Geometric constraints on human brain function

Nature, Год журнала: 2023, Номер 618(7965), С. 566 - 574

Опубликована: Май 31, 2023

The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected a complex array axonal fibres

Язык: Английский

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Standardizing workflows in imaging transcriptomics with the abagen toolbox

eLife, Год журнала: 2021, Номер 10

Опубликована: Ноя. 16, 2021

Gene expression fundamentally shapes the structural and functional architecture of human brain. Open-access transcriptomic datasets like Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack standardization across research groups has given rise myriad processing pipelines for using data. Here, we develop abagen toolbox, open-access software package working with data, use it how methodological variability influences outcomes Atlas. Applying three prototypical analyses outputs 750,000 unique pipelines, find that choice pipeline large impact on findings, parameters commonly varied literature influencing correlations between derived gene other imaging phenotypes by as much ρ ≥ 1.0. Our results further reveal ordering parameter importance, steps influence normalization yielding greatest downstream statistical inferences conclusions. The presented work development toolbox lay foundation more standardized systematic transcriptomics, will help advance future understanding

Язык: Английский

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Information decomposition and the informational architecture of the brain

Trends in Cognitive Sciences, Год журнала: 2024, Номер 28(4), С. 352 - 368

Опубликована: Янв. 9, 2024

To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, is not a monolithic entity. Information decomposition techniques provide way to split into its constituent elements: unique, redundant, and synergistic information. We review disentangling redundant interactions redefining our understanding of integrative function neural organisation. navigates trade-offs between redundancy synergy, converging evidence integrating structural, molecular, functional underpinnings synergy redundancy; their roles in cognition computation; they might arise over evolution development. Overall, provides guiding principle informational architecture cognition.

Язык: Английский

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Virtual brain twins: from basic neuroscience to clinical use

National Science Review, Год журнала: 2024, Номер 11(5)

Опубликована: Фев. 27, 2024

ABSTRACT Virtual brain twins are personalized, generative and adaptive models based on data from an individual’s for scientific clinical use. After a description of the key elements virtual twins, we present standard model personalized whole-brain network models. The personalization is accomplished using subject’s imaging by three means: (1) assemble cortical subcortical areas in subject-specific space; (2) directly map connectivity into models, which can be generalized to other parameters; (3) estimate relevant parameters through inversion, typically probabilistic machine learning. We use healthy ageing five diseases: epilepsy, Alzheimer’s disease, multiple sclerosis, Parkinson’s disease psychiatric disorders. Specifically, introduce spatial masks demonstrate their physiological pathophysiological hypotheses. Finally, pinpoint challenges future directions.

Язык: Английский

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Topographic gradients of intrinsic dynamics across neocortex

eLife, Год журнала: 2020, Номер 9

Опубликована: Дек. 17, 2020

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns neural activity throughout human brain. Applying massive feature extraction to regional haemodynamic activity, systematically estimate over 6000 statistical properties individual brain regions' time-series across neocortex. We identify two robust spatial gradients dynamics, one spanning a ventromedial-dorsolateral axis dominated measures signal autocorrelation, other unimodal-transmodal dynamic range. These reflect gene expression, intracortical myelin cortical thickness, as well structural functional network embedding. Importantly, these correlated with meta-analytic activation, differentiating cognitive versus affective processing sensory higher-order processing. Altogether, findings demonstrate link between architecture, cognition.

Язык: Английский

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Time-resolved structure-function coupling in brain networks

Communications Biology, Год журнала: 2022, Номер 5(1)

Опубликована: Июнь 2, 2022

The relationship between structural and functional connectivity in the brain is a key question systems neuroscience. Modern accounts assume single global structure-function that persists over time. Here we study coupling from dynamic perspective, show it regionally heterogeneous. We use temporal unwrapping procedure to identify moment-to-moment co-fluctuations neural activity, reconstruct time-resolved patterns. find patterns of are region-specific. observe stable unimodal transmodal cortex, intermediate regions, particularly insular cortex (salience network) frontal eye fields (dorsal attention network). Finally, variability region's related distribution its connection lengths. Collectively, our findings provide way relationships perspective.

Язык: Английский

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Toward Best Practices for Imaging Transcriptomics of the Human Brain

Biological Psychiatry, Год журнала: 2022, Номер 93(5), С. 391 - 404

Опубликована: Ноя. 5, 2022

Язык: Английский

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Understanding brain states across spacetime informed by whole-brain modelling

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Год журнала: 2022, Номер 380(2227)

Опубликована: Май 23, 2022

In order to survive in a complex environment, the human brain relies on ability flexibly adapt ongoing behaviour according intrinsic and extrinsic signals. This capability has been linked specific whole-brain activity patterns whose relative stability (order) allows for consistent functioning, supported by sufficient instability needed optimal adaptability. The emergent, spontaneous balance between disorder over spacetime underpins distinct states. For example, depression is characterized excessively rigid, highly ordered states, while psychedelics can bring about more disordered, sometimes overly flexible Recent developments systems, computational theoretical neuroscience have started make inroads into characterization of such dynamics space time. Here, we review recent insights drawn from neuroimaging modelling motivating using mechanistic principles dynamical system theory study characterize We show how different healthy altered states are associated characteristic which turn may offer that time inspire new treatments rebalancing disease. article part theme issue 'Emergent phenomena physical socio-technical systems: cells societies'.

Язык: Английский

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It’s about time: Linking dynamical systems with human neuroimaging to understand the brain

Network Neuroscience, Год журнала: 2022, Номер 6(4), С. 960 - 979

Опубликована: Янв. 1, 2022

Abstract Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these are often interpreted in light dynamic, information-processing concepts, the static, local, and inferential nature approach makes it challenging directly link neuroimaging results plausible underlying mechanisms. Here, we argue dynamical systems theory provides crucial mechanistic framework for characterizing both brain’s time-varying quality its partial stability face perturbations, hence, this perspective can have a profound impact interpretation their relationship with behavior. After briefly reviewing some key terminology, identify three ways which analyses embrace perspective: by shifting from local more global perspective, focusing dynamics instead static snapshots activity, embracing modeling map using “forward” models. Through approach, envisage ample opportunities researchers enrich understanding dynamic mechanisms support wide array brain functions, health setting psychopathology.

Язык: Английский

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Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics

Science Advances, Год журнала: 2023, Номер 9(11)

Опубликована: Март 17, 2023

Model-based data analysis of whole-brain dynamics links the observed to model parameters in a network neural masses. Recently, studies focused on role regional variance parameters. Such analyses however necessarily depend properties preselected mass model. We introduce method infer from functional both representing and region- subject-specific while respecting known structure. apply human resting-state fMRI. find that underlying can be described as noisy fluctuations around single fixed point. The reliably discovers three with clear distinct dynamics, one which is strongly correlated first principal component gene expression spatial map. present approach opens novel way fMRI possible applications for understanding brain during aging or neurodegeneration.

Язык: Английский

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