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You Z, Liu Y, Li Z, Liu J, Li J. Application of Upper Limb Multimodal Tasks Combined With fNIRS Technology in the Assessment of Mild Cognitive Impairment. JOURNAL OF BIOPHOTONICS 2025:e202500020. [PMID: 40364662 DOI: 10.1002/jbio.202500020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2025] [Revised: 03/16/2025] [Accepted: 04/17/2025] [Indexed: 05/15/2025]
Abstract
Mild cognitive impairment (MCI) is primarily characterized by a gradual decline in cognitive function, where early detection and intervention are crucial to preventing Alzheimer's disease progression. This study integrates upper limb multimodal tasks (ULMTs) with functional near-infrared spectroscopy (fNIRS) to assess cognitive and motor functions in MCI patients. Thirty-seven elderly participants were categorized into healthy control (HC) and MCI groups. The experiment consisted of resting state, numerical cognitive task (NCT), motor task (MT), and ULMT phases. fNIRS measured hemodynamic responses in the prefrontal and motor cortices, while an upper limb trainer recorded motor data. Results showed weaker cortical responses in the MCI group during rest and reduced motor cortex activation during NCT. Both groups displayed increased cortical activity during ULMT compared to NCT but reduced motor performance compared to MT. These findings demonstrate the potential of ULMTs combined with fNIRS for early MCI assessment and intervention.
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Affiliation(s)
- Zhenda You
- School of Mechanical Engineering, Hebei University of Technology, Tianjin, China
| | - Ying Liu
- Laboratory of Robotics Mechanism and Cross Innovation, School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, P. R. China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, P. R. China
| | - Jixiao Liu
- School of Mechanical Engineering, Hebei University of Technology, Tianjin, China
| | - Jian Li
- Laboratory of Robotics Mechanism and Cross Innovation, School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, China
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Pu Z, Huang H, Li M, Li H, Shen X, Du L, Wu Q, Fang X, Meng X, Ni Q, Li G, Cui D. Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study. Neuroimage 2025; 310:121130. [PMID: 40058532 DOI: 10.1016/j.neuroimage.2025.121130] [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: 02/23/2024] [Revised: 03/05/2025] [Accepted: 03/06/2025] [Indexed: 03/15/2025] Open
Abstract
BACKGROUND Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) carry the risk of progression to dementia, and accurate screening methods for these conditions are urgently needed. Studies have suggested the potential ability of functional near-infrared spectroscopy (fNIRS) to identify MCI and SCD. The present fNIRS study aimed to develop an early screening method for SCD and MCI based on activated prefrontal functional connectivity (FC) during the performance of cognitive scales and subject-wise cross-validation via machine learning. METHODS Activated prefrontal FC data measured by fNIRS were collected from 55 normal controls, 80 SCD patients, and 111 MCI patients. Differences in FC were analyzed among the groups, and FC strength and cognitive scale performance were extracted as features to build classification and predictive models through machine learning. Model performance was assessed based on accuracy, specificity, sensitivity, and area under the curve (AUC) with 95 % confidence interval (CI) values. RESULTS Statistical analysis revealed a trend toward more impaired prefrontal FC with declining cognitive function. Prediction models were built by combining features of prefrontal FC and cognitive scale performance and applying machine learning models, The models showed generally satisfactory abilities to differentiate among the three groups, especially those employing linear discriminant analysis, logistic regression, and support vector machine. Accuracies of 92.0 % for MCI vs. NC, 80.0 % for MCI vs. SCD, and 76.1 % for SCD vs. NC were achieved, and the highest AUC values were 97.0 % (95 % CI: 94.6 %-99.3 %) for MCI vs. NC, 87.0 % (95 % CI: 81.5 %-92.5 %) for MCI vs. SCD, and 79.2 % (95 % CI: 71.0 %-87.3 %) for SCD vs. NC. CONCLUSION The developed screening method based on fNIRS and machine learning has the potential to predict early-stage cognitive impairment based on prefrontal FC data collected during cognitive scale-induced activation.
