Dataset Information

Neural and computational mechanisms of postponed decisions.

ABSTRACT: We consider the mechanisms that enable decisions to be postponed for a period after the evidence has been provided. Using an information theoretic approach, we show that information about the forthcoming action becomes available from the activity of neurons in the medial premotor cortex in a sequential decision-making task after the second stimulus is applied, providing the information for a decision about whether the first or second stimulus is higher in vibrotactile frequency. The information then decays in a 3-s delay period in which the neuronal activity declines before the behavioral response can be made. The information then increases again when the behavioral response is required. We model this neuronal activity using an attractor decision-making network in which information reflecting the decision is maintained at a low level during the delay period, and is then selectively restored by a nonspecific input when the response is required. One mechanism for the short-term memory is synaptic facilitation, which can implement a mechanism for postponed decisions that can be correct even when there is little neuronal firing during the delay period before the postponed decision. Another mechanism is graded firing rates by different neurons in the delay period, with restoration by the nonspecific input of the low-rate activity from the higher-rate neurons still firing in the delay period. These mechanisms can account for the decision making and for the memory of the decision before a response can be made, which are evident in the activity of neurons in the medial premotor cortex.

SUBMITTER: Martinez-Garcia M

PROVIDER: S-EPMC3136325 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Neural and computational mechanisms of postponed decisions.

Martínez-García Marina M Rolls Edmund T ET Deco Gustavo G Romo Ranulfo R

Proceedings of the National Academy of Sciences of the United States of America 20110627 28

We consider the mechanisms that enable decisions to be postponed for a period after the evidence has been provided. Using an information theoretic approach, we show that information about the forthcoming action becomes available from the activity of neurons in the medial premotor cortex in a sequential decision-making task after the second stimulus is applied, providing the information for a decision about whether the first or second stimulus is higher in vibrotactile frequency. The information ...[more]

PMID: 21709222

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Project description:ImportanceNearly 1 in 3 patients with major depressive disorder who respond to antidepressants relapse within 6 months of treatment discontinuation. No predictors of relapse exist to guide clinical decision-making in this scenario.ObjectivesTo establish whether the decision to invest effort for rewards represents a persistent depression process after remission, predicts relapse after remission, and is affected by antidepressant discontinuation.Design, setting, and participantsThis longitudinal randomized observational prognostic study in a Swiss and German university setting collected data from July 1, 2015, to January 31, 2019, from 66 healthy controls and 123 patients in remission from major depressive disorder in response to antidepressants prior to and after discontinuation. Study recruitment took place until January 2018.ExposureDiscontinuation of antidepressants.Main outcomes and measuresRelapse during the 6 months after discontinuation. Choice and decision times on a task requiring participants to choose how much effort to exert for various amounts of reward and the mechanisms identified through parameters of a computational model.ResultsA total of 123 patients (mean [SD] age, 34.5 [11.2] years; 94 women [76%]) and 66 healthy controls (mean [SD] age, 34.6 [11.0] years; 49 women [74%]) were recruited. In the main subsample, mean (SD) decision times were slower for patients (n?=?74) compared with controls (n?=?34) (1.77 [0.38] seconds vs 1.61 [0.37] seconds; Cohen d?=?0.52; P?=?.02), particularly for those who later relapsed after discontinuation of antidepressants (n?=?21) compared with those who did not relapse (n?=?39) (1.95 [0.40] seconds vs 1.67 [0.34] seconds; Cohen d?=?0.77; P?<?.001). This slower decision time predicted relapse (accuracy?=?0.66; P?=?.007). Patients invested less effort than healthy controls for rewards (F1,98?=?33.970; P?<?.001). Computational modeling identified a mean (SD) deviation from standard drift-diffusion models that was more prominent for patients than controls (patients, 0.67 [1.56]; controls, -0.71 [1.93]; Cohen d?=?0.82; P?<?.001). Patients also showed higher mean (SD) effort sensitivity than controls (patients, 0.31 [0.92]; controls, -0.08 [1.03]; Cohen d?=?0.51; P?=?.05). Relapsers differed from nonrelapsers in terms of the evidence required to make a decision for the low-effort choice (mean [SD]: relapsers, 1.36 [0.35]; nonrelapsers, 1.17 [0.26]; Cohen d?=?0.65; P?=?.02). Group differences generally did not reach significance in the smaller replication sample (27 patients and 21 controls), but decision time prediction models from the main sample generalized to the replication sample (validation accuracy?=?0.71; P?=?.03).Conclusions and relevanceThis study found that the decision to invest effort was associated with prospective relapse risk after antidepressant discontinuation and may represent a persistent disease process in asymptomatic remitted major depressive disorder. Markers based on effort-related decision-making could potentially inform clinical decisions associated with antidepressant discontinuation.

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Neural and computational mechanisms of postponed decisions.

Publications

Neural and computational mechanisms of postponed decisions.

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