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Krieger-Redwood K, Wang X, Souter N, Gonzalez Alam TRDJ, Smallwood J, Jackson RL, Jefferies E. Graded and sharp transitions in semantic function in left temporal lobe. BRAIN AND LANGUAGE 2024; 251:105402. [PMID: 38484446 DOI: 10.1016/j.bandl.2024.105402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 02/23/2024] [Accepted: 03/05/2024] [Indexed: 04/02/2024]
Abstract
Recent work has focussed on how patterns of functional change within the temporal lobe relate to whole-brain dimensions of intrinsic connectivity variation (Margulies et al., 2016). We examined two such 'connectivity gradients' reflecting the separation of (i) unimodal versus heteromodal and (ii) visual versus auditory-motor cortex, examining visually presented verbal associative and feature judgments, plus picture-based context and emotion generation. Functional responses along the first dimension sometimes showed graded change between modality-tuned and heteromodal cortex (in the verbal matching task), and other times showed sharp functional transitions, with deactivation at the extremes and activation in the middle of this gradient (internal generation). The second gradient revealed more visual than auditory-motor activation, regardless of content (associative, feature, context, emotion) or task process (matching/generation). We also uncovered subtle differences across each gradient for content type, which predominantly manifested as differences in relative magnitude of activation or deactivation.
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Affiliation(s)
- Katya Krieger-Redwood
- Department of Psychology, York Neuroimaging Centre, York Biomedical Research Institute, University of York, United Kingdom
| | - Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nicholas Souter
- Department of Psychology, York Neuroimaging Centre, York Biomedical Research Institute, University of York, United Kingdom; School of Psychology, University of Sussex, Brighton, United Kingdom
| | | | | | - Rebecca L Jackson
- Department of Psychology, York Neuroimaging Centre, York Biomedical Research Institute, University of York, United Kingdom
| | - Elizabeth Jefferies
- Department of Psychology, York Neuroimaging Centre, York Biomedical Research Institute, University of York, United Kingdom.
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2
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Lan F, Roquet D, Dalton MA, El-Omar H, Ahmed RM, Piguet O, Irish M. Exploring graded profiles of hippocampal atrophy along the anterior-posterior axis in semantic dementia and Alzheimer's disease. Neurobiol Aging 2024; 135:70-78. [PMID: 38232501 DOI: 10.1016/j.neurobiolaging.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 01/07/2024] [Accepted: 01/09/2024] [Indexed: 01/19/2024]
Abstract
Mounting evidence indicates marked hippocampal degeneration in semantic dementia (SD) however, the spatial distribution of hippocampal atrophy profiles in this syndrome remains unclear. Using a recently developed parcellation approach, we extracted hippocampal volumes from four distinct subregions running from anterior to posterior along the longitudinal axis (anterior, intermediate rostral, intermediate caudal, and posterior). Volumetric differences in hippocampal subregions were compared between 21 SD, 24 matched Alzheimer's disease (AD), and 27 healthy older Control participants. Despite comparable overall hippocampal volume loss, SD and AD groups diverged in terms of the magnitude of atrophy along the anterior-posterior axis of the hippocampus. Global hippocampal atrophy was observed in AD, with no discernible gradation or lateralisation. In contrast, SD patients displayed graded bilateral hippocampal atrophy, most pronounced on the left-hand side, and concentrated in anterior relative to posterior subregions. Finally, we found preliminary evidence that disease-specific vulnerability along the anterior-posterior axis of the hippocampus was associated with canonical clinical features of these syndromes.
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Affiliation(s)
- Fang Lan
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; The University of Sydney, School of Psychology, Sydney, New South Wales, Australia
| | - Daniel Roquet
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; The University of Sydney, School of Psychology, Sydney, New South Wales, Australia
| | - Marshall A Dalton
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; The University of Sydney, School of Psychology, Sydney, New South Wales, Australia
| | - Hashim El-Omar
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia
| | - Rebekah M Ahmed
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; Memory and Cognition Clinic, Department of Clinical Neurosciences, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Olivier Piguet
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; The University of Sydney, School of Psychology, Sydney, New South Wales, Australia
| | - Muireann Irish
- The University of Sydney, Brain and Mind Centre, Sydney, New South Wales, Australia; The University of Sydney, School of Psychology, Sydney, New South Wales, Australia.
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3
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Galdi P, Cabez MB, Farrugia C, Vaher K, Williams LZJ, Sullivan G, Stoye DQ, Quigley AJ, Makropoulos A, Thrippleton MJ, Bastin ME, Richardson H, Whalley H, Edwards AD, Bajada CJ, Robinson EC, Boardman JP. Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth. Hum Brain Mapp 2024; 45:e26660. [PMID: 38488444 PMCID: PMC10941526 DOI: 10.1002/hbm.26660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 01/18/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.
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Affiliation(s)
- Paola Galdi
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- School of InformaticsUniversity of EdinburghEdinburghUK
| | | | - Christine Farrugia
- Faculty of EngineeringUniversity of MaltaVallettaMalta
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
| | - Kadi Vaher
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | - Logan Z. J. Williams
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - Gemma Sullivan
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - David Q. Stoye
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | | | | | | | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Hilary Richardson
- School of Philosophy, Psychology and Language SciencesUniversity of EdinburghEdinburghUK
| | - Heather Whalley
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Centre for Genomic and Experimental MedicineUniversity of EdinburghEdinburghUK
| | - A. David Edwards
- Centre for the Developing BrainKing's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Claude J. Bajada
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
- Department of Physiology and Biochemistry, Faculty of Medicine and SurgeryUniversity of MaltaVallettaMalta
| | - Emma C. Robinson
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - James P. Boardman
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
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4
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Litwińczuk MC, Muhlert N, Trujillo‐Barreto N, Woollams A. Impact of brain parcellation on prediction performance in models of cognition and demographics. Hum Brain Mapp 2024; 45:e26592. [PMID: 38339892 PMCID: PMC10831203 DOI: 10.1002/hbm.26592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 12/18/2023] [Accepted: 12/31/2023] [Indexed: 02/12/2024] Open
Abstract
Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predictive model performance. In this work, structural, functional and combined connectivity were each defined with five different parcellation schemes. The resolution and modality of the parcellation schemes were varied. Each connectivity defined with each parcellation was used to predict individual differences in age, education, sex, executive function, self-regulation, language, encoding and sequence processing. It was found that low-resolution functional parcellation consistently performed above chance at producing generalisable models of both demographics and cognition. However, no single parcellation scheme showed a superior predictive performance across all cognitive domains and demographics. In addition, although parcellation schemes impacted the graph theory measures of each connectivity type (structural, functional and combined), these differences did not account for the out-of-sample predictive performance of the models. Taken together, these findings demonstrate that while high-resolution parcellations may be beneficial for modelling specific individual differences, partial voluming of signals produced by the higher resolution of the parcellation likely disrupts model generalisability.
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Affiliation(s)
| | - Nils Muhlert
- School of Health SciencesUniversity of ManchesterManchesterUK
| | | | - Anna Woollams
- School of Health SciencesUniversity of ManchesterManchesterUK
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5
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. Cereb Cortex 2023; 33:11384-11399. [PMID: 37833772 PMCID: PMC10690868 DOI: 10.1093/cercor/bhad373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/17/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.