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Affiliation(s)
- Zhengping Pu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, PR China; Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Hongna Huang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, PR China
| | - Man Li
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Hongyan Li
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Xiaoyan Shen
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Lizhao Du
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, PR China
| | - Qingfeng Wu
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Xiaomei Fang
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Xiang Meng
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Qin Ni
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China
| | - Guorong Li
- Department of Psychogeriatrics, Kangci Hospital of Jiaxissng, Tongxiang 314500, Zhejiang, PR China.
| | - Donghong Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, PR China.
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Yang B, Deng X, Qu X, Li Y, Guo L, Yu N. Identification of functional near-infrared spectroscopy for older adults with mild cognitive impairment: a systematic review. Front Aging Neurosci 2025; 17:1492800. [PMID: 40271185 PMCID: PMC12014625 DOI: 10.3389/fnagi.2025.1492800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2024] [Accepted: 03/13/2025] [Indexed: 04/25/2025] Open
Abstract
Objective Mild cognitive impairment (MCI), a common state of cognitive impairment without significant impairment in daily functioning among older adults, is mainly identified using various neuropsychological tests, clinical interviews, and collateral history with some subjective interferences. This systematic review aimed to investigate the functional near-infrared spectroscopy (fNIRS) features of older adults with MCI compared with those with normal cognitive function to assist in the diagnosis of MCI. Methods A literature search was conducted in electronic databases, including PubMed, Web of Science, Embase, and Cochrane Library, up to June 15, 2024. The data on article information (first author and year of publication), participant characteristics, task paradigms, regions of interest (ROIs), fNIRS device attributes, and results related to cerebral oxygenation and hemodynamics were extracted. Results Finally, 34 relevant studies were identified, involving 1033 patients with MCI and 1107 age-, sex-, and education-matched controls with normal cognitive function. We found that the studies frequently used working memory-related task paradigms and resting-state measurements. Also, the prefrontal cortex was a primary ROI, and the changes in oxygenated hemoglobin concentration were the most basic research attributes used to derive measures such as functional connectivity (FC), FC variability, slope, and other parameters. However, ROI activation levels differed inconsistently between patients with MCI and individuals with normal cognition across studies. In general, the activation levels in the ROI of MCI patients may be higher than, lower than, or comparable to those in the normal control group. Conclusion Research on fNIRS in elderly patients with MCI aims to provide an objective marker for MCI diagnosis. The current findings are mixed. However, these differences can be partly explained with the theoretical support from the interaction of cognitive load theory and scaffolding theory of aging and cognition, taking into account factors such as unspecified MCI subtypes, task difficulty, task design, monitoring duration, and population characteristics. Therefore, future studies should consider definite MCI subtypes, strict and well-designed paradigms, long-term monitoring, and large sample sizes to obtain the most consistent results, thereby providing objective references for the clinical diagnosis of MCI in elderly patients.
