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Multiple timescales of normalized value coding underlie adaptive choice behavior.

ABSTRACT: Adaptation is a fundamental process crucial for the efficient coding of sensory information. Recent evidence suggests that similar coding principles operate in decision-related brain areas, where neural value coding adapts to recent reward history. However, the circuit mechanism for value adaptation is unknown, and the link between changes in adaptive value coding and choice behavior is unclear. Here we show that choice behavior in nonhuman primates varies with the statistics of recent rewards. Consistent with efficient coding theory, decision-making shows increased choice sensitivity in lower variance reward environments. Both the average adaptation effect and across-session variability are explained by a novel multiple timescale dynamical model of value representation implementing divisive normalization. The model predicts empirical variance-driven changes in behavior despite having no explicit knowledge of environmental statistics, suggesting that distributional characteristics can be captured by dynamic model architectures. These findings highlight the importance of treating decision-making as a dynamic process and the role of normalization as a unifying computation for contextual phenomena in choice.

SUBMITTER: Zimmermann J

PROVIDER: S-EPMC6086888 | biostudies-other | 2018 Aug

REPOSITORIES: biostudies-other

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Multiple timescales of normalized value coding underlie adaptive choice behavior.

Zimmermann Jan J Glimcher Paul W PW Louie Kenway K

Nature communications 20180810 1

Adaptation is a fundamental process crucial for the efficient coding of sensory information. Recent evidence suggests that similar coding principles operate in decision-related brain areas, where neural value coding adapts to recent reward history. However, the circuit mechanism for value adaptation is unknown, and the link between changes in adaptive value coding and choice behavior is unclear. Here we show that choice behavior in nonhuman primates varies with the statistics of recent rewards. ...[more]

PMID: 30097577

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Project description:The cortex represents information across widely varying timescales. For instance, sensory cortex encodes stimuli that fluctuate over few tens of milliseconds, whereas in association cortex behavioural choices can require the maintenance of information over seconds. However, it remains poorly understood whether diverse timescales result mostly from features intrinsic to individual neurons or from neuronal population activity. This question remains unanswered, because the timescales of coding in populations of neurons have not been studied extensively, and population codes have not been compared systematically across cortical regions. Here we show that population codes can be essential to achieve long coding timescales. Furthermore, we find that the properties of population codes differ between sensory and association cortices. We compared coding for sensory stimuli and behavioural choices in auditory cortex and posterior parietal cortex as mice performed a sound localization task. Auditory stimulus information was stronger in auditory cortex than in posterior parietal cortex, and both regions contained choice information. Although auditory cortex and posterior parietal cortex coded information by tiling in time neurons that were transiently informative for approximately 200?milliseconds, the areas had major differences in functional coupling between neurons, measured as activity correlations that could not be explained by task events. Coupling among posterior parietal cortex neurons was strong and extended over long time lags, whereas coupling among auditory cortex neurons was weak and short-lived. Stronger coupling in posterior parietal cortex led to a population code with long timescales and a representation of choice that remained consistent for approximately 1?second. In contrast, auditory cortex had a code with rapid fluctuations in stimulus and choice information over hundreds of milliseconds. Our results reveal that population codes differ across cortex and that coupling is a variable property of cortical populations that affects the timescale of information coding and the accuracy of behaviour.

Project description:BACKGROUND:Suicidal behavior is associated with impaired decision making in contexts of uncertainty. Existing studies, however, do not definitively address whether suidice attempers have 1) impairment in learning from experience or 2) impairment in choice based on comparison of estimated option values. Our reinforcement learning model-based behavioral study tested these hypotheses directly in middle-aged and older suicide attempters representative of those who die by suicide. METHODS:Two samples (sample 1, n = 135; sample 2, n = 125) of suicide attempters with depression (nattempters = 54 and 39, respectively), suicide ideators, nonsuicidal patients with depression, and healthy control participants completed a probabilistic three-choice decision-making task. A second experiment in sample 2 experimentally dissociated long-term learned value from reward magnitude. Analyses combined computational reinforcement learning and mixed-effects models of decision times and choices. RESULTS:With regard to learning, suicide attempters (vs. all comparison groups) were less sensitive to one-back reinforcement, as indicated by a reduced effect on both choices and decision times. Learning deficits scaled with attempt lethality and were partially explained by poor cognitive control. With regard to value-based choice, suicide attempters (vs. all comparison groups) displayed abnormally long decision times when choosing between similarly valued options and were less able to distinguish between the best and second-best options. Group differences in value-based choice were robust to controlling for cognitive performance, comorbidities, impulsivity, psychotropic exposure, and possible brain damage from attempts. CONCLUSIONS:Serious suicidal behavior is associated with impaired reward learning, likely undermining the search for alternative solutions. Attempted suicide is associated with impaired value comparison during the choice process, potentially interfering with the consideration of deterrents and alternatives in a crisis.

Dataset Information

Multiple timescales of normalized value coding underlie adaptive choice behavior.

Publications

Multiple timescales of normalized value coding underlie adaptive choice behavior.

Similar Datasets

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