Resting-state functional near-infrared spectroscopy in neurodegenerative diseases – A systematic review

NeuroImage Clinical, Год журнала: 2025, Номер 45, С. 103733 - 103733

Опубликована: Янв. 1, 2025

To systematically review and summarize alterations found in resting-state activity as measured via functional near-infrared spectroscopy (fNIRS) neurodegenerative diseases. fNIRS is a novel emerging neuroimaging method suitable for variety of study designs. Resting-state the measure brain absence task, which has been investigated yielding information about diseases, mainly using magnetic resonance imaging. We aimed to usage (rsfNIRS) Studies investigating people diagnosed with disease obtained at least two channels. searched three databases publications. After screening, 16 studies were included systematic review. The quality was assessed, data extracted. Data qualitatively synthesized case 10 similar studies, meta-analysis planned. Most Mild cognitive impairment (50%), followed by Alzheimer's (25%). Other diseases encompassed Parkinson's disease, Multiple sclerosis, Amyotrophic lateral sclerosis. All reported oxygenated hemoglobin. Still, heterogeneous terms design, measurement duration, device, montage, pre-processing, analyses. A not considered possible due this heterogeneity. rsfNIRS shows promise most have observed when compared healthy controls. However, inconsistencies across limit comparison meta-analysis. Hence, we strongly advocate application reporting guidelines establishment rsfNIRS-specific guidelines. This will ensure reliable comparable results future research.

Язык: Английский

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A promising tool to explore functional impairment in neurodegeneration: A systematic review of near-infrared spectroscopy in dementia.

Ageing Research Reviews, Год журнала: 2023, Номер 90, С. 101992 - 101992

Опубликована: Июнь 24, 2023

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 this population. From 800 identified records NIRS prodromal stages, 88 were evaluated employed range of tasks testing memory (29), word retrieval (24), motor (8) visuo-spatial function (4), explored the resting state (32). Across these domains, exhibited blunted haemodynamic responses, often localised frontal regions interest, lack task-appropriate lateralisation. Prodromal such mild cognitive impairment, revealed mixed results. Reduced performance accompanied by either diminished functional responses or hyperactivity was identified, latter suggesting compensatory response not present at stage. Despite clear evidence alterations brain oxygenation consensus nature changes is difficult reach. likely partially due standardisation optical techniques processing methods for application dementia. Further are required exploring more naturalistic settings wider subtypes.

Язык: Английский

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Alterations in brain functional connectivity in patients with mild cognitive impairment: A systematic review and meta‐analysis of functional near‐infrared spectroscopy studies

Brain and Behavior, Год журнала: 2024, Номер 14(4)

Опубликована: Апрель 1, 2024

Abstract Emerging evidences suggest that cognitive deficits in individuals with mild impairment (MCI) are associated disruptions brain functional connectivity (FC). This systematic review and meta‐analysis aimed to comprehensively evaluate alterations FC between MCI healthy control (HC) using near‐infrared spectroscopy (fNIRS). Thirteen studies were included qualitative analysis, two synthesized for quantitative meta‐analysis. Overall, patients exhibited reduced resting‐state FC, predominantly the prefrontal, parietal, occipital cortex. Meta‐analysis of revealed a significant reduction from right prefrontal cortex (standardized mean difference [SMD] = −.56; p < .001), left (SMD −.68; −.53; .001) compared HC. During naming animal‐walking task, enhanced motor, cortex, whereas decrease was observed during calculating‐walking task. In working memory tasks, showed increased medial However, decreased shifted distribution noted verbal frequency conclusion, fNIRS effectively identified abnormalities HC, indicating disrupted as potential markers early detection MCI. Future should investigate use task‐ region‐specific sensitive biomarker

Язык: Английский

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Correlation Between Prefrontal Functional Connectivity and the Degree of Cognitive Impairment in Alzheimer’s Disease: A Functional Near-Infrared Spectroscopy Study

Journal of Alzheimer s Disease, Год журнала: 2024, Номер 98(4), С. 1287 - 1300

Опубликована: Март 22, 2024

Background: The development of Alzheimer’s disease (AD) can be divided into subjective cognitive decline (SCD), mild impairment (MCI), and dementia. Early recognition pre-AD stages may slow the progression Objective: This study aimed to explore functional connectivity (FC) changes brain prefrontal cortex (PFC) in AD continuum using near-infrared spectroscopy (fNIRS), analyze its correlation with function. Methods: All participants underwent 48-channel fNIRS at resting-state. Based on Brodmann partitioning, PFC was eight subregions. NIRSIT Analysis Tool (v3.7.5) used mean ΔHbO2 FC. Spearman analysis examine associations between FC Results: Compared HC group, were different multiple subregions continuum. Both left dorsolateral average decreased sequentially from SCD MCI groups. Additionally, seven pairs differed among three groups: differences groups heterotopic connectivity; intrahemispheric homotopic whereas only connectivity. results showed that FCs positively correlated Conclusions: These suggest key cortical AD. Furthermore, there are resting-state network patterns continuum, degree is reduced strength.

