Visual statistical learning is associated with changes in low-dimensional cortical architecture DOI Creative Commons

Keanna Rowchan,

Daniel J. Gale,

Qasem Nick

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 25, 2023

Our brains are in a near constant state of generating predictions, extracting regularities from seemingly random sensory inputs to support later cognition and behavior, process called statistical learning (SL). Yet, the activity patterns across cortex subcortex that this form associative remain unresolved. Here we use human fMRI visual SL task investigate changes neural as participants implicitly learn associations sequence. By projecting functional connectivity onto low-dimensional manifold, reveal is selectively supported by along single dimension spanning visual-parietal perirhinal (PRC). During learning, expanded dimension, segregating other networks, while dorsal attention network (DAN) regions contracted, integrating with higher-order transmodal cortex. When violated learned associations, PRC entorhinal cortex, which initially showed no evidence learning-related effects, now contracted default mode DAN, decreasing covariance Whereas previous studies have linked either broad cortical or medial temporal lobe changes, our findings suggest an integrative view, whereby reorganize during association formation, respond their violation.

Language: Английский

Large-scale neural dynamics in a shared low-dimensional state space reflect cognitive and attentional dynamics DOI Creative Commons
Hayoung Song, Won Mok Shim, Monica D. Rosenberg

et al.

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

Published: July 3, 2023

Cognition and attention arise from the adaptive coordination of neural systems in response to external internal demands. The low-dimensional latent subspace that underlies large-scale dynamics relationships these cognitive attentional states, however, are unknown. We conducted functional magnetic resonance imaging as human participants performed tasks, watched comedy sitcom episodes an educational documentary, rested. Whole-brain traversed a common set states spanned canonical gradients brain organization, with global desynchronization among networks modulating state transitions. Neural were synchronized across people during engaging movie watching aligned narrative event structures. reflected fluctuations such different indicated engaged task naturalistic contexts, whereas lapses both contexts. Together, results demonstrate traversals along organization reflect dynamics.

Language: Английский

Citations

32
Language network lateralization is reflected throughout the macroscale functional organization of cortex DOI Creative Commons
Loïc Labache, Tian Ge, B.T. Thomas Yeo

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: June 9, 2023

Hemispheric specialization is a fundamental feature of human brain organization. However, it not yet clear to what extent the lateralization specific cognitive processes may be evident throughout broad functional architecture cortex. While majority people exhibit left-hemispheric language dominance, substantial minority population shows reverse lateralization. Using twin and family data from Human Connectome Project, we provide evidence that atypical dominance associated with global shifts in cortical Individuals organization corresponding hemispheric differences macroscale gradients situate discrete large-scale networks along continuous spectrum, extending unimodal through association territories. Analyses reveal both gradient asymmetries are, part, driven by genetic factors. These findings pave way for deeper understanding origins relationships linking population-level variability properties

Language: Английский

Citations

31
Omnipresence of the sensorimotor-association axis topography in the human connectome DOI Creative Commons
Karl‐Heinz Nenning, Ting Xu, Alexandre R. Franco

et al.

NeuroImage, Journal Year: 2023, Volume and Issue: 272, P. 120059 - 120059

Published: March 30, 2023

Low-dimensional representations are increasingly used to study meaningful organizational principles within the human brain. Most notably, sensorimotor-association axis consistently explains most variance in connectome as its so-called principal gradient, suggesting that it represents a fundamental principle. While recent work indicates these low dimensional relatively robust, they limited by modeling only certain aspects of functional connectivity structure. To date, majority studies have restricted approaches strongest connections brain, treating weaker or negative noise despite evidence structure among them. The present examines gradients across full range strengths and explores implications for outcomes individual differences, identifying potential dependencies on thresholds opportunities improve prediction tasks. Interestingly, emerged gradient entire levels. Moreover, at intermediate encoded better followed individual-specific anatomical features, was also more predictive intelligence. Taken together, our results add principle brain's organization, since is evident even lenient thresholds. These loosely coupled further appear contain valuable potentially important information could be understanding diagnosis, treatment outcomes.

Language: Английский

Citations

12
Connectivity gradients in spontaneous brain activity at multiple frequency bands DOI
Zhu-Qing Gong, Xi‐Nian Zuo

Cerebral Cortex, Journal Year: 2023, Volume and Issue: 33(17), P. 9718 - 9728

Published: June 28, 2023

Abstract The intrinsic organizational structure of the brain is reflected in spontaneous oscillations. Its functional integration and segregation hierarchy have been discovered space by leveraging gradient approaches to low-frequency connectivity. This oscillations has not yet fully understood, since previous studies mainly concentrated on from a single limited frequency range (~ 0.01–0.1 Hz). In this work, we extended performed analysis across multiple bands fast resting-state fMRI signals Human Connectome Project condensed frequency-rank cortical map highest gradient. We found that coarse skeletons organization are generalizable bands. Beyond that, levels connectivity vary domain different large-scale networks. These findings replicated another independent dataset demonstrated networks can integrate information at varying rates, indicating significance examining architecture activity perspective

Language: Английский

Citations

12
Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions DOI Creative Commons
Xuan Li, Simon B. Eickhoff, Susanne Weis

et al.

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(3)

Published: Feb. 15, 2025

While the use of naturalistic stimuli such as movie clips for understanding individual differences and brain-behaviour relationships attracts increasing interest, influence stimulus selection remains largely unclear. By using machine learning to predict traits (phenotypes) from brain activity evoked during various clips, we show that different can result in distinct prediction performances. In regions related lower-level processing stimulus, a certain degree benefits stronger synchronisation across subjects. contrast, better predictions frontoparietal are mainly associated with larger inter-subject variability. Furthermore, demonstrate while rich social content general achieve predictions, importance specific features highly depends on phenotype under investigation. Overall, our findings underscore careful provide novel insights into conditions, opening new avenues future research.

