Changes in brain connectivity and neurovascular dynamics during dexmedetomidine-induced loss of consciousness DOI Creative Commons
Panagiotis Fotiadis, Andrew R. McKinstry-Wu, Sarah M. Weinstein

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 7, 2024

ABSTRACT Understanding the neurophysiological changes that occur during loss and recovery of consciousness is a fundamental aim in neuroscience has marked clinical relevance. Here, we utilize multimodal magnetic resonance neuroimaging to investigate regional network connectivity neurovascular dynamics as brain transitions from wakefulness dexmedetomidine-induced unconsciousness, finally into early-stage consciousness. We observed widespread decreases functional strength across whole brain, targeted increases structure-function coupling (SFC) select networks— especially cerebellum—as individuals transitioned hypnosis. also robust cerebral blood flow (CBF) brain—especially within brainstem, thalamus, cerebellum. Moreover, hypnosis was characterized by significant amplitude low-frequency fluctuations (ALFF) resting-state oxygen level-dependent signal, localized visual somatomotor regions. Critically, when transitioning early stages recovery, SFC—but not CBF—started reverting towards their awake levels, even before behavioral arousal. By further testing for relationship between alterations, wakefulness, regions with higher ALFF displayed lower rest brain. During hypnosis, weaker structural connectivity. Correspondingly, stronger showed greater reductions CBF onset Earlier associated baseline (awake) levels strength, CBF, ALFF, well female sex. Across our findings, highlight role cerebellum recurrent marker states Collectively, these results demonstrate induction of, emergence unconsciousness are dynamics.

Язык: Английский

Structure–function coupling in macroscale human brain networks DOI
Panagiotis Fotiadis, Linden Parkes, Kathryn A. Davis

и другие.

Nature reviews. Neuroscience, Год журнала: 2024, Номер 25(10), С. 688 - 704

Опубликована: Авг. 5, 2024

Язык: Английский

Процитировано

26
Is depression a global brain disorder with topographic dynamic reorganization? DOI Creative Commons
Georg Northoff, Dušan Hirjak

Translational Psychiatry, Год журнала: 2024, Номер 14(1)

Опубликована: Июль 5, 2024

Abstract Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence remain yet unclear. Rather than linking localizing single to specific regions or networks, this perspective proposes more global dynamic topographic approach. We first review recent findings on brain activity changes during both rest task states in MDD showing reorganization with shift from unimodal transmodal regions. Next, we out two candidate that may underlie mediate abnormal uni-/transmodal topography, namely shifts shorter longer timescales abnormalities the excitation-inhibition balance. Finally, show how relates various their co-occurrence. This amounts what describe as ‘Topographic reorganization’ which extends our earlier ‘Resting state hypothesis depression’ complements other models MDD.

Язык: Английский

Процитировано

15
Multi-modal and multi-model interrogation of large-scale functional brain networks DOI Creative Commons
Francesca Castaldo, Francisco Páscoa dos Santos, Ryan C. Timms

и другие.

NeuroImage, Год журнала: 2023, Номер 277, С. 120236 - 120236

Опубликована: Июнь 24, 2023

Existing whole-brain models are generally tailored to the modelling of a particular data modality (e.g., fMRI or MEG/EEG). We propose that despite differing aspects neural activity each captures, they originate from shared network dynamics. Building on universal principles self-organising delay-coupled nonlinear systems, we aim link distinct features brain - captured across modalities dynamics unfolding macroscopic structural connectome. To jointly predict connectivity, spatiotemporal and transient signal modalities, consider two large-scale Stuart Landau Wilson Cowan which generate short-lived 40 Hz oscillations with varying levels realism. this end, measure functional connectivity metastable oscillatory modes (MOMs) in MEG signals compare them against simulated data. show both can represent (FC), (FCD) MOMs comparable degree. This is achieved by adjusting global coupling mean conduction time delay and, WC model, through inclusion balance between excitation inhibition. For models, omission delays dramatically decreased performance. fMRI, SL model performed worse for FCD MOMs, highlighting importance balanced emergence patterns ultra-slow Notably, optimal working points varied no was able achieve correlation empirical FC higher than 0.4 same set parameters. Nonetheless, displayed extended beyond constraints anatomical structure. Finally, empirical-like properties such as size (number regions engaging mode) duration (continuous interval during mode appears). Our results demonstrate static dynamic at different timescales networks oscillators Hz. Given dependence underlying suggest mesoscale heterogeneities circuitry may be critical parallel cross-modal should accounted future endeavours.

Язык: Английский

Процитировано

21
Understanding structural-functional connectivity coupling in patients with major depressive disorder: A white matter perspective DOI
Tongpeng Chu, Xiaopeng Si, Xicheng Song

и другие.

Journal of Affective Disorders, Год журнала: 2025, Номер 373, С. 219 - 226

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

0
Temporal Lobe Epilepsy Perturbs the Brain‐Wide Excitation‐Inhibition Balance: Associations with Microcircuit Organization, Clinical Parameters, and Cognitive Dysfunction DOI Creative Commons
Ke Xie, Jessica Royer, Raúl Rodríguez‐Cruces

и другие.

