Network Neuroscience最新文献_第5页

Neural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF. 面向大众的神经肿块建模：使用FastDMF实现全脑生物物理建模的民主化。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00410

Rubén Herzog, Pedro A M Mediano, Fernando E Rosas, Andrea I Luppi, Yonatan Sanz-Perl, Enzo Tagliazucchi, Morten L Kringelbach, Rodrigo Cofré, Gustavo Deco

{"title":"Neural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF.","authors":"Rubén Herzog, Pedro A M Mediano, Fernando E Rosas, Andrea I Luppi, Yonatan Sanz-Perl, Enzo Tagliazucchi, Morten L Kringelbach, Rodrigo Cofré, Gustavo Deco","doi":"10.1162/netn_a_00410","DOIUrl":"10.1162/netn_a_00410","url":null,"abstract":"Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances-including a novel estimation of the feedback inhibition control parameter and a Bayesian optimization algorithm-the FastDMF circumvents various computational bottlenecks of previous implementations, improving interpretability, performance, and memory use. Furthermore, these advances allow the FastDMF to increase the number of simulated regions by one order of magnitude, as confirmed by the good fit to fMRI data parcellated at 90 and 1,000 regions. These advances open the way to the widespread use of biophysically grounded whole-brain models for investigating the interplay between anatomy, function, and brain dynamics and to identify mechanistic explanations of recent results obtained from fine-grained neuroimaging recordings.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1590-1612"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of Parkinson's disease on striatal network connectivity and corticostriatal drive: An in silico study. 帕金森病对纹状体网络连接和皮层驱动的影响：模拟研究

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00394

Ilaria Carannante, Martina Scolamiero, J J Johannes Hjorth, Alexander Kozlov, Bo Bekkouche, Lihao Guo, Arvind Kumar, Wojciech Chachólski, Jeanette Hellgren Kotaleski

{"title":"The impact of Parkinson's disease on striatal network connectivity and corticostriatal drive: An in silico study.","authors":"Ilaria Carannante, Martina Scolamiero, J J Johannes Hjorth, Alexander Kozlov, Bo Bekkouche, Lihao Guo, Arvind Kumar, Wojciech Chachólski, Jeanette Hellgren Kotaleski","doi":"10.1162/netn_a_00394","DOIUrl":"10.1162/netn_a_00394","url":null,"abstract":"Striatum, the input stage of the basal ganglia, is important for sensory-motor integration, initiation and selection of behavior, as well as reward learning. Striatum receives glutamatergic inputs from mainly cortex and thalamus. In rodents, the striatal projection neurons (SPNs), giving rise to the direct and the indirect pathway (dSPNs and iSPNs, respectively), account for 95% of the neurons, and the remaining 5% are GABAergic and cholinergic interneurons. Interneuron axon terminals as well as local dSPN and iSPN axon collaterals form an intricate striatal network. Following chronic dopamine depletion as in Parkinson's disease (PD), both morphological and electrophysiological striatal neuronal features have been shown to be altered in rodent models. Our goal with this in silico study is twofold: (a) to predict and quantify how the intrastriatal network connectivity structure becomes altered as a consequence of the morphological changes reported at the single-neuron level and (b) to investigate how the effective glutamatergic drive to the SPNs would need to be altered to account for the activity level seen in SPNs during PD. In summary, we predict that the richness of the connectivity motifs in the striatal network is significantly decreased during PD while, at the same time, a substantial enhancement of the effective glutamatergic drive to striatum is present.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1149-1172"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulated brain networks reflecting progression of Parkinson's disease. 反映帕金森病进展的模拟大脑网络。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00406

