Unveiling the Role of Thalamic Core-Matrix Functional Architecture in Loss of Consciousness

2471 

Abstract Submission 

Zirui Huang¹, George Mashour¹, Anthony Hudetz¹

¹University of Michigan, Ann Arbor, MI

Zirui Huang  
University of Michigan
Ann Arbor, MI

George Mashour  
University of Michigan
Ann Arbor, MI

Anthony Hudetz  
University of Michigan
Ann Arbor, MI

Human neuroimaging data and biophysical modeling simulations suggest that loss of consciousness during general anesthesia is attributed to a targeted suppression of nonspecific, higher order thalamocortical connectivity (Liu et al., 2013; Munn et al., 2023). However, previous research predominantly examined the thalamus as a whole or concentrated on specific subregions, neglecting the identity of distinct neuronal subpopulations. The thalamus, characterized by a heterogeneous cytoarchitecture, comprises at least two discernible cell classes known as core and matrix cells, each sending distinct projections to the cortex. Given the widespread distribution of core and matrix cells throughout the thalamus from lower-order and higher-order nuclei, a comprehensive exploration of the spatial distribution of thalamocortical connectivity with a specific emphasis on the core-matrix architecture is justified. We hypothesized that loss of consciousness due to anesthesia would be associated with a disruption of core–matrix functional architecture of thalamocortical connectivity.

We performed functional magnetic resonance imaging (fMRI) investigation in twenty-seven healthy volunteers under conscious baseline, deep sedation, and the subsequent recovery phase. Deep sedation was achieved through a gradual increase of the effect site concentration of the anesthetic propofol until behavioral responsiveness was lost. We advanced the functional gradient mapping method (Margulies et al., 2016) to map the functional geometry of thalamocortical circuits by aligning it with the unimodal-transmodal functional axis of the cortex. First, we utilized cortical gradient mapping to transform the functional brain connectome into a non-linear diffusion space. Second, we examined the thalamic correlates of the unimodal-transmodal cortical gradient. We computed pair-wise correlations between the thalamocortical connectivity values of each thalamic voxel and the cortical gradient values, ultimately generating a topographical map of thalamocortical correlation coefficients. This map highlighted the correlations with the principal cortical gradient and was referred to as the gradient correlation coefficient (GCC). To determine the relative contributions of core and matrix cells in explaining the variations in GCC between conscious and unconscious states, we conducted a multiple regression analysis within a general linear model framework. In this analysis, we integrated the spatial densities of two calcium-binding proteins, Calbindin (abundant in matrix cells) and Parvalbumin (prevalent in core cells), provided by the Allen Human Brain Atlas (Hawrylycz et al., 2012; Müller et al., 2020), as covariates while considering the GCC difference between conscious and unconscious states as the dependent variable.

We found that unconsciousness was associated with specific alterations in a functional hierarchy within thalamocortical circuits. Namely, there was a shift from a balanced unimodal-transmodal geometry during consciousness to a dominantly unimodal geometry during unconsciousness. This shift in functional geometry was depended on the spatial distribution of matrix cells within the thalamus. Specifically, thalamic regions with a high density of matrix cells exhibited a pronounced reduction in transmodal thalamocortical functional connectivity during unconsciousness.

Propofol-induced loss of consciousness is accompanied by a shift from balanced core–matrix functional geometry to unimodal core dominance. By synthesizing cellular-level data with systems-level findings, our research illuminates the pivotal role of thalamic matrix cells in understanding the neural mechanisms of states of consciousness.

fMRI Connectivity and Network Modeling

Task-Independent and Resting-State Analysis ²

Subcortical Structures

Consciousness and Awareness ¹

Consciousness

Cortex

Data analysis

FUNCTIONAL MRI

Thalamus