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Inter-modality source coupling: A fully automated whole-brain data-driven structure-function fingerprint shows replicable links to reading in large-scale (N~8K) analysis 46

Inter-modality source coupling: A fully automated whole-brai...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Kotoski, Aline Morris, Robin Calhoun, Vince Georgia State University TReNDS Center and Neuroscience Institute Atlanta United States Georgia State University Department of Psychology Atlanta United States Georgia Tech Emory University TReNDS Center Georgia State Atlanta United States

ISBN: (纸本)9798350371499

We propose a method called inter-modality source coupling (IMSC) to study the coupling between the function and structure of the brain and its relationship to reading ability in school-age children. We performed an analysis focused on the relationship of IMSC to overall reading score. Our findings indicate that key brain regions are linked to differences in function-structure coupling in the context of reading ability and language processing. Higher reading ability was linked with increased function-structure coupling among higher-level cortical regions and lower reading ability was associated with enhanced function-structure coupling among occipital networks and early language processes areas. © 2024 IEEE.

关键词： MRI reading development structure-function coupling

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Genome-wide association study of brain functional and structural networks

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NETWORK NEUROSCIENCE 2024年第1期8卷 319-334页

作者： Cheng, Ruonan Yin, Ruochen Zhao, Xiaoyu Wang, Wei Gong, Gaolang Chen, Chuansheng Xue, Gui Dong, Qi Chen, Chunhui Beijing Normal Univ State Key Lab Cognit Neurosci & Learning Beijing Peoples R China Beijing Normal Univ McGovern Inst Brain Res IDG Beijing Peoples R China Jilin Engn Normal Univ Educ Sci Inst Jilin Peoples R China Univ Calif Irvine Dept Psychol Sci Irvine CA USA

Imaging genetics studies with large samples have identified many genes associated with brain functions and structures, but little is known about genes associated with brain functional and structural network properties. The current genome-wide association study examined graph theory measures of brain structural and functional networks with 497 healthy Chinese participants (17-28 years). Four genes (TGFB3, LGI1, TSPAN18, and FAM155A) were identified to be significantly associated with functional network global efficiency, and two (NLRP6 and ICE2) with structural network global efficiency. Meta-analysis of structural and functional brain network property confirmed the four functional-related genes and revealed two more (RBFOX1 and WWOX). They were reported to be significantly associated with regional brain structural or functional measurements in the UK Biobank project;and showed differential gene expression level between low and high structure-function coupling regions according to Allen Human Brain Atlas gene expression data. Taken together, our results suggest that brain structural and functional networks had shared and unique genetic bases, consistent with the notion of many-to-many structure-function coupling of the brain. Genome-wide association studies on brain were often conducted with regional measurements of the brain (e.g., regional volume, thickness) rather than whole-brain properties. Here we associated whole genome to whole-brain structural and functional network properties (global efficiency, local efficiency, small-worldness), and identified four genes (TGFB3, LGI1, TSPAN18, and FAM155A) associated with functional brain network and two genes (NLRP6 and ICE2) with structural network. Two more genes (RBFOX1 and WWOX) were identified by meta-analysis. These genes were reported to be associated with brain regional measurements in the UK Biobank project, and they showed differential gene expression level between low and high structure-function coupling regio

关键词： GWAS structure-function coupling Brain network Graph theory Connectome

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A Hybrid Routing Pattern in Human Brain Structural Network Revealed By Evolutionary Computation

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2024年第5期43卷 1895-1909页

作者： Liang, Quanmin Ma, Junji Chen, Xitian Lin, Qixiang Shu, Ni Dai, Zhengjia Lin, Ying Sun Yat Sen Univ Dept Psychol Guangzhou 510006 Peoples R China Peng Cheng Lab Res Ctr Artificial Intelligence Shenzhen 518066 Peoples R China Emory Univ Sch Med Dept Neurol Atlanta GA 30322 USA Beijing Normal Univ State Key Lab Cognit Neurosci & Learning Beijing 100875 Peoples R China Beijing Normal Univ IDG McGovern Inst Brain Res Beijing 100875 Peoples R China Sun Yat Sen Univ Zhongshan Sch Med Guangdong Prov Key Lab Brain Funct & Dis Guangzhou 510080 Peoples R China

