Spatiotemporally heterogeneous coordination of cholinergic and neocortical activity

Nature Neuroscience, Journal Year: 2022, Volume and Issue: 25(12), P. 1706 - 1713

Published: Nov. 28, 2022

Language: Английский

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Why is everyone talking about brain state?

Trends in Neurosciences, Journal Year: 2023, Volume and Issue: 46(7), P. 508 - 524

Published: May 8, 2023

The rapid and coordinated propagation of neural activity across the brain provides foundation for complex behavior cognition. Technical advances neuroscience subfields have advanced understanding these dynamics, but points convergence are often obscured by semantic differences, creating silos subfield-specific findings. In this review we describe how a parsimonious conceptualization state as fundamental building block whole-brain offers common framework to relate findings scales species. We present examples diverse techniques commonly used study states associated with physiology higher-order cognitive processes, discuss integration them will enable more comprehensive mechanistic characterization dynamics that crucial survival disrupted in disease.

Language: Английский

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Facemap: a framework for modeling neural activity based on orofacial tracking

Nature Neuroscience, Journal Year: 2023, Volume and Issue: 27(1), P. 187 - 195

Published: Nov. 20, 2023

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand nature and function these signals, we need better computational models to characterize relate them activity. Here developed Facemap, framework consisting keypoint tracker deep network encoder for predicting Our algorithm tracking mouse was more accurate than existing pose estimation tools, while processing speed several times faster, making it powerful tool real-time experimental interventions. The Facemap easy adapt data from new labs, requiring as few 10 annotated frames near-optimal performance. We used keypoints inputs which predicts ~50,000 simultaneously-recorded neurons and, visual cortex, doubled amount explained variance compared previous methods. Using this model, found neuronal clusters were well predicted behavior spatially spread out cortex. also behavioral features model had stereotypical, sequential dynamics not reversible time. In summary, provides stepping stone toward understanding brain-wide signals their relation behavior.

Language: Английский

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Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

Neuron, Journal Year: 2022, Volume and Issue: 110(19), P. 3064 - 3075

Published: July 20, 2022

Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances technology, allowing large-scale neural recordings awake and behaving animal, have transformed our understanding activity. Studies using these discovered high-dimensional patterns, correlation between behavior, dissimilarity sensory-driven patterns. These findings supported by evidence from developing animals, where a transition toward characteristics is observed as circuit matures, well mature animals across species. newly revealed call for formulation new computation.

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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VTA projections to M1 are essential for reorganization of layer 2-3 network dynamics underlying motor learning

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 2, 2025

The primary motor cortex (M1) is crucial for skill learning. Previous studies demonstrated that acquisition requires dopaminergic VTA (ventral-tegmental area) signaling in M1, however little known regarding the effect of these inputs at neuronal and network levels. Using dexterity task, calcium imaging, chemogenetic inhibiting, geometric data analysis, we demonstrate VTA-dependent reorganization M1 layer 2-3 during While average activity functional connectivity remain stable learning, kinetics, correlational configuration connectivity, strength neurons gradually transform towards an expert configuration. Additionally, sensory tone representation shifts to success-failure outcome signaling. Inhibiting prevents all changes. Our findings formation new network, supporting storing skills. Motor learning relies on (M1), but how from ventral tegmental area (VTA) affect levels remains unclear. Here, authors show essential neurons, transforming their

Language: Английский

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DySCo: A general framework for dynamic functional connectivity

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(3), P. e1012795 - e1012795

Published: March 7, 2025

A crucial challenge in neuroscience involves characterising brain dynamics from high-dimensional recordings. Dynamic Functional Connectivity (dFC) is an analysis paradigm that aims to address this challenge. dFC consists of a time-varying matrix (dFC matrix) expressing how pairwise interactions across areas change over time. However, the main approaches have been developed and applied mostly empirically, lacking common theoretical framework clear view on interpretation results derived matrices. Moreover, community has not using most efficient algorithms compute process matrices efficiently, which prevented showing its full potential with datasets and/or real-time applications. In paper, we introduce Symmetric Matrix (DySCo), associated repository. DySCo presents commonly used measures language implements them computationally way. This allows study activity at different spatio-temporal scales, down voxel level. provides single to: (1) Use as tool capture interaction patterns data form easily translatable imaging modalities. (2) Provide comprehensive set quantify properties evolution time: amount connectivity, similarity between matrices, their informational complexity. By combining it possible perform analysis. (3) Leverage Temporal Covariance EVD algorithm (TCEVD) store eigenvectors values then also EVD. Developing eigenvector space orders magnitude faster more memory than naïve space, without loss information. The methodology here validated both synthetic dataset rest/N-back task experimental fMRI Human Connectome Project dataset. We show all proposed are sensitive changes configurations consistent time subjects. To illustrate computational efficiency toolbox, performed level, demanding but afforded by TCEVD.

Language: Английский

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Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Jan. 24, 2024

Abstract Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no applied this data collected from model organisms. Here, we analyze structural and functional imaging lightly anesthetized mice through lens. We find evidence of “bursty” events - brief periods high-amplitude connectivity. Further, show that on a per-frame basis best explain static FC can be divided into series hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas largely adhere the boundaries algorithmically detected brain systems. then investigate connectivity undergirding patterns. induce modular bipartitions inter-areal axonal projections. Finally, replicate these same findings dataset. In summary, report recapitulates organism many phenomena observed previously analyses data. However, unlike subjects, murine nervous system is amenable invasive experimental perturbations. Thus, sets stage for future investigation causal origins co-fluctuations. Moreover, cross-species consistency reported enhances likelihood translation.

Language: Английский

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Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception

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

Published: June 18, 2024

Abstract Empathy enables understanding and sharing of others’ feelings. Human neuroimaging studies have identified critical brain regions supporting empathy for pain, including the anterior insula (AI), cingulate (ACC), amygdala, inferior frontal gyrus (IFG). However, to date, precise spatio-temporal profiles empathic neural responses inter-regional communications remain elusive. Here, using intracranial electroencephalography, we investigated electrophysiological signatures vicarious pain perception. Others’ perception induced early increases in high-gamma activity IFG, beta power ACC, but decreased AI amygdala. Vicarious also altered beta-band-coordinated coupling between AI, as well increased modulation IFG amplitudes by phases amygdala/AI/ACC. We a necessary combination features decoding These spatio-temporally specific regional activities interactions within network suggest neurodynamic model human empathy.

Language: Английский

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Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(2)

Published: Jan. 31, 2024

Traumatic brain injury (TBI) is the leading cause of death in young people and can cognitive motor dysfunction disruptions functional connectivity between regions. In human TBI patients rodent models TBI, decreased after injury. Recovery associated with improved cognition memory, suggesting an important link outcome. We examined widespread alterations following using simultaneous widefield mesoscale GCaMP7c calcium imaging electrocorticography (ECoG) mice injured controlled cortical impact (CCI) model TBI. Combining CCI provides us unprecedented access to characterize network changes throughout entire cortex over time. Our data demonstrate that profoundly disrupts immediately injury, followed by partial recovery 3 weeks. Examining discrete periods locomotion stillness reveals alters reduces theta power only during behavioral stillness. Together, these findings causes dynamic, state-dependent ECoG activity across cortex.

Language: Английский

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