Refined prefrontal working memory network as a neuromarker for Alzheimer's disease

An fNIRS-based investigation of cerebral hemodynamic responses during verbal fluency task and n-back task in individuals with mild cognitive impairment

Background

Early detection of mild cognitive impairment (MCI) is crucial for preventing Alzheimer's disease (AD). This study aims to explore alterations in brain co-functional connectivity between cognitively healthy individuals and those with cognitive impairment during a verbal fluency task (VFT) using functional near-infrared spectroscopy (fNIRS). The investigation examines changes in brain activation patterns in both MCI patients and healthy controls during the VFT and 1-back task, and identifies correlations between cognitive function and brain activation areas using fNIRS technology.

Methods

This study evaluated markers for screening MCI by performing the VFT and 1-back task using a 67-channel fNIRS to measure changes in oxyhemoglobin (HbO) levels in the bilateral prefrontal and temporal lobes of 108 healthy controls (HC) and 103 participants with MCI. The severity of patients' symptoms was assessed using the Montreal Cognitive Assessment (MoCA) scale, neuropsychiatric symptoms were evaluated with the Symptom Checklist-90 (SCL-90), and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI).

Results

Compared with the HC group, the MCI group showed a significant reduction in MoCA scores, with no significant differences in education level, PSQI, and SCL-90 scores. There was no significant difference in brain activation levels between the MCI and HC groups during the VFT. However, during the 1-back task, the MCI group exhibited significantly reduced activation levels in channels 33, 54, 49, and 47, as well as in the dorsolateral prefrontal cortex (DLPFC) and frontal eye fields (FEF). Moreover, the mean HbO levels in these channels, DLPFC, and FEF during the 1-back task were found to be significantly correlated with MoCA scores.

Discussion

When performing the VFT and 1-back task, our study found that patients with MCI exhibited reduced brain activity levels in the DLPFC and FEF only during the 1-back task. This diminished task-induced brain activity was significantly positively correlated with MoCA scores and was less influenced by mental health and sleep quality. The 1-back task may be a more optimal paradigm for the early detection of MCI compared to the VFT.

Identification of functional near-infrared spectroscopy for older adults with mild cognitive impairment: a systematic review

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.

Acute ketone monoester supplementation in young adults: modulating metabolic and neurocognitive functions across body weights

This study investigated the acute effects of ketone monoester on metabolic and neurocognitive indicators and underlying metabolism-brain-cognition interactions among young adults of healthy weight (HW) and those with overweight/obesity (OW). Forty participants were divided into two groups: HW (n = 20, age 23.80 ± 3.96 years, body mass index (BMI) 21.49 ± 1.80 kg/m2) and OW (n = 20, age 22.00 ± 2.13 years, BMI 28.23 ± 3.48 kg/m2). Each participant completed two trials (ketone monoester vs. placebo, 395 mg/kg dose) in a randomized order. Metabolic indicators (blood beta-hydroxybutyrate (BHB) and glucose) and neurocognitive function (causal density via functional near-infrared spectroscopy and cognitive interference via the Stroop task) were measured at baseline, 30 min, and 90 min post-supplementation. A chain mediation model was constructed to test the indirect effects of BHB level on cognitive interference through mediators like blood glucose and causal density. In the linear mixed models, significant effects were observed for trial (β = -0.92, 0.20, -0.04, 25.53) and assessment time (β = 0.50, -0.14, 0.09, -62.88) in BHB, glucose, causal density, and cognitive interference (p < 0.05), but not for group factors. Compared to OW, the effects of ketone monoester on prefrontal connectomes were more enduring in the HW (p < 0.05). Elevated BHB level improved cognitive function through decreasing glucose level and increasing causal density, with an estimate of -0.63. Acute ketone monoester supplementation elevated levels of blood BHB and prefrontal connectomes and decreased levels of glucose and cognitive interference, regardless of weight status. Elevated blood BHB enhanced cognitive function through multi-tiered neurometabolic pathways. Clinical trial registration: ClinicalTrials.gov (ID: NCT06368297).

Diagnostic machine learning applications on clinical populations using functional near infrared spectroscopy: a review

Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n = 12), attention deficit and hyperactivity disorder (n = 7), and autism spectrum disorder (n = 6) are the most studied populations. There is a significant negative correlation between sample size (>21) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Concentration changes in oxy-hemoglobin (ΔHbO) based features were used more than concentration changes in deoxy-hemoglobin (ΔHb) based ones and the most popular ΔHbO-based features were mean ΔHbO (n = 11) and ΔHbO-based functional connections (n = 11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification.

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

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.

Hotspots and trends in fNIRS disease research: A bibliometric analysis

OBJECTIVE

To summarize the general information and hotspots of functional near-infrared spectroscopy (fNIRS)-based clinical disease research over the past 10 years and provide some references for future research.

METHODS

The related literature published between 1 January 2011 and 31 January 2022 was retrieved from the Web of Science core database (WoS). Bibliometric visualization analysis of countries/regions, institutions, authors, journals, keywords and references were conducted by using CiteSpace 6.1.R3.

RESULTS

A total of 467 articles were included, and the annual number of articles published over nearly a decade showed an upward trend year-by-year. These articles mainly come from 39 countries/regions and 280 institutions. The representative country and institution were the USA and the University of Tubingen. We identified 266 authors, among which Andreas J Fallgatter and Ann-Christine Ehlis were the influential authors. Neuroimage was the most co-cited journal. The major topics in fNIRS disease research included activation, prefrontal cortex, working memory, cortex, and functional magnetic resonance imaging (fMRI). In recent years, the Frontier topics were executive function, functional connectivity, performance, diagnosis, Alzheimer's disease, children, and adolescents. Based on the burst of co-cited references, gait research has received much attention.

CONCLUSION

This study conducted a comprehensive, objective, and visual analysis of publications, and revealed the status of relevant studies, hot topics, and trends concerning fNIRS disease research from 2011 to 2022. It is hoped that this work would help researchers to identify new perspectives on potential collaborators, important topics, and research Frontiers.

Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy

INTRODUCTION

Alzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million new cases every year. There is a need for relatively less costly and more objective methods of screening and early diagnosis.

METHODS

Functional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD. For a practical clinically relevant system, a smaller number of optimally placed channels are clearly preferable. In this study, we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations. Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study.

RESULTS

We have shown that resting-state fNIRS recordings from a small number of prefrontal locations provide a promising methodology for detecting AD and monitoring its progression. A high-density continuous-wave fNIRS system was first used to verify the relatively lower hemodynamic activity in the prefrontal cortical areas observed in patients with AD. By using the episode averaged standard deviation of the oxyhemoglobin concentration changes as features that were fed into a Support Vector Machine; we then showed that the accuracy of subsets of optical channels in predicting the presence and severity of AD was significantly above chance. The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score with ≤5 channels.

DISCUSSION

These scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression.