


Rethinking peer influence and risk taking: A strengths-based approach to adolescence in a new era.

Allen J Dev Psychopathol. 2024; 36(5):2244-2255.

PMID: 38752571 PMC: 11568074. DOI: 10.1017/S0954579424000877.


Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies.

Ding Y, Ou Y, Yan H, Liu F, Li H, Li P Biomedicines. 2023; 11(12).

PMID: 38137360 PMC: 10740577. DOI: 10.3390/biomedicines11123138.


References
1.
Paulus M, Yu A . Emotion and decision-making: affect-driven belief systems in anxiety and depression. Trends Cogn Sci. 2012; 16(9):476-83. PMC: 3446252. DOI: 10.1016/j.tics.2012.07.009. View

2.
Simmons A, Strigo I, Matthews S, Paulus M, Stein M . Anticipation of aversive visual stimuli is associated with increased insula activation in anxiety-prone subjects. Biol Psychiatry. 2006; 60(4):402-9. DOI: 10.1016/j.biopsych.2006.04.038. View

3.
Chua P, Krams M, Toni I, Passingham R, Dolan R . A functional anatomy of anticipatory anxiety. Neuroimage. 1999; 9(6 Pt 1):563-71. DOI: 10.1006/nimg.1999.0407. View

4.
Brooks A, Pammi V, Noussair C, Capra C, Engelmann J, Berns G . From bad to worse: striatal coding of the relative value of painful decisions. Front Neurosci. 2010; 4:176. PMC: 2987510. DOI: 10.3389/fnins.2010.00176. View

5.
Ruiz S, Birbaumer N, Sitaram R . Abnormal Neural Connectivity in Schizophrenia and fMRI-Brain-Computer Interface as a Potential Therapeutic Approach. Front Psychiatry. 2013; 4:17. PMC: 3605516. DOI: 10.3389/fpsyt.2013.00017. View