Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes

Naze, Sébastien; Proix, Timothée; Atasoy, Selen; Kozloski, James

doi:10.1016/j.neuroimage.2020.117364

Cited by 21 publications

(37 citation statements)

References 75 publications

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“…The choice of k was previously discussed regarding a related technique, the Isomap algorithm (Tenenbaum et al, 2000;Balasubramanian et al, 2002): k should be chosen such that a balance between local and global features is achieved. The amount of local and global connections has been suggested to have a major impact on the performance of the harmonic decomposition (Haak et al, 2018;Naze et al, 2021). At the same time, k might vary in a subject-or state-specific manner, revealing further interesting properties of cortical organization.…”

Section: Discussionmentioning

confidence: 99%

Functional harmonics reveal multi-dimensional basis functions underlying cortical organization

et al. 2021

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Section: Discussionmentioning

confidence: 99%

Functional harmonics reveal multi-dimensional basis functions underlying cortical organization

et al. 2021

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“…In unconsciousness, our analysis reveals that functional brain activity becomes more constrained by the structure of the human connectome, as indicated by an increased contribution of low-frequency, large-scale harmonic modes and a more restricted repertoire. In contrast, the psychedelic-induced energy shift to high-frequency harmonics indicates a departure from standard activity patterns encoded in the structural connectome, in favour of increasingly diverse and variable ones (Naze et al, 2021) - a plausible neural correlate for the phenomenologically rich state of mind induced by psychedelics (Atasoy et al, 2017, 2018b, 2018a), according to leading theoretical accounts (Carhart-Harris, 2018; Carhart-Harris and Friston, 2019; Carhart-Harris et al, 2014; Sarasso et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Distributed harmonic patterns of structure-function dependence orchestrate human consciousness

Luppi

Vohryzek

Kringelbach

et al. 2020

Preprint

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A central question in neuroscience is how cognition and consciousness arise from human brain activity. Here, we decompose cortical dynamics of resting-state functional MRI into their constituent elements: the harmonics of the human connectome. Mapping a wide spectrum of consciousness onto these elementary brain states reveals a generalisable connectome harmonic signature of loss of consciousness, whether due to anaesthesia or severe brain injury. Remarkably, its mirror-reversed image corresponds to the harmonic signature of the psychedelic state induced by ketamine or LSD, identifying meaningful relationships between neurobiology, brain function, and conscious experience. The repertoire of connectome harmonics further provides a fine-tuned indicator of level of consciousness, sensitive to differences in anaesthetic dose and clinically relevant sub-categories of patients with disorders of consciousness. Overall, we reveal that the emergence of consciousness from human brain dynamics follows the same universal principles shared by a multitude of physical and biological phenomena: the mathematics of harmonic modes.

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“…Edges representing spatial adjacency can be added to a brain network to account for presumed local influences. Doing so can enhance the modeling of functionally meaningful connectome harmonics patterns on cortical surface ( Naze, Proix, Atasoy, & Kozloski, 2021 ). The intrinsic curvature of the cortical surface mesh, which is influenced by differential growth patterns, has been proposed as a marker of local connectivity that could serve as an edge weight ( Ecker et al, 2013 ; Ronan et al, 2012 ).…”

Section: Future Directionsmentioning

confidence: 99%

Edges in brain networks: Contributions to models of structure and function

Faskowitz

Betzel

Sporns

2021

Network Neuroscience

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Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher-order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher-order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.

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Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes

Cited by 21 publications

References 75 publications

Functional harmonics reveal multi-dimensional basis functions underlying cortical organization

Functional harmonics reveal multi-dimensional basis functions underlying cortical organization

Distributed harmonic patterns of structure-function dependence orchestrate human consciousness

Edges in brain networks: Contributions to models of structure and function

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