Abstract
Transfers of large-scale neural activity into, within and between corticothalamic neural populations and brain hemispheres are analysed using time-integrated transfer functions and state parameters obtained from neural field theory for a variety of arousal states. It is shown that the great majority of activity results from feedbacks within the corticothalamic system, including significant transfer between hemispheres, but only a small minority arises via net input from the external world, with the brain thus in a near-critical, highly introspective state. Notably, the total excitatory and inhibitory influences on cortical neurons are balanced to within a few per cent across arousal states. Strong negative intrahemispheric feedforward exists to the cortex, and even larger interhemispheric positive feedforward, but these are modified by feedback loops to yield near-critical positive overall gain. The results underline the utility of transfer functions for the analysis of brain activity.
Highlights
Work over the last two decades has shown that the great majority of spikes that reach a given cortical neuron are not the result of direct input, nor even a direct chain of feedforward relays from the outside world, but are largely the outcome of recirculation of activity within the brain that leads to a near-critical state in humans, as confirmed by electroencephalography (EEG) of up to 1500 subjects and by functional magnetic resonance imaging [1,2,3,4,5,6,7,8,9,10,11]
In functional connectivity simulations [2,3,5,6,7,10,19] artificial cell culture experiments saw related avalanche behaviour [12], and other authors have argued for slightly subcritical dynamics on the basis of spiking avalanches observed in animals [13]
We have used neural field transfer functions to analyse the transfer, stability and balance of large-scale, time-integrated activity into, within and between corticothalamic populations and hemispheres, using gain parameters found for various brain states in prior studies
Summary
Work over the last two decades has shown that the great majority of spikes that reach a given cortical neuron are not the result of direct input, nor even a direct chain of feedforward relays from the outside world, but are largely the outcome of recirculation of activity within the brain that leads to a near-critical state in humans, as confirmed by electroencephalography (EEG) of up to 1500 subjects and by functional magnetic resonance imaging (fMRI) [1,2,3,4,5,6,7,8,9,10,11]. Based neural field theory (NFT) is well suited to analysis of large-scale brain dynamics, including inference of gains. It has yielded gain values for a range of arousal states through fits of its predictions to experimental EEG spectra [1,2,3,7] and fits of its predictions of activity eigenmodes and eigenvalues to fMRI data [6,8]. This allows us to obtain expressions for feedforward and total gains in the system.
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