Translational Psychiatry, Journal Year: 2024, Volume and Issue: 14(1)
Published: Sept. 9, 2024
Language: Английский
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
Citations
20
Journal of Neurolinguistics, Journal Year: 2023, Volume and Issue: 70, P. 101180 - 101180
Published: Nov. 21, 2023
Language: Английский
Citations
15
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown
Published: Oct. 23, 2023
Variability drives the organization and behavior of complex systems, including human brain. Understanding variability brain signals is thus necessary to broaden our window into function behavior. Few empirical investigations macroscale signal have yet been undertaken, given difficulty in separating biological sources variance from artefactual noise. Here, we characterize temporal most predominant signal, fMRI BOLD systematically investigate its statistical, topographical neurobiological properties. We contrast acquisition protocols, integrate across histology, microstructure, transcriptomics, neurotransmitter receptor metabolic data, static connectivity, simulated magnetoencephalography data. show that represents a spatially heterogeneous, central property multi-scale multi-modal organization, distinct Our work establishes relevance provides lens on stochasticity spatial scales.
Language: Английский
Citations
15
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: March 11, 2024
Dynamic functional network connectivity (dFNC) analysis is a widely used approach for studying brain function and offering insight into how networks evolve over time. Typically, dFNC studies utilized fixed spatial maps evaluate transient changes in coupling among time courses estimated from independent component (ICA). This manuscript presents complementary that relaxes this assumption by spatially reordering the components dynamically at each timepoint to optimize smooth gradient FNC (i.e., ICA values). Several methods are presented summarize dynamic gradients (dFNGs) time, starting with static (sFNGs), then exploring properties as well dynamics of themselves. We apply dataset schizophrenia (SZ) patients healthy controls (HC). Functional dysconnectivity between different regions has been reported schizophrenia, yet neural mechanisms behind it remain elusive. Using resting state fMRI on consisting 151 160 age gender-matched controls, we extracted 53 intrinsic (ICNs) subject using fully automated constrained approach. develop several summaries our analysis, both sense, computed Pearson correlation coefficient full series, sliding window followed based gradient, group differences. Static revealed significantly stronger subcortical (SC), auditory (AUD) visual (VIS) patients, hypoconnectivity sensorimotor (SM) relative controls. sFNG highlighted distinctive clustering patterns HCs along cognitive control (CC)/ default mode (DMN), SC/ AUD/ SM/ cerebellar (CB), VIS gradients. Furthermore, observed significant differences sFNGs groups SC CB domains. dFNG suggested SZ spend more first while favor SM/DMN state. For second however, exhibited higher activity domains, contrasting HCs' DMN engagement. The synchrony conveyed shifts transmodal CC/ patients. In addition, distinct SC, SM domains compared HCs. To recap, results advance understanding modulation examining trajectories. provides complete spatiotemporal summary data, contributing growing body current literature regarding By employing dFNG, highlight new perspective capture large scale fluctuations across maintaining convenience low dimensional measures.
Language: Английский
Citations
4
Trends in Neurosciences, Journal Year: 2024, Volume and Issue: 47(7), P. 551 - 568
Published: May 31, 2024
Disentangling how cognitive functions emerge from the interplay of brain dynamics and network architecture is among major challenges that neuroscientists face. Pharmacological pathological perturbations consciousness provide a lens to investigate these complex challenges. Here, we review recent advances about brain's functional organisation have been driven by common denominator: decomposing function into fundamental constituents time, space, information. Whereas unconsciousness increases structure-function coupling across scales, psychedelics may decouple structure. Convergent effects also emerge: anaesthetics, psychedelics, disorders can exhibit similar reconfigurations unimodal-transmodal axis. Decomposition approaches reveal potential translate discoveries species, with computational modelling providing path towards mechanistic integration.
Language: Английский
Citations
4
PNAS Nexus, Journal Year: 2024, Volume and Issue: 3(10)
Published: Sept. 19, 2024
Complexity and entropy play crucial roles in understanding dynamic systems across various disciplines. Many intuitively perceive them as distinct measures assume that they have a concave-down relationship. In everyday life, there is common consensus while never decreases, complexity does decrease after an initial increase during the process of blending coffee milk. However, this primarily conceptual lacks empirical evidence. Here, we provide comprehensive evidence challenges prevailing consensus. We demonstrate is, fact, illusion resulting from choice system characterization (dimension) unit observation (resolution). By employing measure designed for natural patterns, find coffee-milk decreases if appropriately characterized terms dimension resolution. Also, aligns experimentally theoretically with entropy, suggesting it not represent so-called effective complexity. These findings rectify reshape our relationship between entropy. It therefore to exercise caution pay close attention accurately precisely characterize before delving into their underlying mechanisms, despite maturity research fields dealing patterns such geography ecology. The characterization/observation (dimension resolution) fundamentally determines assessment using existing understanding.
Language: Английский
Citations
4
Psychiatry and Clinical Neurosciences, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 11, 2025
Aim Autistic traits exhibit neurodiversity with varying behaviors across developmental stages. Brain complexity theory, illustrating the dynamics of neural activity, may elucidate evolution autistic over time. Our study explored patterns brain in individuals from childhood to adulthood. Methods We analyzed functional magnetic resonance imaging data 1087 participants and neurotypical controls aged 6 30 years within ABIDE I (Autism Imaging Data Exchange) set. Sample entropy was calculated measure among 90 regions, utilizing an automated anatomical labeling template for voxel parcellation. Participants were grouped using sliding age windows partial overlaps. assessed average entire regions both groups categories. Cluster analysis conducted generalized association plots identify similar trajectories. Finally, relationship between region examined. Results tend toward higher whole‐brain during adolescence lower adulthood, indicating possible distinct However, these results do not remain after Bonferroni correction. Two clusters identified, each unique changes Correlations complexity, age, also identified. Conclusion The revealed trajectories individuals, providing insight into autism suggesting that age‐related could be a potential neurodevelopmental marker dynamic nature autism.
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 14, 2025
Psychotic disorders, such as schizophrenia and bipolar disorder, pose significant diagnostic challenges with major implications on mental health. The measures of resting-state fMRI spatiotemporal complexity offer a powerful tool for identifying irregularities in brain activity. To capture global connectivity, we employed information-theoretic metrics, overcoming the limitations pairwise correlation analysis approaches. This enables more comprehensive exploration higher-order interactions multiscale intrinsic connectivity networks (ICNs) psychotic brain. In this study, provide converging evidence suggesting that exhibits states randomness across both spatial temporal dimensions. further investigate these disruptions, estimated network using redundancy synergy measures, aiming to assess integration segregation topological information Our findings reveal disruption balance between redundant synergistic information, phenomenon term brainquake which highlights instability disorganization psychosis. Moreover, our functional reveals profound disruptions integration. Aberrant were observed cortical subcortical ICNs. We specifically identified most easily affected sensorimotor, visual, temporal, default mode, fronto-parietal networks, well hippocampal amygdalar regions, all showed disruptions. These underscore severe impact critical alteration brain's organizational states.
Language: Английский
Citations
0
Advances in Continuous and Discrete Models, Journal Year: 2025, Volume and Issue: 2025(1)
Published: Feb. 10, 2025
Language: Английский
Citations
0
Biological Psychiatry, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
Language: Английский
Citations
0