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bioRxiv Preprint Server

203 papers in the library · 588 citations · publishing 2015-2026

Papers

COALIA: a computational model of human EEG for consciousness research

bioRxiv Preprint Server March 12, 2019 Siouar Bensaid, Julien Modolo, Isabelle Merlet et al. preprint

A computational model called COALIA simulates human cortical micro-circuits, including specific neuron types and thalamo-cortical regulation of cortico-cortical connectivity. The model generates EEG that matches brain rhythms recorded in humans during wakefulness and sleep. It reproduces disynaptic disinhibition of basket cells and pyramidal neurons via long-range activation of VIP interneurons. The model predicts that thalamic output strength and dynamics control local and long-range cortical information processing. It also reproduces and explains clinical TMS-evoked EEG complexity in disorders of consciousness patients and healthy volunteers through modulation of thalamo-cortical connectivity governing cortico-cortical communication.

Dissociating neural activity associated with the subjective phenomenology of monocular stereopsis: an EEG study

bioRxiv Preprint Server January 30, 2019 Makoto Uji, Ines Jentzsch, James Redburn et al. preprint

The vivid sense of depth and solidity that defines stereopsis is usually attributed to the brain's processing of binocular disparity. However, the same impression can occur when viewing a picture with one eye through a small hole. By measuring EEG brain activity while people looked at images of 2D and 3D shapes under different viewing conditions, a specific pattern of neural activity was identified that accompanied this qualitative depth experience. Only the monocular aperture condition, which produces the strongest depth impression, showed elevated gamma-band synchronization in the parietal cortex when comparing 3D to 2D shapes. This suggests that the subjective experience of stereopsis involves neural processes distinct from those that compute binocular disparity.

The emergence of integrated information, complexity, and consciousness at criticality

bioRxiv Preprint Server January 15, 2019 Sina Khajehabdollahi, Pubuditha M. Abeyasinghe, Adrian M. Owen et al. preprint

Using the critical Ising model of the brain, integrated information—a measure of consciousness—was measured in toy models of generic neural networks. Monte Carlo simulations were run on 159 random weighted networks analogous to small 5-node neural network motifs. Integrated information, as a type of order parameter like magnetism, undergoes a phase transition at the model's critical point, where the system's 'consciousness' is maximally susceptible to perturbations and on the boundary between ordered and disordered forms. This adds evidence that the emergence of consciousness coincides with self-organized criticality, evolution, the emergence of complexity, and the integration of complex systems.