Connectivity reflects coding: a model of voltage-based STDP with homeostasis.
Electrophysiological connectivity patterns in cortex often have a few strong connections, which are sometimes bidirectional, among a lot of weak connections. To explain these connectivity patterns, we created a model of spike timing-dependent plasticity (STDP) in which synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential, filtered with two different time constants. Our model describes several nonlinear effects that are observed in STDP experiments, as well as the voltage dependence of plasticity. We found that, in a simulated recurrent network of spiking neurons, our plasticity rule led not only to development of localized receptive fields but also to connectivity patterns that reflect the neural code. For temporal coding procedures with spatio-temporal input correlations, strong connections were predominantly unidirectional, whereas they were bidirectional under rate-coded input with spatial correlations only. Thus, variable connectivity patterns in the brain could reflect different coding principles across brain areas; moreover, our simulations suggested that plasticity is fast.
Clopath
Claudia
C
Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. claudia.clopath@epfl.ch
Büsing
Lars
L
Vasilaki
Eleni
E
Gerstner
Wulfram
W
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006706:Homeostasis / Q000502:physiology*; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D016012:Poisson Distribution; D017729:Presynaptic Terminals / Q000502:physiology; D013997:Time Factors; D014793:Visual Cortex / Q000502:physiology