Abstract
Understanding the origin of the main physiological processes involved in consciousness is a major challenge of contemporary neuroscience, with crucial implications for the study of Disorders of Consciousness (DOC). The difficulties in achieving this task include the considerable quantity of experimental data in this field, along with the non-intuitive, nonlinear nature of neuronal dynamics. One possibility of integrating the main results from the experimental literature into a cohesive framework, while accounting for nonlinear brain dynamics, is the use of physiologically-inspired computational models. In this study, we present a physiologically-grounded computational model, attempting to account for the main micro-circuits identified in the human cortex, while including the specificities of each neuronal type. More specifically, the model accounts for thalamo-cortical (vertical) regulation of cortico-cortical (horizontal) connectivity, which is a central mechanism for brain information integration and processing. The distinct neuronal assemblies communicate through feedforward and feedback excitatory and inhibitory synaptic connections implemented in a template brain accounting for long-range connectome. The EEG generated by this physiologically-based simulated brain is validated through comparison with brain rhythms recorded in humans in two states of consciousness (wakefulness, sleep). Using the model, it is possible to reproduce the local disynaptic disinhibition of basket cells (fast GABAergic inhibition) and glutamatergic pyramidal neurons through long-range activation of vasoactive intestinal-peptide (VIP) interneurons that induced inhibition of somatostatin positive (SST) interneurons. The model (COALIA) predicts that the strength and dynamics of the thalamic output on the cortex control the local and long-range cortical processing of information. Furthermore, the model reproduces and explains clinical results regarding the complexity of transcranial magnetic stimulation TMS-evoked EEG responses in DOC patients and healthy volunteers, through a modulation of thalamo-cortical connectivity that governs the level of cortico-cortical communication. This new model provides a quantitative framework to accelerate the study of the physiological mechanisms involved in the emergence, maintenance and disruption (sleep, anesthesia, DOC) of consciousness.
Highlights
The characterization and understanding of the mechanisms underlying consciousness is one, if not the greatest challenge that contemporary neuroscience is facing
Neural mass models (NMMs) can model the local field potential (LFP) of an entire cortical region using only few state variables (Breakspear, 2017), whereas in detailed models this activity is meticulously described at the level of spatially distributed and interconnected neuron models, each including the properties of ionic channels, axons and dendrites (Wang and Buzsáki, 1996; Whittington et al, 2000; Maex and De Schutter, 2007)
Formal Description of Neocortical Model Based on the above information, we have developed a neocortical module involving pyramidal cells (PCs) and three types of inhibitory subpopulations, namely, basket cells (BC), somatostatin positive (SST) and vasoactive intestinal-peptide (VIP)
Summary
The characterization and understanding of the mechanisms underlying consciousness is one, if not the greatest challenge that contemporary neuroscience is facing. One of the first theories that found a significant echo in the neuroscience community is the Dynamic Core Hypothesis (DCH; Tononi and Edelman, 1998), which was the first to relate the concept of information with consciousness In this theory, functional clusters in the thalamocortical system are central, and involve fast re-entrant interactions, as well as a high level of integration and differentiation giving rise to complex patterns of neuronal activity. Segregation, or differentiation of information, is key in IIT: for example, large-scale synchronization of several regions with the same activity is integrated, with low complexity (Koch et al, 2016). The ‘‘awareness’’ component of consciousness depends on large-scale synchronized communication among distant neuronal populations distributed over the neocortex (see Figure 1A, left panel)
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