Individualized event structure drives individual differences in whole-brain functional connectivity

NeuroImage, Journal Year: 2022, Volume and Issue: 252, P. 118993 - 118993

Published: Feb. 19, 2022

Resting-state functional connectivity is typically modeled as the correlation structure of whole-brain regional activity. It studied widely, both to gain insight into brain's intrinsic organization but also develop markers sensitive changes in an individual's cognitive, clinical, and developmental state. Despite this, origins drivers connectivity, especially at level densely sampled individuals, remain elusive. Here, we leverage novel methodology decompose its precise framewise contributions. Using two dense sampling datasets, investigate individualized focusing specifically on role brain network "events" - short-lived peaked patterns high-amplitude cofluctuations. a statistical test identify events empirical recordings. We show that cofluctuation expressed during are repeated across multiple scans same individual represent idiosyncratic variants template group level. Lastly, propose simple model based event cofluctuations, demonstrating group-averaged cofluctuations suboptimal for explaining participant-specific connectivity. Our work complements recent studies implicating brief instants primary static, extends those studies, individualized, positing dynamic basis

Language: Английский

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Living on the edge: network neuroscience beyond nodes

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(11), P. 1068 - 1084

Published: Sept. 15, 2023

Network neuroscience has emphasized the connectional properties of neural elements - cells, populations, and regions. This come at expense anatomical functional connections that link these to one another. A new perspective namely emphasizes 'edges' may prove fruitful in addressing outstanding questions network neuroscience. We highlight recently proposed 'edge-centric' method review its current applications, merits, limitations. also seek establish conceptual mathematical links between this previously approaches science neuroimaging literature. conclude by presenting several avenues for future work extend refine existing edge-centric analysis.

Language: Английский

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Synchronous high-amplitude co-fluctuations of functional brain networks during movie-watching

Imaging Neuroscience, Journal Year: 2023, Volume and Issue: 1, P. 1 - 21

Published: Oct. 19, 2023

Abstract Recent studies have shown that functional connectivity can be decomposed into its exact frame-wise contributions, revealing short-lived, infrequent, and high-amplitude time points referred to as “events.” Events contribute disproportionately the time-averaged pattern, improve identifiability brain-behavior associations, differences in their expression been linked endogenous hormonal fluctuations autism. Here, we explore characteristics of events while subjects watch movies. Using two independently-acquired imaging datasets which participants passively watched movies, find synchronize across individuals based on level synchronization, categorized three distinct classes: those at boundaries between during do not all. We boundary events, compared other categories, exhibit greater amplitude, co-fluctuation patterns, temporal propagation. show underlying events1 is a specific mode involving activation control salience systems alongside deactivation visual systems. movie, hand, display pattern time-locked movie stimulus. Finally, found subjects’ time-varying brain networks are most similar one another these synchronous events.

Language: Английский

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The diversity and multiplexity of edge communities within and between brain systems

Cell Reports, Journal Year: 2021, Volume and Issue: 37(7), P. 110032 - 110032

Published: Nov. 1, 2021

The human brain is composed of functionally specialized systems that support cognition. Recently, we proposed an edge-centric model for detecting overlapping communities. It remains unclear how these communities and are related. Here, address this question using data from the Midnight Scan Club show all linked via at least two edge We then examine diversity within each system, finding heteromodal more diverse than sensory systems. Next, cluster entire cortex to reveal it according regions' edge-community profiles. find regions in likely form their own clusters. Finally, personalized. Our work reveals pervasive overlap across relationship with provides pathways future research networks.

Language: Английский

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BOLD cofluctuation ‘events’ are predicted from static functional connectivity

NeuroImage, Journal Year: 2022, Volume and Issue: 260, P. 119476 - 119476

Published: July 14, 2022

Recent work identified single time points ("events") of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low points. This suggested that events might be a discrete, temporally sparse signal drives connectivity (FC) over the timeseries. However, different, not yet explored possibility is differences between are driven by sampling variability on constant, static, noisy signal. Using combination real and simulated data, we examined relationship structure asked if this was unique, or it could arise from alone. First, show discrete - there gradually increasing cofluctuation; ∼50% samples very strong structure. Second, using simulations predicted static FC. Finally, randomly selected can capture about as well events, largely because their temporal spacing. Together, these results suggest that, while exhibit particularly representations FC, little evidence unique timepoints drive FC Instead, parsimonious explanation for data but noisy,

Language: Английский

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Edge-centric analysis of stroke patients: An alternative approach for biomarkers of lesion recovery

