Unique spatiotemporal fMRI dynamics in the awake mouse brain

Current Biology, Journal Year: 2022, Volume and Issue: 32(3), P. 631 - 644.e6

Published: Jan. 7, 2022

Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally states. However, whether and how this phenomenon can be generalized lower mammalian species remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping non-anesthetized, head-fixed mice, we investigated functional network topography dynamic structure of wakeful animals. We found rsfMRI networks the awake state, while anatomically comparable those observed under anesthesia, are topologically configured maximize interregional communication, departing from underlying community mouse axonal connectome. further report animals unique dynamics characterized by state-dependent, dominant occurrence coactivation patterns encompassing prominent participation arousal-related forebrain nuclei anti-coordination between visual-auditory polymodal cortical areas. finally show mice stereotypical temporal structure, which state-dominant as attractors. These findings suggest is critically shaped state-specific involvement basal arousal systems document its recapitulates distinctive, evolutionarily relevant principles predictive states higher species.

Language: Английский

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A parsimonious description of global functional brain organization in three spatiotemporal patterns

Nature Neuroscience, Journal Year: 2022, Volume and Issue: 25(8), P. 1093 - 1103

Published: July 28, 2022

Language: Английский

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Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Oct. 3, 2022

Psychedelics including lysergic acid diethylamide (LSD) and psilocybin temporarily alter subjective experience through their neurochemical effects. Serotonin 2a (5-HT2a) receptor agonism by these compounds is associated with more diverse (entropic) brain activity. We postulate that this increase in entropy may arise part from a flattening of the brain's control energy landscape, which can be observed using network theory to quantify required transition between recurrent states. Using states derived existing functional magnetic resonance imaging (fMRI) datasets, we show LSD reduce for state transitions compared placebo. Furthermore, across individuals, reduction correlates frequent increased dynamics. Through analysis incorporates spatial distribution 5-HT2a receptors (obtained publicly available positron emission tomography (PET) data under non-drug conditions), demonstrate an association reduced energy. Our findings provide evidence agonist allow facile temporally More broadly, receptor-informed model impact neuropharmacological manipulation on activity

Language: Английский

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Controversies and progress on standardization of large-scale brain network nomenclature

Network Neuroscience, Journal Year: 2023, Volume and Issue: 7(3), P. 864 - 905

Published: Jan. 1, 2023

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level macroscale organization brain, beginning to confront challenges associated with developing a taxonomy its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy NETworks (WHATNET) was formed 2020 as an Organization Human Brain Mapping (OHBM)-endorsed best practices committee provide recommendations on points consensus, identify open questions, and highlight areas ongoing debate service moving field toward standardized reporting network neuroscience results. conducted survey catalog current large-scale brain nomenclature. A few well-known names (e.g., default mode network) dominated responses survey, number illuminating disagreement emerged. We summarize results initial considerations from workgroup. This perspective piece includes selective review this enterprise, including (1) scale, resolution, hierarchies; (2) interindividual variability networks; (3) dynamics nonstationarity (4) consideration affiliations subcortical structures; (5) multimodal information. close minimal guidelines cognitive communities adopt.

Language: Английский

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Higher-order organization of multivariate time series

Nature Physics, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 2, 2023

Language: Английский

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Partial entropy decomposition reveals higher-order information structures in human brain activity

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(30)

Published: July 19, 2023

The standard approach to modeling the human brain as a complex system is with network, where basic unit of interaction pairwise link between two regions. While powerful, this limited by inability assess higher-order interactions involving three or more elements directly. In work, we explore method for capturing dependencies in multivariate data: partial entropy decomposition (PED). Our decomposes joint whole into set nonnegative atoms that describe redundant, unique, and synergistic compose system's structure. PED gives insight mathematics functional connectivity its limitation. When applied resting-state fMRI data, find robust evidence synergies are largely invisible analyses. can also be localized time, allowing frame-by-frame analysis how distributions redundancies change over course recording. We different ensembles regions transiently from being redundancy-dominated synergy-dominated temporal pattern structured time. These results provide strong there exists large space unexplored structures data have been missed focus on bivariate network models. This structure dynamic time likely will illuminate interesting links behavior. Beyond brain-specific application, provides very general understanding variety systems.

Language: Английский

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Brain connectomics: time for a molecular imaging perspective?

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(4), P. 353 - 366

Published: Jan. 6, 2023

Language: Английский

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Multivariate information theory uncovers synergistic subsystems of the human cerebral cortex

Communications Biology, Journal Year: 2023, Volume and Issue: 6(1)

Published: April 24, 2023

One of the most well-established tools for modeling brain is functional connectivity network, which constructed from pairs interacting regions. While powerful, network model limited by restriction that only pairwise dependencies are considered and potentially higher-order structures missed. Here, we explore how multivariate information theory reveals in human brain. We begin with a mathematical analysis O-information, showing analytically numerically it related to previously established theoretic measures complexity. then apply O-information data, synergistic subsystems widespread Highly typically sit between canonical networks, may serve an integrative role. use simulated annealing find maximally subsystems, finding such systems comprise ≈10 regions, recruited multiple systems. Though ubiquitous, highly invisible when considering connectivity, suggesting form kind shadow structure has been unrecognized network-based analyses. assert interactions represent under-explored space that, accessible theory, offer novel scientific insights.

Language: Английский

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Enhancing precision in human neuroscience

eLife, Journal Year: 2023, Volume and Issue: 12

Published: Aug. 9, 2023

Human neuroscience has always been pushing the boundary of what is measurable. During last decade, concerns about statistical power and replicability – in science general, but also specifically human have fueled an extensive debate. One important insight from this discourse need for larger samples, which naturally increases power. An alternative to increase precision measurements, focus review. This option often overlooked, even though benefits increasing as much sample size. Nonetheless, at heart good scientific practice neuroscience, with researchers relying on lab traditions or rules thumb ensure sufficient their studies. In review, we encourage a more systematic approach precision. We start by introducing measurement its importance well-powered studies neuroscience. Then, determinants range neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, Endocrinology) are elaborated. end discussing how evaluation application respective insights can lead reproducibility

Language: Английский

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An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

Frontiers in Artificial Intelligence, Journal Year: 2020, Volume and Issue: 3

Published: June 9, 2020

The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges prevent entropic accumulation. In FEP-AI, minds brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) considering preconditions a system to intrinsically exist, well axioms regarding nature of consciousness. IIT has produced controversy because its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; possibility fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating integrated information only entails consciousness perspectival reference frames capable generating models spatial, temporal, causal coherence self world. Without connection external reality, could have arbitrarily high amounts information, but nonetheless would not entail subjective experience. further an integration frameworks may contribute their evolution unified theories emergent causation. Then, inspired both Global Neuronal Workspace (GNWT) Harmonic Brain Modes framework, streams emerge evolving generation sensorimotor predictions, precise composition experiences depending on abilities synchronous complexes self-organizing harmonic modes (SOHMs). These dynamics particularly likely occur via richly connected subnetworks affording body-centric sources phenomenal binding executive control. Along connectivity backbones, SOHMs proposed implement turbo coding loopy message-passing over (autoencoding) networks, thus maximum posteriori estimates coherent vectors governing neural evolution, alpha frequencies basic awareness, cross-frequency phase-coupling within theta access volitional dynamic cores also function global workspaces, centered posterior cortices, being entrained frontal cortices interoceptive hierarchies, agentic World Modeling (IWMT) represents synthetic approach reveals compatibility between leading consciousness, enabling inferential synergy.

Language: Английский

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