title: Optimal control of transient dynamics in balanced networks supports generation of complex movements.
abstract: Populations of neurons in motor cortex engage in complex transient dynamics of large amplitude during the execution of limb movements. Traditional network models with stochastically assigned synapses cannot reproduce this behavior. Here we introduce a class of cortical architectures with strong and random excitatory recurrence that is stabilized by intricate, fine-tuned inhibition, optimized from a control theory perspective. Such networks transiently amplify specific activity states and can be used to reliably execute multidimensional movement patterns. Similar to the experimental observations, these transients must be preceded by a steady-state initialization phase from which the network relaxes back into the background state by way of complex internal dynamics. In our networks, excitation and inhibition are as tightly balanced as recently reported in experiments across several brain areas, suggesting inhibitory control of complex excitatory recurrence as a generic organizational principle in cortex.
authors.affiliation: School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK. Electronic address: gjeh2@cam.ac.uk.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Hennequin
authors.affiliation: School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; Centre for Neural Circuits and Behaviour, University of Oxford, Oxford OX1 3SR, UK.
authors.forename: Tim P
authors.initials: TP
authors.lastname: Vogels
authors.affiliation: School of Computer and Communication Sciences and Brain Mind Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
authors.forename: Wulfram
authors.initials: W
authors.lastname: Gerstner
mesh_terms: D000818:Animals; D000882:Haplorhini; D009044:Motor Cortex / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D011897:Random Allocation; D055366:Synaptic Potentials / Q000502:physiology*