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Affiliation(s)
- Bo Yang
- Department of Center for Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Xia Deng
- Department of Center for Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Xianfeng Qu
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yingjie Li
- Department of Neurology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Lei Guo
- Department of Neurology, Xindu District People’s Hospital of Chengdu, Chengdu, China
| | - Nengwei Yu
- Department of Neurology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
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Yang G, Fan C, Li H, Tong Y, Lin S, Feng Y, Liu F, Bao C, Xie H, Wu Y. Resting-State Brain Network Characteristics Related to Mild Cognitive Impairment: A Preliminary fNIRS Proof-of-Concept Study. J Integr Neurosci 2025; 24:26406. [PMID: 40018781 DOI: 10.31083/jin26406] [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: 09/02/2024] [Revised: 11/25/2024] [Accepted: 12/04/2024] [Indexed: 03/01/2025] Open
Abstract
BACKGROUND This study investigates the reliability of functional near-infrared spectroscopy (fNIRS) in detecting resting-state brain network characteristics in patients with mild cognitive impairment (MCI), focusing on static resting-state functional connectivity (sRSFC) and dynamic resting-state functional connectivity (dRSFC) patterns in MCI patients and healthy controls (HCs) without cognitive impairment. METHODS A total of 89 MCI patients and 83 HCs were characterized using neuropsychological scales. Subject sRSFC strength and dRSFC variability coefficients were evaluated via fNIRS. The study evaluated the feasibility of using fNIRS to measure these connectivity metrics and compared resting-state brain network characteristics between the two groups. Correlations with Montreal Cognitive Assessment (MoCA) scores were also explored. RESULTS sRSFC strength in homologous brain networks was significantly lower than in heterologous networks (p < 0.05). A significant negative correlation was also observed between sRSFC strength and dRSFC variability at both the group and individual levels (p < 0.001). While sRSFC strength did not differentiate between MCI patients and HCs, the dRSFC variability between the dorsal attention network (DAN) and default mode network (DMN), and between the ventral attention network (VAN) and visual network (VIS), emerged as sensitive biomarkers after false discovery rate correction (p < 0.05). No significant correlation was found between MoCA scores and connectivity measures. CONCLUSIONS fNIRS can be used to study resting-state brain networks, with dRSFC variability being more sensitive than sRSFC strength for discriminating between MCI patients and HCs. The DAN-DMN and VAN-VIS regions were found to be particularly useful for the identification of dRSFC differences between the two groups. CLINICAL TRIAL REGISTRATION ChiCTR2200057281, registered on 6 March, 2022; https://www.chictr.org.cn/showproj.html?proj=133808.
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Affiliation(s)
- Guohui Yang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Chenyu Fan
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Haozheng Li
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yu Tong
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Shuang Lin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yashuo Feng
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, 201203 Shanghai, China
| | - Fengzhi Liu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Chunrong Bao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200030 Shanghai, China
| | - Hongyu Xie
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
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Albrecht F, Kvist A, Franzén E. Resting-state functional near-infrared spectroscopy in neurodegenerative diseases - A systematic review. Neuroimage Clin 2025; 45:103733. [PMID: 39889542 PMCID: PMC11833346 DOI: 10.1016/j.nicl.2025.103733] [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: 09/27/2024] [Revised: 01/09/2025] [Accepted: 01/09/2025] [Indexed: 02/03/2025]
Abstract
OBJECTIVE To systematically review and summarize alterations found in resting-state activity as measured via functional near-infrared spectroscopy (fNIRS) in neurodegenerative diseases. BACKGROUND fNIRS is a novel and emerging neuroimaging method suitable for a variety of study designs. Resting-state is the measure of brain activity in the absence of a task, which has been investigated for yielding information about neurodegenerative diseases, mainly using magnetic resonance imaging. We aimed to systematically review the usage of resting-state fNIRS (rsfNIRS) in neurodegenerative diseases. INCLUSION CRITERIA Studies investigating people diagnosed with a neurodegenerative disease and resting-state activity obtained with fNIRS using at least two channels. METHODS We searched three databases for publications. After the screening, 16 studies were included in the systematic review. The quality of the studies was assessed, and data were extracted. Data were qualitatively synthesized and in the case of at least 10 similar studies, a meta-analysis was planned. RESULTS Most studies investigated Mild cognitive impairment (50%), followed by Alzheimer's disease (25%). Other neurodegenerative diseases encompassed Parkinson's disease, Multiple sclerosis, and Amyotrophic lateral sclerosis. All studies reported oxygenated hemoglobin. Still, studies were heterogeneous in terms of study design, measurement duration, fNIRS device, montage, pre-processing, and analyses. A meta-analysis was not considered possible due to this heterogeneity. CONCLUSION rsfNIRS shows promise in neurodegenerative disease, as most studies have observed resting-state alterations when compared to healthy controls. However, inconsistencies across studies limit data comparison and meta-analysis. Hence, we strongly advocate the application of fNIRS reporting guidelines and the establishment of rsfNIRS-specific guidelines. This will ensure reliable and comparable results in future research.
