Dynamical Response Properties of Neocortical Neuron Ensembles: Multiplicative versus Additive Noise

Abstract

To understand the mechanisms of fast information processing in the brain, it is necessary to determine how rapidly populations of neurons can respond to incoming stimuli in a noisy environment. Recently, it has been shown experimentally that an ensemble of neocortical neurons can track a time-varying input current in the presence of additive correlated noise very fast, up to frequencies of several hundred hertz. Modulations in the firing rate of presynaptic neuron populations affect, however, not only the mean but also the variance of the synaptic input to postsynaptic cells. It has been argued that such modulations of the noise intensity (multiplicative modulation) can be tracked much faster than modulations of the mean input current (additive modulation). Here, we compare the response characteristics of an ensemble of neocortical neurons for both modulation schemes. We injected sinusoidally modulated noisy currents (additive and multiplicative modulation) into layer V pyramidal neurons of the rat somatosensory cortex and measured the trial and ensemble-averaged spike responses for a wide range of stimulus frequencies. For both modulation paradigms, we observed low-pass behavior. The cutoff frequencies were markedly high, considerably higher than the average firing rates. We demonstrate that modulations in the variance can be tracked significantly faster than modulations in the mean input. Extremely fast stimuli (up to 1 kHz) can be reliably tracked, provided the stimulus amplitudes are sufficiently high.

Static frequency tuning accounts for changes in neural synchrony evoked by transient communication signals

“…Because P-unit action potentials lock onto the EOD (Hagiwara and Morita 1963), their membrane time constant is likely to be shorter than a single EOD period (ϳ1 ms) and thus potentially explains the ability of the P-units to quickly follow such a mean-coded signal. Cortical neurons also have been shown to rapidly follow mean-coded signals (Boucsein et al 2009;Tchumatchenko et al 2011). A variancecoded transmission that was suggested for rapid signal transmission (Silberberg et al 2004) is therefore not required.…”

How Connectivity, Background Activity, and Synaptic Properties Shape the Cross-Correlation between Spike Trains

“…The linear response function R E to input current modulations of different frequencies has been studied theoretically (Brunel et al, 2001;Fourcaud-Trocmé et al, 2003;Richardson, 2007) and experimentally (Köndgen et al, 2008;Boucsein et al, 2009), whereas its equivalent in time R E is closely related to the Wiener kernel (Poliakov et al, 1997) and the STA current of the neuron (Paninski, 2006;Badel et al, 2008a) (see Appendix). For both LIF and EIF models, the response R E to modulated current is essentially a low-pass filter, the cutoff frequency of which decreases with increasing background synaptic noise.…”

Action potential initiation in a multi-compartmental model with cooperatively gating Na channels in the axon initial segment

“…It was shown that the onset rapidness could be an indirect measure of cut-off frequency (Fourcaud-Trocme et al 2003). Furthermore, the recent in vitro studies provided information about high cut-off frequencies of real neurons (Köndgen et al 2008;Boucsein et al 2009) and a recent theoretical work reported that smaller timescales at the AP onset help to reproduce such high cut-off frequencies (Wei and Wolf 2011). Combining these results, it can be concluded that very rapid onsets, i.e.…”