Pattern segmentation with activity dependent natural frequency shift and sub-threshold resonance.
Understanding the mechanisms underlying distributed pattern formation in brain networks and its content driven dynamical segmentation is an area of intense study. We investigate a theoretical mechanism for selective activation of diverse neural populations that is based on dynamically shifting cellular resonances in functionally or structurally coupled networks. We specifically show that sub-threshold neuronal depolarization from synaptic coupling or external input can shift neurons into and out of resonance with specific bands of existing extracellular oscillations, and this can act as a dynamic readout mechanism during information storage and retrieval. We find that this mechanism is robust and suggest it as a general coding strategy that can be applied to any network with oscillatory nodes.
Applied Physics Program, University of Michigan - Ann Arbor 48109, USA.
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Shtrahman
1] Department of Physics, University of Michigan - Ann Arbor 48109, USA [2] Biophysics Program, University of Michigan - Ann Arbor 48109, USA.
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M
Zochowski
D000818:Animals; D019521:Body Patterning / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*