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Affiliation(s)
- Franziska Albrecht
- Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Karolinska University Hospital, Women's Health and Allied Health Professionals Theme, Medical unit Occupational Therapy & Physiotherapy, Stockholm Sweden.
| | - Alexander Kvist
- Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Karolinska University Hospital, Women's Health and Allied Health Professionals Theme, Medical unit Occupational Therapy & Physiotherapy, Stockholm Sweden
| | - Erika Franzén
- Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Karolinska University Hospital, Women's Health and Allied Health Professionals Theme, Medical unit Occupational Therapy & Physiotherapy, Stockholm Sweden; Stockholm's Sjukhem Foundation, Stockholm, Sweden
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Pu Z, Huang H, Li M, Li H, Shen X, Wu Q, Ni Q, Lin Y, Cui D. An exploration of distinguishing subjective cognitive decline and mild cognitive impairment based on resting-state prefrontal functional connectivity assessed by functional near-infrared spectroscopy. Front Aging Neurosci 2025; 16:1468246. [PMID: 39845444 PMCID: PMC11750998 DOI: 10.3389/fnagi.2024.1468246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 12/19/2024] [Indexed: 01/24/2025] Open
Abstract
Purpose Functional near-infrared spectroscopy (fNIRS) has shown feasibility in evaluating cognitive function and brain functional connectivity (FC). Therefore, this fNIRS study aimed to develop a screening method for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) based on resting-state prefrontal FC and neuropsychological tests via machine learning. Methods Functional connectivity data measured by fNIRS were collected from 55 normal controls (NCs), 80 SCD individuals, and 111 MCI individuals. Differences in FC were analyzed among the groups. FC strength and neuropsychological test scores were extracted as features to build classification and predictive models through machine learning. Model performance was assessed based on accuracy, specificity, sensitivity, and area under the curve (AUC) with 95% confidence interval (CI) values. Results Statistical analysis revealed a trend toward compensatory enhanced prefrontal FC in SCD and MCI individuals. The models showed a satisfactory ability to differentiate among the three groups, especially those employing linear discriminant analysis, logistic regression, and support vector machine. Accuracies of 94.9% for MCI vs. NC, 79.4% for MCI vs. SCD, and 77.0% for SCD vs. NC were achieved, and the highest AUC values were 97.5% (95% CI: 95.0%-100.0%) for MCI vs. NC, 83.7% (95% CI: 77.5%-89.8%) for MCI vs. SCD, and 80.6% (95% CI: 72.7%-88.4%) for SCD vs. NC. Conclusion The developed screening method based on resting-state prefrontal FC measured by fNIRS and machine learning may help predict early-stage cognitive impairment.
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Affiliation(s)
- Zhengping Pu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Hongna Huang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Man Li
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Hongyan Li
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Xiaoyan Shen
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Qingfeng Wu
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Qin Ni
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Yong Lin
- Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China
| | - Donghong Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Wang Z, Zhang Y, Ma N, Qiao H, Xia M, Li D. Study on cognitive impairment evaluation based on photoelectric neural information. J Alzheimers Dis Rep 2025; 9:25424823251325537. [PMID: 40125335 PMCID: PMC11930469 DOI: 10.1177/25424823251325537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2025] [Accepted: 02/13/2025] [Indexed: 03/25/2025] Open
Abstract
Background Whether there is a cognitive load-dependent brain activation pattern in the pre-Alzheimer's disease phase is unknown. Multimodal system provides a powerful technical tool. Objective We evaluated brain activity patterns under different cognitive loads in patients with mild cognitive impairment. Methods Functional near-infrared spectroscopy signals and electroencephalography signals were acquired from the mild cognitive impairment group (MCI, n = 20) and the healthy control group (HC, n = 24) under four cognitive loads. We analyzed the respective brain activity features and performed correlation analyses. Results (1) During the encoding phase, both the left occipital (p cond = 0.05, p group < 0.01) and left temporal (p cond = 0.02, p group = 0.03) skewness condition effects and between-group effects were significant. (2) As the cognitive load increased, the clustering coefficients and local efficiencies were significantly lower for the HC group. (3) The left occipital and left temporal activation skewness in the MCI group were significantly correlated with left occipital electrical features, whereas the left occipital activation intensity and skewness were significantly correlated with left occipital electrical features in HC group. Conclusions The pattern of brain activity in MCI depends on cognitive load. Left occipital and left temporal may be important brain regions for evaluating MCI and need to be focused on in the future.
