scholarly journals Two classes of functional connectivity in dynamical processes in networks

2021 ◽  
Vol 18 (183) ◽  
Author(s):  
Venetia Voutsa ◽  
Demian Battaglia ◽  
Louise J. Bracken ◽  
Andrea Brovelli ◽  
Julia Costescu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Network Architecture ◽  
Structural Connectivity ◽  
Ecological Systems ◽  
Dynamical Processes ◽  
Structure And Dynamics ◽  
Theoretical View ◽  
And Function ◽  
The Relationship ◽  
Simultaneous Activity

The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines—from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity—one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes—excitations, regular and chaotic oscillators—and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.

scholarly journals Network controllability mediates the relationship between rigid structure and flexible dynamics

2021 ◽  
pp. 1-38
Author(s):  
Shi Gu ◽  
Panagiotis Fotiadis ◽  
Linden Parkes ◽  
Cedric H. Xia ◽  
Ruben C. Gur ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Network Architecture ◽  
Structural Connectivity ◽  
Network Control ◽  
Theoretical Frameworks ◽  
Wide Range ◽  
Complex Functions ◽  
Structural Network ◽  
Temporal Flexibility ◽  
The Relationship

Abstract Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid inter-areal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain’s structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region’s functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes’ boundary controllability, suggesting that a region’s strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.

scholarly journals Multi-Hops Functional Connectivity Improves Individual Prediction of Fusiform Face Activation via a Graph Neural Network

2021 ◽  
Vol 14 ◽  
Author(s):  
Dongya Wu ◽  
Xin Li ◽  
Jun Feng
Keyword(s):  
Neural Network ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Face Area ◽  
The Face ◽  
The Individual ◽  
The Right ◽  
And Function ◽  
The Relationship ◽  
The Brain

Brain connectivity plays an important role in determining the brain region’s function. Previous researchers proposed that the brain region’s function is characterized by that region’s input and output connectivity profiles. Following this proposal, numerous studies have investigated the relationship between connectivity and function. However, this proposal only utilizes direct connectivity profiles and thus is deficient in explaining individual differences in the brain region’s function. To overcome this problem, we proposed that a brain region’s function is characterized by that region’s multi-hops connectivity profile. To test this proposal, we used multi-hops functional connectivity to predict the individual face activation of the right fusiform face area (rFFA) via a multi-layer graph neural network and showed that the prediction performance is essentially improved. Results also indicated that the two-layer graph neural network is the best in characterizing rFFA’s face activation and revealed a hierarchical network for the face processing of rFFA.

scholarly journals Characterizing the role of the structural connectome in seizure dynamics

Brain ◽  
2019 ◽  
Vol 142 (7) ◽  
pp. 1955-1972 ◽  
Author(s):  
Preya Shah ◽  
Arian Ashourvan ◽  
Fadi Mikhail ◽  
Adam Pines ◽  
Lohith Kini ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Focal Epilepsy ◽  
Diffusion Imaging ◽  
Structural Connectivity ◽  
Patient Specific ◽  
High Angular Resolution ◽  
Intracranial Eeg ◽  
Structural Connectome ◽  
The Relationship

Abstract How does the human brain’s structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural—through surgery or laser ablation—but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions.

scholarly journals Network controllability mediates the relationship between rigid structure and flexible dynamics

2021 ◽  
Author(s):  
Shi Gu ◽  
Panagiotis Fotiadis ◽  
Linden Parkes ◽  
Cedric H. Xia ◽  
Ruben C. Gur ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Control Theory ◽  
Network Architecture ◽  
Functional Module ◽  
Structural Connectivity ◽  
Cognitive Networks ◽  
Neural Dynamics ◽  
Boundary Controllability ◽  
Wide Range ◽  
Structural Network

ABSTRACTPrecisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid inter-areal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain’s structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region’s functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes’ boundary controllability, suggesting that a region’s strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.AUTHOR SUMMARYPrecisely how the relatively rigid white matter wiring of the human brain gives rise to a diverse repertoire of functional neural dynamics is not well understood. In this work, we combined tools from network science and control theory to address this question. Capitalizing on a large developmental cohort, we demonstrated that the ability of a brain region to flexibly change its functional module allegiance over time (i.e., its modular flexibility), was positively correlated with its proportion of anatomical edges projecting to multiple cognitive networks (i.e., its structural participation coefficient). Moreover, this relationship was strongly mediated by the region’s boundary controllability, a metric capturing its capacity to integrate information across multiple cognitive domains.

scholarly journals Multi-hops functional connectivity improves individual prediction of fusiform face activation via a graph neural network

2020 ◽  
Author(s):  
Dongya Wu ◽  
Xin Li ◽  
Jun Feng
Keyword(s):  
Neural Network ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Face Area ◽  
The Face ◽  
The Individual ◽  
The Right ◽  
And Function ◽  
The Relationship ◽  
The Brain

AbstractBrain connectivity plays an important role in determining the brain region’s function. Previous researchers proposed that the brain region’s function is characterized by that region’s input and output connectivity profiles. Following this proposal, numerous studies have investigated the relationship between connectivity and function. However, based on a preliminary analysis, this proposal is deficient in explaining individual differences in the brain region’s function. To overcome this problem, we proposed that a brain region’s function is characterized by that region’s multi-hops connectivity profile. To test this proposal, we used multi-hops functional connectivity to predict the individual face response of the right fusiform face area (rFFA) via a multi-layers graph neural network and showed that the prediction performance is essentially improved. Results also indicated that the 2-layers graph neural network is the best in characterizing rFFA’s face response and revealed a hierarchical network for the face processing of rFFA.

