TY - JOUR
T1 - Dissociable Effects of Mood-Anxiety and Compulsive Symptom Dimensions on Motivational Biases in Decision-Making
AU - Scholz, Vanessa
AU - Kandroodi, Mojtaba Rostami
AU - Algermissen, Johannes
AU - Ouden, Hanneke den
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Background: Motivation shape our behaviour in a seemingly automatic fashion. Rewards tend to trigger behavioural activation, whereas punishment prompts response inhibition. Such motivational biases appear to embody what is globally adaptive responding in our environment, where getting a reward usually requires taking action. Still, their automatic execution can result in maladaptive behaviour when bias-incongruent responses are required, and adaptive suppression fails. As changes in motivational processes represent a core feature of many psychiatric disorders, our goal was to examine the clinical relevance of these biases. Method(s): Data from a population sample (N=500) was acquired online using clinical questionnaires and an established Go-Nogo task to capture motivational biases. We used computational modelling to identify mechanisms associated with variability across clinical dimensions encapsulating mood-anxiety and compulsivity. Result(s): Strikingly, higher levels of mood-anxiety were linked to an improved ability to overcome motivational biases when these were maladaptive (s=-0.254, p=.008). Meanwhile, more compulsive individuals showed a general learning deficit, captured by an overall decreased learning rate (s=-0.011, p=.008). This double dissociation was mirrored in effects on reaction time. More mood-anxiety was associated with a slowing on incorrect responses, while slower correct responses were characteristic for higher compulsivity. Conclusion(s): Our study reveals a double dissociation for mood-anxiety and compulsivity in motivational decision-making. Speculatively, the improved performance and longer reaction times in more anxious-depressed individuals could originate from a more ruminative decision style and be computationally operationalized as increased decision-threshold. Meanwhile, decreased performance for higher compulsivity might be linked to reported deficits in model-based decision making in obsessive compulsive disorder. Supported By: DFG, NWO Keywords: Computational Psychiatry, Reinforcement Learning, Mood Disorder, Compulsivity, Motivational BiasesCopyright © 2020
AB - Background: Motivation shape our behaviour in a seemingly automatic fashion. Rewards tend to trigger behavioural activation, whereas punishment prompts response inhibition. Such motivational biases appear to embody what is globally adaptive responding in our environment, where getting a reward usually requires taking action. Still, their automatic execution can result in maladaptive behaviour when bias-incongruent responses are required, and adaptive suppression fails. As changes in motivational processes represent a core feature of many psychiatric disorders, our goal was to examine the clinical relevance of these biases. Method(s): Data from a population sample (N=500) was acquired online using clinical questionnaires and an established Go-Nogo task to capture motivational biases. We used computational modelling to identify mechanisms associated with variability across clinical dimensions encapsulating mood-anxiety and compulsivity. Result(s): Strikingly, higher levels of mood-anxiety were linked to an improved ability to overcome motivational biases when these were maladaptive (s=-0.254, p=.008). Meanwhile, more compulsive individuals showed a general learning deficit, captured by an overall decreased learning rate (s=-0.011, p=.008). This double dissociation was mirrored in effects on reaction time. More mood-anxiety was associated with a slowing on incorrect responses, while slower correct responses were characteristic for higher compulsivity. Conclusion(s): Our study reveals a double dissociation for mood-anxiety and compulsivity in motivational decision-making. Speculatively, the improved performance and longer reaction times in more anxious-depressed individuals could originate from a more ruminative decision style and be computationally operationalized as increased decision-threshold. Meanwhile, decreased performance for higher compulsivity might be linked to reported deficits in model-based decision making in obsessive compulsive disorder. Supported By: DFG, NWO Keywords: Computational Psychiatry, Reinforcement Learning, Mood Disorder, Compulsivity, Motivational BiasesCopyright © 2020
KW - Computational Psychiatry
KW - Reinforcement Learning
KW - Mood Disorder
UR - https://www.mendeley.com/catalogue/4dedb33f-e8b0-34e5-9a45-f1edc8229fa8/
U2 - 10.1016/j.biopsych.2020.02.979
DO - 10.1016/j.biopsych.2020.02.979
M3 - Article
SN - 0006-3223
VL - 87
SP - S382-S383
JO - Biological Psychiatry
JF - Biological Psychiatry
IS - 9
ER -