NeuroImage Clinical, Journal Year: 2022, Volume and Issue: 35, P. 103055 - 103055

Published: Jan. 1, 2022

Most neuroimaging studies of post-stroke recovery rely on analyses derived from standard node-centric functional connectivity to map the distributed effects in stroke patients. Here, given importance nonlocal and diffuse damage, we use an edge-centric approach order provide alternative description this disorder. These techniques allow for rendering metrics such as normalized entropy, which describes diversity edge communities at each node. Moreover, enables identification high amplitude co-fluctuations fMRI time series. We found that entropy is associated with lesion severity continually increases across patients' recovery. Furthermore, not only relate but are also level The current study first application a clinical population longitudinal dataset demonstrates how different perspective data analysis can further characterize topographic modulations brain dynamics.

Language: Английский

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Multi-policy models of interregional communication in the human connectome

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: May 9, 2022

Network models of communication, e.g. shortest paths, diffusion, navigation, have become useful tools for studying structure-function relationships in the brain. These generate estimates communication efficiency between all pairs brain regions, which can then be linked to correlation structure recorded activity, i.e. functional connectivity (FC). At present, however, a number limitations, including difficulty adjudicating and absence generic framework modeling multiple interacting policies at regional level. Here, we present that allows us incorporate region-specific fit them empirical FC. Briefly, show many policies, paths greedy modeled as biased random walks, enabling these incorporated into same multi-policy model alongside unbiased processes, diffusion. We outperform existing measures while yielding neurobiologically interpretable preferences. Further, explain majority variance time-varying patterns Collectively, our represents an advance network-based establishes strong link Our findings open up new avenues future inquiries flexible anatomically-constrained communication.

Language: Английский

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A low dimensional embedding of brain dynamics enhances diagnostic accuracy and behavioral prediction in stroke

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Sept. 21, 2023

Abstract Large-scale brain networks reveal structural connections as well functional synchronization between distinct regions of the brain. The latter, referred to connectivity (FC), can be derived from neuroimaging techniques such magnetic resonance imaging (fMRI). FC studies have shown that are severely disrupted by stroke. However, since data usually large and high-dimensional, extracting clinically useful information this vast amount is still a great challenge, our understanding consequences stroke remains limited. Here, we propose dimensionality reduction approach simplify analysis complex neural data. By using autoencoders, find low-dimensional representation encoding fMRI which preserves typical anomalies known present in patients. employing latent representations emerging enhanced patients’ diagnostics severity classification. Furthermore, showed how increased accuracy recovery prediction.

Language: Английский

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Individualized event structure drives individual differences in whole-brain functional connectivity

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2021, Volume and Issue: unknown

Published: March 12, 2021

Resting-state functional connectivity is typically modeled as the correlation structure of whole-brain regional activity. It studied widely, both to gain insight into brain’s intrinsic organization but also develop markers sensitive changes in an individual’s cognitive, clinical, and developmental state. Despite this, origins drivers connectivity, especially at level densely sampled individuals, remain elusive. Here, we leverage novel methodology decompose its precise framewise contributions. Using two dense sampling datasets, investigate individualized focusing specifically on role brain network “events” – short-lived peaked patterns high-amplitude cofluctuations. a statistical test identify events empirical recordings. We show that cofluctuation expressed during are repeated across multiple scans same individual represent idiosyncratic variants template group level. Lastly, propose simple model based event cofluctuations, demonstrating group-averaged cofluctuations suboptimal for explaining participant-specific connectivity. Our work complements recent studies implicating brief instants primary static, extends those studies, individualized, positing dynamic basis

Language: Английский

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Hierarchical organization of spontaneous co-fluctuations in densely-sampled individuals using fMRI

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: March 7, 2022

ABSTRACT Edge time series decompose FC into its framewise contributions. Previous studies have focused on characterizing the properties of high-amplitude frames, including their cluster structure. Less is known about middle- and low-amplitude co-fluctuations. Here, we address those questions directly, using data from two dense-sampling studies: MyConnectome project Midnight Scan Club. We develop a hierarchical clustering algorithm to group peak co-fluctuations all magnitudes nested multi-scale clusters based pairwise concordance. At coarse scale, find evidence three large that, collectively, engage virtually canonical brain systems. finer scales, however, each dissolved, giving way increasingly refined patterns involving specific sets also an increase in global co-fluctuation magnitude with scale. Finally, comment amount needed estimate pattern implications for brain-behavior studies. Collectively, findings reported here fill several gaps current knowledge concerning heterogeneity richness as estimated edge while providing some practical guidance future

Language: Английский

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