Kyesam Jung, Simon B Eickhoff, Julian Caspers, Oleksandr V Popovych

{"title":"Simulated brain networks reflecting progression of Parkinson's disease.","authors":"Kyesam Jung, Simon B Eickhoff, Julian Caspers, Oleksandr V Popovych","doi":"10.1162/netn_a_00406","DOIUrl":"10.1162/netn_a_00406","url":null,"abstract":"The neurodegenerative progression of Parkinson's disease affects brain structure and function and, concomitantly, alters the topological properties of brain networks. The network alteration accompanied by motor impairment and the duration of the disease has not yet been clearly demonstrated in the disease progression. In this study, we aim to resolve this problem with a modeling approach using the reduced Jansen-Rit model applied to large-scale brain networks derived from cross-sectional MRI data. Optimizing whole-brain simulation models allows us to discover brain networks showing unexplored relationships with clinical variables. We observe that the simulated brain networks exhibit significant differences between healthy controls (n = 51) and patients with Parkinson's disease (n = 60) and strongly correlate with disease severity and disease duration of the patients. Moreover, the modeling results outperform the empirical brain networks in these clinical measures. Consequently, this study demonstrates that utilizing the simulated brain networks provides an enhanced view of network alterations in the progression of motor impairment and identifies potential biomarkers for clinical indices.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1400-1420"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting an individual's functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects. 从结构连接体预测个体的功能连通性：证据、建议和未来前景的评估。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00400

Andrew Zalesky, Tabinda Sarwar, Ye Tian, Yuanzhe Liu, B T Thomas Yeo, Kotagiri Ramamohanarao

{"title":"Predicting an individual's functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects.","authors":"Andrew Zalesky, Tabinda Sarwar, Ye Tian, Yuanzhe Liu, B T Thomas Yeo, Kotagiri Ramamohanarao","doi":"10.1162/netn_a_00400","DOIUrl":"10.1162/netn_a_00400","url":null,"abstract":"Several recent studies have optimized deep neural networks to learn high-dimensional relationships linking structural and functional connectivity across the human connectome. However, the extent to which these models recapitulate individual-specific characteristics of resting-state functional brain networks remains unclear. A core concern relates to whether current individual predictions outperform simple benchmarks such as group averages and null conditions. Here, we consider two measures to statistically evaluate whether functional connectivity predictions capture individual effects. We revisit our previously published functional connectivity predictions for 1,000 healthy adults and provide multiple lines of evidence supporting that our predictions successfully capture subtle individual-specific variation in connectivity. While predicted individual effects are statistically significant and outperform several benchmarks, we find that effect sizes are small (i.e., 8%-11% improvement relative to group-average benchmarks). As such, initial expectations about individual prediction performance expressed by us and others may require moderation. We conclude that individual predictions can significantly outperform appropriate benchmark conditions and we provide several recommendations for future studies in this area. Future studies should statistically assess the individual prediction performance of their models using one of the measures and benchmarks provided here.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1291-1309"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674402/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transcranial ultrasound stimulation effect in the redundant and synergistic networks consistent across macaques. 经颅超声刺激对猕猴冗余和协同网络的影响。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00388

Marilyn Gatica, Cyril Atkinson-Clement, Pedro A M Mediano, Mohammad Alkhawashki, James Ross, Jérôme Sallet, Marcus Kaiser

{"title":"Transcranial ultrasound stimulation effect in the redundant and synergistic networks consistent across macaques.","authors":"Marilyn Gatica, Cyril Atkinson-Clement, Pedro A M Mediano, Mohammad Alkhawashki, James Ross, Jérôme Sallet, Marcus Kaiser","doi":"10.1162/netn_a_00388","DOIUrl":"10.1162/netn_a_00388","url":null,"abstract":"Low-intensity transcranial ultrasound stimulation (TUS) is a noninvasive technique that safely alters neural activity, reaching deep brain areas with good spatial accuracy. We investigated the effects of TUS in macaques using a recent metric, the synergy minus redundancy rank gradient, which quantifies different kinds of neural information processing. We analyzed this high-order quantity on the fMRI data after TUS in two targets: the supplementary motor area (SMA-TUS) and the frontal polar cortex (FPC-TUS). The TUS produced specific changes at the limbic network at FPC-TUS and the motor network at SMA-TUS and altered the sensorimotor, temporal, and frontal networks in both targets, mostly consistent across macaques. Moreover, there was a reduction in the structural and functional coupling after both stimulations. Finally, the TUS changed the intrinsic high-order network topology, decreasing the modular organization of the redundancy at SMA-TUS and increasing the synergistic integration at FPC-TUS.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1032-1050"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cognitive abilities are associated with rapid dynamics of electrophysiological connectome states. 认知能力与电生理连接体状态的快速动态有关。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00390

