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Roth RW, Schwen Blackett D, Gleichgerrcht E, Wilmskoetter J, Rorden C, Newman-Norlund R, Sen S, Fridriksson J, Busby N, Bonilha L. Long-range white matter fibres and post-stroke verbal and non-verbal cognition. Brain Commun 2024; 6:fcae262. [PMID: 39185028 PMCID: PMC11342249 DOI: 10.1093/braincomms/fcae262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 06/04/2024] [Accepted: 08/14/2024] [Indexed: 08/27/2024] Open
Abstract
Among stroke survivors, linguistic and non-linguistic impairments exhibit substantial inter-individual variability. Stroke lesion volume and location do not sufficiently explain outcomes, and the neural mechanisms underlying the severity of aphasia or non-verbal cognitive deficits remain inadequately understood. Converging evidence supports the idea that white matter is particularly susceptible to ischaemic injury, and long-range fibres are commonly associated with verbal and non-verbal function. Here, we investigated the relationship among post-stroke aphasia severity, cognition, and white matter integrity. Eighty-seven individuals in the chronic stage of stroke underwent diffusion MRI and behavioural testing, including language and cognitive measures. We used whole-brain structural connectomes from each participant to calculate the ratio of long-range fibres to short-range fibres. We found that a higher proportion of long-range fibres was associated with lower aphasia severity, more accurate picture naming, and increased performance on non-verbal semantic memory/processing and non-verbal reasoning while controlling for lesion volume, key damage areas, age, and years post stroke. Our findings corroborate the hypothesis that, after accounting for age and lesion anatomy, inter-individual differences in post-stroke aphasia severity, verbal, and non-verbal cognitive outcomes are related to the preservation of long-range white matter fibres beyond the lesion.
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Affiliation(s)
- Rebecca W Roth
- Department of Neurology, Emory University, Atlanta, GA 30329, USA
| | - Deena Schwen Blackett
- Department of Otolaryngology, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
| | | | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | | | - Souvik Sen
- Department of Neurology, University of South Carolina, Columbia, SC 29209, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Leonardo Bonilha
- Department of Neurology, University of South Carolina, Columbia, SC 29209, USA
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2
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Li D, Mao M, Zhang X, Hou D, Zhang S, Hao J, Cui X, Niu Y, Xiang J, Wang B. Gender effects on the controllability of hemispheric white matter networks. Cereb Cortex 2023; 33:1643-1658. [PMID: 35483707 DOI: 10.1093/cercor/bhac162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 04/03/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Male and female adults exhibited significant group differences in brain white matter (WM) asymmetry and WM network controllability. However, gender differences in controllability of hemispheric WM networks between males and females remain to be determined. Based on 1 principal atlas and 1 replication atlas, this work characterized the average controllability (AC) and modal controllability (MC) of hemispheric WM network based on 1 principal dataset and 2 replication datasets. All results showed that males had higher AC of left hemispheric networks than females. And significant hemispheric asymmetry was revealed in regional AC and MC. Furthermore, significant gender differences in the AC asymmetry were mainly found in regions lie in the frontoparietal network, and the MC asymmetry was found in regions involving auditory and emotion process. Finally, we found significant associations between regional controllability and cognitive features. Taken together, this work could provide a novel perspective for understanding gender differences in hemispheric WM asymmetry and cognitive function between males and females.
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Affiliation(s)
- Dandan Li
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Min Mao
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Xi Zhang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Dianni Hou
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Shanshan Zhang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Jiangping Hao
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Xiaohong Cui
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
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Wang S, Planton S, Chanoine V, Sein J, Anton JL, Nazarian B, Dubarry AS, Pallier C, Pattamadilok C. Graph theoretical analysis reveals the functional role of the left ventral occipito-temporal cortex in speech processing. Sci Rep 2022; 12:20028. [PMID: 36414688 PMCID: PMC9681757 DOI: 10.1038/s41598-022-24056-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 11/09/2022] [Indexed: 11/23/2022] Open
Abstract
The left ventral occipito-temporal cortex (left-vOT) plays a key role in reading. Interestingly, the area also responds to speech input, suggesting that it may have other functions beyond written word recognition. Here, we adopt graph theoretical analysis to investigate the left-vOT's functional role in the whole-brain network while participants process spoken sentences in different contexts. Overall, different connectivity measures indicate that the left-vOT acts as an interface enabling the communication between distributed brain regions and sub-networks. During simple speech perception, the left-vOT is systematically part of the visual network and contributes to the communication between neighboring areas, remote areas, and sub-networks, by acting as a local bridge, a global bridge, and a connector, respectively. However, when speech comprehension is explicitly required, the specific functional role of the area and the sub-network to which the left-vOT belongs change and vary with the quality of speech signal and task difficulty. These connectivity patterns provide insightful information on the contribution of the left-vOT in various contexts of language processing beyond its role in reading. They advance our general understanding of the neural mechanisms underlying the flexibility of the language network that adjusts itself according to the processing context.