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Affiliation(s)
- Zehua Wang
- School of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Ye Zhang
- School of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Ning Ma
- School of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Huiting Qiao
- School of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Meiyun Xia
- Innovation Center for Medical Engineering &Engineering Medicine, Hangzhou International Innovation Institute, Beihang University, Hangzhou, China
| | - Deyu Li
- School of Biological Science and Medical Engineering, Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
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Ishii T, Narita N, Iwaki S, Kamiya K, Shimosaka M, Yamaguchi H, Uchida T, Kantake I, Shibutani K. Cross-modal representation of chewing food in posterior parietal and visual cortex. PLoS One 2024; 19:e0310513. [PMID: 39453981 PMCID: PMC11508057 DOI: 10.1371/journal.pone.0310513] [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: 12/20/2023] [Accepted: 09/03/2024] [Indexed: 10/27/2024] Open
Abstract
Even though the oral cavity is not visible, food chewing can be performed without damaging the tongue, oral mucosa, or other intraoral parts, with cross-modal perception of chewing possibly critical for appropriate recognition of its performance. This study was conducted to clarify the relationship of chewing food cross-modal perception with cortex activities based on examinations of the posterior parietal cortex (PPC) and visual cortex during chewing in comparison with sham chewing without food, imaginary chewing, and rest using functional near-infrared spectroscopy. Additionally, the effects of a deafferent tongue dorsum on PPC/visual cortex activities during chewing performance were examined. The results showed that chewing food increased activity in the PPC/visual cortex as compared with imaginary chewing, sham chewing without food, and rest. Nevertheless, those activities were not significantly different during imaginary chewing or sham chewing without food as compared with rest. Moreover, subjects with a deafferent tongue dorsum showed reduced PPC/visual cortex activities during chewing food performance. These findings suggest that chewing of food involves cross-modal recognition, while an oral somatosensory deficit may modulate such cross-modal activities.
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Affiliation(s)
- Tomohiro Ishii
- Department of Removable Prosthodontics and Geriatric Oral Health, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
| | - Noriyuki Narita
- Research Institute of Oral Science, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
| | - Sunao Iwaki
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Kazunobu Kamiya
- Research Institute of Oral Science, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
| | - Michiharu Shimosaka
- Department of Anesthesiology, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
| | - Hidenori Yamaguchi
- Department of Anesthesiology, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
| | | | | | - Koh Shibutani
- Department of Anesthesiology, Nihon University School of Dentistry at Matsudo, Matsudo, Chiba, Japan
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Wang S, Wang W, Chen J, Yu X. Alterations in brain functional connectivity in patients with mild cognitive impairment: A systematic review and meta-analysis of functional near-infrared spectroscopy studies. Brain Behav 2024; 14:e3414. [PMID: 38616330 PMCID: PMC11016629 DOI: 10.1002/brb3.3414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 04/16/2024] Open
Abstract
Emerging evidences suggest that cognitive deficits in individuals with mild cognitive impairment (MCI) are associated with disruptions in brain functional connectivity (FC). This systematic review and meta-analysis aimed to comprehensively evaluate alterations in FC between MCI individuals and healthy control (HC) using functional near-infrared spectroscopy (fNIRS). Thirteen studies were included in qualitative analysis, with two studies synthesized for quantitative meta-analysis. Overall, MCI patients exhibited reduced resting-state FC, predominantly in the prefrontal, parietal, and occipital cortex. Meta-analysis of two studies revealed a significant reduction in resting-state FC from the right prefrontal to right occipital cortex (standardized mean difference [SMD] = -.56; p < .001), left prefrontal to left occipital cortex (SMD = -.68; p < .001), and right prefrontal to left occipital cortex (SMD = -.53; p < .001) in MCI patients compared to HC. During naming animal-walking task, MCI patients exhibited enhanced FC in the prefrontal, motor, and occipital cortex, whereas a decrease in FC was observed in the right prefrontal to left prefrontal cortex during calculating-walking task. In working memory tasks, MCI predominantly showed increased FC in the medial and left prefrontal cortex. However, a decreased in prefrontal FC and a shifted in distribution from the left to the right prefrontal cortex were noted in MCI patients during a verbal frequency task. In conclusion, fNIRS effectively identified abnormalities in FC between MCI and HC, indicating disrupted FC as potential markers for the early detection of MCI. Future studies should investigate the use of task- and region-specific FC alterations as a sensitive biomarker for MCI.
