Inhibitory Modulation of Cortical Up States

Abstract

The balance between excitation and inhibition is critical in the physiology of the cerebral cortex. To understand the influence of inhibitory control on the emergent activity of the cortical network, inhibition was progressively blocked in a slice preparation that generates spontaneous rhythmic up states at a similar frequency to those occurring in vivo during slow-wave sleep or anesthesia. Progressive removal of inhibition induced a parametric shortening of up state duration and elongation of the down states, the frequency of oscillations decaying. Concurrently, a gradual increase in the network firing rate during up states occurred. The slope of transitions between up and down states was quantified for different levels of inhibition. The slope of upward transitions reflects the recruitment of the local network and was progressively increased when inhibition was decreased, whereas the speed of activity propagation became faster. Removal of inhibition eventually resulted in epileptiform activity. Whereas gradual reduction of inhibition induced linear changes in up/down states and their propagation, epileptiform activity was the result of a nonlinear transformation. A computational network model showed that strong recurrence plus activity-dependent hyperpolarizing currents were sufficient to account for the observed up state modulations and predicted an increase in activity-dependent hyperpolarization following up states when inhibition was decreased, which was confirmed experimentally.

Exploring the spectrum of dynamical regimes and timescales in spontaneous cortical activity

“…Such preferred states are particularly evident in the bimodal distribution of MUA during time in logarithmic scale in Fig. 3c, usually observed in Up/Down slow oscillations experiments (Sanchez-Vives et al 2008;Sanchez-Vives et al 2010;Reig et al 2010).…”

“…1d, e is obtained, the residence times in one of the two preferred states (Up or Down) have approximately an exponential distribution (Gigante et al 2007;Martí et al 2008;Mejias et al 2010), in analogy to the problem of the diffusion over a barrier (Risken 1989). On the other hand, slow oscillation in vitro are quite regular with a relatively low coefficient of variation (Sanchez-Vives and McCormick 2000; Sanchez-Vives et al 2008;Sanchez-Vives et al 2010;Reig et al 2010), as shown in Fig. 3d for an example recording.…”

Overexpression ofDyrk1A, a Down Syndrome Candidate, Decreases Excitability and Impairs Gamma Oscillations in the Prefrontal Cortex

“…The relative firing rate was taken as the MUA value of the peak corresponding to UP states after normalizing MUA to be zero during DOWN periods. Detected transitions were used to compute the statistics of UP and DOWN state durations and upward transition slope, as well as to characterize propagation modes of traveling waves in multielectrode recordings (for details, see Reig et al, 2010;Sanchez-Vives et al, 2010;Ruiz-Mejias et al, 2011). Power spectral density was estimated relying on a standard Welch's method.…”

“…It encodes a serine/ threonine kinase highly expressed in the brain and plays key roles in cell proliferation and survival, neuronal differentiation, synaptic plasticity, and neurodegeneration (for review, see Park et al, 2009;Tejedor and Hammerle, 2011;. Altered expression levels of DYRK1A produce cognitive impairment and neuronal alterations linked to intellectual disability .…”

“…Altered expression levels of DYRK1A produce cognitive impairment and neuronal alterations linked to intellectual disability . DYRK1A haploinsufficiency in partial monosomy of chromosome 21 in humans (HSA21) leads to microcephaly and intellectual disability (Møller et al, 2008;van Bon et al, 2011;Courcet et al, 2012;Ji et al, 2015). Altered learning and memory and neuronal microarchitecture are also present in heterozygous Dyrk1A mice (Fotaki et al, 2002;Benavides-Piccione et al, 2005).…”