Network structure of cascading neural systems predicts stimulus propagation and recovery

Ju, Harang; Kim, Jason Z.; Beggs, John M.; Bassett, Danielle S.

doi:10.1088/1741-2552/abbff1

Cited by 9 publications

(7 citation statements)

References 106 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The correlation with cumulative path transitivity indicates that top-down signaling encounters a greater number of returning detours nearer to the top of the S-F axis. In our model, the presence of local detours creates cycles that may give rise to sustained activity patterns 74 . In turn, the early occurrence of these detours may result in the earlier onset of sustained activity patterns for top-down state transitions.…”

Section: Cytoarchitecture Shapes the Connectomementioning

confidence: 99%

Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome

Parkes

Kim

Stiso

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Cortical variations in cytoarchitecture form a sensory-fugal axis that systematically shapes regional profiles of extrinsic connectivity. Additionally, this axis is thought to guide signal propagation and integration across the cortical hierarchy. While human neuroimaging work has shown that this axis constrains local properties of the human connectome, it remains unclear whether it also shapes the asymmetric signaling that arises from higher-order connectome topology. Here, we used network control theory to examine the amount of energy required to propagate dynamics across the sensory-fugal axis. Our results revealed an asymmetry in this energy indicating that bottom-up transitions were easier to complete compared to top-down transitions. Supporting analyses demonstrated that this asymmetry was underpinned by a connectome topology that is wired to support efficient bottom-up signaling. Finally, we found that this asymmetry correlated with changes in intrinsic neuronal timescales and lessened throughout youth. Our results show that cortical variation in cytoarchitecture may guide the formation of macroscopic connectome topology.

show abstract

Section: Cytoarchitecture Shapes the Connectomementioning

confidence: 99%

Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome

Parkes

Kim

Stiso

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…More specifically, given a region in the brain network with specific topological properties such as high degree, betweenness centrality, closeness centrality, or location between different modules, what is the relationship between its role in information integration or processing and its role in controllability and observability? The tri-faceted interface of communication, control, and network topology holds great possibilities for future work, and some recent efforts have begun to relate the three (Ju, Kim, & Bassett, 2018).…”

Section: Models Of Communication and Control For Brain Networkmentioning

confidence: 99%

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Srivastava¹,

Nozari²,

Kim³

et al. 2020

Network Neuroscience

Self Cite

View full text Add to dashboard Cite

Recent advances in computational models of signal propagation and routing in the human brain have underscored the critical role of white matter structure. A complementary approach has utilized the framework of network control theory to better understand how white matter constrains the manner in which a region or set of regions can direct or control the activity of other regions. Despite the potential for both of these approaches to enhance our understanding of the role of network structure in brain function, little work has sought to understand the relations between them. Here, we seek to explicitly bridge computational models of communication and principles of network control in a conceptual review of the current literature. By drawing comparisons between communication and control models in terms of the level of abstraction, the dynamical complexity, the dependence on network attributes, and the interplay of multiple spatiotemporal scales, we highlight the convergence of and distinctions between the two frameworks. Based on the understanding of the intertwined nature of communication and control in human brain networks, this work provides an integrative perspective for the field and outlines exciting directions for future work.

show abstract

“…The EI-associated changes in network topology characterised above will impact dynamics and ultimately information processing (Ju et al, 2020). In particular, σ > 1 suggests the emergence of a supercritical state (Meisel, 2020) which should impair network response properties (Shew et al, 2009).…”

Section: Seizure Dynamics Are Chaotic Which Impairs Network Response Propertiesmentioning

confidence: 99%

Single-cell Networks Reorganise to Facilitate Whole-brain Supercritical Dynamics During Epileptic Seizures

Burrows

Diana

Pimpel

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Excitation-inhibition (EI) balance may be required for the organisation of brain dynamics to a phase transition, criticality, which confers computational benefits. Brain pathology associated with EI imbalance may therefore occur due to a deviation from criticality. However, evidence linking critical dynamics with EI imbalance-induced pathology is lacking. Here, we studied the effect of EI imbalance-induced epileptic seizures on brain dynamics, using in vivo whole-brain 2-photon imaging of GCaMP6s larval zebrafish at single-neuron resolution. We demonstrate the importance of EI balance for criticality, with EI imbalance causing a loss of whole-brain critical statistics. Using network models we show that a reorganisation of network topology drives this loss of criticality. Seizure dynamics match theoretical predictions for networks driven away from a phase transition into disorder, with the emergence of chaos and a loss of network-mediated separation, dynamic range and metastability. These results demonstrate that EI imbalance drives a pathological deviation from criticality.

show abstract

Network structure of cascading neural systems predicts stimulus propagation and recovery

Cited by 9 publications

References 106 publications

Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome

Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Single-cell Networks Reorganise to Facilitate Whole-brain Supercritical Dynamics During Epileptic Seizures

Contact Info

Product

Resources

About