scholarly journals Multimodal interferometric imaging of nanoscale structure and macromolecular motion uncovers UV induced cellular paroxysm

2018 ◽  
Author(s):  
Scott Gladstein ◽  
Luay M. Almassalha ◽  
Lusik Cherkezyan ◽  
John E. Chandler ◽  
Adam Eshein ◽  
...  
Keyword(s):  
Uv Light ◽  
Stem Cell Differentiation ◽  
Live Cells ◽  
Label Free ◽  
Interferometric Imaging ◽  
Structure And Dynamics ◽  
Nanoscale Structure ◽  
And Function ◽  
The Relationship

AbstractWe present a multimodal label-free interferometric imaging platform for measuring intracellular nanoscale structure and macromolecular dynamics in living cells with a sensitivity to macromolecules as small as 20nm and millisecond temporal resolution. We validate this system by pairing experimental measurements of nanosphere phantoms with a novel interferometric theory. Applying this system in vitro, we explore changes in higher-order chromatin structure and dynamics that occur due to cellular fixation, stem cell differentiation, and ultraviolet (UV) light irradiation. Finally, we discover a new phenomenon, cellular paroxysm, a near-instantaneous, synchronous burst of motion that occurs early in the process of UV induced cell death. Given this platform’s ability to obtain nanoscale sensitive, millisecond resolved information within live cells without concerns of photobleaching, it has the potential to answer a broad range of critical biological questions about macromolecular behavior in live cells, particularly about the relationship between cellular structure and function.

scholarly journals Cooperative Contributions of Structural and Functional Connectivity to Successful Memory and Aging

2017 ◽  
Author(s):  
Simon W Davis ◽  
Amanda Szymanski ◽  
Homa Boms ◽  
Thomas Fink ◽  
Roberto Cabeza
Keyword(s):  
Functional Connectivity ◽  
Associative Memory ◽  
Latent Variables ◽  
Memory Performance ◽  
Structural Connectivity ◽  
Equation Modeling ◽  
Cognitive Changes ◽  
Age Related ◽  
The Relationship ◽  
Age Related Changes

AbstractUnderstanding the precise relation between functional connectivity and structural (white-matter) connectivity and how these relationships account for cognitive changes in older adults are major challenges for neuroscience. We investigate these issues using a new approach in which structural equation modeling (SEM) is employed to integrate functional and structural connectivity data analyzed with a common framework based on regions connected by canonical tract groups (CTGs). CTGs (e.g., uncinate fasciculus, cingulum, etc.) serve as a common currency between functional and structural connectivity matrices, and ensures that the same amount of data contributing to brain-behavior relationships. We used this approach to investigate the neural mechanisms supporting memory for items and memory for associations, and how they are affected by healthy aging. Our results are threefold. Firstly, structural and functional CTGs made independent contributions to associative memory performance, suggesting that both forms of connectivity underlie age-related changes in associative memory. Secondly, distinct groups of CTGs supported associative versus item memory. Lastly, the relationship between functional and structural connectivity was best explained by the relationship between latent variables describing functional and structural CTGs based on a constrained set of tracts—but no one specific CTG group—suggesting that age effects in connectivity are constrained to specific pathways. These results provide further insights into the interplay between structural and functional connectivity patterns, and help to elucidate their relative contribution to age-related changes in associative memory performance.

scholarly journals Local structural connectivity directs seizure spread in focal epilepsy

2018 ◽  
Author(s):  
Preya Shah ◽  
Arian Ashourvan ◽  
Fadi Mikhail ◽  
Adam Pines ◽  
Lohith Kini ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Focal Epilepsy ◽  
Diffusion Imaging ◽  
Structural Connectivity ◽  
Patient Specific ◽  
High Angular Resolution ◽  
Intracranial Eeg ◽  
Functional Dynamics ◽  
The Relationship

AbstractHow does the human brain’s structural scaffold give rise to its intricate functional dynamics? This is a central challenge in translational neuroscience, particularly in epilepsy, a disorder that affects over 50 million people worldwide. Treatment for medication-resistant focal epilepsy is often structural – through surgery, devices or focal laser ablation – but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG (iEEG). Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and iEEG, across preictal and ictal periods in 45 seizures from 9 patients with unilateral drug-resistant focal epilepsy. We use High Angular Resolution Diffusion Imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered iEEG. Across all frequency bands, we find significant increases in structure-function coupling from preictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are stereotyped, and a function of each patient’s individual anatomy. These results suggest that seizures harness the underlying structural connectome as they propagate. Our findings suggest that the relationship between structural and functional connectivity in epilepsy may inform current and new therapies to map and alter seizure spread, and pave the way for better-targeted, patient-specific interventions.

scholarly journals Structure supports function: informing directed and dynamic functional connectivity with anatomical priors

2021 ◽  
pp. 1-37
Author(s):  
David Pascucci ◽  
Maria Rubega ◽  
Joan Rué-Queralt ◽  
Sebastien Tourbier ◽  
Patric Hagmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Meta Analysis ◽  
Structural Connectivity ◽  
Eeg Data ◽  
Functional Brain Networks ◽  
And Function ◽  
Combine Information ◽  
Anatomical Priors

Abstract The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. We show that, particularly under conditions of low signal-to-noise ratio, SC priors can help to refine estimates of directed FC, promoting sparse functional networks that combine information from structure and function. In addition, the proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new tool for multimodal imaging in the context of dynamic and directed FC analysis.

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