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001014283 1001_ $$0P:(DE-Juel1)186881$$aWybo, Willem A. M.$$b0$$eCorresponding author
001014283 245__ $$aNMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways
001014283 260__ $$aWashington, DC$$bNational Acad. of Sciences$$c2023
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001014283 520__ $$aWhile sensory representations in the brain depend on context, it remains unclearhow such modulations are implemented at the biophysical level, and how processinglayers further in the hierarchy can extract useful features for each possible contex-tual state. Here, we demonstrate that dendritic N-Methyl-D-Aspartate spikes can,within physiological constraints, implement contextual modulation of feedforwardprocessing. Such neuron-specific modulations exploit prior knowledge, encoded instable feedforward weights, to achieve transfer learning across contexts. In a network ofbiophysically realistic neuron models with context-independent feedforward weights,we show that modulatory inputs to dendritic branches can solve linearly nonseparablelearning problems with a Hebbian, error-modulated learning rule. We also demonstratethat local prediction of whether representations originate either from different inputs,or from different contextual modulations of the same input, results in representationlearning of hierarchical feedforward weights across processing layers that accommodatea multitude of contexts.
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001014283 536__ $$0G:(DE-Juel1)jinm60_20190501$$aFunctional Neural Architectures (jinm60_20190501)$$cjinm60_20190501$$fFunctional Neural Architectures$$x6
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001014283 7001_ $$0P:(DE-HGF)0$$aTsai, Matthias C.$$b1
001014283 7001_ $$0P:(DE-Juel1)192408$$aTran, Viet Anh Khoa$$b2$$ufzj
001014283 7001_ $$0P:(DE-HGF)0$$aIlling, Bernd$$b3
001014283 7001_ $$0P:(DE-HGF)0$$aJordan, Jakob$$b4
001014283 7001_ $$0P:(DE-Juel1)151166$$aMorrison, Abigail$$b5
001014283 7001_ $$0P:(DE-HGF)0$$aSenn, Walter$$b6
001014283 773__ $$0PERI:(DE-600)1461794-8$$a10.1073/pnas.2300558120$$gVol. 120, no. 32, p. e2300558120$$n32$$pe2300558120$$tProceedings of the National Academy of Sciences of the United States of America$$v120$$x0027-8424$$y2023
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001014283 8564_ $$uhttps://juser.fz-juelich.de/record/1014283/files/Wybo2023NMDAdrivenDendriticModulationEnablesMultitaskRepresentationLearning.pdf$$yOpenAccess
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