Top-Down Influences on Local Networks: Basic Theory with Experimental Implications

Ramesh Srinivasan,Paul L Nunez,Samuel Thorpe

doi:10.3389/fncom.2013.00029

Abstract

The response of a population of cortical neurons to an external stimulus depends not only on the receptive field properties of the neurons, but also the level of arousal and attention or goal-oriented cognitive biases that guide information processing. These top-down effects on cortical neurons bias the output of the neurons and affect behavioral outcomes such as stimulus detection, discrimination, and response time. In any physiological study, neural dynamics are observed in a specific brain state; the background state partly determines neuronal excitability. Experimental studies in humans and animal models have also demonstrated that slow oscillations (typically in the alpha or theta bands) modulate the fast oscillations (gamma band) associated with local networks of neurons. Cross-frequency interaction is of interest as a mechanism for top-down or bottom up interactions between systems at different spatial scales. We develop a generic model of top-down influences on local networks appropriate for comparison with EEG. EEG provides excellent temporal resolution to investigate neuronal oscillations but is space-averaged on the cm scale. Thus, appropriate EEG models are developed in terms of population synaptic activity. We used the Wilson–Cowan population model to investigate fast (gamma band) oscillations generated by a local network of excitatory and inhibitory neurons. We modified the Wilson–Cowan equations to make them more physiologically realistic by explicitly incorporating background state variables into the model. We found that the population response is strongly influenced by the background state. We apply the model to reproduce the modulation of gamma rhythms by theta rhythms as has been observed in animal models and human ECoG and EEG studies. The concept of a dynamic background state presented here using the Wilson–Cowan model can be readily applied to incorporate top-down modulation in more detailed models of specific cortical systems.

Highlights

A fundamental question in any neurophysiological study is whether observed modulations of neural responses in cortex by cognitive processes are the result of the action of a local network or due to the interactions between this local network and the rest of the brain in global networks
As one important “window on the mind,” EEG has long provided a critical tool in pursuit of connecting neural dynamics to cognitive processes
The essence of our approach is to immerse the local network in a dynamic background state

Summary

Introduction

A fundamental question in any neurophysiological study is whether observed modulations of neural responses in cortex by cognitive processes are the result of the action of a local network or due to the interactions between this local network and the rest of the brain in global networks. Even when signals are recorded from a small number of neurons (or even just one neuron) the observed dynamics result both from the intrinsic properties of the local network and from the influence of other neurons located in nearby or even distant cortex (Mountcastle, 1997) This simple distinction can be understood in terms of behavior – the response of neurons to inputs depends on the receptive field of the neurons and on the level of arousal, typically by the action of neuromodulators, and attention or goal-oriented cognitive biases that guide information processing. Detailed models may not lead to generalized principles that can potentially guide experimental studies in a variety of behavioral contexts; detailed cellular models are not compared

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