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10.7554/eLife.20944 http://scihub22266oqcxt.onion/10.7554/eLife.20944 C5380437!5380437!28374674     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       eLife 2017 ; 6 (ä): ä Nephropedia Template TP {{tp|p=28374674|t=2017. Rules and mechanisms for efficient two-stage learning in neural circuits |pdf=|usr=}}{{28374674}} gab.com Text Rules and mechanisms for efficient two-stage learning in neural circuits JO: eLife http://www.kidney.de/pget.php?&tw=1&pmid=28374674 #FOAvip Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ?tutor? circuits (e.g., LMAN) should match plasticity mechanisms in ?student? circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.DOI:http://dx.doi.org/10.7554/eLife.20944.001 Twit Text FOAVip Rules and mechanisms for efficient two-stage learning in neural circuits ????eLife http://www.kidney.de/pget.php?&tw=1&pmid=28374674 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28374674 #FOAvip English Wikipedia <ref>{{Cite pmid|28374674}}</ref> Rules and mechanisms for efficient two-stage learning in neural circuits #MMPMID28374674 Te?ileanu T; Ölveczky B; Balasubramanian V eLife 2017[]; 6 (ä): ä PMID28374674show ga Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ?tutor? circuits (e.g., LMAN) should match plasticity mechanisms in ?student? circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.DOI:http://dx.doi.org/10.7554/eLife.20944.001 äRules and mechanisms for efficient two-stage learning in neural circui(epmc).pdf DeepDyve Pubget Overpricing