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Fotiadis P, Parkes L, Davis KA, Satterthwaite TD, Shinohara RT, Bassett DS. Structure-function coupling in macroscale human brain networks. Nat Rev Neurosci 2024; 25:688-704. [PMID: 39103609 DOI: 10.1038/s41583-024-00846-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2024] [Indexed: 08/07/2024]
Abstract
Precisely how the anatomical structure of the brain gives rise to a repertoire of complex functions remains incompletely understood. A promising manifestation of this mapping from structure to function is the dependency of the functional activity of a brain region on the underlying white matter architecture. Here, we review the literature examining the macroscale coupling between structural and functional connectivity, and we establish how this structure-function coupling (SFC) can provide more information about the underlying workings of the brain than either feature alone. We begin by defining SFC and describing the computational methods used to quantify it. We then review empirical studies that examine the heterogeneous expression of SFC across different brain regions, among individuals, in the context of the cognitive task being performed, and over time, as well as its role in fostering flexible cognition. Last, we investigate how the coupling between structure and function is affected in neurological and psychiatric conditions, and we report how aberrant SFC is associated with disease duration and disease-specific cognitive impairment. By elucidating how the dynamic relationship between the structure and function of the brain is altered in the presence of neurological and psychiatric conditions, we aim to not only further our understanding of their aetiology but also establish SFC as a new and sensitive marker of disease symptomatology and cognitive performance. Overall, this Review collates the current knowledge regarding the regional interdependency between the macroscale structure and function of the human brain in both neurotypical and neuroatypical individuals.
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Affiliation(s)
- Panagiotis Fotiadis
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Anaesthesiology, University of Michigan, Ann Arbor, MI, USA.
| | - Linden Parkes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn A Davis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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Criado-Marrero M, Ravi S, Bhaskar E, Barroso D, Pizzi MA, Williams L, Wellington CL, Febo M, Abisambra JF. Age dictates brain functional connectivity and axonal integrity following repetitive mild traumatic brain injuries in mice. Neuroimage 2024; 298:120764. [PMID: 39089604 DOI: 10.1016/j.neuroimage.2024.120764] [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: 04/30/2024] [Revised: 07/08/2024] [Accepted: 07/29/2024] [Indexed: 08/04/2024] Open
Abstract
Traumatic brain injuries (TBI) present a major public health challenge, demanding an in-depth understanding of age-specific symptoms and risk factors. Aging not only significantly influences brain function and plasticity but also elevates the risk of hospitalizations and death following TBIs. Repetitive mild TBIs (rmTBI) compound these issues, resulting in cumulative and long-term brain damage in the brain. In this study, we investigate the impact of age on brain network changes and white matter properties following rmTBI by employing a multi-modal approach that integrates resting-state functional magnetic resonance imaging (rsfMRI), graph theory analysis, diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI). Our hypothesis is that the effects of rmTBI are worsened in aged animals, with this group showing more pronounced alterations in brain connectivity and white matter structure. Utilizing the closed-head impact model of engineered rotational acceleration (CHIMERA) model, we conducted rmTBIs or sham (control) procedures on young (2.5-3-months-old) and aged (22-months-old) male and female mice to model high-risk groups. Functional and structural imaging unveiled age-related reductions in communication efficiency between brain regions, while injuries induced opposhigh-risking effects on the small-world index across age groups, influencing network segregation. Functional connectivity analysis also identified alterations in 79 out of 148 brain regions by age, treatment (sham vs. rmTBI), or their interaction. Injuries exerted pronounced effects on sensory integration areas, including insular and motor cortices. Age-related disruptions in white matter integrity were observed, indicating alterations in various diffusion directions (mean diffusivity, radial diffusivity, axial diffusivity, and fractional anisotropy) and density neurite properties (dispersion index, intracellular and isotropic volume fraction). Neuroinflammation, assessed through Iba-1 and GFAP markers, correlated with higher dispersion in the optic tract, suggesting a neuroinflammatory response in injured aged animals compared to sham aged. These findings offer insight into the interplay between age, injuries, and brain connectivity, shedding light on the long-term consequences of rmTBI.
