Network Neuroscience最新文献_第2页

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

Exploring memory-related network via dorsal hippocampus suppression. 通过海马背侧抑制探索记忆相关网络。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00401

Xu Han, Samuel R Cramer, Dennis C Y Chan, Nanyin Zhang

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

Generative dynamical models for classification of rsfMRI data. rsfMRI数据分类的生成动力学模型。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00412

Grace Huckins, Russell A Poldrack

{"title":"Generative dynamical models for classification of rsfMRI data.","authors":"Grace Huckins, Russell A Poldrack","doi":"10.1162/netn_a_00412","DOIUrl":"10.1162/netn_a_00412","url":null,"abstract":"The growing availability of large-scale neuroimaging datasets and user-friendly machine learning tools has led to a recent surge in studies that use fMRI data to predict psychological or behavioral variables. Many such studies classify fMRI data on the basis of static features, but fewer try to leverage brain dynamics for classification. Here, we pilot a generative, dynamical approach for classifying resting-state fMRI (rsfMRI) data. By fitting separate hidden Markov models to the classes in our training data and assigning class labels to test data based on their likelihood under those models, we are able to take advantage of dynamical patterns in the data without confronting the statistical limitations of some other dynamical approaches. Moreover, we demonstrate that hidden Markov models are able to successfully perform within-subject classification on the MyConnectome dataset solely on the basis of transition probabilities among their hidden states. On the other hand, individual Human Connectome Project subjects cannot be identified on the basis of hidden state transition probabilities alone-although a vector autoregressive model does achieve high performance. These results demonstrate a dynamical classification approach for rsfMRI data that shows promising performance, particularly for within-subject classification, and has the potential to afford greater interpretability than other approaches.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1613-1633"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903859","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

FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease. FAST功能连接暗示P300连接在阿尔茨海默病的工作记忆缺陷中。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00411

Om Roy, Yashar Moshfeghi, Agustin Ibanez, Francisco Lopera, Mario A Parra, Keith M Smith

{"title":"FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease.","authors":"Om Roy, Yashar Moshfeghi, Agustin Ibanez, Francisco Lopera, Mario A Parra, Keith M Smith","doi":"10.1162/netn_a_00411","DOIUrl":"10.1162/netn_a_00411","url":null,"abstract":"Measuring transient functional connectivity is an important challenge in electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high-temporal resolution is confounded by the inherent noise of the medium and the spurious nature of correlations computed over short temporal windows. We propose a methodology to overcome these problems called filter average short-term (FAST) functional connectivity. First, a long-term, stable, functional connectivity is averaged across an entire study cohort for a given pair of visual short-term memory (VSTM) tasks. The resulting average connectivity matrix, containing information on the strongest general connections for the tasks, is used as a filter to analyze the transient high-temporal resolution functional connectivity of individual subjects. In simulations, we show that this method accurately discriminates differences in noisy event-related potentials (ERPs) between two conditions where standard connectivity and other comparable methods fail. We then apply this to analyze an activity related to visual short-term memory binding deficits in two cohorts of familial and sporadic Alzheimer's disease (AD)-related mild cognitive impairment (MCI). Reproducible significant differences were found in the binding task with no significant difference in the shape task in the P300 ERP range. This allows new sensitive measurements of transient functional connectivity, which can be implemented to obtain results of clinical significance.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1467-1490"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903854","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

Discovering prominent differences in structural and functional connectomes using a multinomial stochastic block model. 使用多项随机块模型发现结构和功能连接体的显著差异。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00399

Nina Braad Iskov, Anders Stevnhoved Olsen, Kristoffer Hougaard Madsen, Morten Mørup

