Dendritic solutions to the credit assignment problem

•Learning in hierarchical neural networks requires credit assignment.•Credit assignment is difficult if regular inputs mix with credit signals.•Dendritic mechanisms provide potential means of distinguishing credit signals.•Evidence supports credit assignment in apical dendrites of pyramidal neurons....

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Veröffentlicht in:Current opinion in neurobiology 2019-02, Vol.54, p.28-36
Hauptverfasser: Richards, Blake A, Lillicrap, Timothy P
Format: Artikel
Sprache:eng
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Zusammenfassung:•Learning in hierarchical neural networks requires credit assignment.•Credit assignment is difficult if regular inputs mix with credit signals.•Dendritic mechanisms provide potential means of distinguishing credit signals.•Evidence supports credit assignment in apical dendrites of pyramidal neurons. Guaranteeing that synaptic plasticity leads to effective learning requires a means for assigning credit to each neuron for its contribution to behavior. The ‘credit assignment problem’ refers to the fact that credit assignment is non-trivial in hierarchical networks with multiple stages of processing. One difficulty is that if credit signals are integrated with other inputs, then it is hard for synaptic plasticity rules to distinguish credit-related activity from non-credit-related activity. A potential solution is to use the spatial layout and non-linear properties of dendrites to distinguish credit signals from other inputs. In cortical pyramidal neurons, evidence hints that top-down feedback signals are integrated in the distal apical dendrites and have a distinct impact on spike-firing and synaptic plasticity. This suggests that the distal apical dendrites of pyramidal neurons help the brain to solve the credit assignment problem.
ISSN:0959-4388
1873-6882
DOI:10.1016/j.conb.2018.08.003