Input-output transformations in the awake mouse brain using whole-cell recordings and probabilistic analysis

Abstract

The activity of cortical neurons in awake brains changes dynamically as a function of the behavioural and attentional state. The primary motor cortex (M1) plays a central role in regulating complex motor behaviors. Despite a growing knowledge on its connectivity and spiking pattern, little is known about intra-cellular mechanism and rhythms underlying motor-command generation. In the last decade, whole-cell recordings in awake animals has become a powerful tool for characterising both sub-and supra-threshold activity during behaviour. Seminal in vivo studies have shown that changes in input structure and sub-threshold regime determine spike output during behaviour (input-output transformations). In this thesis I make use of computational and experimental techniques to better understand (i) how the brain regulates the sub-threshold activity of the neurons during movement and (ii) how this reflects in their input-output transformation properties. In the first part of this work I present a novel probabilistic technique to infer input statistics from in-vivo voltage-clamp traces. This approach, based on Bayesian belief networks, outperforms current methods and allows an estimation of synaptic input (i) kinetic properties, (ii) frequency, and (iii) weight distribution. I first validate the model on simulated data, thus I apply it to voltage-clamp recordings of cerebellar interneurons in awake mice. I found that synaptic weight distributions have long tails, which on average do not change during movement. Interestingly, the increase in synaptic current observed during movement is a consequence of the increase in input frequency only. In the second part, I study how the brain regulates the activity of pyramidal neurons in the M1 of awake mice during movement. I performed whole-cell recordings of pyramidal neurons in layer 5B (L5B), which represent one of the main descending output channels from motor cortex. I found that slow large-amplitude membrane potential fluctuations, typical of quiet periods, were suppressed in all L5B pyramidal neurons during movement, which by itself reduced membrane potential (Vm) variability, input sensitivity and output firing rates. However, a sub-population of L5B neurons ( 50%) concurrently experienced an increase in excitatory drive that depolarized mean Vm, enhanced input sensitivity and elevated firing rates. Thus, movement-related bidirectional modulation in L5B neurons is mediated by two opposing mechanisms: 1) a global reduction in network driven Vm variability and 2) a coincident, targeted increase in excitatory drive to a subpopulation of L5B neurons.