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Wang Q, Shin B, Oh S, Hwang S, Kim KW. Functional Near-Infrared Spectroscopy Signal as a Potential Biomarker for White Matter Hyperintensity Progression in Patients With Subcortical Vascular Cognitive Impairment: A Pilot Study. Brain Behav 2025; 15:e70598. [PMID: 40444679 PMCID: PMC12123445 DOI: 10.1002/brb3.70598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2024] [Revised: 05/09/2025] [Accepted: 05/12/2025] [Indexed: 06/02/2025] Open
Abstract
BACKGROUND White matter hyperintensities (WMH) are a common cause of subcortical vascular cognitive impairment (SVCI). The silent yet progressive nature of WMH in cognitive decline underscores the need for reliable biomarkers for early detection and monitoring of its progression. This study aims to investigate the association between functional near-infrared spectroscopy (fNIRS) signals during mental and physical activities and WMH volume. Additionally, it explores the relationship between fNIRS signals and WMH progression. MATERIAL AND METHODS We recruited 27 patients with mild cognitive impairment (MCI) presenting WMH clinical characteristics. Data from fNIRS and MRI scans were collected during their first visit. Ten of them underwent fNIRS and MRI scans in a second visit two years later. WMH volume analysis used volBrain lesionBrain 1.0 (https://www.volbrain.net). ROC curve analysis was applied to the normalized WMH volume to determine a cut-off value for distinguishing between the subcortical vascular MCI (svMCI) and amnestic MCI (aMCI) groups. We compared fNIRS data during cognitive tests and physical activities between svMCI and aMCI groups at the first visit and in the two-year follow-up. RESULTS While cognitive profiles were similar between groups, svMCI patients showed significantly reduced fNIRS signals, particularly in the left orbitofrontal cortex (OFC) during verbal fluency tasks (P = 0.005), with further reductions in the left dorsolateral prefrontal cortex (P = 0.049), left OFC (P = 0.012), and right OFC (P = 0.02) over two years. Baseline WMH volume correlated negatively with fNIRS signals during the Stroop test (r = -0.837, P = 0.005). Changes in WMH volume over two years correlated positively with changes in fNIRS signals in the right ventrolateral prefrontal cortex during memory tasks (r = 0.886, P = 0.033) and left OFC during balance tasks (r = 0.786, P = 0.028). CONCLUSION Our results suggest that fNIRS signals have the potential to serve as biomarkers for WMH progression.
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Affiliation(s)
- Qi Wang
- Department of Medicine, Medical SchoolJeonbuk National UniversityJeonjuRepublic of Korea
| | - Byoung‐Soo Shin
- Department of NeurologyJeonbuk National University Medical School and HospitalJeonjuRepublic of Korea
- Research Institute of Clinical Medicine of Jeonbuk National University‐Biomedical Research Institute of Jeonbuk National University HospitalJeonjuRepublic of Korea
| | - Sun‐Young Oh
- Department of NeurologyJeonbuk National University Medical School and HospitalJeonjuRepublic of Korea
- Research Institute of Clinical Medicine of Jeonbuk National University‐Biomedical Research Institute of Jeonbuk National University HospitalJeonjuRepublic of Korea
| | - Seungbae Hwang
- Research Institute of Clinical Medicine of Jeonbuk National University‐Biomedical Research Institute of Jeonbuk National University HospitalJeonjuRepublic of Korea
- Department of RadiologyJeonbuk National University Medical School and HospitalJeonjuRepublic of Korea
| | - Ko Woon Kim
- Department of NeurologyJeonbuk National University Medical School and HospitalJeonjuRepublic of Korea
- Research Institute of Clinical Medicine of Jeonbuk National University‐Biomedical Research Institute of Jeonbuk National University HospitalJeonjuRepublic of Korea
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Madden DJ, Merenstein JL, Mullin HA, Jain S, Rudolph MD, Cohen JR. Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance. Brain Struct Funct 2024; 229:1533-1559. [PMID: 38856933 PMCID: PMC11374505 DOI: 10.1007/s00429-024-02807-2] [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: 12/29/2023] [Accepted: 05/13/2024] [Indexed: 06/11/2024]
Abstract
Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA.
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- Department of Psychology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, 32804, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
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