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Journal Article

Ultrafast Population Encoding by Cortical Neurons

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Tchumatchenko,  Tatjana
Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Wolf,  Fred
Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Tchumatchenko, T., Malyshev, A., Wolf, F., & Volgushev, M. (n.d.). Ultrafast Population Encoding by Cortical Neurons. The Journal of Neuroscience, 31, 12171-12179. doi:10.1523/​JNEUROSCI.2182-11.2011.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-17EA-9
Abstract
The processing speed of the brain depends on the ability of neurons to rapidly relay input changes. Previous theoretical and experimental studies of the timescale of population firing rate responses arrived at controversial conclusions, some advocating an ultrafast response scale but others arguing for an inherent disadvantage of mean encoded signals for rapid detection of the stimulus onset. Here we assessed the timescale of population firing rate responses of neocortical neurons in experiments performed in the time domain and the frequency domain in vitro and in vivo. We show that populations of neocortical neurons can alter their firing rate within 1 ms in response to somatically delivered weak current signals presented on a fluctuating background. Signals with amplitudes of miniature postsynaptic currents can be robustly and rapidly detected in the population firing.Wefurther show that population firing rate of neurons of rat visual cortex in vitro and cat visual cortex in vivo can reliably encode weak signals varying at frequencies up to ~200 –300 Hz, or ~50 times faster than the firing rate of individual neurons. These results provide coherent evidence for the ultrafast, millisecond timescale of cortical population responses. Notably, fast responses to weak stimuli are limited to the mean encoding. Rapid detection of current variance changes requires extraordinarily large signal amplitudes. Our study presents conclusive evidence showing that cortical neurons are capable of rapidly relaying subtle mean current signals. This provides a vital mechanism for the propagation of rate-coded information within and across brain areas.