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Affiliation(s)
- Shuai Wang
- grid.462776.60000 0001 2206 2382Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France ,grid.5399.60000 0001 2176 4817Aix Marseille Univ, Institute of Language, Communication and the Brain, Aix-en-Provence, France
| | - Samuel Planton
- grid.462776.60000 0001 2206 2382Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France ,grid.7429.80000000121866389Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin Center, Gif/Yvette, France
| | - Valérie Chanoine
- grid.462776.60000 0001 2206 2382Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France ,grid.5399.60000 0001 2176 4817Aix Marseille Univ, Institute of Language, Communication and the Brain, Aix-en-Provence, France
| | - Julien Sein
- grid.462486.a0000 0004 4650 2882Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED, Institut de Neurosciences de la Timone, UMR 7289 Marseille, France
| | - Jean-Luc Anton
- grid.462486.a0000 0004 4650 2882Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED, Institut de Neurosciences de la Timone, UMR 7289 Marseille, France
| | - Bruno Nazarian
- grid.462486.a0000 0004 4650 2882Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED, Institut de Neurosciences de la Timone, UMR 7289 Marseille, France
| | - Anne-Sophie Dubarry
- grid.462776.60000 0001 2206 2382Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France ,grid.4444.00000 0001 2112 9282 Aix Marseille Univ, CNRS, LNC, Marseille, France
| | - Christophe Pallier
- grid.7429.80000000121866389Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin Center, Gif/Yvette, France
| | - Chotiga Pattamadilok
- grid.462776.60000 0001 2206 2382Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France
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Ridwan AR, Niaz MR, Wu Y, Qi X, Zhang S, Kontzialis M, Javierre-Petit C, Tazwar M, Bennett DA, Yang Y, Arfanakis K. Development and evaluation of a high performance T1-weighted brain template for use in studies on older adults. Hum Brain Mapp 2021; 42:1758-1776. [PMID: 33449398 PMCID: PMC7978143 DOI: 10.1002/hbm.25327] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 11/16/2020] [Accepted: 12/13/2020] [Indexed: 01/03/2023] Open
Abstract
Τhe accuracy of template-based neuroimaging investigations depends on the template's image quality and representativeness of the individuals under study. Yet a thorough, quantitative investigation of how available standardized and study-specific T1-weighted templates perform in studies on older adults has not been conducted. The purpose of this work was to construct a high-quality standardized T1-weighted template specifically designed for the older adult brain, and systematically compare the new template to several other standardized and study-specific templates in terms of image quality, performance in spatial normalization of older adult data and detection of small inter-group morphometric differences, and representativeness of the older adult brain. The new template was constructed with state-of-the-art spatial normalization of high-quality data from 222 older adults. It was shown that the new template (a) exhibited high image sharpness, (b) provided higher inter-subject spatial normalization accuracy and (c) allowed detection of smaller inter-group morphometric differences compared to other standardized templates, (d) had similar performance to that of study-specific templates constructed with the same methodology, and (e) was highly representative of the older adult brain.
