The high-conductance state of cortical networks.
We studied the dynamics of large networks of spiking neurons with conductance-based (nonlinear) synapses and compared them to networks with current-based (linear) synapses. For systems with sparse and inhibition-dominated recurrent connectivity, weak external inputs induced asynchronous irregular firing at low rates. Membrane potentials fluctuated a few millivolts below threshold, and membrane conductances were increased by a factor 2 to 5 with respect to the resting state. This combination of parameters characterizes the ongoing spiking activity typically recorded in the cortex in vivo. Many aspects of the asynchronous irregular state in conductance-based networks could be sufficiently well characterized with a simple numerical mean field approach. In particular, it correctly predicted an intriguing property of conductance-based networks that does not appear to be shared by current-based models: they exhibit states of low-rate asynchronous irregular activity that persist for some period of time even in the absence of external inputs and without cortical pacemakers. Simulations of larger networks (up to 350,000 neurons) demonstrated that the survival time of self-sustained activity increases exponentially with network size.
Kumar
Arvind
A
Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, D-79104 Freiburg, Germany. arvind_kumar@brown.edu
Schrader
Sven
S
Aertsen
Ad
A
Rotter
Stefan
S
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002462:Cell Membrane / Q000502:physiology; D002540:Cerebral Cortex / Q000502:physiology*; D003198:Computer Simulation; D003344:Cortical Synchronization; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology; D006801:Humans; D053444:Inhibitory Postsynaptic Potentials / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D009435:Synaptic Transmission / Q000502:physiology*; D013997:Time Factors