The human brain functional connectivity network (FCN) is constrained and shaped by the communication processes in the structural connectivity network (SCN). The underlying communication mechanism thus becomes a critical issue for understanding the formation and organization of the FCN. A number of communication models supported by different routing strategies have been proposed, with shortest path (SP), random diffusion (DIF), and spatial navigation (NAV) as the most typical, respectively requiring network global knowledge, local knowledge, and both for path seeking. Yet these models all assumed every brain region to use one routing strategy uniformly, ignoring convergent evidence that supports the regional heterogeneity in both terms of biological substrates and functional roles. In this regard, the current study developed a hybrid communication model that allowed each brain region to choose a routing strategy from SP, DIF, and NAV independently. A genetic algorithm was designed to uncover the underlying region-wise hybrid routing strategy (namely HYB). The HYB was found to outperform the three typical routing strategies in predicting FCN and facilitating robust communication. Analyses on HYB further revealed that brain regions in lower-order functional modules inclined to route signals using global knowledge, while those in higher-order functional modules preferred DIF that requires only local knowledge. Compared to regions that used global knowledge for routing, regions using DIF had denser structural connections, participated in more functional modules, but played a less dominant role within modules. Together, our findings further evidenced that hybrid routing underpins efficient SCN communication and locally heterogeneous structure-function coupling.

关键词： Brain connectome communication routing structure-function coupling evolutionary computation

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Limbic system abnormalities in episodic cluster headache: a 7T MRI multimodal study

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JOURNAL OF HEADACHE AND PAIN 2025年第1期26卷 1-13页

作者： Wang, Xinyu Zhang, Luhua Xiong, Yongqin Hou, Mengmeng Zhang, Shuhua Duan, Caohui Wang, Song Wang, Xiaoyu Lu, Haoxuan Huang, Jiayu Li, Yan Li, Zhixuan Dong, Zhao Lou, Xin Chinese Peoples Liberat Army Gen Hosp Med Ctr 1 Dept Radiol Fuxing Rd 28 Beijing 100853 Peoples R China Chinese Peoples Liberat Army Gen Hosp Med Ctr 1 Dept Neurol Fuxing Rd 28 Beijing 100853 Peoples R China Nankai Univ Sch Med Tianjin 300071 Peoples R China

Background Although the limbic system has long been thought to be involved in the pathophysiology of cluster headache, inconsistencies in imaging studies of episodic cluster headache (eCH) patients and limited understanding of the specific regions within the limbic system have prevented a full explanation of its involvement in the disease. Therefore, we performed multimodal imaging analysis using 7 T MRI with the aim of exploring structural-functional abnormalities in subregions of the limbic system and their relationship with clinical features. Methods In this cross-sectional study, we employed 7T MRI to investigate structural (volumetric) and functional (fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo)) alterations in limbic subregions (hypothalamus, thalamus, amygdala, hippocampus) among 69 in-bout but outside the attacks eCH patients and 63 healthy controls (HCs). Automated volumetry and resting-state functional MRI analyses were performed after adjusting for age, Generalized Anxiety Disorder scale, sex (and intracranial volume when evaluating volumetric measures). Then functional-structural coupling indices were computed to assess network-level relationships. Results In eCH patients, volumes in right anterior inferior and right posterior of hypothalamus, left molecular_layer_hippocampal-head, left lateral-nucleus and left Central-nucleus on the headache side, as well as left tuberal inferior and left tuberal superior of hypothalamus, and right parasubiculum on the contralateral side were significantly altered compared with HCs (P < 0.05). Additionally, the volume of the right anterior inferior was positively correlated with the duration of last headache episode. After false discovery rate correction, widespread alterations in fALFF and ReHo values were observed among hypothalamic, thalamic, hippocampal, and amygdalar subregions, some of which correlated with clinical measures. Furthermore, the structure-function coupling i

关键词： Episodic cluster headache Hypothalamus Thalamus Amygdala Hippocampus 7T MRI structure-function coupling

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Concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease

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NEURORADIOLOGY 2025年第4期67卷 833-844页

作者： Wang, Wenwen Huang, Jing Cheng, Runtian Liu, Xiaoshuang Luo, Tianyou Chongqing Med Univ Affiliated Hosp 1 Chongqing Peoples R China