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Affiliation(s)
- Veronica Diveica
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
- Department of Neurology and Neurosurgery & Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, York, YO10 5DD, United Kingdom
| | - Richard J Binney
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
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6
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Jiang P, Cui S, Yao S, Cai H, Zhu J, Yu Y. The hierarchical organization of the precuneus captured by functional gradients. Brain Struct Funct 2023; 228:1561-1572. [PMID: 37378854 PMCID: PMC10335959 DOI: 10.1007/s00429-023-02672-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 06/16/2023] [Indexed: 06/29/2023]
Abstract
The precuneus shows considerable heterogeneity in multiple dimensions including anatomy, function, and involvement in brain disorders. Leveraging the state-of-the-art functional gradient approach, we aimed to investigate the hierarchical organization of the precuneus, which may hold promise for a unified understanding of precuneus heterogeneity. Resting-state functional MRI data from 793 healthy individuals were used to discover and validate functional gradients of the precuneus, which were calculated based on the voxel-wise precuneus-to-cerebrum functional connectivity patterns. Then, we further explored the potential relationships of the precuneus functional gradients with cortical morphology, intrinsic geometry, canonical functional networks, and behavioral domains. We found that the precuneus principal and secondary gradients showed dorsoanterior-ventral and ventroposterior-dorsal organizations, respectively. Concurrently, the principal gradient was associated with cortical morphology, and both the principal and secondary gradients showed geometric distance dependence. Importantly, precuneus functional subdivisions corresponding to canonical functional networks (behavioral domains) were distributed along both gradients in a hierarchical manner, i.e., from the sensorimotor network (somatic movement and sensation) at one extreme to the default mode network (abstract cognitive functions) at the other extreme for the principal gradient and from the visual network (vision) at one end to the dorsal attention network (top-down control of attention) at the other end for the secondary gradient. These findings suggest that the precuneus functional gradients may provide mechanistic insights into the multifaceted nature of precuneus heterogeneity.
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Affiliation(s)
- Ping Jiang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Shunshun Cui
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Shanwen Yao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China.
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.
- Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China.
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7
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Shen Y, Cai H, Mo F, Yao S, Yu Y, Zhu J. Functional connectivity gradients of the cingulate cortex. Commun Biol 2023; 6:650. [PMID: 37337086 DOI: 10.1038/s42003-023-05029-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/08/2023] [Indexed: 06/21/2023] Open
Abstract
Heterogeneity of the cingulate cortex is evident in multiple dimensions including anatomy, function, connectivity, and involvement in networks and diseases. Using the recently developed functional connectivity gradient approach and resting-state functional MRI data, we found three functional connectivity gradients that captured distinct dimensions of cingulate hierarchical organization. The principal gradient exhibited a radiating organization with transitions from the middle toward both anterior and posterior parts of the cingulate cortex and was related to canonical functional networks and corresponding behavioral domains. The second gradient showed an anterior-posterior axis across the cingulate cortex and had prominent geometric distance dependence. The third gradient displayed a marked differentiation of subgenual and caudal middle with other parts of the cingulate cortex and was associated with cortical morphology. Aside from providing an updated framework for understanding the multifaceted nature of cingulate heterogeneity, the observed hierarchical organization of the cingulate cortex may constitute a novel research agenda with potential applications in basic and clinical neuroscience.
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Affiliation(s)
- Yuhao Shen
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Fan Mo
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Shanwen Yao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China.
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China.
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China.
- Research Center of Clinical Medical Imaging, Anhui Province, 230032, Hefei, China.
- Anhui Provincial Institute of Translational Medicine, 230032, Hefei, China.
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8
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526818. [PMID: 36778322 PMCID: PMC9915604 DOI: 10.1101/2023.02.02.526818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.
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Affiliation(s)
- Veronica Diveica
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
| | - Michael C. Riedel
- Department of Physics, Florida International University, Miami, FL, USA
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Rebecca L. Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, UK
| | - Richard J. Binney
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
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9
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Humphreys GF, Jung J, Lambon Ralph MA. The convergence and divergence of episodic and semantic functions across lateral parietal cortex. Cereb Cortex 2022; 32:5664-5681. [PMID: 35196706 PMCID: PMC9753060 DOI: 10.1093/cercor/bhac044] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 11/22/2021] [Accepted: 01/22/2022] [Indexed: 01/25/2023] Open
Abstract
Decades of research have highlighted the importance of lateral parietal cortex (LPC) across a myriad of cognitive domains. Yet, the underlying function of LPC remains unclear. Two domains that have emphasized LPC involvement are semantic memory and episodic memory retrieval. From each domain, sophisticated functional models have been proposed, as well as the more domain-general assumption that LPC is engaged by any form of internally directed cognition (episodic/semantic retrieval being examples). Here we used a combination of functional magnetic resonance imaging, functional connectivity, and diffusion tensor imaging white-matter connectivity to show that (i) ventral LPC (angular gyrus [AG]) was positively engaged during episodic retrieval but disengaged during semantic memory retrieval and (ii) activity negatively varied with task difficulty in the semantic task whereas episodic activation was independent of difficulty. In contrast, dorsal LPC (intraparietal sulcus) showed domain general activation that was positively correlated with task difficulty. Finally, (iii) a dorsal-ventral and anterior-posterior gradient of functional and structural connectivity was found across the AG (e.g. mid-AG connected with episodic retrieval). We propose a unifying model in which LPC as a whole might share a common underlying neurocomputation (multimodal buffering) with variations in the emergent cognitive functions across subregions arising from differences in the underlying connectivity.
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Affiliation(s)
- Gina F Humphreys
- MRC Cognition & Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom
| | - JeYoung Jung
- School of Psychology, University of Nottingham, Nottingham NG9 2RD, United Kingdom
| | - Matthew A Lambon Ralph
- MRC Cognition & Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom
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10
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Guell X. Functional Gradients of the Cerebellum: a Review of Practical Applications. CEREBELLUM (LONDON, ENGLAND) 2022; 21:1061-1072. [PMID: 34741753 PMCID: PMC9072599 DOI: 10.1007/s12311-021-01342-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/25/2021] [Indexed: 11/29/2022]
Abstract
Gradient-based analyses have contributed to the description of cerebellar functional neuroanatomy. More recently, functional gradients of the cerebellum have been used as a multi-purpose tool for neuroimaging research. Here, we provide an overview of the many practical applications of cerebellar functional gradient analyses. These practical applications include examination of intra-cerebellar and cerebellar-extracerebellar organization; transformation of functional gradients into parcellations with discrete borders; projection of functional gradients calculated within cerebellar structures to other extracerebellar structures; interpretation of cerebellar neuroimaging findings using qualitative and quantitative methods; detection of differences in patient populations; and other more complex practical applications of cerebellar gradient-based analyses. This review may serve as an introduction and catalog of options for neuroscientists who wish to design and analyze imaging studies using functional gradients of the cerebellum.
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Affiliation(s)
- Xavier Guell
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA, 20114, USA.
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research at MIT, Massachusetts Institute of Technology, Cambridge, MA, USA.
