The Why, How, and When of Representations for Complex Systems

SIAM Review, Journal Year: 2021, Volume and Issue: 63(3), P. 435 - 485

Published: Jan. 1, 2021

Complex systems, composed at the most basic level of units and their interactions, describe phenomena in a wide variety domains, from neuroscience to computer science economics. The applications has resulted two key challenges: generation many domain-specific strategies for complex systems analyses that are seldom revisited, compartmentalization representation analysis ideas within domain due inconsistency language. In this work we propose basic, domain-agnostic language order advance toward more cohesive vocabulary. We use evaluate each step pipeline, beginning with system under study data collected, then moving through different mathematical frameworks encoding observed (i.e., graphs, simplicial complexes, hypergraphs), relevant computational methods framework. At consider types dependencies; these properties how existence an interaction among set may affect possibility another relation. discuss dependencies arise they alter interpretation results or entirety pipeline. close real-world examples using coauthorship email communications illustrate study, therein, research question, choice influence results. hope can serve as opportunity reflection experienced scientists, well introductory resource new researchers.

Language: Английский

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Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: June 9, 2021

Abstract Dynamical brain state transitions are critical for flexible working memory but the network mechanisms incompletely understood. Here, we show that performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pharmacological fMRI, genetic analyses control theory. The stability relates to dopamine D1 receptor gene expression while influenced by D2 modulation. Individuals schizophrenia altered properties, including more diverse energy landscape decreased representations. Our results demonstrate relevance signaling steering whole-brain dynamics during link these processes pathophysiology.

Language: Английский

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Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation

Nature Biomedical Engineering, Journal Year: 2021, Volume and Issue: 5(4), P. 324 - 345

Published: Feb. 1, 2021

Language: Английский

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Macroscopic resting-state brain dynamics are best described by linear models

Nature Biomedical Engineering, Journal Year: 2023, Volume and Issue: 8(1), P. 68 - 84

Published: Dec. 11, 2023

It is typically assumed that large networks of neurons exhibit a repertoire nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements local field potentials via intracranial electroencephalography and whole-brain blood-oxygen-level-dependent brain activity functional magnetic resonance imaging. We used state-of-the-art linear families to describe spontaneous resting-state 700 participants in the Human Connectome Project 122 Restoring Active Memory project. found autoregressive provide best fit across both data types three performance metrics: predictive power, computational complexity extent residual dynamics unexplained model. To explain observation, show microscopic can be counteracted or masked four factors associated with macroscopic dynamics: averaging over space time, which are inherent aggregated activity, observation noise limited samples, stem technological limitations. therefore argue easier-to-interpret faithfully during conditions.

Language: Английский

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Neuroscience Needs Network Science

Journal of Neuroscience, Journal Year: 2023, Volume and Issue: 43(34), P. 5989 - 5995

Published: Aug. 23, 2023

The brain is a complex system comprising myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as powerful tool for studying such intricate systems, offering framework integrating multiscale data complexity. Here, we discuss the application network study brain, addressing topics models metrics, connectome, role dynamics neural networks. We explore opportunities multiple streams transitions from development to healthy function disease, potential collaboration between neuroscience communities. underscore importance fostering interdisciplinary through funding initiatives, workshops, conferences, well supporting students postdoctoral fellows with interests both disciplines. By uniting communities, can develop novel network-based methods tailored circuits, paving way towards deeper functions.

Language: Английский

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Neuroimaging and fluid biomarkers in Parkinson’s disease in an era of targeted interventions

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 5, 2024

Abstract A major challenge in Parkinson’s disease is the variability symptoms and rates of progression, underpinned by heterogeneity pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring progression precise treatment. These were previously lacking, but recently, novel imaging fluid biomarkers have been developed. Here, we consider new approaches showing sensitivity to brain tissue composition, examine specificity processes, including seed amplification assays extracellular vesicles. We reflect on these context biological staging systems, emerging techniques currently development.

