[Comp-neuro] New paper on Cortico-striatal plasticity in PLoS Biology

Kevin Gurney k.gurney at sheffield.ac.uk
Fri Jan 23 16:40:15 CET 2015

 This paper integrates  several levels of description - from the synaptic,
through systems modelling, to behaviour.

Gurney, K.N., Humphries, M.D., Redgrave, P., 2015. A New Framework for
Cortico-Striatal Plasticity: Behavioural Theory Meets In Vitro Data at the
Reinforcement-Action Interface. PLoS biology 13, e1002034.

Operant learning requires that reinforcement signals interact with action
representations at a suitable neural interface. Much evidence suggests that
this occurs when phasic dopamine, acting as a reinforcement prediction
error, gates plasticity at cortico-striatal synapses, and thereby changes
the future likelihood of selecting the action(s) coded by striatal neurons.
But this hypothesis faces serious challenges. First, cortico-striatal
plasticity is inexplicably complex, depending on spike timing, dopamine
level, and dopamine receptor type. Second, there is a credit assignment
problem—action selection signals occur long before the consequent dopamine
reinforcement signal. Third, the two types of striatal output neuron have
apparently opposite effects on action selection. Whether these factors rule
out the interface hypothesis and how they interact to produce reinforcement
learning is unknown. We present a computational framework that addresses
these challenges. We first predict the expected activity changes over an
operant task for both types of action-coding striatal neuron, and show they
co-operate to promote action selection in learning and compete to promote
action suppression in extinction. Separately, we derive a complete model of
dopamine and spike-timing dependent cortico-striatal plasticity from in
vitro data. We then show this model produces the predicted activity changes
necessary for learning and extinction in an operant task, a remarkable
convergence of a bottom-up data-driven plasticity model with the top-down
behavioural requirements of learning theory. Moreover, we show the complex
dependencies of cortico-striatal plasticity are not only sufficient but
necessary for learning and extinction. Validating the model, we show it can
account for behavioural data describing extinction, renewal, and
reacquisition, and replicate in vitro experimental data on cortico-striatal
plasticity. By bridging the levels between the single synapse and
behaviour, our model shows how striatum acts as the action-reinforcement

Kevin Gurney, PhD, FSB
Professor of Computational Neuroscience
Adaptive Behaviour Research Group
Department of Psychology, University of Sheffield, S10 2TP, UK

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Stanford University,  and winner of the 1974 Turing Award.
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