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11
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Hodgson VJ, Lambon Ralph MA, Jackson RL. The cross-domain functional organization of posterior lateral temporal cortex: insights from ALE meta-analyses of 7 cognitive domains spanning 12,000 participants. Cereb Cortex 2022; 33:4990-5006. [PMID: 36269034 PMCID: PMC10110446 DOI: 10.1093/cercor/bhac394] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 09/08/2022] [Accepted: 09/09/2022] [Indexed: 11/12/2022] Open
Abstract
The posterior lateral temporal cortex is implicated in many verbal, nonverbal, and social cognitive domains and processes. Yet without directly comparing these disparate domains, the region's organization remains unclear; do distinct processes engage discrete subregions, or could different domains engage shared neural correlates and processes? Here, using activation likelihood estimation meta-analyses, the bilateral posterior lateral temporal cortex subregions engaged in 7 domains were directly compared. These domains comprised semantics, semantic control, phonology, biological motion, face processing, theory of mind, and representation of tools. Although phonology and biological motion were predominantly associated with distinct regions, other domains implicated overlapping areas, perhaps due to shared underlying processes. Theory of mind recruited regions implicated in semantic representation, tools engaged semantic control areas, and faces engaged subregions for biological motion and theory of mind. This cross-domain approach provides insight into how posterior lateral temporal cortex is organized and why.
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Affiliation(s)
- Victoria J Hodgson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, United Kingdom
| | - Matthew A Lambon Ralph
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, United Kingdom
| | - Rebecca L Jackson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, United Kingdom.,Department of Psychology & York Biomedical Research Institute, University of York, Heslington, York, YO10 5DD, United Kingdom
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12
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Wang R, Mo F, Shen Y, Song Y, Cai H, Zhu J. Functional connectivity gradients of the insula to different cerebral systems. Hum Brain Mapp 2022; 44:790-800. [PMID: 36206289 PMCID: PMC9842882 DOI: 10.1002/hbm.26099] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/16/2022] [Accepted: 09/24/2022] [Indexed: 01/25/2023] Open
Abstract
The diverse functional roles of the insula may emerge from its heavy connectivity to an extensive network of cortical and subcortical areas. Despite several previous attempts to investigate the hierarchical organization of the insula by applying the recently developed gradient approach to insula-to-whole brain connectivity data, little is known about whether and how there is variability across connectivity gradients of the insula to different cerebral systems. Resting-state functional MRI data from 793 healthy subjects were used to discover and validate functional connectivity gradients of the insula, which were computed based on its voxel-wise functional connectivity profiles to distinct cerebral systems. We identified three primary patterns of functional connectivity gradients of the insula to distinct cerebral systems. The connectivity gradients to the higher-order transmodal associative systems, including the prefrontal, posterior parietal, temporal cortices, and limbic lobule, showed a ventroanterior-dorsal axis across the insula; those to the lower-order unimodal primary systems, including the motor, somatosensory, and occipital cortices, displayed radiating transitions from dorsoanterior toward both ventroanterior and dorsoposterior parts of the insula; the connectivity gradient to the subcortical nuclei exhibited an organization along the anterior-posterior axis of the insula. Apart from complementing and extending previous literature on the heterogeneous connectivity patterns of insula subregions, the presented framework may offer ample opportunities to refine our understanding of the role of the insula in many brain disorders.
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Affiliation(s)
- Rui Wang
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Fan Mo
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Yuhao Shen
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Yu Song
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Huanhuan Cai
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Jiajia Zhu
- Department of RadiologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina,Research Center of Clinical Medical Imaging, Anhui ProvinceHefeiChina,Anhui Provincial Institute of Translational MedicineHefeiChina
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13
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Royer J, Rodríguez-Cruces R, Tavakol S, Larivière S, Herholz P, Li Q, Vos de Wael R, Paquola C, Benkarim O, Park BY, Lowe AJ, Margulies D, Smallwood J, Bernasconi A, Bernasconi N, Frauscher B, Bernhardt BC. An Open MRI Dataset For Multiscale Neuroscience. Sci Data 2022; 9:569. [PMID: 36109562 PMCID: PMC9477866 DOI: 10.1038/s41597-022-01682-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 08/24/2022] [Indexed: 12/17/2022] Open
Abstract
AbstractMultimodal neuroimaging grants a powerful window into the structure and function of the human brain at multiple scales. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends (also referred to as gradients) in brain microstructure and connectivity, offering an integrative framework to study multiscale brain organization. Here, we share a multimodal MRI dataset for Microstructure-Informed Connectomics (MICA-MICs) acquired in 50 healthy adults (23 women; 29.54 ± 5.62 years) who underwent high-resolution T1-weighted MRI, myelin-sensitive quantitative T1 relaxometry, diffusion-weighted MRI, and resting-state functional MRI at 3 Tesla. In addition to raw anonymized MRI data, this release includes brain-wide connectomes derived from (i) resting-state functional imaging, (ii) diffusion tractography, (iii) microstructure covariance analysis, and (iv) geodesic cortical distance, gathered across multiple parcellation scales. Alongside, we share large-scale gradients estimated from each modality and parcellation scale. Our dataset will facilitate future research examining the coupling between brain microstructure, connectivity, and function. MICA-MICs is available on the Canadian Open Neuroscience Platform data portal (https://portal.conp.ca) and the Open Science Framework (https://osf.io/j532r/).
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14
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Subregions of DLPFC Display Graded yet Distinct Structural and Functional Connectivity. J Neurosci 2022; 42:3241-3252. [PMID: 35232759 PMCID: PMC8994544 DOI: 10.1523/jneurosci.1216-21.2022] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 11/10/2021] [Accepted: 01/02/2022] [Indexed: 02/02/2023] Open
Abstract
The human dorsolateral prefrontal cortex (DLPFC; approximately corresponding to Brodmann areas 9 and 46) has demonstrable roles in diverse executive functions such as working memory, cognitive flexibility, planning, inhibition, and abstract reasoning. However, it remains unclear whether this is the result of one functionally homogeneous region or whether there are functional subdivisions within the DLPFC. Here, we divided the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically and explored their respective patterns of structural and functional connectivity. In vivo probabilistic tractography (11 females and 13 males) and resting-state functional magnetic resonance imaging (fMRI; 57 females and 21 males) were employed to map out the patterns of connectivity from each DLPFC subregion. Structural connectivity demonstrated graded intraregional connectivity within the DLPFC. The patterns of structural connectivity between the DLPFC subregions and other cortical areas revealed that the dorsal-rostral subregions connections were restricted to other frontal and limbic areas, whereas the ventral-caudal region was widely connected to frontal, parietal, and limbic cortex. Functional connectivity analyses demonstrated that subregions of DLPFC were strongly interconnected to each other. The dorsal subregions were associated with the default mode network (DMN), while middle dorsal-rostral subregions were linked with the multiple demand network (MDN). The ventral-caudal subregion showed increased functional coupling with both DMN and MDN. Our results suggest that the connectivity of the DLPFC may be subdivided along a dorsorostral-ventrocaudal axis with differing (albeit graded) patterns of connectivity reflecting the integrative executive function of the DLPFC.SIGNIFICANCE STATEMENT Research has shown that the dorsolateral prefrontal cortex (DLPFC) plays a role in various executive functions. By dividing the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically, we explored their patterns of structural and functional connectivity. The patterns of connectivity within DLPFC subregions demonstrated graded intraregional connectivity. There were distinctive patterns of connectivity with other cortical areas in dorsal-rostral and ventral-caudal DLPFC subregions. Divisions across DLPFC subregions seem to align with their structural and functional connectivity. Our results suggest that DLPFC may be subdivided by the diagonal axis of the dorsal-ventral axis and rostral-caudal axis, supporting the framework of a functional organization along the anterior-posterior axis in the lateral PFC.