Suhnyoung Jun, Stephen M Malone, Thomas H Alderson, Jeremy Harper, Ruskin H Hunt, Kathleen M Thomas, Sylia Wilson, William G Iacono, Sepideh Sadaghiani

{"title":"Cognitive abilities are associated with rapid dynamics of electrophysiological connectome states.","authors":"Suhnyoung Jun, Stephen M Malone, Thomas H Alderson, Jeremy Harper, Ruskin H Hunt, Kathleen M Thomas, Sylia Wilson, William G Iacono, Sepideh Sadaghiani","doi":"10.1162/netn_a_00390","DOIUrl":"10.1162/netn_a_00390","url":null,"abstract":"Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, hold significant implications for cognition. However, connectome dynamics at fast (>1 Hz) timescales highly relevant to cognition are poorly understood due to the dominance of inherently slow fMRI in connectome studies. Here, we investigated the behavioral significance of rapid electrophysiological connectome dynamics using source-localized EEG connectomes during resting state (N = 926, 473 females). We focused on dynamic connectome features pertinent to individual differences, specifically those with established heritability: Fractional Occupancy (i.e., the overall duration spent in each recurrent connectome state) in beta and gamma bands and Transition Probability (i.e., the frequency of state switches) in theta, alpha, beta, and gamma bands. Canonical correlation analysis found a significant relationship between the heritable phenotypes of subsecond connectome dynamics and cognition. Specifically, principal components of Transition Probabilities in alpha (followed by theta and gamma bands) and a cognitive factor representing visuospatial processing (followed by verbal and auditory working memory) most notably contributed to the relationship. We conclude that rapid connectome state transitions shape individuals' cognitive abilities and traits. Such subsecond connectome dynamics may inform about behavioral function and dysfunction and serve as endophenotypes for cognitive abilities.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1089-1104"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CoCoNest: A continuous structural connectivity-based nested family of parcellations of the human cerebral cortex. 椰壳：人类大脑皮层基于连续结构连通性的嵌套家族。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00409

Adrian Allen, Zhengwu Zhang, Andrew Nobel

{"title":"CoCoNest: A continuous structural connectivity-based nested family of parcellations of the human cerebral cortex.","authors":"Adrian Allen, Zhengwu Zhang, Andrew Nobel","doi":"10.1162/netn_a_00409","DOIUrl":"10.1162/netn_a_00409","url":null,"abstract":"Despite the widespread exploration and availability of parcellations for the functional connectome, parcellations designed for the structural connectome are comparatively limited. Current research suggests that there may be no single \"correct\" parcellation and that the human brain is intrinsically a multiresolution entity. In this work, we propose the Continuous Structural Connectivitity-based, Nested (CoCoNest) family of parcellations-a fully data-driven, multiresolution family of parcellations derived from structural connectome data. The CoCoNest family is created using agglomerative (bottom-up) clustering and error-complexity pruning, which strikes a balance between the complexity of each parcellation and how well it preserves patterns in vertex-level, high-resolution connectivity data. We draw on a comprehensive battery of internal and external evaluation metrics to show that the CoCoNest family is competitive with or outperforms widely used parcellations in the literature. Additionally, we show how the CoCoNest family can serve as an exploratory tool for researchers to investigate the multiresolution organization of the structural connectome.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1439-1466"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contrasting topologies of synchronous and asynchronous functional brain networks. 同步和异步脑功能网络拓扑结构的对比。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00413

Clayton C McIntyre, Mohsen Bahrami, Heather M Shappell, Robert G Lyday, Jeremie Fish, Erik M Bollt, Paul J Laurienti

{"title":"Contrasting topologies of synchronous and asynchronous functional brain networks.","authors":"Clayton C McIntyre, Mohsen Bahrami, Heather M Shappell, Robert G Lyday, Jeremie Fish, Erik M Bollt, Paul J Laurienti","doi":"10.1162/netn_a_00413","DOIUrl":"10.1162/netn_a_00413","url":null,"abstract":"We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy and compared aFN topology with the correlation-based synchronous functional networks (sFNs), which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and Neurodevelopment in Adolescence study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks. After adjusting for differences in network density, aFNs had higher global efficiency but lower local efficiency than the sFNs. In the aFNs, nodes with the highest outgoing global efficiency tended to be in the brainstem and orbitofrontal cortex. aFN nodes with the highest incoming global efficiency tended to be members of the default mode network in sFNs. Age interacted with node global efficiency in aFNs and node local efficiency in sFNs to influence connection probability. We conclude that the sFN and aFN both offer information about functional brain connectivity that the other type of network does not.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1491-1506"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675104/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gamma frequency connectivity in frontostriatal networks associated with social preference is reduced with traumatic brain injury. 脑外伤导致与社交偏好相关的前额纹状体网络伽马频率连通性降低。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00416