{"title":"Discovering prominent differences in structural and functional connectomes using a multinomial stochastic block model.","authors":"Nina Braad Iskov, Anders Stevnhoved Olsen, Kristoffer Hougaard Madsen, Morten Mørup","doi":"10.1162/netn_a_00399","DOIUrl":"10.1162/netn_a_00399","url":null,"abstract":"Understanding the differences between functional and structural human brain connectivity has been a focus of an extensive amount of neuroscience research. We employ a novel approach using the multinomial stochastic block model (MSBM) to explicitly extract components that characterize prominent differences across graphs. We analyze structural and functional connectomes derived from high-resolution diffusion-weighted MRI and fMRI scans of 250 Human Connectome Project subjects, analyzed at group connectivity level across 50 subjects. The inferred brain partitions revealed consistent, spatially homogeneous clustering patterns across inferred resolutions demonstrating the MSBM's reliability in identifying brain areas with prominent structure-function differences. Prominent differences in low-resolution brain maps (K = {3, 4} clusters) were attributed to weak functional connectivity in the bilateral anterior temporal lobes, while higher resolution results (K ≥ 25) revealed stronger interhemispheric functional than structural connectivity. Our findings emphasize significant differences in high-resolution functional and structural connectomes, revealing challenges in extracting meaningful connectivity measurements from both modalities, including tracking fibers through the corpus callosum and attenuated functional connectivity in anterior temporal lobe fMRI data, which we attribute to increased noise levels. The MSBM emerges as a valuable tool for understanding differences across graphs, with potential future applications and avenues beyond the current focus on characterizing modality-specific distinctions in connectomics data.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1243-1264"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903658","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

Hemodynamic cortical ripples through cyclicity analysis. 通过周期性分析研究皮层血液动力学涟漪。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00392

Ivan Abraham, Somayeh Shahsavarani, Benjamin Zimmerman, Fatima T Husain, Yuliy Baryshnikov

{"title":"Hemodynamic cortical ripples through cyclicity analysis.","authors":"Ivan Abraham, Somayeh Shahsavarani, Benjamin Zimmerman, Fatima T Husain, Yuliy Baryshnikov","doi":"10.1162/netn_a_00392","DOIUrl":"10.1162/netn_a_00392","url":null,"abstract":"A fine-grained understanding of dynamics in cortical networks is crucial to unpacking brain function. Resting-state functional magnetic resonance imaging (fMRI) gives rise to time series recordings of the activity of different brain regions, which are aperiodic and lack a base frequency. Cyclicity analysis, a novel technique robust under time reparametrizations, is effective in recovering the temporal ordering of such time series, collectively considered components of a multidimensional trajectory. Here, we extend this analytical method for characterizing the dynamic interaction between distant brain regions and apply it to the data from the Human Connectome Project. Our analysis detected cortical traveling waves of activity propagating along a spatial axis, resembling cortical hierarchical organization with consistent lead-lag relationships between specific brain regions in resting-state scans. In fMRI scans involving tasks, we observed short bursts of task-modulated strong temporal ordering that dominate overall lead-lag relationships between pairs of regions in the brain that align temporally with stimuli from the tasks. Our results suggest a possible role played by waves of excitation sweeping through brain regions that underlie emergent cognitive functions.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1105-1128"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903861","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

Segregation-to-integration transformation model of memory evolution. 记忆演化的分离-集成转换模型。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00415

Luz Bavassi, Lluís Fuentemilla

{"title":"Segregation-to-integration transformation model of memory evolution.","authors":"Luz Bavassi, Lluís Fuentemilla","doi":"10.1162/netn_a_00415","DOIUrl":"10.1162/netn_a_00415","url":null,"abstract":"Memories are thought to use coding schemes that dynamically adjust their representational structure to maximize both persistence and efficiency. However, the nature of these coding scheme adjustments and their impact on the temporal evolution of memory after initial encoding is unclear. Here, we introduce the Segregation-to-Integration Transformation (SIT) model, a network formalization that offers a unified account of how the representational structure of a memory is transformed over time. The SIT model asserts that memories initially adopt a highly modular or segregated network structure, functioning as an optimal storage buffer by balancing protection from disruptions and accommodating substantial information. Over time, a repeated combination of neural network reactivations involving activation spreading and synaptic plasticity transforms the initial modular structure into an integrated memory form, facilitating intercommunity spreading and fostering generalization. The SIT model identifies a nonlinear or inverted U-shaped function in memory evolution where memories are most susceptible to changing their representation. This time window, located early during the transformation, is a consequence of the memory's structural configuration, where the activation diffusion across the network is maximized.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1529-1544"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903815","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