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15
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Eschenburg KM, Grabowski TJ, Haynor DR. Learning Cortical Parcellations Using Graph Neural Networks. Front Neurosci 2021; 15:797500. [PMID: 35002611 PMCID: PMC8739886 DOI: 10.3389/fnins.2021.797500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
Deep learning has been applied to magnetic resonance imaging (MRI) for a variety of purposes, ranging from the acceleration of image acquisition and image denoising to tissue segmentation and disease diagnosis. Convolutional neural networks have been particularly useful for analyzing MRI data due to the regularly sampled spatial and temporal nature of the data. However, advances in the field of brain imaging have led to network- and surface-based analyses that are often better represented in the graph domain. In this analysis, we propose a general purpose cortical segmentation method that, given resting-state connectivity features readily computed during conventional MRI pre-processing and a set of corresponding training labels, can generate cortical parcellations for new MRI data. We applied recent advances in the field of graph neural networks to the problem of cortical surface segmentation, using resting-state connectivity to learn discrete maps of the human neocortex. We found that graph neural networks accurately learn low-dimensional representations of functional brain connectivity that can be naturally extended to map the cortices of new datasets. After optimizing over algorithm type, network architecture, and training features, our approach yielded mean classification accuracies of 79.91% relative to a previously published parcellation. We describe how some hyperparameter choices including training and testing data duration, network architecture, and algorithm choice affect model performance.
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Affiliation(s)
- Kristian M. Eschenburg
- Department of Bioengineering, University of Washington, Seattle, WA, United States
- Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA, United States
| | - Thomas J. Grabowski
- Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA, United States
- Department of Radiology, University of Washington Medical Center, Seattle, WA, United States
- Department of Neurology, University of Washington Medical Center, Seattle, WA, United States
| | - David R. Haynor
- Department of Bioengineering, University of Washington, Seattle, WA, United States
- Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA, United States
- Department of Radiology, University of Washington Medical Center, Seattle, WA, United States
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16
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Blazquez Freches G, Haak KV, Beckmann CF, Mars RB. Connectivity gradients on tractography data: Pipeline and example applications. Hum Brain Mapp 2021; 42:5827-5845. [PMID: 34559432 PMCID: PMC8596970 DOI: 10.1002/hbm.25623] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 07/03/2021] [Accepted: 07/30/2021] [Indexed: 11/08/2022] Open
Abstract
Gray matter connectivity can be described in terms of its topographical organization, but the differential role of white matter connections underlying that organization is often unknown. In this study, we propose a method for unveiling principles of organization of both gray and white matter based on white matter connectivity as assessed using diffusion magnetic ressonance imaging (MRI) tractography with spectral embedding gradient mapping. A key feature of the proposed approach is its capacity to project the individual connectivity gradients it reveals back onto its input data in the form of projection images, allowing one to assess the contributions of specific white matter tracts to the observed gradients. We demonstrate the ability of our proposed pipeline to identify connectivity gradients in prefrontal and occipital gray matter. Finally, leveraging the use of tractography, we demonstrate that it is possible to observe gradients within the white matter bundles themselves. Together, the proposed framework presents a generalized way to assess both the topographical organization of structural brain connectivity and the anatomical features driving it.
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Affiliation(s)
- Guilherme Blazquez Freches
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
| | - Koen V. Haak
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Christian F. Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nufeld Department of Clinical NeurosciencesJohn Radclife Hospital, University of OxfordOxfordUK
| | - Rogier B. Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
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17
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Gonzalez Alam TRDJ, Mckeown BLA, Gao Z, Bernhardt B, Vos de Wael R, Margulies DS, Smallwood J, Jefferies E. A tale of two gradients: differences between the left and right hemispheres predict semantic cognition. Brain Struct Funct 2021; 227:631-654. [PMID: 34510282 PMCID: PMC8844158 DOI: 10.1007/s00429-021-02374-w] [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: 02/23/2021] [Accepted: 08/27/2021] [Indexed: 01/21/2023]
Abstract
Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.
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Affiliation(s)
| | | | - Zhiyao Gao
- Department of Psychology, University of York, York, UK
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) and Université de Paris, INCC UMR 8002, Paris, France
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18
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Braunsdorf M, Blazquez Freches G, Roumazeilles L, Eichert N, Schurz M, Uithol S, Bryant KL, Mars RB. Does the temporal cortex make us human? A review of structural and functional diversity of the primate temporal lobe. Neurosci Biobehav Rev 2021; 131:400-410. [PMID: 34480913 DOI: 10.1016/j.neubiorev.2021.08.032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 08/03/2021] [Accepted: 08/30/2021] [Indexed: 10/20/2022]
Abstract
Temporal cortex is a primate specialization that shows considerable variation in size, morphology, and connectivity across species. Human temporal cortex is involved in many behaviors that are considered especially well developed in humans, including semantic processing, language, and theory of mind. Here, we ask whether the involvement of temporal cortex in these behaviors can be explained in the context of the 'general' primate organization of the temporal lobe or whether the human temporal lobe contains unique specializations indicative of a 'step change' in the lineage leading to modern humans. We propose that many human behaviors can be explained as elaborations of temporal cortex functions observed in other primates. However, changes in temporal lobe white matter suggest increased integration of information within temporal cortex and between posterior temporal cortex and other association areas, which likely enable behaviors not possible in other species.
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Affiliation(s)
- Marius Braunsdorf
- Donders Institute for Brain Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands.
| | - Guilherme Blazquez Freches
- Donders Institute for Brain Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Matthias Schurz
- Donders Institute for Brain Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands; Institute of Psychology, University of Innsbruck, Innsbruck, Austria
| | - Sebo Uithol
- Donders Institute for Brain Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Rogier B Mars
- Donders Institute for Brain Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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19
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Vos de Wael R, Royer J, Tavakol S, Wang Y, Paquola C, Benkarim O, Eichert N, Larivière S, Xu T, Misic B, Smallwood J, Valk SL, Bernhardt BC. Structural Connectivity Gradients of the Temporal Lobe Serve as Multiscale Axes of Brain Organization and Cortical Evolution. Cereb Cortex 2021; 31:5151-5164. [PMID: 34148082 PMCID: PMC8491677 DOI: 10.1093/cercor/bhab149] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The temporal lobe is implicated in higher cognitive processes and is one of the regions that underwent substantial reorganization during primate evolution. Its functions are instantiated, in part, by the complex layout of its structural connections. Here, we identified low-dimensional representations of structural connectivity variations in human temporal cortex and explored their microstructural underpinnings and associations to macroscale function. We identified three eigenmodes which described gradients in structural connectivity. These gradients reflected inter-regional variations in cortical microstructure derived from quantitative magnetic resonance imaging and postmortem histology. Gradient-informed models accurately predicted macroscale measures of temporal lobe function. Furthermore, the identified gradients aligned closely with established measures of functional reconfiguration and areal expansion between macaques and humans, highlighting their potential role in shaping temporal lobe function throughout primate evolution. Findings were replicated in several datasets. Our results provide robust evidence for three axes of structural connectivity in human temporal cortex with consistent microstructural underpinnings and contributions to large-scale brain network function.
