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Goal-directed decision making with spiking neurons


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Publication Date: 2015

Journal Title: Journal of Neuroscience

Publisher: Society for Neuroscience

Language: English

Type: Article

Metadata: Show full item record

Citation: Friedrich, J., & Lengyel, M. (2015). Goal-directed decision making with spiking neurons. Journal of Neuroscience

Description: This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by the Society for Neuroscience.

Abstract: Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way, and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance, and solves one-step decision making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision making tasks within a second. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, while the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision making tasks with multiple rewards.

Sponsorship: This research was supported by the Swiss National Science Foundation (J.F., Grant PBBEP3 146112) and the Wellcome Trust (J.F. and M.L.).

Embargo Lift Date: 2300-01-01

Identifiers:

This record's URL: https://www.repository.cam.ac.uk/handle/1810/252913





Author: Friedrich, JohannesLengyel, Máté

Source: https://www.repository.cam.ac.uk/handle/1810/252913



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