Patterns of the left thalamus embedding into the connectome associated with reading skills in children with reading disabilities. 左丘脑嵌入连接体的模式与阅读障碍儿童的阅读技能有关。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00414

Chenglin Lou, Alexandra M Cross, Lien Peters, Daniel Ansari, Marc F Joanisse

{"title":"Patterns of the left thalamus embedding into the connectome associated with reading skills in children with reading disabilities.","authors":"Chenglin Lou, Alexandra M Cross, Lien Peters, Daniel Ansari, Marc F Joanisse","doi":"10.1162/netn_a_00414","DOIUrl":"10.1162/netn_a_00414","url":null,"abstract":"We examined how thalamocortical connectivity structure reflects children's reading performance. Diffusion-weighted MRI at 3 T and a series of reading measures were collected from 64 children (33 girls) ages 8-14 years with and without dyslexia. The topological properties of the left and right thalamus were computed based on the whole-brain white matter network and a hub-attached reading network, and were correlated with scores on several tests of children's reading and reading-related abilities. Significant correlations between topological metrics of the left thalamus and reading scores were observed only in the hub-attached reading network. Local efficiency was negatively correlated with rapid automatized naming. Transmission cost was positively correlated with phonemic decoding, and this correlation was independent of network efficiency scores; follow-up analyses further demonstrated that this effect was specific to the pulvinar and mediodorsal nuclei of the left thalamus. We validated these results using an independent dataset and demonstrated that that the relationship between thalamic connectivity and phonemic decoding was specifically robust. Overall, the results highlight the role of the left thalamus and thalamocortical network in understanding the neurocognitive bases of skilled reading and dyslexia in children.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1507-1528"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903866","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 serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in in vitro cortical neural circuits. 5-羟色胺能迷幻剂 N,N-二丙基色胺改变了体外皮层神经回路的信息处理动态。

IF 3.6 3区医学

Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI: 10.1162/netn_a_00408

Thomas F Varley, Daniel Havert, Leandro Fosque, Abolfazl Alipour, Naruepon Weerawongphrom, Hiroki Naganobori, Lily O'Shea, Maria Pope, John Beggs

{"title":"The serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in in vitro cortical neural circuits.","authors":"Thomas F Varley, Daniel Havert, Leandro Fosque, Abolfazl Alipour, Naruepon Weerawongphrom, Hiroki Naganobori, Lily O'Shea, Maria Pope, John Beggs","doi":"10.1162/netn_a_00408","DOIUrl":"10.1162/netn_a_00408","url":null,"abstract":"Most of the recent work in psychedelic neuroscience has been done using noninvasive neuroimaging, with data recorded from the brains of adult volunteers under the influence of a variety of drugs. While these data provide holistic insights into the effects of psychedelics on whole-brain dynamics, the effects of psychedelics on the mesoscale dynamics of neuronal circuits remain much less explored. Here, we report the effects of the serotonergic psychedelic N,N-diproptyltryptamine (DPT) on information-processing dynamics in a sample of in vitro organotypic cultures of cortical tissue from postnatal rats. Three hours of spontaneous activity were recorded: an hour of predrug control, an hour of exposure to 10-μM DPT solution, and a final hour of washout, once again under control conditions. We found that DPT reversibly alters information dynamics in multiple ways: First, the DPT condition was associated with a higher entropy of spontaneous firing activity and reduced the amount of time information was stored in individual neurons. Second, DPT also reduced the reversibility of neural activity, increasing the entropy produced and suggesting a drive away from equilibrium. Third, DPT altered the structure of neuronal circuits, decreasing the overall information flow coming into each neuron, but increasing the number of weak connections, creating a dynamic that combines elements of integration and disintegration. Finally, DPT decreased the higher order statistical synergy present in sets of three neurons. Collectively, these results paint a complex picture of how psychedelics regulate information processing in mesoscale neuronal networks in cortical tissue. Implications for existing hypotheses of psychedelic action, such as the entropic brain hypothesis, are discussed.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1421-1438"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903901","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