The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro

Harold Köndgen, Caroline Geisler, Stefano Fusi, Xiao Jing Wang, Hans Rudolf Lüscher, Michele Giugliano

Research output: Contribution to journalArticle

Abstract

Cortical neurons are often classified by current-frequency relationship. Such a static description is inadequate to interpret neuronal responses to time-varying stimuli. Theoretical studies suggested that single-cell dynamical response properties are necessary to interpret ensemble responses to fast input transients. Further, it was shown that input-noise linearizes and boosts the response bandwidth, and that the interplay between the barrage of noisy synaptic currents and the spike-initiation mechanisms determine the dynamical properties of the firing rate. To test these model predictions, we estimated the linear response properties of layer 5 pyramidal cells by injecting a superposition of a small-amplitude sinusoidal wave and a background noise. We characterized the evoked firing probability across many stimulation trials and a range of oscillation frequencies (1-1000 Hz), quantifying response amplitude and phase-shift while changing noise statistics. We found that neurons track unexpectedly fast transients, as their response amplitude has no attenuation up to 200 Hz. This cut-off frequency is higher than the limits set by passive membrane properties (∼50 Hz) and average firing rate (∼20 Hz) and is not affected by the rate of change of the input. Finally, above 200 Hz, the response amplitude decays as a power-law with an exponent that is independent of voltage fluctuations induced by the background noise.

Original languageEnglish (US)
Pages (from-to)2086-2097
Number of pages12
JournalCerebral Cortex
Volume18
Issue number9
DOIs
StatePublished - Sep 1 2008

Keywords

  • Dynamics
  • Frequency response
  • Noise
  • Oscillations
  • Pyramidal cell
  • Somatosensory cortex

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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