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Affiliation(s)
- Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Jessica Royer
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Shahin Tavakol
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Yezhou Wang
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Oualid Benkarim
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Sara Larivière
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, NY 10022, USA
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | | | - Sofie L Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
| | - Boris C Bernhardt
- Address correspondence to Boris C. Bernhardt, McConnell Brain Imaging Centre, Montreal Neurological Institute (NW-256), McGill University, 3801 Rue University, Montréal, QC H3A2B4, Canada.
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20
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Jackson RL, Bajada CJ, Lambon Ralph MA, Cloutman LL. The Graded Change in Connectivity across the Ventromedial Prefrontal Cortex Reveals Distinct Subregions. Cereb Cortex 2021; 30:165-180. [PMID: 31329834 PMCID: PMC7029692 DOI: 10.1093/cercor/bhz079] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/21/2019] [Accepted: 03/19/2019] [Indexed: 11/20/2022] Open
Abstract
The functional heterogeneity of the ventromedial prefrontal cortex (vmPFC) suggests it may include distinct functional subregions. To date these have not been well elucidated. Regions with differentiable connectivity (and as a result likely dissociable functions) may be identified using emergent data-driven approaches. However, prior parcellations of the vmPFC have only considered hard splits between distinct regions, although both hard and graded connectivity changes may exist. Here we determine the full pattern of change in structural and functional connectivity across the vmPFC for the first time and extract core distinct regions. Both structural and functional connectivity varied along a dorsomedial to ventrolateral axis from relatively dorsal medial wall regions to relatively lateral basal orbitofrontal cortex. The pattern of connectivity shifted from default mode network to sensorimotor and multimodal semantic connections. This finding extends the classical distinction between primate medial and orbital regions by demonstrating a similar gradient in humans for the first time. Additionally, core distinct regions in the medial wall and orbitofrontal cortex were identified that may show greater correspondence to functional differences than prior hard parcellations. The possible functional roles of the orbitofrontal cortex and medial wall are discussed.
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Affiliation(s)
- Rebecca L Jackson
- Medical Research Council Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Claude J Bajada
- Faculty of Medicine and Surgery, University of Malta, Msida, MSD, Malta
| | - Matthew A Lambon Ralph
- Medical Research Council Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Lauren L Cloutman
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology (Zochonis Building), University of Manchester, Manchester, UK
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21
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Park BY, Vos de Wael R, Paquola C, Larivière S, Benkarim O, Royer J, Tavakol S, Cruces RR, Li Q, Valk SL, Margulies DS, Mišić B, Bzdok D, Smallwood J, Bernhardt BC. Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function. Neuroimage 2020; 224:117429. [PMID: 33038538 DOI: 10.1016/j.neuroimage.2020.117429] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 09/13/2020] [Accepted: 09/30/2020] [Indexed: 12/14/2022] Open
Abstract
Human cognition is dynamic, alternating over time between externally-focused states and more abstract, often self-generated, patterns of thought. Although cognitive neuroscience has documented how networks anchor particular modes of brain function, mechanisms that describe transitions between distinct functional states remain poorly understood. Here, we examined how time-varying changes in brain function emerge within the constraints imposed by macroscale structural network organization. Studying a large cohort of healthy adults (n = 326), we capitalized on manifold learning techniques that identify low dimensional representations of structural connectome organization and we decomposed neurophysiological activity into distinct functional states and their transition patterns using Hidden Markov Models. Structural connectome organization predicted dynamic transitions anchored in sensorimotor systems and those between sensorimotor and transmodal states. Connectome topology analyses revealed that transitions involving sensorimotor states traversed short and intermediary distances and adhered strongly to communication mechanisms of network diffusion. Conversely, transitions between transmodal states involved spatially distributed hubs and increasingly engaged long-range routing. These findings establish that the structure of the cortex is optimized to allow neural states the freedom to vary between distinct modes of processing, and so provides a key insight into the neural mechanisms that give rise to the flexibility of human cognition.
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Affiliation(s)
- Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Raul R Cruces
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Qiongling Li
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Sofie L Valk
- Institute of Neuroscience and Medicine (INM-7: Brain & Behaviour), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Daniel S Margulies
- Frontlab, Institut du Cerveau et de la Moelle épinière, UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Bratislav Mišić
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Danilo Bzdok
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Mila - Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
| | - Jonathan Smallwood
- Department of Psychology, York Neuroimaging Centre, University of York, New York, United Kingdom
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
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22
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Understanding brain organisation in the face of functional heterogeneity and functional multiplicity. Neuroimage 2020; 220:117061. [DOI: 10.1016/j.neuroimage.2020.117061] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/20/2020] [Accepted: 06/13/2020] [Indexed: 01/28/2023] Open
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23
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Arioli M, Gianelli C, Canessa N. Neural representation of social concepts: a coordinate-based meta-analysis of fMRI studies. Brain Imaging Behav 2020; 15:1912-1921. [DOI: 10.1007/s11682-020-00384-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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24
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Bajada CJ, Costa Campos LQ, Caspers S, Muscat R, Parker GJM, Lambon Ralph MA, Cloutman LL, Trujillo-Barreto NJ. A tutorial and tool for exploring feature similarity gradients with MRI data. Neuroimage 2020; 221:117140. [PMID: 32650053 PMCID: PMC7116330 DOI: 10.1016/j.neuroimage.2020.117140] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 06/09/2020] [Accepted: 07/02/2020] [Indexed: 11/15/2022] Open
Abstract
There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various "neural gradients" (for example based on region studied "cortical gradients," "cerebellar gradients," "hippocampal gradients" etc … or feature of interest "functional gradients," "cytoarchitectural gradients," "myeloarchitectural gradients" etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by "gradient analysis". We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term "the Vogt-Bailey index" for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work.
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Affiliation(s)
- Claude J Bajada
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, The University of Malta, Malta; Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK; Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany.
| | - Lucas Q Costa Campos
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany; Institute of Complex Systems and Institute for Advanced Simulation (ICS-2/IAS-2), Research Centre Jülich, 52425, Jülich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany; Institute for Anatomy I, Medical Faculty, Heinrich-Heine-University Duesseldorf, 40221, Duesseldorf, Germany; JARA-BRAIN, Jülich-Aachen Research Alliance, 52425, Jülich, Germany
| | - Richard Muscat
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, The University of Malta, Malta
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Computer Science, and Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, UK; Bioxydyn Limited, Manchester, UK
| | | | - Lauren L Cloutman
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
| | - Nelson J Trujillo-Barreto
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
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25
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The anterior and medial thalamic nuclei and the human limbic system: tracing the structural connectivity using diffusion-weighted imaging. Sci Rep 2020; 10:10957. [PMID: 32616764 PMCID: PMC7331724 DOI: 10.1038/s41598-020-67770-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 06/15/2020] [Indexed: 12/03/2022] Open
Abstract
The limbic system is a phylogenetically old, behaviorally defined system that serves as a center for emotions. It controls the expression of anger, fear, and joy and also influences sexual behavior, vegetative functions, and memory. The system comprises a collection of tel-, di-, and mesencephalic structures whose components have evolved and increased over time. Previous animal research indicates that the anterior nuclear group of the thalamus (ANT), as well as the habenula (Hb) and the adjacent mediodorsal nucleus (MD) each play a vital role in the limbic circuitry. Accordingly, diffusion imaging data of 730 subjects obtained from the Human Connectome Project and the masks of six nuclei (anterodorsal, anteromedial, anteroventral, lateral dorsal, Hb, and MD) served as seed regions for a direct probabilistic tracking to the rest of the brain using diffusion-weighted imaging. The results revealed that the ANT nuclei are part of the limbic and the memory system as they mainly connect via the mammillary tract, mammillary body, anterior commissure, fornix, and retrosplenial cortices to the hippocampus, amygdala, medio-temporal, orbito-frontal and occipital cortices. Furthermore, the ANT nuclei showed connections to the mesencephalon and brainstem to varying extents, a pattern rarely described in experimental findings. The habenula—usually defined as part of the epithalamus—was closely connected to the tectum opticum and seems to serve as a neuroanatomical hub between the visual and the limbic system, brainstem, and cerebellum. Finally, in contrast to experimental findings with tracer studies, directly determined connections of MD were mainly confined to the brainstem, while indirect MD fibers form a broad pathway connecting the hippocampus and medio-temporal areas with the mediofrontal cortex.