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Affiliation(s)
- Shuangyan Wang
- Department of Geriatric Neurology, Guangzhou First People's HospitalThe Second Affiliated Hospital of South China University of TechnologyGuangzhouGuangdongChina
| | - Weijia Wang
- Department of LibrarySun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Jinglong Chen
- Department of Geriatric Neurology, Guangzhou First People's HospitalThe Second Affiliated Hospital of South China University of TechnologyGuangzhouGuangdongChina
| | - Xiaoqi Yu
- Department of Geriatric Neurology, Guangzhou First People's HospitalThe Second Affiliated Hospital of South China University of TechnologyGuangzhouGuangdongChina
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Mingming Z, Wenhong C, Xiaoying M, Yang J, Liu HH, Lingli S, Hongwu M, Zhirong J. Abnormal prefrontal functional network in adult obstructive sleep apnea: A resting-state fNIRS study. J Sleep Res 2024; 33:e14033. [PMID: 37723923 DOI: 10.1111/jsr.14033] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 08/13/2023] [Accepted: 08/16/2023] [Indexed: 09/20/2023]
Abstract
To assess prefrontal brain network abnormality in adults with obstructive sleep apnea (OSA), resting-state functional near infrared spectroscopy (rs-fNIRS) was used to evaluate 52 subjects, including 27 with OSA and 25 healthy controls (HC). The study found that patients with OSA had a decreased connection edge number, particularly in the connection between the right medial frontal cortex (MFG-R) and other right-hemisphere regions. Graph-based analysis also revealed that patients with OSA had a lower global efficiency, local efficiency, and clustering coefficient than the HC group. Additionally, the study found a significant positive correlation between the Montreal Cognitive Assessment (MoCA) score and both the connection edge number and the graph-based indicators in patients with OSA. These preliminary results suggest that prefrontal rs-fNIRS could be a useful tool for objectively and quantitatively assessing cognitive function impairment in patients with OSA.
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Affiliation(s)
- Zhao Mingming
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Chen Wenhong
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Mo Xiaoying
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Jianrong Yang
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Howe Hao Liu
- Physical Therapy Department, Allen College, Waterloo, Lowa, USA
| | - Shi Lingli
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Ma Hongwu
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
| | - Jiang Zhirong
- Department of Sleep Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, Nan Ning, China
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Zhang M, Qu Y, Li Q, Gu C, Zhang L, Chen H, Ding M, Zhang T, Zhen R, An H. Correlation Between Prefrontal Functional Connectivity and the Degree of Cognitive Impairment in Alzheimer's Disease: A Functional Near-Infrared Spectroscopy Study. J Alzheimers Dis 2024; 98:1287-1300. [PMID: 38517784 DOI: 10.3233/jad-230648] [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] [Indexed: 03/24/2024]
Abstract
Background The development of Alzheimer's disease (AD) can be divided into subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia. Early recognition of pre-AD stages may slow the progression of dementia. Objective This study aimed to explore functional connectivity (FC) changes of the brain prefrontal cortex (PFC) in AD continuum using functional near-infrared spectroscopy (fNIRS), and to analyze its correlation with cognitive function. Methods All participants underwent 48-channel fNIRS at resting-state. Based on Brodmann partitioning, the PFC was divided into eight subregions. The NIRSIT Analysis Tool (v3.7.5) was used to analyze mean ΔHbO2 and FC. Spearman correlation analysis was used to examine associations between FC and cognitive function. Results Compared with HC group, the mean ΔHbO2 and FC were different between multiple subregions in the AD continuum. Both mean ΔHbO2 in the left dorsolateral PFC and average FC decreased sequentially from SCD to MCI to AD groups. Additionally, seven pairs of subregions differed in FC among the three groups: the differences between the MCI and SCD groups were in heterotopic connectivity; the differences between the AD and SCD groups were in left intrahemispheric and homotopic connectivity; whereas the MCI and AD groups differed only in homotopic connectivity. Spearman correlation results showed that FCs were positively correlated with cognitive function. Conclusions These results suggest that the left dorsolateral PFC may be the key cortical impairment in AD. Furthermore, there are different resting-state prefrontal network patterns in AD continuum, and the degree of cognitive impairment is positively correlated with reduced FC strength.
