Chronic and Acute Stress Promote Overexploitation in Serial Decision Making

Abstract

Many decisions that humans make resemble foraging problems in which a currently available, known option must be weighed against an unknown alternative option. In such foraging decisions, the quality of the overall environment can be used as a proxy for estimating the value of future unknown options against which current prospects are compared. We hypothesized that such foraging-like decisions would be characteristically sensitive to stress, a physiological response that tracks biologically relevant changes in environmental context. Specifically, we hypothesized that stress would lead to more exploitative foraging behavior. To test this, we investigated how acute and chronic stress, as measured by changes in cortisol in response to an acute stress manipulation and subjective scores on a questionnaire assessing recent chronic stress, relate to performance in a virtual sequential foraging task. We found that both types of stress bias human decision makers toward overexploiting current options relative to an optimal policy. These findings suggest a possible computational role of stress in decision making in which stress biases judgments of environmental quality.

Lactobacillus plantarumMTCC 9510 supplementation protects from chronic unpredictable and sleep deprivation-induced behaviour, biochemical and selected gut microbial aberrations in mice

“…Various neurobehavioral despair such as anxiety, depression, compulsive behaviours and loss of cognitive functions precipitated by various stresses have already been described (Kumar et al 2011;Chanana and Kumar 2016;Petit et al 2016;Lenow et al 2017;Mataix-Cols et al 2017;Perez et al 2017;Zhukovsky et al 2017). We also observed reduction in the spontaneous motor activity along with a concomitant increase in immobility time in the FST and TST which reflects a state of behavioural despair.…”

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“…Recent work in humans further resolves the computational challenge of learning dynamic environmental richness, by demonstrating that sequential choice behavior is best captured by an MVT inspired learning model. Specifically, both decisions to leave a patch and explore the environment in patch foraging (Constantino and Daw, 2015;Lenow et al, 2017) and capture behavior in prey selection (Garrett and Daw, 2019) adhere to the MVT predicted optimality policy that compares yields against fluctuating environmental richness which is learned via a standard delta rule. This later work further demonstrated that beliefs about environmental richness update with asymmetric bias, whereby improvements are learned at a higher rate than deteriorations; the 'naïve perseverance of optimism' (Garrett and Daw, 2019).…”

“…In addition, contexts like the boom and downturn examples above rarely remain in steady-state, further requiring perturbation-driven behaviour adjustments. Recent work in humans resolves both issues, by demonstrating that sequential choice behaviour is best captured by an MVT inspired learning model (Constantino & Daw, 2015;Garrett & Daw, 2019;Lenow, Constantino, Daw & Phelps, 2017). Specifically, the decision to depart one patch of potential resources to harvest in another during a dynamic patch foraging task is predicated on a leave threshold, defined as the harvest sacrificed when leaving.…”

“…Specifically, the decision to depart one patch of potential resources to harvest in another during a dynamic patch foraging task is predicated on a leave threshold, defined as the harvest sacrificed when leaving. The threshold adheres to an optimality policy that compares harvests against fluctuating environmental richness (i.e., the average starting yield of iteratively depleting patches) which are learned via a standard delta rule (Constantino & Daw, 2015;Lenow et al, 2017). Garrett and Daw (2019) later extended the application of MVT learning models to a prey selection task, and demonstrated that sequential capture behaviour also adheres to trialwise appraisal of prey quality relative to learned beliefs about fluctuating environmental richness (i.e., the concentration of hi or low quality prey).…”

“…Dynamic changes of their stress state may serve as an implicit indicator of their appraisal of the environment and could potentially telegraph learning dependent shifts in selection criteria. At present only one study has indirectly explored the relationship of stress related endocrine activity and foraging behaviour by linking both acute and chronic stress elevation to overharvesting tendencies in a patch foraging task (Lenow et al, 2017). However, the main assays in that study (cortisol and self-report) probed stress fluctuations operating on longer time horizons than the time scales associated with faster acting learning needed to update beliefs about environmental richness.…”