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Abstract
The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low-dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an “energy” variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising KATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛp, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛp could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed “neuron-energy” unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as non-invasive brain stimulation for stroke patients.
Highlights
A key tenet of the contemporary neuroscience states that neurons constitute the primary units of brain’s information processing networks
Both the models show bursting under low ɛp and moderate Iext conditions, thereby suggesting metabolic basis of bursting. We demonstrate this effect in Model 1, wherein low ɛp conditions result in activations of KATP channels and show bursting at some moderate values of Iext
Low ɛp is thought to represent the “metabolically compromised” network state and depicts that lower frequencies local field potential (LFP) dominate. This is similar to that observed under propofolanesthetic conditions [associated with reduced metabolism [58, 59]], which is characterized by decreased LFP power [60,61,62]
Summary
A key tenet of the contemporary neuroscience states that neurons constitute the primary units of brain’s information processing networks. There is growing evidence suggesting an imperative role of the “other brain” in sustaining the brain’s physiological activity [2,3,4]. This other brain comprises the glial cells that occupy around half of the brain’s volume, though the exact numbers and neuron/glia ratio vary across the brain [5,6,7,8]. There are significant studies speculating on the contributions of glial cells in brain’s computations [21, 22]
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