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26
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Irish M, Vatansever D. Rethinking the episodic-semantic distinction from a gradient perspective. Curr Opin Behav Sci 2020. [DOI: 10.1016/j.cobeha.2020.01.016] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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27
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Nakae T, Matsumoto R, Kunieda T, Arakawa Y, Kobayashi K, Shimotake A, Yamao Y, Kikuchi T, Aso T, Matsuhashi M, Yoshida K, Ikeda A, Takahashi R, Lambon Ralph MA, Miyamoto S. Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study. Cereb Cortex 2020; 30:4633-4650. [PMID: 32232373 PMCID: PMC7325718 DOI: 10.1093/cercor/bhaa065] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Revised: 01/27/2020] [Accepted: 02/18/2020] [Indexed: 12/11/2022] Open
Abstract
In the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity between the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively in 14 patients who had undergone surgical resection for a brain tumor or epileptic focus. Four-dimensional visualization of the combined CCEP data showed that the pars opercularis (Broca’s area) is connected to the posterior temporal cortices and the supramarginal gyrus, whereas the pars orbitalis is connected to the anterior lateral temporal cortices and angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior–posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bidirectionally connected to the temporal or parietal area. This study shows that each IFG subdivision has different connectivity to the temporal lobe with an anterior–posterior gradient and supports the classical connectivity concept of Dejerine; that is, the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double fan-shaped structure anchored at the limen insulae.
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Affiliation(s)
- Takuro Nakae
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Department of Neurosurgery, Shiga General Hospital, Moriyama, Shiga 524-0022, Japan
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Division of Neurology, Kobe University Graduate School of Medicine, Kobe, Hyogo 650-0017, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Department of Neurosurgery, Ehime University Graduate School of Medicine, To-on, Ehime 791-0295, Japan
| | - Yoshiki Arakawa
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Akihiro Shimotake
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Yukihiro Yamao
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Toshihiko Aso
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Hyogo 650-0047, Japan
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | | | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
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28
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Marino Dávolos J, Arias JC, Jefferies E. Linking individual differences in semantic cognition to white matter microstructure. Neuropsychologia 2020; 141:107438. [PMID: 32171737 DOI: 10.1016/j.neuropsychologia.2020.107438] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 02/28/2020] [Accepted: 03/10/2020] [Indexed: 12/15/2022]
Abstract
Semantic cognition is thought to involve the interaction of heteromodal conceptual representations with control processes that (i) focus retrieval on currently-relevant information, and (ii) suppress dominant yet irrelevant features and associations. Research suggests that semantic control demands are higher when retrieving a link between weakly-associated word pairs, since there is a mismatch between the pattern of semantic retrieval required by the task and the dominant associations of individual words. In addition, given that heteromodal concepts are thought to reflect the integration of vision, audition, valence and other features, the control demands of semantic tasks should be higher when there is less consistency between these features. In the present study, 62 volunteers completed a semantic decision task, where association strength and semantic-affective congruence were manipulated. We used diffusion tensor magnetic resonance imaging to obtain fractional anisotropy (FA) measures of white matter tracts hypothesized to be part of the semantic network. The behavioural data revealed an interaction between semantic-affective congruence and strength of association, suggesting these manipulations both contribute to semantic control demands. Next we considered how individual differences in these markers of semantic control relate to the microstructure of canonical white matter tracts, complementing previous studies that have largely focused on measures of intrinsic functional connectivity. Repeated-measures analysis of covariance showed opposing interactions between semantic control markers and FA of two tracts: left inferior longitudinal fasciculus (ILF) and right inferior fronto-occipital fasciculus (IFOF). Participants with higher FA in left ILF showed more efficient retrieval of weak associations, and more accurate performance for weak associations when meaning and valence were incongruent, consistent with the hypothesis that this left hemisphere tract supports semantic control. In contrast, participants with higher FA in right IFOF were more accurate for trials in which meaning and valence were congruent, and consequently when semantic control demands were minimised. These findings are consistent with recent studies showing that semantic control processes are strongly left-lateralised. In contrast, long-range connections from vision to semantic regions in the right hemisphere might support relatively automatic patterns of semantic retrieval.
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Affiliation(s)
- Julián Marino Dávolos
- Department of Psychology and York Neuroimaging Centre, University of York, YO10 5DD, York, UK.
| | - Juan Cruz Arias
- Instituto de Investigación Oulton, Córdoba, Córdoba, Argentina.
| | - Elizabeth Jefferies
- Department of Psychology and York Neuroimaging Centre, University of York, YO10 5DD, York, UK.
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29
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Principles of temporal association cortex organisation as revealed by connectivity gradients. Brain Struct Funct 2020; 225:1245-1260. [PMID: 32157450 PMCID: PMC7270054 DOI: 10.1007/s00429-020-02047-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/10/2020] [Indexed: 01/10/2023]
Abstract
To establish the link between structure and function of any large area of the neocortex, it is helpful to identify its principles of organisation. One way to establish such principles is to investigate how differences in whole-brain connectivity are structured across the area. Here, we use Laplacian eigenmaps on diffusion MRI tractography data to investigate the organisational principles of the human temporal association cortex. We identify three overlapping gradients of connectivity that are, for the most part, consistent across hemispheres. The first gradient reveals an inferior–superior organisation of predominantly longitudinal tracts and separates visual and auditory unimodal and multimodal cortices. The second gradient radiates outward from the posterior middle temporal cortex with the arcuate fascicle as a distinguishing feature; the third gradient is concentrated in the anterior temporal lobe and emanates towards its posterior end. We describe the functional relevance of each of these gradients through the meta-analysis of data from the neuroimaging literature. Together, these results unravel the overlapping dimensions of structural organization of the human temporal cortex and provide a framework underlying its functional multiplicity.