Language: Английский

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Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands

Communications Biology, Journal Year: 2020, Volume and Issue: 3(1)

Published: May 22, 2020

A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these guide the temporal progression large-scale brain activity patterns in different Here, we analyze brain's trajectories across a single time point from functional magnetic resonance imaging data acquired during resting state and an n-back working memory task. We find that specific sequences are modulated by load, associated with age, related to task performance. Using diffusion-weighted same subjects, apply tools network control theory show linear spread along constrains probabilities at rest, while stimulus-driven visual inputs explain observed Overall, results elucidate structural underpinnings cognitively developmentally relevant spatiotemporal dynamics.

Language: Английский

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A practical guide to methodological considerations in the controllability of structural brain networks

Journal of Neural Engineering, Journal Year: 2020, Volume and Issue: 17(2), P. 026031 - 026031

Published: Jan. 22, 2020

Objective. Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding relationship between neural connectivity and activity. Network theory is powerful tool from physical engineering sciences that provide insights regarding relationship; it formalizes study dynamics complex system arise its underlying structure interconnected units. Approach. Given recent use network in neuroscience, now timely offer practical guide methodological considerations controllability structural networks. Here we systematic overview framework, examine impact modeling choices on frequently studied metrics, suggest potentially useful theoretical extensions. We ground our discussions, numerical demonstrations, advances dataset high-resolution diffusion imaging with 730 directions acquired over approximately 1 h scanning ten healthy young adults. Main results. Following didactic introduction theory, probe selection affects four common statistics: average controllability, modal minimum energy, optimal energy. Next, extend current state-of-the-art two ways: first, developing an alternative measure accounts for radial propagation activity through abutting tissue, second, defining complementary metric quantifying complexity energy landscape system. close recommendations discussion constraints. Significance. Our hope this accessible account will inspire neuroimaging community more fully exploit potential tackling pressing questions cognitive, developmental, clinical neuroscience.

Language: Английский

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Optimization of energy state transition trajectory supports the development of executive function during youth

eLife, Journal Year: 2020, Volume and Issue: 9

Published: March 27, 2020

Executive function develops during adolescence, yet it remains unknown how structural brain networks mature to facilitate activation of the fronto-parietal system, which is critical for executive function. In a sample 946 human youths (ages 8-23y) who completed diffusion imaging, we capitalized upon recent advances in linear dynamical network control theory calculate energetic cost necessary activate system through multiple regions given existing topology. We found that energy required declined with development, and pattern regional predicts unseen individuals' maturity. Finally, requirements cingulate cortex were negatively correlated performance, partially mediated development performance age. Our results reveal mechanism by develop adolescence reduce theoretical costs transitions states

Language: Английский

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Reducing the Cognitive Footprint of Brain Tumor Surgery

Frontiers in Neurology, Journal Year: 2021, Volume and Issue: 12

Published: Aug. 16, 2021

The surgical management of brain tumors is based on the principle that extent resection improves patient outcomes. Traditionally, neurosurgeons have considered lesions in "non-eloquent" cerebrum can be more aggressively surgically managed compared to "eloquent" regions with known functional relevance. Furthermore, advancements multimodal imaging technologies improved our ability extend rate while minimizing risk inducing new neurologic deficits, together referred as "onco-functional balance." However, despite common utilization invasive techniques such cortical mapping identify eloquent tissue responsible for language and motor functions, glioma patients continue present post-operatively poor cognitive morbidity higher-order functions. Such observations are likely related difficulty interpreting highly-dimensional information these us regarding cognition addition classically understanding structural neuroanatomy underlying complex reduction into isolated without consideration complex, interacting networks which function within subserve inherently prevents successful navigation true non-eloquent cerebrum. Fortunately, recent large-scale movements neuroscience community, Human Connectome Project (HCP), provided updated neural data detailing many intricate macroscopic connections between integrate process human behavior a "connectome." Connectomic provide better maps how understand convoluted subcortical relationships tumor begin make informed decisions during surgery maximize onco-functional balance. connectome-based neurosurgery applications neurorehabilitation relatively nascent require further work moving forward optimize add highly valuable connectomic armamentarium. In this manuscript, we review four concepts detailed examples will help post-operative outcomes guide utilize connectomics reduce following cerebral surgery.

Language: Английский

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