Purpose To investigate the concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease (CSVD). Methods Thirty normal controls and 65 CSVD patients, including 33 patients with mild cognitive impairment and 32 patients with no cognitive impairment were included. Structural and resting-state functional MRI measures, including gray matter volume (GMV) and white matter volume (WMV) using voxel-based morphometry (VBM) analysis and amplitude of low-frequency fluctuation (ALFF), were obtained and compared among the three groups. Associations between cognitive scores and ALFF/VBM coupling in the co-altered regions were investigated in CSVD groups. Results Multiple brain regions showed significant differences in GMV and WMV among the three groups (P < 0.01). Abnormal ALFF among the three groups was identified in the left putamen, Rolandic operculum, fusiform gyrus, caudate, parahippocampal gyrus, insula, middle cingulum, bilateral lingual gyrus, and right frontal lobe (P < 0.01). Importantly, a decrease in VBM and increase in ALFF in the left parahippocampal gyrus, caudate and Rolandic operculum, a reduction of the WMV and ALFF in the right superior frontal lobe, and a united rise of GMV and ALFF in the left caudate were detected in CSVD groups. In addition, abnormal ALFF/VBM coupling was significantly related to multiple cognitive assessments. Conclusion The study indicated a reversed pattern of the brain structural deficits and functional activation in the left parahippocampal gyrus, caudate, and Rolandic operculum, suggesting structure-function decoupling in CSVD groups. These might help further understand the pathophysiological mechanism of CSVD.

关键词： Cerebral small vessel disease Cognitive impairment structure-function coupling Amplitude of low-frequency fluctuations Voxel-based morphometry Magnetic resonance imaging

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Structural and functional connectivity coupling as an imaging marker for bone metastasis pain in lung cancer patients

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BRAIN RESEARCH BULLETIN 2025年 221卷 111210-111210页

作者： Zheng, Jiahui Wang, Chengfang Zhou, Xiaoyu Tang, Yu Tang, Lin Tan, Yong Zhang, Jing Yu, Hong Zhang, Jiuquan Liu, Daihong Chongqing Univ Canc Hosp Dept Radiol Chongqing 400030 Peoples R China Chongqing Univ Sch Med Chongqing Peoples R China

Background: Cancer pain is a common symptom in patients with malignant tumors and associated with poor prognosis and a high risk of death. Structural connectivity (SC) and functional connectivity (FC) couplings have not yet been explored in lung cancer patients with bone metastasis pain. Methods: In total, 51 patients with lung cancer without bone metastasis pain (BMP-), 52 patients with lung cancer with bone metastasis pain (BMP+), and 28 healthy controls (HC) were prospectively enrolled in our study. Firstly, SC-FC couplings were measured and analyzed at global, regional, and modular levels. Subsequently, individualized SC-FC coupling networks were constructed based on the Euclidean distance metric. In addition, the convolutional neural network (CNN) model was selected to analyze and classify three groups based on individualized networks. Results: The coupling analysis demonstrated that weaker SC-FC couplings related to lung cancer itself were present at various levels, including global, regional, inter-network, and intra-network couplings. Notably, hypercouplings related to bone metastasis pain were present in several brain regions, mainly involving the default mode network, frontoparietal network, salience network, and limbic system. Significant positive correlations were observed between regional coupling in the right amygdala and the numeric rating scale scores in BMP+. Moreover, CNN model built on individualized networks exhibited relatively great classification performance. Conclusion: Alterations in SC-FC coupling patterns may play a crucial role in the development and modulation of bone metastasis pain. Understanding these changes could provide valuable insights into the neural mechanisms underlying cancer pain.

关键词： Bone metastasis pain Resting-state functional magnetic resonance imaging Diffusion spectrum imaging Brain networks structure-function coupling

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Can structure predict function at individual level in the human connectome?

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BRAIN structure & function 2024年第5期229卷 1209-1223页

作者： Smolders, Lars De Baene, Wouter Rutten, Geert-Jan van der Hofstad, Remco Florack, Luc Eindhoven Univ Technol Dept Math & Comp Sci POB 513 NL-5600 MB Eindhoven Netherlands Elisabeth TweeSteden Hosp Dept Neurosurg Hilvarenbeekseweg 60 NL-5022 GC Tilburg Netherlands Tilburg Univ Dept Cognit Neuropsychol Warandelaan 2 NL-5000 LE Tilburg Netherlands