Advanced Science, Год журнала: 2025, Номер unknown

Опубликована: Янв. 13, 2025

Abstract Excitation‐inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I at macroscale, whole‐brain level, and microcircuit‐level mechanisms clinical significance remain incompletely understood. Here, Hurst exponent, an index ratio, computed from resting‐state fMRI time series, microcircuit parameters are simulated using biophysical models. A broad decrease exponent observed pharmaco‐resistant temporal lobe epilepsy (TLE), suggesting more excitable network dynamics. Connectome decoders point to temporolimbic frontocentral cortices plausible epicenters imbalance. Furthermore, computational simulations reveal that enhancing cortical excitability TLE reflects atypical increases recurrent connection strength local neuronal ensembles. Mixed cross‐sectional longitudinal analyses show stronger ratio elevation patients longer disease duration, frequent electroclinical seizures well interictal epileptic spikes, worse cognitive functioning. exponent‐informed classifiers discriminate healthy controls high accuracy (72.4% [57.5%–82.5%]). Replicated independent dataset, this work provides vivo evidence macroscale shift balance points progressive functional imbalances relate decline.

Язык: Английский

Процитировано

0
Antisocial personality disorder:Failure to balance excitation/inhibition? DOI Creative Commons
Klaus‐Peter Lesch, Nikita Gorbunov

Neuropharmacology, Год журнала: 2025, Номер unknown, С. 110321 - 110321

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
The overgrowth of structure-function coupling in premature brain during infancy DOI Creative Commons

Rong Wang,

Tianyu Fang,

Yue Zhang

и другие.

Developmental Cognitive Neuroscience, Год журнала: 2025, Номер 72, С. 101535 - 101535

Опубликована: Фев. 21, 2025

Язык: Английский

Процитировано

0
How the layer-dependent ratio of excitatory to inhibitory cells shapes cortical coding in balanced networks DOI Open Access
Arezoo Alizadeh, Bernhard Englitz, Fleur Zeldenrust

и другие.

Опубликована: Фев. 27, 2025

The cerebral cortex exhibits a sophisticated neural architecture across its six layers. Recently, it was found that these layers exhibit different ratios of excitatory to inhibitory (EI) neurons, ranging from 4 9. This ratio is key factor for achieving the often reported balance excitation and inhibition, hallmark cortical computation. However, neither previous theoretical nor simulation studies have addressed how differences in EI will affect layer-specific dynamics computational properties. We investigate this question using sparsely connected network model neurons. To keep physiological range firing rates, we varied threshold or synaptic strength between find decreasing allows explore higher-dimensional space enhance capacity represent complex input. By comparing empirical layer 2/3 rodent barrel cortex, predict has higher dimensionality coding than 4. Furthermore, our analysis primary visual data Allen Brain Institute corroborates modelling results, also demonstrating increased capabilities 2/3.

Язык: Английский

Процитировано

0
How the layer-dependent ratio of excitatory to inhibitory cells shapes cortical coding in balanced networks DOI Open Access
Arezoo Alizadeh, Bernhard Englitz, Fleur Zeldenrust

и другие.

Опубликована: Фев. 27, 2025

The cerebral cortex exhibits a sophisticated neural architecture across its six layers. Recently, it was found that these layers exhibit different ratios of excitatory to inhibitory (EI) neurons, ranging from 4 9. This ratio is key factor for achieving the often reported balance excitation and inhibition, hallmark cortical computation. However, neither previous theoretical nor simulation studies have addressed how differences in EI will affect layer-specific dynamics computational properties. We investigate this question using sparsely connected network model neurons. To keep physiological range firing rates, we varied threshold or synaptic strength between find decreasing allows explore higher-dimensional space enhance capacity represent complex input. By comparing empirical layer 2/3 rodent barrel cortex, predict has higher dimensionality coding than 4. Furthermore, our analysis primary visual data Allen Brain Institute corroborates modelling results, also demonstrating increased capabilities 2/3.

Язык: Английский

Процитировано

0
Detection of structural-functional coupling abnormalities using multimodal brain networks in Alzheimer’s disease: A comparison of three computational models DOI Creative Commons
Yinping Lu, Lu-Yao Wang,

Toshiya Murai

и другие.

NeuroImage Clinical, Год журнала: 2025, Номер 46, С. 103764 - 103764

Опубликована: Янв. 1, 2025

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the disconnection of white matter fibers and disrupted functional connectivity gray matter; however, pathological mechanisms linking structural changes remain unclear. This study aimed to explore interaction between brain network in AD using advanced structural-functional coupling (S-F coupling) models assess whether these correlate with cognitive function, Aβ deposition levels, gene expression. In this study, we utilized multimodal magnetic resonance imaging data from 41 individuals AD, 112 mild impairment, 102 healthy controls mechanisms. We applied different computational examine S-F associated AD. Our results showed that communication graph harmonic demonstrated greater heterogeneity were more sensitive than statistical detecting AD-related changes. addition, increases progression at global, subnetwork, regional node especially medial prefrontal anterior cingulate cortices. The regions also partially mediated decline deposition. Furthermore, enrichment analysis revealed strongly regulation cellular catabolic processes. advances our understanding highlights importance elucidating neural underlying

Язык: Английский

Процитировано

0