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Affiliation(s)
- Mengxue Zhang
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yanjie Qu
- Department of Traditional Chinese Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qian Li
- Department of Traditional Chinese Medicine, Changqiao Street Community Health Service Center of Xuhui District, Shanghai, China
| | - Chao Gu
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Limin Zhang
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hongxu Chen
- Cardiff University Brain Research Imaging Center, Cardiff University, Wales, UK
| | - Minrui Ding
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Tong Zhang
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Rongrong Zhen
- Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hongmei An
- Department of Science and Technology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Butters E, Srinivasan S, O'Brien JT, Su L, Bale G. A promising tool to explore functional impairment in neurodegeneration: A systematic review of near-infrared spectroscopy in dementia. Ageing Res Rev 2023; 90:101992. [PMID: 37356550 DOI: 10.1016/j.arr.2023.101992] [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: 04/07/2023] [Revised: 06/15/2023] [Accepted: 06/22/2023] [Indexed: 06/27/2023]
Abstract
This systematic review aimed to evaluate previous studies which used near-infrared spectroscopy (NIRS) in dementia given its suitability as a diagnostic and investigative tool in this population. From 800 identified records which used NIRS in dementia and prodromal stages, 88 studies were evaluated which employed a range of tasks testing memory (29), word retrieval (24), motor (8) and visuo-spatial function (4), and which explored the resting state (32). Across these domains, dementia exhibited blunted haemodynamic responses, often localised to frontal regions of interest, and a lack of task-appropriate frontal lateralisation. Prodromal stages, such as mild cognitive impairment, revealed mixed results. Reduced cognitive performance accompanied by either diminished functional responses or hyperactivity was identified, the latter suggesting a compensatory response not present at the dementia stage. Despite clear evidence of alterations in brain oxygenation in dementia and prodromal stages, a consensus as to the nature of these changes is difficult to reach. This is likely partially due to the lack of standardisation in optical techniques and processing methods for the application of NIRS to dementia. Further studies are required exploring more naturalistic settings and a wider range of dementia subtypes.
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Affiliation(s)
- Emilia Butters
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK; Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Sruthi Srinivasan
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Neuroscience, University of Sheffield, 385a Glossop Rd, Broomhall, Sheffield S10 2HQ, UK
| | - Gemma Bale
- Department of Physics, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0FA, UK
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Mei X, Zou CJ, Hu J, Liu XL, Zheng CY, Zhou DS. Functional near-infrared spectroscopy in elderly patients with four types of dementia. World J Psychiatry 2023; 13:203-214. [PMID: 37303929 PMCID: PMC10251357 DOI: 10.5498/wjp.v13.i5.203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 03/02/2023] [Accepted: 04/04/2023] [Indexed: 05/19/2023] Open
Abstract
BACKGROUND Functional near-infrared spectroscopy (fNIRS) is commonly used to study human brain function by measuring the hemodynamic signals originating from cortical activation and provides a new noninvasive detection method for identifying dementia.