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Affiliation(s)
- Abdur Raquib Ridwan
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Mohammad Rakeen Niaz
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Yingjuan Wu
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Xiaoxiao Qi
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Shengwei Zhang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Marinos Kontzialis
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Carles Javierre-Petit
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Mahir Tazwar
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | | | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Yongyi Yang
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA.,Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, Illinois, USA
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5
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Loughrey DG, Pakhomov SVS, Lawlor BA. Altered verbal fluency processes in older adults with age-related hearing loss. Exp Gerontol 2019; 130:110794. [PMID: 31790801 DOI: 10.1016/j.exger.2019.110794] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 10/27/2019] [Accepted: 11/24/2019] [Indexed: 11/28/2022]
Abstract
Epidemiological studies have linked age-related hearing loss (ARHL) with an increased risk of neurocognitive decline. Difficulties in speech perception with subsequent changes in brain morphometry, including regions important for lexical-semantic memory, are thought to be a possible mechanism for this relationship. This study investigated differences in automatic and executive lexical-semantic processes on verbal fluency tasks in individuals with acquired hearing loss. The primary outcomes were indices of automatic (clustering/word retrieval at start of task) and executive (switching/word retrieval after start of the task) processes from semantic and phonemic fluency tasks. To extract indices of clustering and switching, we used both manual and computerised methods. There were no differences between groups on indices of executive fluency processes or on any indices from the semantic fluency task. The hearing loss group demonstrated weaker automatic processes on the phonemic fluency task. Further research into differences in lexical-semantic processes with ARHL is warranted.
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Affiliation(s)
- David G Loughrey
- Global Brain Health Institute, Trinity College Dublin, Ireland; Global Brain Health Institute, University of California, San Francisco, USA; Trinity College Institute of Neuroscience, Trinity College Dublin.
| | | | - Brian A Lawlor
- Global Brain Health Institute, Trinity College Dublin, Ireland; Global Brain Health Institute, University of California, San Francisco, USA; Mercer's Institute for Successful Ageing, St James Hospital, Dublin, Ireland
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6
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Zhou W, Liu Y, Su M, Yan M, Shu H. Alternating-color words influence Chinese sentence reading: Evidence from neural connectivity. BRAIN AND LANGUAGE 2019; 197:104663. [PMID: 31404828 DOI: 10.1016/j.bandl.2019.104663] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/15/2019] [Accepted: 07/17/2019] [Indexed: 06/10/2023]
Abstract
In order to investigate how language and attention systems are affected by word boundary information during reading, we conducted a functional magnetic resonance imaging (fMRI) experiment in which text-color in naturally unspaced Chinese sentences were systematically manipulated in three experimental conditions, that is, text-color alternation consistent or inconsistent with word boundary (i.e., alternating-color word and non-word conditions), as well as a mono-color baseline condition. Twenty college students (14 females; 23.1 years old) were required to silently read 72 sentences during fMRI scanning. We found that the conditions of word boundary modulated the brain connections between the visual word form area (VWFA) and dorsal attention regions, and between the VWFA and language-related regions. These results suggest that the coordination between the VWFA and dorsal attention regions plays an important role in grouping characters and guiding the saccade according to perceptual grouping based on color, and that the connection between VWFA and MTG could be the neural mechanism of lexical access during Chinese text reading.
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Affiliation(s)
- Wei Zhou
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
| | - Yimei Liu
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
| | - Mengmeng Su
- Elementary Educational College, Capital Normal University, Beijing, China
| | - Ming Yan
- Department of Psychology, University of Macau, Taipa, Macau.
| | - Hua Shu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
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Wen H, Liu Y, Rekik I, Wang S, Zhang J, Zhang Y, Peng Y, He H. Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children. Hum Brain Mapp 2017; 38:3988-4008. [PMID: 28474385 PMCID: PMC6866946 DOI: 10.1002/hbm.23643] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 04/17/2017] [Accepted: 04/24/2017] [Indexed: 01/18/2023] Open
Abstract
Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Hongwei Wen
- Research Center for Brain‐inspired Intelligence, Institute of Automation, Chinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yue Liu
- Department of RadiologyBeijing Children's Hospital, Capital Medical UniversityBeijingChina
| | - Islem Rekik
- CVIP, Computing, School of Science and EngineeringUniversity of DundeeUK
| | - Shengpei Wang
- Research Center for Brain‐inspired Intelligence, Institute of Automation, Chinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Jishui Zhang
- Department of NeurologyBeijing Children's Hospital, Capital Medical UniversityBeijingChina
| | - Yue Zhang
- Department of RadiologyBeijing Children's Hospital, Capital Medical UniversityBeijingChina
| | - Yun Peng
- Department of RadiologyBeijing Children's Hospital, Capital Medical UniversityBeijingChina
| | - Huiguang He
- Research Center for Brain‐inspired Intelligence, Institute of Automation, Chinese Academy of SciencesBeijingChina
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
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Abstract
Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.
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