Morteza Salimi, Tianzhi Tang, Milad Nazari, Jyoti Mishra, Houtan Totonchi Afshar, Miranda Francoeur Koloski, Dhakshin S Ramanathan

{"title":"Gamma frequency connectivity in frontostriatal networks associated with social preference is reduced with traumatic brain injury.","authors":"Morteza Salimi, Tianzhi Tang, Milad Nazari, Jyoti Mishra, Houtan Totonchi Afshar, Miranda Francoeur Koloski, Dhakshin S Ramanathan","doi":"10.1162/netn_a_00416","DOIUrl":"10.1162/netn_a_00416","url":null,"abstract":"Among the myriad of complications associated with traumatic brain injury (TBI), impairments in social behaviors and cognition have emerged as a significant area of concern. Animal models of social behavior are necessary to explore the underlying brain mechanisms contributing to chronic social impairments following brain injury. Here, we utilize large-scale brain recordings of local field potentials to identify neural signatures linked with social preference deficits following frontal brain injury. We used a controlled cortical impact model of TBI to create a severe bilateral injury centered on the prefrontal cortex. Behavior (social preference and locomotion) and brain activity (power and coherence) during a three-chamber social preference task were compared between sham and injured animals. Sham rats preferred to spend time with a social conspecific over an inanimate object. An analysis of local field oscillations showed that social preference was associated with a significant increase in coherence in gamma frequency band across widespread brain regions in these animals. Animals with a frontal TBI showed a significant reduction in this social preference, visiting an inanimate object more frequently and for more time. Reflecting these changes in social behavior, these animals also showed a significant reduction in gamma frequency (25-60 Hz) coherence associated with social preference.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1634-1653"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00396

Yunge Zhang, Lin Lin, Dongyue Zhou, Yang Song, Abigail Stein, Shuqin Zhou, Huashuai Xu, Wei Zhao, Fengyu Cong, Jin Sun, Huanjie Li, Fei Du

{"title":"Age-related unstable transient states and imbalanced activation proportion of brain networks in people with autism spectrum disorder: A resting-state fMRI study using coactivation pattern analyses.","authors":"Yunge Zhang, Lin Lin, Dongyue Zhou, Yang Song, Abigail Stein, Shuqin Zhou, Huashuai Xu, Wei Zhao, Fengyu Cong, Jin Sun, Huanjie Li, Fei Du","doi":"10.1162/netn_a_00396","DOIUrl":"10.1162/netn_a_00396","url":null,"abstract":"The atypical static brain functions related to the executive control network (ECN), default mode network (DMN), and salience network (SN) in people with autism spectrum disorder (ASD) has been widely reported. However, their transient functions in ASD are not clear. We aim to identify transient network states (TNSs) using coactivation pattern (CAP) analysis to characterize the age-related atypical transient functions in ASD. CAP analysis was performed on a resting-state fMRI dataset (78 ASD and 78 healthy control (CON) juveniles, 54 ASD and 54 CON adults). Six TNSs were divided into the DMN-TNSs, ECN-TNSs, and SN-TNSs. The DMN-TNSs were major states with the highest stability and proportion, and the ECN-TNSs and SN-TNSs were minor states. Age-related abnormalities on spatial stability and TNS proportion were found in ASD. The spatial stability of DMN-TNSs was found increasing with age in CON, but was not found in ASD. A lower proportion of DMN-TNSs was found in ASD compared with CON of the same age, and ASD juveniles had a higher proportion of SN-TNSs while ASD adults had a higher proportion of ECN-TNSs. The abnormalities on spatial stability and TNS proportion were related to social deficits. Our results provided new evidence for atypical transient brain functions in people with ASD.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1173-1191"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0