Poster No:
2019
Submission Type:
Abstract Submission
Authors:
Hyunwoo Jang1, Anthony Hudetz1, Zirui Huang1
Institutions:
1University of Michigan, Ann Arbor, MI
First Author:
Co-Author(s):
Introduction:
Consciousness, the very essence of human experience, arises from the dynamic interplay of brain activity across large-scale neural networks (Alkire et al., 2008). While previous research has shown that functional connectivity (FC) patterns reconfigure as consciousness state changes, a crucial question remains: are there canonical recurrent connectivity patterns that underlie different states of consciousness (Bolt et al., 2022)? This study addresses this gap by identifying robust FC patterns across various levels of consciousness (wakefulness, sedation, anesthesia, psychedelics). We then examine how they are linked to the brain's structural connections (structure-function coupling; SFC) and the balance between integrated and segregated information processing (Barttfeld et al., 2015; Demertzi et al., 2019; Jang et al., 2024). By uncovering these relationships, we aim to shed light on the large-scale neural mechanisms associated with states of consciousness.
Methods:
We analyzed resting-state fMRI datasets encompassing a range of consciousness levels, including typical wakefulness (n = 1009), propofol-induced sedation (n = 54) and LSD-induced psychedelic states (n = 15). Canonical dynamic FC states were extracted via k-means clustering followed by meta-clustering to ensure stability and generalizability (Castro et al., 2024; Demertzi et al., 2019). Since the number of canonical brain states are unclear, we scanned a range of cluster solutions (3 to 10). For each state, we quantified SFC by correlating its centroid FC matrix with a structural connectivity matrix derived from diffusion-weighted imaging. ISD, defined as the difference between global efficiency and global clustering coefficient, served as a measure of integration-segregation balance (Jang et al., 2024). We additionally assessed the complexity of temporal state transitions using entropy-based metrics (Coppola et al., 2022).
Results:
We identified a set of robust, canonical dynamic FC states that consistently emerged across individuals and datasets. Normal wakeful consciousness was dominated by FC states showing lower SFC, balanced ISD, and higher temporal complexity, suggesting a more flexible and integrative functional architecture. In contrast, lower levels of consciousness were associated with FC states exhibiting higher SFC, lower complexity, and a shift to predominantly segregated states, indicative of a more rigid and structurally constrained organization. We further observed an inverse relationship between SFC and integration (i.e., efficiency), revealing that higher SFC states tended to display lower integrative capacity. This negative correlation underscores the delicate interplay between anatomical constraints and the flexible integration of information in shaping conscious brain states.
Conclusions:
Our findings demonstrate that canonical dynamic connectivity states provide a powerful framework for understanding how changing levels of consciousness shape the interplay between brain structure and function. The relationship between SFC and integration-segregation balance emerges as a key factor differentiating states of consciousness, with implications for understanding cognitive capacity and complexity. This integrative perspective sets the stage for future research into the biological basis of consciousness and its cognitive correlates, ultimately deepening our understanding of how the brain's structural constraints and dynamic functional reconfigurations give rise to the subjective experience.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Diffusion MRI
Perception, Attention and Motor Behavior:
Consciousness and Awareness 1
Keywords:
Consciousness
Data analysis
FUNCTIONAL MRI
MRI
STRUCTURAL MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
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Not applicable
Please indicate which methods were used in your research:
Functional MRI
Structural MRI
Diffusion MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
AFNI
Provide references using APA citation style.
Alkire, M. T., Hudetz, A. G., & Tononi, G. (2008). Consciousness and Anesthesia. Science, 322(5903), 876–880. https://doi.org/10.1126/science.1149213
Barttfeld, P., Uhrig, L., Sitt, J. D., Sigman, M., Jarraya, B., & Dehaene, S. (2015). Signature of consciousness in the dynamics of resting-state brain activity. Proceedings of the National Academy of Sciences, 112(3), 887–892. https://doi.org/10.1073/pnas.1418031112
Bolt, T., Nomi, J. S., Bzdok, D., Salas, J. A., Chang, C., Thomas Yeo, B. T., Uddin, L. Q., & Keilholz, S. D. (2022). A parsimonious description of global functional brain organization in three spatiotemporal patterns. Nature Neuroscience, 25(8), 1093–1103. https://doi.org/10.1038/s41593-022-01118-1
Castro, P., Luppi, A., Tagliazucchi, E., Perl, Y. S., Naci, L., Owen, A. M., Sitt, J. D., Destexhe, A., & Cofré, R. (2024). Dynamical structure-function correlations provide robust and generalizable signatures of consciousness in humans. Communications Biology, 7(1), 1224. https://doi.org/10.1038/s42003-024-06858-3
Coppola, P., Allanson, J., Naci, L., Adapa, R., Finoia, P., Williams, G. B., Pickard, J. D., Owen, A. M., Menon, D. K., & Stamatakis, E. A. (2022). The complexity of the stream of consciousness. Communications Biology, 5(1), 1173. https://doi.org/10.1038/s42003-022-04109-x
Demertzi, A., Tagliazucchi, E., Dehaene, S., Deco, G., Barttfeld, P., Raimondo, F., Martial, C., Fernández-Espejo, D., Rohaut, B., Voss, H. U., Schiff, N. D., Owen, A. M., Laureys, S., Naccache, L., & Sitt, J. D. (2019). Human consciousness is supported by dynamic complex patterns of brain signal coordination. Science Advances, 5(2), eaat7603. https://doi.org/10.1126/sciadv.aat7603
Jang, H., Mashour, G. A., Hudetz, A. G., & Huang, Z. (2024). Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep in humans. Nature Communications, 15(1), 9164. https://doi.org/10.1038/s41467-024-53299-x
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