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30
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Reuter N, Genon S, Kharabian Masouleh S, Hoffstaedter F, Liu X, Kalenscher T, Eickhoff SB, Patil KR. CBPtools: a Python package for regional connectivity-based parcellation. Brain Struct Funct 2020; 225:1261-1275. [PMID: 32144496 PMCID: PMC7271019 DOI: 10.1007/s00429-020-02046-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 02/08/2020] [Indexed: 02/02/2023]
Abstract
Regional connectivity-based parcellation (rCBP) is a widely used procedure for investigating the structural and functional differentiation within a region of interest (ROI) based on its long-range connectivity. No standardized software or guidelines currently exist for applying rCBP, making the method only accessible to those who develop their own tools. As such, there exists a discrepancy between the laboratories applying the procedure each with their own software solutions, making it difficult to compare and interpret the results. Here, we outline an rCBP procedure accompanied by an open source software package called CBPtools. CBPtools is a Python (version 3.5+) package that allows users to run an extensively evaluated rCBP analysis workflow on a given ROI. It currently supports two modalities: resting-state functional connectivity and structural connectivity based on diffusion-weighted imaging, along with support for custom connectivity matrices. Analysis parameters are customizable and the workflow can be scaled to a large number of subjects using a parallel processing environment. Parcellation results with corresponding validity metrics are provided as textual and graphical output. Thus, CBPtools provides a simple plug-and-play, yet customizable way to conduct rCBP analyses. By providing an open-source software we hope to promote reproducible and comparable rCBP analyses and, importantly, make the rCBP procedure readily available. Here, we demonstrate the utility of CBPtools using a voluminous data set on an average compute-cluster infrastructure by performing rCBP on three ROIs prominently featured in parcellation literature.
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Affiliation(s)
- Niels Reuter
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Sarah Genon
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Shahrzad Kharabian Masouleh
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Xiaojin Liu
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Tobias Kalenscher
- Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany.
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
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31
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Vos de Wael R, Benkarim O, Paquola C, Lariviere S, Royer J, Tavakol S, Xu T, Hong SJ, Langs G, Valk S, Misic B, Milham M, Margulies D, Smallwood J, Bernhardt BC. BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Commun Biol 2020; 3:103. [PMID: 32139786 PMCID: PMC7058611 DOI: 10.1038/s42003-020-0794-7] [Citation(s) in RCA: 214] [Impact Index Per Article: 53.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 01/24/2020] [Indexed: 11/21/2022] Open
Abstract
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be described in a compact manner with multivariate machine learning approaches that identify manifolds often described as cortical gradients. By quantifying topographic principles of macroscale organization, cortical gradients lend an analytical framework to study structural and functional brain organization across species, throughout development and aging, and its perturbations in disease. Here, we present BrainSpace, a Python/Matlab toolbox for (i) the identification of gradients, (ii) their alignment, and (iii) their visualization. Our toolbox furthermore allows for controlled association studies between gradients with other brain-level features, adjusted with respect to null models that account for spatial autocorrelation. Validation experiments demonstrate the usage and consistency of our tools for the analysis of functional and microstructural gradients across different spatial scales.
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Affiliation(s)
- Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Oualid Benkarim
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Sara Lariviere
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Jessica Royer
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Shahin Tavakol
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Ting Xu
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
- Center for the Developing Brain, Child Mind Institute, New York, USA
| | - Seok-Jun Hong
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
- Center for the Developing Brain, Child Mind Institute, New York, USA
| | - Georg Langs
- Medical University of Vienna, Vienna, Austria
| | - Sofie Valk
- Institute for Neuroscience and Medicine; 7/Institute of Systems Neuroscience, Forschungszentrum Juelich - Heinrich Heine Universitaet Duesseldorf, Juelich, Germany
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Michael Milham
- Center for the Developing Brain, Child Mind Institute, New York, USA
| | - Daniel Margulies
- Frontlab, Institut du Cerveau et de la Moelle épinière, UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | | | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
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32
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Bajada CJ, Trujillo-Barreto NJ, Parker GJM, Cloutman LL, Lambon Ralph MA. A structural connectivity convergence zone in the ventral and anterior temporal lobes: Data-driven evidence from structural imaging. Cortex 2019; 120:298-307. [PMID: 31377672 PMCID: PMC6838667 DOI: 10.1016/j.cortex.2019.06.014] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 03/28/2019] [Accepted: 06/26/2019] [Indexed: 01/12/2023]
Abstract
The hub-and-spoke model of semantic cognition seeks to reconcile embodied views of a fully distributed semantic network with patient evidence, primarily from semantic dementia, who demonstrate modality-independent conceptual deficits associated with atrophy centred on the ventrolateral anterior temporal lobe. The proponents of this model have recently suggested that the temporal cortex is a graded representational space where concepts become less linked to a specific modality as they are processed farther away from primary and secondary sensory cortices and towards the ventral anterior temporal lobe. To explore whether there is evidence that the connectivity patterns of the temporal lobe converge in its ventral anterior end the current study uses three dimensional Laplacian eigenmapping, a technique that allows visualisation of similarity in a low dimensional space. In this space similarity is encoded in terms of distances between data points. We found that the ventral and anterior temporal lobe is in a unique position of being at the centre of mass of the data points within the connective similarity space. This can be interpreted as the area where the connectivity profiles of all other temporal cortex voxels converge. This study is the first to explicitly investigate the pattern of connectivity and thus provides the missing link in the evidence that the ventral anterior temporal lobe can be considered a multi-modal graded hub.
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Affiliation(s)
- Claude J Bajada
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK; Faculty of Medicine and Surgery, University of Malta, Malta.
| | - Nelson J Trujillo-Barreto
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
| | - Geoff J M Parker
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK; Bioxydyn Limited, Manchester, UK; Centre for Medical Image Computing, Department of Computer Science, and Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, UK; Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, University of Malta, Malta
| | - Lauren L Cloutman
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
| | - Matthew A Lambon Ralph
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK; MRC, Cognition and Brain Sciences Unit, The University of Cambridge, Cambridge, UK.
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33
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Guell X, Goncalves M, Kaczmarzyk JR, Gabrieli JDE, Schmahmann JD, Ghosh SS. LittleBrain: A gradient-based tool for the topographical interpretation of cerebellar neuroimaging findings. PLoS One 2019; 14:e0210028. [PMID: 30650101 PMCID: PMC6334893 DOI: 10.1371/journal.pone.0210028] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 12/14/2018] [Indexed: 11/19/2022] Open
Abstract
Gradient-based approaches to brain function have recently unmasked fundamental properties of brain organization. Diffusion map embedding analysis of resting-state fMRI data revealed a primary-to-transmodal axis of cerebral cortical macroscale functional organization. The same method was recently used to analyze resting-state data within the cerebellum, revealing for the first time a sensorimotor-fugal macroscale organization principle of cerebellar function. Cerebellar gradient 1 extended from motor to non-motor task-unfocused (default-mode network) areas, and cerebellar gradient 2 isolated task-focused processing regions. Here we present a freely available and easily accessible tool that applies this new knowledge to the topographical interpretation of cerebellar neuroimaging findings. LittleBrain illustrates the relationship between cerebellar data (e.g., volumetric patient study clusters, task activation maps, etc.) and cerebellar gradients 1 and 2. Specifically, LittleBrain plots all voxels of the cerebellum in a two-dimensional scatterplot, with each axis corresponding to one of the two principal functional gradients of the cerebellum, and indicates the position of cerebellar neuroimaging data within these two dimensions. This novel method of data mapping provides alternative, gradual visualizations that complement discrete parcellation maps of cerebellar functional neuroanatomy. We present application examples to show that LittleBrain can also capture subtle, progressive aspects of cerebellar functional neuroanatomy that would be difficult to visualize using conventional mapping techniques. Download and use instructions can be found at https://xaviergp.github.io/littlebrain.