Язык: Английский

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An fNIRS representation and fNIRS-scales multimodal fusion method for auxiliary diagnosis of amnestic mild cognitive impairment

Biomedical Signal Processing and Control, Год журнала: 2024, Номер 96, С. 106646 - 106646

Опубликована: Июль 18, 2024

Amnestic mild cognitive impairment (aMCI) is the prodromal period of more serious neurodegenerative diseases (e.g., Alzheimer's disease), characterized by declines in memory and thinking abilities. Auxiliary assessment early diagnosis aMCI are crucial preventing continued deterioration abilities; nevertheless, this task poses a formidable challenge due to inconspicuous nature symptoms. Functional near-infrared spectroscopy (fNIRS) non-invasive, low-cost, user-friendly neuroimaging technique, which capable detecting subtle changes brain activity among different subjects. Moreover, multimodal fusion can assess cognition status from perspectives enhance auxiliary accuracy significantly. This paper proposes an fNIRS representation fNIRS-scales method for aMCI. Specifically, we convert one-dimensional time-series signals into two-dimensional images with Gramian Angular Field achieve end-to-end convolutional neural network. Then, integrate extracted features scales at decision-making level improve aMCI, employing data balance strategy prevent biased prediction. What more, based on features, also propose data-driven scales-screening help physician higher efficiency. We conducted experiments 86 subjects (including 53 patients 33 normal controls) recruited Foshan First People's Hospital. The reaches 88.02% 93.90% further fusion, respectively. With scales-screening, delete 50% scales, reducing test time but only losing 2.54% accuracy.

Язык: Английский

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The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study

Frontiers in Neuroscience, Год журнала: 2023, Номер 17

Опубликована: Май 5, 2023

Post-stroke cognitive impairment (PSCI) is a considerable risk factor for developing dementia and reoccurrence of stroke. Understanding the neural mechanisms after stroke can facilitate early identification intervention.Using functional near-infrared spectroscopy (fNRIS), present study aimed to examine whether resting-state connectivity (FC) brain networks differs in patients with PSCI, Non-PSCI (NPSCI), healthy controls (HCs), these features could be used clinical diagnosis PSCI.The recruited 16 HCs 32 post-stroke patients. Based on diagnostic criteria were divided PSCI or NPSCI group. All participants underwent 6-min fNRIS test measure hemodynamic responses from regions interests (ROIs) that primarily distributed prefrontal, somatosensory, motor cortices.The results showed that, when compared HC group, group exhibited significantly decreased interhemispheric FC intra-right hemispheric FC. ROI analyses among somatosensory cortex, dorsolateral prefrontal medial cortex than However, no significant difference was found between groups.Our findings provide evidence compromised suggesting fNIRS promising approach investigate effects networks.

Язык: Английский

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An exploration of distinguishing subjective cognitive decline and mild cognitive impairment based on resting-state prefrontal functional connectivity assessed by functional near-infrared spectroscopy

Frontiers in Aging Neuroscience, Год журнала: 2025, Номер 16

Опубликована: Янв. 8, 2025

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 decline (SCD) mild impairment (MCI) based on resting-state prefrontal FC neuropsychological tests via machine learning. data measured by were collected from 55 normal controls (NCs), 80 SCD individuals, 111 MCI individuals. Differences analyzed among the groups. strength test scores extracted as features build classification predictive models through Model performance was assessed accuracy, specificity, sensitivity, area under curve (AUC) with 95% confidence interval (CI) values. Statistical analysis revealed trend toward compensatory enhanced The showed satisfactory ability differentiate three groups, especially those employing linear discriminant analysis, logistic regression, support vector machine. Accuracies of 94.9% vs. NC, 79.4% SCD, 77.0% NC achieved, highest AUC values 97.5% (95% CI: 95.0%-100.0%) 83.7% 77.5%-89.8%) 80.6% 72.7%-88.4%) NC. developed learning may help predict early-stage impairment.