Several studies predicting functional Connectivity (FC) from Structural Connectivity (SC) at individual level have been published in recent years, each promising increased performance and utility. We investigated three of these studies, analyzing whether the results truly represent a meaningful individual-level mapping from SC to FC. Using data from the Human Connectome Project shared accross the three studies, we constructed a predictor by averaging FC of training data and analyzed its performance in the same way. In each case, we found that group average FC is an equivalent or better predictor of individual FC than the predictive models in terms of raw prediction performance. Furthermore, we showed that additional analyses performed by the authors of the three studies, in which they attempt to show that their predicted FC has value beyond raw prediction performance, could also be reproduced using the group average FC predictor. This makes it unclear whether any of the three methods represent a meaningful individual-level predictive model. We conclude that either the methods are not appropriate for the data, that the sample size is too small, or that the data does not contain sufficient information to learn a mapping from SC to FC. We advise future individual-level studies to explicitly report results in comparison to the performance of the group average, and carefully demonstrate that their predictions contain meaningful individual-level information. Finally, we believe that investigating alternatives for the construction of SC and FC may improve the chances of developing a meaningful individual-level mapping from SC to FC.

关键词： Machine learning structure-function coupling Structural connectivity functional connectivity Human connectome - reproducibility

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AGING BRAIN 2024年 5卷 100105页

作者： Khalilian, Maedeh Toba, Monica N. Roussel, Martine Tasseel-Ponche, Sophie Godefroy, Olivier Aarabi, Ardalan Univ Picardy Jules Verne Univ Res Ctr CURS Lab Funct Neurosci & Pathol UR UPJV 4559 Amiens France Univ Picardy Jules Verne Fac Med Amiens France Univ Picardy Jules Verne Amiens Univ Hosp Neurol Phys Med & Rehabil Dept Amiens France Amiens Univ Hosp Neurol Dept Amiens France

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased betweennetwork RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the languageauditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

关键词： Brain structural connectivity Brain functional connectivity Rich-club organization structure-function coupling Vulnerability analysis Aging

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DYNAMIC FUSION OF MULTIMODAL MRI DATA CAPTURES FLEXIBLE, TIME-SENSITIVE structure-function LINKAGES IN THE BRAIN 21

DYNAMIC FUSION OF MULTIMODAL MRI DATA CAPTURES FLEXIBLE, TIM...

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21st IEEE International Symposium on Biomedical Imaging (ISBI)

作者： Duda, Marlena Agcaoglu, Oktay Calhoun, Vince D. Georgia State Univ Ctr Translat Res Neuroimaging & Data Sci TReNDS Georgia Tech Atlanta GA 30303 USA Emory Univ Atlanta GA 30303 USA

ISBN: (纸本)9798350313345;9798350313338

A major branch of neuroimaging involves capturing and understanding the relationship between brain structure and function, which is known to vary across several timescales. To this end, most recent work has approached this question by estimating a single structural basis set of the brain and then attempting to represent functional activation time series as a linear combination of that structural basis, without consideration of how the structural basis might also vary. Here, we introduce dynamic fusion, an ICA-based symmetric fusion, and show evidence that challenges current approaches and suggests time-resolved structural basis sets, derived from dynamic functional connectivity (dFNC) states, can better represent changing functional manifolds and better capture diagnostic differences.

关键词： multimodal data fusion dynamic FNC fMRI sMRI dynamic fusion structure-function coupling

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Subnet Communicability: Diffusive Communication Across the Brain Through a Backbone Subnetwork 14th

Subnet Communicability: Diffusive Communication Across the B...

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14th International Workshop on Computational Diffusion MRI (CDMRI)

作者： Shailja, S. Parlett, Jonathan Jeyapratap, Abhishek Shokoufandeh, Ali Tunc, Birkan Osmanlioglu, Yusuf Drexel Univ Dept Comp Sci Philadelphia PA 19104 USA Childrens Hosp Philadelphia Philadelphia PA USA

ISBN: (纸本)9783031472916;9783031472923

One of the fundamental challenges in modern neuroscience is understanding the interplay between the brain's functional activity and its underlying structural pathways. To address this question, we propose a novel communication pattern called subnet communicability, which models diffusive communication between pairs of regions through a small, intermediary subnetwork of brain regions as opposed to spreading messages through the entire network. We demonstrate that subnet communicability strengthens coupling between the structural and functional connectomes better than previous models, including communicability. Over two large datasets, we show that the optimal subnetwork is consistent across the population. Subnet communicability provides new insights into structure-function coupling in the brain and offers a balance between redundancy in message passing and economy of brain wiring.

关键词： structure-function coupling Connectomics Neuroimaging Communicability Subnet Communicability

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