A computational investigation of the relationships between single-neuron and network dynamics in the cerebral cortex

TL;DR

This paper develops mathematical models and statistical tools to understand how single-neuron activities relate to and influence the overall network dynamics in the cerebral cortex, bridging microscopic and macroscopic neural measures.

Contribution

It introduces new network models and analysis techniques that clarify the impact of single-neuron dynamics on population-level neural signals like LFP and EEG.

Findings

Identified robust mathematical rules to infer single-neuron firing from mass signals.

Developed models linking microscopic neuron activity to mesoscopic and macroscopic neural signals.

Applied methods to mouse neocortex data, revealing general relationships between neuron firing and circuit activity.

Abstract

Functions of brain areas in complex animals are believed to rely on the dynamics of networks of neurons rather than on single neurons. On the other hand, the network dynamics reflect and arise from the integration and coordination of the activity of populations of single neurons. Understanding how single-neurons and neural-circuits dynamics complement each other to produce brain functions is thus of paramount importance. LFPs and EEGs are good indicators of the dynamics of mesoscopic and macroscopic populations of neurons, while microscopic-level activities can be documented by measuring the membrane potential, the synaptic currents or the spiking activity of individual neurons. In this thesis we develop mathematical modelling and mathematical analysis tools that can help the interpretation of joint measures of neural activity at microscopic and mesoscopic or macroscopic scales. In particular, we develop network models of recurrent cortical circuits that can clarify the impact of several aspects of single-neuron (i.e., microscopic-level) dynamics on the activity of the whole neural population (as measured by LFP). We then develop statistical tools to characterize the relationship between the action potential firing of single neurons and mass signals. We apply these latter analysis techniques to joint recordings of the firing activity of individual cell-type identified neurons and mesoscopic (i.e., LFP) and macroscopic (i.e., EEG) signals in the mouse neocortex. We identified several general aspects of the relationship between cell-specific neural firing and mass circuit activity, providing for example general and robust mathematical rules which infer single-neuron firing activity from mass measures such as the LFP and the EEG.