AIM To investigate the fNIRS imaging technique and its clinical application in differential diagnosis of subtype dementias including frontotemporal lobe dementia, Lewy body dementia, Parkinson’s disease dementia (PDD) and Alzheimer’s disease (AD).
METHODS Four patients with different types of dementia were examined with fNIRS during two tasks and a resting state. We adopted the verbal fluency task, working memory task and resting state task. Each patient was compared on the same task. We conducted and analyzed the fNIRS data using a general linear model and Pearson’s correlation analysis.
RESULTS Compared with other types of dementias, fNIRS showed the left frontotemporal and prefrontal lobes to be poorly activated during the verbal fluency task in frontotemporal dementia. In Lewy body dementia, severe asymmetry of prefrontal lobes appeared during both verbal fluency and working memory tasks, and the patient had low functional connectivity during a resting state. In PDD, the patient’s prefrontal cortex showed lower excitability than the temporal lobe during the verbal fluency task, while the prefrontal cortex showed higher excitability during the working memory task. The patient with AD showed poor prefrontal and temporal activation during the working memory task, and more activation of frontopolar instead of the dorsolateral prefrontal cortex.
CONCLUSION Different hemodynamic characteristics of four types of dementia (as seen by fNIRS imaging) provides evidence that fNIRS can serve as a potential tool for the diagnosis between dementia subtypes.
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Affiliation(s)
- Xi Mei
- Key Lab, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
| | - Chen-Jun Zou
- Department of Geriatric, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
| | - Jun Hu
- Department of Geriatric, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
| | - Xiao-Li Liu
- Key Lab, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
| | - Cheng-Ying Zheng
- Department of Geriatric, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
| | - Dong-Sheng Zhou
- Key Lab, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
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Zou J, Yin Y, Lin Z, Gong Y. The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study. Front Neurosci 2023; 17:1168773. [PMID: 37214384 PMCID: PMC10196111 DOI: 10.3389/fnins.2023.1168773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 04/18/2023] [Indexed: 05/24/2023] Open
Abstract
Background Post-stroke cognitive impairment (PSCI) is a considerable risk factor for developing dementia and reoccurrence of stroke. Understanding the neural mechanisms of cognitive impairment after stroke can facilitate early identification and intervention. Objectives Using functional near-infrared spectroscopy (fNRIS), the present study aimed to examine whether resting-state functional connectivity (FC) of brain networks differs in patients with PSCI, patients with Non-PSCI (NPSCI), and healthy controls (HCs), and whether these features could be used for clinical diagnosis of PSCI. Methods The present study recruited 16 HCs and 32 post-stroke patients. Based on the diagnostic criteria of PSCI, post-stroke patients were divided to the PSCI or NPSCI group. All participants underwent a 6-min resting-state fNRIS test to measure the hemodynamic responses from regions of interests (ROIs) that were primarily distributed in the prefrontal, somatosensory, and motor cortices. Results The results showed that, when compared to the HC group, the PSCI group exhibited significantly decreased interhemispheric FC and intra-right hemispheric FC. ROI analyses showed significantly decreased FC among the regions of somatosensory cortex, dorsolateral prefrontal cortex, and medial prefrontal cortex for the PSCI group than for the HC group. However, no significant difference was found in the FC between the PSCI and the NPSCI groups. Conclusion Our findings provide evidence for compromised interhemispheric and intra-right hemispheric functional connectivity in patients with PSCI, suggesting that fNIRS is a promising approach to investigate the effects of stroke on functional connectivity of brain networks.
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Affiliation(s)
- Jiahuan Zou
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu,Sichuan, China
| | - Yongyan Yin
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu,Sichuan, China
| | - Zhenfang Lin
- Department of Neurology, Sichuan Bayi Rehabilitation Center (Sichuan Provincial Rehabilitation Hospital), Chengdu, Sichuan, China
| | - Yulai Gong
- Department of Neurology, Sichuan Bayi Rehabilitation Center (Sichuan Provincial Rehabilitation Hospital), Chengdu, Sichuan, China
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