Язык: Английский

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Alterations in brain function in patients with post-stroke cognitive impairment: a resting-state functional magnetic resonance imaging study

Frontiers in Aging Neuroscience, Год журнала: 2025, Номер 17

Опубликована: Фев. 19, 2025

Cognitive impairment is a common dysfunction following stroke, significantly affecting patients' quality of life. Studies suggest that post-stroke cognitive (PSCI) may be related to neural activity in specific brain regions. However, the mechanisms remain further explored. This study aimed investigate alterations function patients with PSCI. was case-control study. Thirty PSCI, thirty non-PSCI (NPSCI), and age- gender-matched healthy controls (HCs) were selected 1:1:1 ratio. Resting-state functional magnetic resonance imaging (rs-fMRI) acquired from all participants potential PSCI by comparing differences fractional amplitude low-frequency fluctuation (fALFF), Kendall's coefficient concordance-regional homogeneity (KCC-ReHo), seed-based connectivity (FC). Additionally, Montreal Assessment (MoCA) scores collected, Pearson correlation used analyze between indicators performance patients. fALFF analysis revealed group had decreased zfALFF values left caudate, right inferior temporal gyrus (ITG), anterior cingulate cortex (ACC), putamen, superior gyrus. In contrast, increased observed Cerebellum_6. KCC-ReHo indicated SzKCC-ReHo middle frontal (MFG) postcentral lobe, while cerebellum_ crus 1, cerebellum_4-5. Furthermore, FC zFC regions group, especially angular precuneus. showed value ACC positively correlated MoCA group. demonstrated significant changes spontaneous intensity, regional homogeneity, multiple cognition-related patients, shedding light on underlying

Язык: Английский

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Resting-State Brain Network Characteristics Related to Mild Cognitive Impairment: A Preliminary fNIRS Proof-of-Concept Study

Journal of Integrative Neuroscience, Год журнала: 2025, Номер 24(2)

Опубликована: Янв. 25, 2025

Background: This study investigates the reliability of functional near-infrared spectroscopy (fNIRS) in detecting resting-state brain network characteristics patients with mild cognitive impairment (MCI), focusing on static connectivity (sRSFC) and dynamic (dRSFC) patterns MCI healthy controls (HCs) without impairment. Methods: A total 89 83 HCs were characterized using neuropsychological scales. Subject sRSFC strength dRSFC variability coefficients evaluated via fNIRS. The feasibility fNIRS to measure these metrics compared between two groups. Correlations Montreal Cognitive Assessment (MoCA) scores also explored. Results: homologous networks was significantly lower than heterologous (p < 0.05). significant negative correlation observed at both group individual levels 0.001). While did not differentiate HCs, dorsal attention (DAN) default mode (DMN), ventral (VAN) visual (VIS), emerged as sensitive biomarkers after false discovery rate correction No found MoCA measures. Conclusions: can be used networks, being more for discriminating HCs. DAN-DMN VAN-VIS regions particularly useful identification differences Clinical Trial Registration: ChiCTR2200057281, registered 6 March, 2022; https://www.chictr.org.cn/showproj.html?proj=133808.

Язык: Английский

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Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study

NeuroImage, Год журнала: 2025, Номер unknown, С. 121130 - 121130

Опубликована: Март 1, 2025

Subjective cognitive decline (SCD) and mild impairment (MCI) carry the risk of progression to dementia, accurate screening methods for these conditions are urgently needed. Studies have suggested potential ability functional near-infrared spectroscopy (fNIRS) identify MCI SCD. The present fNIRS study aimed develop an early method SCD based on activated prefrontal connectivity (FC) during performance scales subject-wise cross-validation via machine learning. Activated FC data measured by were collected from 55 normal controls, 80 patients, 111 patients. Differences in analyzed among groups, strength scale extracted as features build classification predictive models through Model was assessed accuracy, specificity, sensitivity, area under curve (AUC) with 95% confidence interval (CI) values. Statistical analysis revealed a trend toward more impaired declining function. Prediction built combining applying learning models, showed generally satisfactory abilities differentiate three especially those employing linear discriminant analysis, logistic regression, support vector machine. Accuracies 92.0% vs. NC, 80.0% SCD, 76.1% NC achieved, highest AUC values 97.0% (95% CI: 94.6%-99.3%) 87.0% 81.5%-92.5%) 79.2% 71.0%-87.3%) NC. developed has predict early-stage scale-induced activation.

Язык: Английский

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