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Affiliation(s)
- Xavier Guell
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
| | - Mathias Goncalves
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Jakub R. Kaczmarzyk
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - John D. E. Gabrieli
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Jeremy D. Schmahmann
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Ataxia Unit, Cognitive Behavioral Neurology Unit, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Otolaryngology, Harvard Medical School, Boston, Massachusetts, United States of America
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34
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Model testing for distinctive functional connectivity gradients with resting-state fMRI data. Neuroimage 2019; 185:102-110. [DOI: 10.1016/j.neuroimage.2018.10.022] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 09/15/2018] [Accepted: 10/07/2018] [Indexed: 11/15/2022] Open
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35
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Bajada CJ, Schreiber J, Caspers S. Fiber length profiling: A novel approach to structural brain organization. Neuroimage 2018; 186:164-173. [PMID: 30399419 DOI: 10.1016/j.neuroimage.2018.10.070] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 10/03/2018] [Accepted: 10/26/2018] [Indexed: 10/27/2022] Open
Abstract
There has been a recent increased interest in the structural connectivity of the cortex. However, an important feature of connectivity remains relatively unexplored; tract length. In this article, we develop an approach to characterize fiber length distributions across the human cerebral cortex. We used data from 76 participants of the Adult WU-Minn Human Connectome Project using probabilistic tractography. We found that connections of different lengths are not evenly distributed across the cortex. They form patterns where certain areas have a high density of fibers of a specific length while other areas have very low density. To assess the relevance of these new maps in relation to established characteristics, we compared them to structural indices such as cortical myelin content and cortical thickness. Additionally, we assessed their relation to resting state network organization. We noted that areas with very short fibers have relatively more myelin and lower cortical thickness while the pattern is inverted for longer fibers. Furthermore, the cortical fiber length distributions produce specific correlation patterns with functional resting state networks. Specifically, we find evidence that as resting state networks increase in complexity, their length profiles change. The functionally more complex networks correlate with maps of varying lengths while primary networks have more restricted correlations. We posit that these maps are a novel way of differentiating between 'local modules' that have restricted connections to 'neighboring' areas and 'functional integrators' that have more far reaching connectivity.
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Affiliation(s)
- Claude J Bajada
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany; Faculty of Medicine and Surgery, University of Malta, Msida, MSD, 2080, Malta
| | - Jan Schreiber
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany; Institute for Anatomy I, Medical Faculty, Heinrich-Heine-University Duesseldorf, 40221, Duesseldorf, Germany; JARA-BRAIN, Juelich-Aachen Research Alliance, 52425, Juelich, Germany.
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Hoffman P, Lambon Ralph MA. From percept to concept in the ventral temporal lobes: Graded hemispheric specialisation based on stimulus and task. Cortex 2018; 101:107-118. [PMID: 29475076 PMCID: PMC5885984 DOI: 10.1016/j.cortex.2018.01.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 11/29/2017] [Accepted: 01/17/2018] [Indexed: 01/28/2023]
Abstract
The left and right ventral anterior temporal lobes (vATL) have been implicated as key regions for the representation of conceptual knowledge. However, the nature and degree of hemispheric specialisation in their function is unclear. To address this issue, we investigated hemispheric specialisation in the ventral temporal lobes using a distortion-corrected spin-echo fMRI protocol that enhanced signal in vATL. We employed an orthogonal manipulation of stimulus (written words vs pictured objects) and task (naming vs recognition). Words elicited left-lateralised vATL activation while objects elicited bilateral activation with no hemispheric bias. In contrast, posterior ventral temporal cortex exhibited a rightward bias for objects as well as a leftward bias for words. Naming tasks produced left-lateralised activation in vATL while activity for recognition was equal in left and right vATLs. These findings are incompatible with proposals that left and right ATLs are strongly modular in function, since these predict rightward as well as leftward biases. Instead, they support an alternative model in which (a) left and right ATL together form a bilateral, integrated system for the representation of concepts and (b) within this system, graded hemispheric specialisation emerges as a consequence of differential connectivity with other neural systems. On this view, greater left vATL activation for written word processing develops as a consequence of the inputs this region receives from left-lateralised visual word processing system in posterior temporal cortex. Greater left vATL activation during naming tasks is most likely due to connectivity with left-lateralised speech output systems in prefrontal and motor cortices.
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Affiliation(s)
- Paul Hoffman
- Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), Department of Psychology, University of Edinburgh, UK; Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences, University of Manchester, UK.
| | - Matthew A Lambon Ralph
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences, University of Manchester, UK
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37
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Tittgemeyer M, Rigoux L, Knösche TR. Cortical parcellation based on structural connectivity: A case for generative models. Neuroimage 2018; 173:592-603. [PMID: 29407457 DOI: 10.1016/j.neuroimage.2018.01.077] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Revised: 01/26/2018] [Accepted: 01/29/2018] [Indexed: 12/14/2022] Open
Abstract
One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions.
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Affiliation(s)
| | - Lionel Rigoux
- Max-Planck-Institute for Metabolism Research, Cologne, Germany
| | - Thomas R Knösche
- Max-Planck-Institute for Cognitive and Brain Sciences, Leipzig, Germany
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Jackson RL, Bajada CJ, Rice GE, Cloutman LL, Lambon Ralph MA. An emergent functional parcellation of the temporal cortex. Neuroimage 2017; 170:385-399. [PMID: 28419851 DOI: 10.1016/j.neuroimage.2017.04.024] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 04/07/2017] [Accepted: 04/08/2017] [Indexed: 12/13/2022] Open
Abstract
The temporal lobe has been associated with various cognitive functions which include memory, auditory cognition and semantics. However, at a higher level of conceptualisation, all of the functions associated with the temporal lobe can be considered as lying along one major axis; from modality-specific to modality-general processing. This paper used a spectral reordering technique on resting-state and task-based functional data to extract the major organisational axis of the temporal lobe in a bottom-up, data-driven fashion. Independent parcellations were performed on resting-state scans from 71 participants and active semantic task scans from 23 participants acquired using dual echo gradient echo planar imaging in order to preserve signal in inferior temporal cortex. The resulting organisational axis was consistent (over dataset and hemisphere) and progressed from superior temporal gyrus and posterior inferior temporal cortex to ventrolateral anterior temporal cortex. A hard parcellation separated a posterior (superior temporal and posterior fusiform and inferior temporal gyri) and an anterior cluster (ventrolateral anterior temporal lobe). The functional connectivity of the hard clusters supported the hypothesis that the connectivity gradient separated modality-specific and modality-general regions. This hypothesis was then directly tested by performing a VOI analysis upon an independent semantic task-based data set including auditory and visually presented stimuli. This confirmed that the ventrolateral anterior aspects of the temporal lobe are associated with modality-general processes whilst posterior and superior aspects are specific to certain modalities, with the posterior inferior subregions involved in visual processes and superior regions involved in audition.
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Affiliation(s)
- Rebecca L Jackson
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences (Zochonis Building), University of Manchester, M13 9PL, UK
| | - Claude J Bajada
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences (Zochonis Building), University of Manchester, M13 9PL, UK
| | - Grace E Rice
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences (Zochonis Building), University of Manchester, M13 9PL, UK
| | - Lauren L Cloutman
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences (Zochonis Building), University of Manchester, M13 9PL, UK
| | - Matthew A Lambon Ralph
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology, School of Biological Sciences (Zochonis Building), University of Manchester, M13 9PL, UK.
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