Does computational neuroscience need new synaptic learning paradigms?

Computational neuroscience is dominated by a few paradigmatic models, but it remains an open question whether the existing modelling frameworks are sufficient to explain observed behavioural phenomena in terms of neural implementation. We take learning and synaptic plasticity as an example and point to open questions, such as one-shot learning and acquiring internal representations of the world for flexible planning.


Published in:
Current Opinion in Behavioral Sciences
Year:
2016
Publisher:
Amsterdam, Elsevier Science Bv
Laboratories:




 Record created 2016-06-06, last modified 2018-12-03

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