Language: Английский

Citations

0
Hierarchical feature extraction on functional brain networks for autism spectrum disorder identification with resting-state fMRI data DOI

Yiqian Luo,

Qiurong Chen,

Fali Li

et al.

Neural Networks, Journal Year: 2025, Volume and Issue: 188, P. 107450 - 107450

Published: April 12, 2025

Language: Английский

Citations

0
Connectopic mapping techniques do not reflect functional gradients in the brain DOI Creative Commons
David Watson, Timothy J. Andrews

NeuroImage, Journal Year: 2023, Volume and Issue: 277, P. 120228 - 120228

Published: June 18, 2023

Functional gradients, in which response properties change gradually across a brain region, have been proposed as key organising principle of the brain. Recent studies using both resting-state and natural viewing paradigms indicated that these gradients may be reconstructed from functional connectivity patterns via "connectopic mapping" analyses. However, local confounded by spatial autocorrelations artificially introduced during data analysis, for instance smoothing or interpolation between coordinate spaces. Here, we investigate whether such confounds can produce illusory connectopic gradients. We generated datasets comprising random white noise subjects' volume spaces, then optionally applied and/or interpolated to different surface space. Both induced sufficient mapping volume- surface-based numerous regions. Furthermore, appeared highly similar those obtained real data, although were statistically certain scenarios. also global whole-brain - while less susceptible artificial autocorrelations, ability reproduce previously reported was closely linked specific features analysis pipeline. These results indicate identified techniques some cases poorly pipelines. findings imply need interpreted with caution.

Language: Английский

Citations

10
Altered Hemispheric Asymmetry of Functional Hierarchy in Schizophrenia DOI Creative Commons

Yi Zhen,

Hongwei Zheng, Yi Zheng

et al.

Brain Sciences, Journal Year: 2025, Volume and Issue: 15(3), P. 313 - 313

Published: March 16, 2025

Background/Objectives: Schizophrenia is a severe psychiatric disorder characterized by deficits in perception and advanced cognitive functions. Prior studies have reported abnormal lateralization cortical morphology functional connectivity schizophrenia. However, it remains unclear whether schizophrenia affects hemispheric asymmetry the hierarchical organization of connectome. Methods: Here, we apply gradient mapping framework to connectome estimate first three gradients, which characterize unimodal-to-transmodal, visual-to-somatomotor, somatomotor/default mode-to-multiple demand hierarchy axes. We then assess between-group differences intra- inter-hemispheric asymmetries these gradients. Results: find that, compared healthy controls, patients with exhibit significantly altered across multiple networks, including dorsal attention, ventral visual, control networks. Region-level analyses further reveal that show several regions prefrontal gyrus, medial superior frontal somatomotor areas. Lastly, gradients can differentiate between controls predict severity positive symptoms Conclusions: Collectively, findings suggest associated hierarchy, providing novel perspectives for understanding atypical brain

Language: Английский

Citations

0
Dynamic and Static Functional Gradient in Temporal Lobe Epilepsy With Hippocampal Sclerosis Versus Healthy Controls DOI Creative Commons
Kangrun Wang,

JiaYao Li,

Fangfang Xie

et al.

CNS Neuroscience & Therapeutics, Journal Year: 2025, Volume and Issue: 31(4)

Published: April 1, 2025

ABSTRACT Aims The gradient captures the continuous transitions in connectivity, representing an intrinsic hierarchical architecture of brain. Previous works hinted at dynamics but did not verify them. Cognitive impairment is a common comorbidity temporal lobe epilepsy (TLE). Gradient techniques provide framework that could promote understanding neural correlations cognitive decline. Methods Thirty patients with TLE and hippocampal sclerosis 29 matched healthy controls (HC) were investigated verbal fluency task‐based functional MRI techniques. correlation between activation/deactivation gradients, dynamic features calculated sliding window approaches was compared HC TLE. Results allegiance real data more widespread to static null models. has lower recruitment gradient, atypical activation‐gradient correlation, contracted principal gradient. Correlation analysis proved reconfiguration drive reorganization activation. activation pattern impaired correlated cognition scales Discussion dynamic. disrupted patterns, which

Language: Английский

Citations

0
The efficacy of low frequency repetitive transcial magnetic stimulation for treating auditory verbal hallucinations in schizophrenia: Insights from functional gradient analyses DOI Creative Commons
Yuanjun Xie, Chenxi Li, Muzhen Guan

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(9), P. e30194 - e30194

Published: April 24, 2024

BackgroundAuditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the foundation mechanisms its efficacy necessitate further elucidation.ObjectiveThis study investigate cortical gradient characteristics and their associations with clinical responses schizophrenia patients mediated through 1 Hz rTMS targeting left temporoparietal junction.MethodFunctional metrics were employed to examine hierarchy patterns organization, capturing whole-brain functional connectivity profiles controls.ResultsThe treatment effectively ameliorated positive symptoms patients, specifically AVH. Intimal evaluations revealed expanded global distribution specific principal variations certain brain regions compared control cohort. Following treatment, these divergent local showed signs normalizing. Furthermore, there was observed closer alignment between-network dispersion among various networks after including somatomotor, attention, limbic networks, indicating potential harmonization functionality.ConclusionLow-frequency induces alternations patterns, may serve as imaging markers elucidate underpinning on AVH

Language: Английский

Citations

2