The impact of a closed-loop thalamocortical model on the spatiotemporal dynamics of cortical and thalamic traveling waves

Propagation of activity in spatially structured neuronal networks has been observed in awake, anesthetized, and sleeping brains. How these wave patterns emerge and organize across brain structures, and how network connectivity affects spatiotemporal neural activity remains unclear. Here, we develop...

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Bibliographic Details
Published in:	Scientific reports 2021-07, Vol.11 (1), p.14359-14359, Article 14359
Main Authors:	Bhattacharya, Sayak, Cauchois, Matthieu B L, Iglesias, Pablo A, Chen, Zhe Sage
Format:	Article
Language:	eng
Subjects:	Algorithms Brain Cerebral Cortex - physiology Computational neuroscience Computer engineering Computer Simulation Electrodes Engineering schools Humans Mathematical models Models, Neurological Models, Theoretical Neural networks Neurons Neurons - metabolism Neurosciences Neurosciences - trends Oscillometry Physiology Simulation Sleep Thalamus Thalamus - physiology Wakefulness
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Summary:	Propagation of activity in spatially structured neuronal networks has been observed in awake, anesthetized, and sleeping brains. How these wave patterns emerge and organize across brain structures, and how network connectivity affects spatiotemporal neural activity remains unclear. Here, we develop a computational model of a two-dimensional thalamocortical network, which gives rise to emergent traveling waves similar to those observed experimentally. We illustrate how spontaneous and evoked oscillatory activity in space and time emerge using a closed-loop thalamocortical architecture, sustaining smooth waves in the cortex and staggered waves in the thalamus. We further show that intracortical and thalamocortical network connectivity, cortical excitation/inhibition balance, and thalamocortical or corticothalamic delay can independently or jointly change the spatiotemporal patterns (radial, planar and rotating waves) and characteristics (speed, direction, and frequency) of cortical and thalamic traveling waves. Computer simulations predict that increased thalamic inhibition induces slower cortical frequencies and that enhanced cortical excitation increases traveling wave speed and frequency. Overall, our results provide insight into the genesis and sustainability of thalamocortical spatiotemporal patterns, showing how simple synaptic alterations cause varied spontaneous and evoked wave patterns. Our model and simulations highlight the need for spatially spread neural recordings to uncover critical circuit mechanisms for brain functions.
ISSN:	2045-2322 2045-2322