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Affiliation(s)
- Marangelie Criado-Marrero
- Center for Translational Research in Neurodegenerative Disease (CTRND), University of Florida, Gainesville, FL 32610, USA; Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA
| | - Sakthivel Ravi
- Center for Translational Research in Neurodegenerative Disease (CTRND), University of Florida, Gainesville, FL 32610, USA; Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA
| | - Ekta Bhaskar
- Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; Department of Computer of Information Science and Engineering (CISE), University of Florida, Gainesville, FL 32610, USA
| | - Daylin Barroso
- Center for Translational Research in Neurodegenerative Disease (CTRND), University of Florida, Gainesville, FL 32610, USA; Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA
| | - Michael A Pizzi
- Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA; Brain Injury Rehabilitation and Neuroresilience (BRAIN) Center University of Florida, Gainesville, FL 32610, USA; Department of Neurology, University of Florida, Gainesville, FL 32610, USA
| | - Lakiesha Williams
- J. Crayton Pruitt Family Department of Biomedical Engineering, Gainesville, FL 32610, USA
| | - Cheryl L Wellington
- Department of Pathology and Laboratory Medicine, Djavad Mowafaghian Center for Brain Health, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Marcelo Febo
- McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA; Department of Psychiatry, University of Florida, Gainesville, FL 32610, USA; Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL 32610, USA
| | - Jose Francisco Abisambra
- Center for Translational Research in Neurodegenerative Disease (CTRND), University of Florida, Gainesville, FL 32610, USA; Department of Neuroscience, University of Florida, Gainesville, FL 32610, USA; McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA; Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL 32610, USA; Brain Injury Rehabilitation and Neuroresilience (BRAIN) Center University of Florida, Gainesville, FL 32610, USA.
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Gugger JJ, Walter AE, Diaz‐Arrastia R, Huang J, Jack CR, Reid R, Kucharska‐Newton AM, Gottesman RF, Schneider ALC, Johnson EL. Association between structural brain MRI abnormalities and epilepsy in older adults. Ann Clin Transl Neurol 2024; 11:342-354. [PMID: 38155477 PMCID: PMC10863905 DOI: 10.1002/acn3.51955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/21/2023] [Accepted: 11/11/2023] [Indexed: 12/30/2023] Open
Abstract
OBJECTIVE To determine the association between brain MRI abnormalities and incident epilepsy in older adults. METHODS Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status. RESULTS Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3). INTERPRETATION This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.
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Affiliation(s)
- James J. Gugger
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexa E. Walter
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Ramon Diaz‐Arrastia
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Juebin Huang
- Department of NeurologyUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Robert Reid
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Anna M. Kucharska‐Newton
- Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research ProgramBethesdaMarylandUSA
| | - Andrea L. C. Schneider
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
- Department of Biostatistics, Epidemiology, and InformaticsUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Emily L. Johnson
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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Criado-Marrero M, Ravi S, Bhaskar E, Barroso D, Pizzi MA, Williams L, Wellington CL, Febo M, Abisambra JF. Age dictates brain functional connectivity and axonal integrity following repetitive mild traumatic brain injuries. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.25.577316. [PMID: 38328104 PMCID: PMC10849649 DOI: 10.1101/2024.01.25.577316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Traumatic brain injuries (TBI) present a major public health challenge, demanding an in-depth understanding of age-specific signs and vulnerabilities. Aging not only significantly influences brain function and plasticity but also elevates the risk of hospitalizations and death following repetitive mild traumatic brain injuries (rmTBIs). In this study, we investigate the impact of age on brain network changes and white matter properties following rmTBI employing a multi-modal approach that integrates resting-state functional magnetic resonance imaging (rsfMRI), graph theory analysis, diffusion tensor imaging (DTI), and Neurite Orientation Dispersion and Density Imaging (NODDI). Utilizing the CHIMERA model, we conducted rmTBIs or sham (control) procedures on young (2.5-3 months old) and aged (22-month-old) male and female mice to model high risk groups. Functional and structural imaging unveiled age-related reductions in communication efficiency between brain regions, while injuries induced opposing effects on the small-world index across age groups, influencing network segregation. Functional connectivity analysis also identified alterations in 79 out of 148 brain regions by age, treatment (sham vs. rmTBI), or their interaction. Injuries exerted pronounced effects on sensory integration areas, including insular and motor cortices. Age-related disruptions in white matter integrity were observed, indicating alterations in various diffusion directions (mean, radial, axial diffusivity, fractional anisotropy) and density neurite properties (dispersion index, intracellular and isotropic volume fraction). Inflammation, assessed through Iba-1 and GFAP markers, correlated with higher dispersion in the optic tract, suggesting a neuroinflammatory response in aged animals. These findings provide a comprehensive understanding of the intricate interplay between age, injuries, and brain connectivity, shedding light on the long-term consequences of rmTBIs.
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