https://scholar.gist.ac.kr/handle/local/7980 Fri, 14 Aug 2026 03:21:41 GMT 2026-08-14T03:21:41Z https://scholar.gist.ac.kr/handle/local/31973 Title: Toward Early Alzheimer’s Disease Diagnosis: Development of an Integrated EEG-fNIRS System and EEG-Based Evaluation of P300 Latency as a Physiological Marker Author(s): Manal Mustafa Mohamedali Mohamed Abstract: The primary focus of this dissertation is the neurophysiological analysis of event-related potentials (ERPs), with particular emphasis on P300 latency, to identify reliable biomarkers for the early detection of Alzheimer’s Disease (AD). By investigating electrophysiological signals associated with early cognitive decline, this research aims to distinguish the preclinical stages of AD. Based on the analytical requirements and insights derived from this investigation, we subsequently developed and validated a novel multimodal brain monitoring system that integrates electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to enhance detection sensitivity and spatial resolution. Chapter 1 presents a comprehensive overview of Alzheimer’s Disease (AD), beginning with the increasing global burden of the disease and the pressing need for early detection during its asymptomatic and prodromal AD stages. It outlines the clinical progression of AD, from healthy aging through the preclinical and mild cognitive impairment phases to overt dementia, highlighting key pathological hallmarks such as amyloid-beta accumulation, tau neurofibrillary tangles, neuroinflammation, synaptic dysfunction, and structural and functional brain alterations. The chapter critically evaluates existing diagnostic approaches, including the AT(N) framework and other biomarker-based criteria, while emphasizing the limitations of conventional neuroimaging and cerebrospinal fluid analyses in early-stage detection due to their invasiveness, cost, and limited accessibility. As a response, it introduces electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) as non-invasive, cost-effective alternatives capable of capturing complementary neurophysiological information. Special focus is placed on the event-related P300 component, elicited via the oddball paradigm, due to its sensitivity to attention and working memory processes that are often compromised early in the AD continuum. This rationale supports the need for integrated, time-efficient, and scalable brain monitoring tools that can serve as early biomarkers and enhance both clinical screening and public health intervention strategies. Chapter 2 investigates P300 ERP indices—specifically peak latency and amplitude—as potential biomarkers for distinguishing between healthy controls (HC), individuals with asymptomatic AD (AAD), and those with prodromal AD (PAD). EEG data were collected during a visual oddball task from 79 participants. Findings reveal that P300 peak latency, but not amplitude, significantly differentiates PAD from both AAD and HC. Moreover, P300 latency correlates significantly with memory domain scores, reinforcing its role as a neurophysiological marker of early cognitive impairment. This chapter focuses exclusively on EEG-based analysis, as fNIRS-related investigations are being pursued by other research groups. The integration of EEG and fNIRS data remains a direction for future work. Chapter 3 extends the investigation to a larger cohort of 117 participants and explores the topographical distribution of P300 latency across the left, middle, and right brain regions. Results show that P300 latency from the left hemisphere distinguishes HC from AAD, while latency from all regions separates HC from PAD. Receiver Operating Characteristic (ROC) analyses confirm the diagnostic potential of P300 latency with favorable sensitivity and specificity, particularly in the left and middle regions. However, differentiation between AAD and PAD remains limited, suggesting a need for complementary multimodal or longitudinal approaches. Chapter 4 details the design and implementation of a portable, low-cost EEG/fNIRS brain function monitoring system. The system incorporates the ADS1298IPAG analog front-end and a Teensy 3.2 microcontroller, allowing for simultaneous acquisition of two-channel EEG and six-channel fNIRS signals. The system’s hardware, software, and graphical user interface (GUI) are described, and performance validation confirms its suitability for real-time, dual-modal brain monitoring. Chapter 5 concludes by summarizing the successful development of a low-cost, integrated EEG/fNIRS system and the identification of P300 latency as a viable physiological marker for early AD screening. This dissertation contributes a scalable, accessible neurodiagnostic platform that bridges engineering innovation with clinical neuroscience. Future directions include system miniaturization, the integration of EEG and fNIRS data for Alzheimer's Disease classification, the incorporation of machine learning models to enhance diagnostic accuracy, and validation across larger and more diverse populations. Together, this work advances biomedical engineering by delivering a novel brain monitoring solution that is both physiologically informative and practically applicable for early Alzheimer’s Disease detection. Tue, 31 Dec 2024 15:00:00 GMT https://scholar.gist.ac.kr/handle/local/31973 2024-12-31T15:00:00Z https://scholar.gist.ac.kr/handle/local/19818 Title: Therapeutic Effects of Auditory Stimulation at 40 Hz on Sleep Disturbances in an Alzheimer`s Disease Mouse Model: Focusing on the Role of Astrocytes Author(s): 박민철 Abstract: The sensory stimulation at 40 Hz showed therapeutic impacts on Alzheimer`s disease (AD). Previous studies reported that amyloid-beta (Aβ) accumulation and sleep disturbances in AD have positive feedback loop and impaired Ca2+ influx and volume transient in astrocytes. However, the role of astrocytes to sleep disturbances remains unknown. We hypothesized that 40-Hz auditory stimulation could ameliorate sleep disturbances by enhancing the astrocytic Ca2+ influx. We used 6-month-old 5xFAD as Alzheimer`s disease model. Two-hour daily 40-Hz auditory stimulation were applied for two-weeks. We recorded the 24-hour electroencephalographic (EEG) for sleep-wake analysis at pre- and post-stimulation day. Reactive astrocytes and GABA were measured using immunohistochemistry. Patch clamping recordings measured the tonic GABA currents of nNOS neurons. Using GCaMP6f and intrinsic optical singals were measured astrocytic Ca2+ and volume swelling. qRT-PCR measured the transcriptional levels. Our studiy demonstrated that repeated auditory steady state responses (rASSR) at 40 Hz mitigated Aβ pathology and sleep disturbances. We observed that astrocytic γ-aminobutyric acid (GABA) reduced inhibition on neuronal nitric oxide synthase (nNOS)-containing neurons, sleep-promoting cortical neurons, by rASSR. Additionally, rASSR enhanced neuronal activity-induced transient volume and Ca2+ influx in astrocytes, which subsequently decreased monoamine oxidase B (MAO-B) and increased nuclear factor erythroid 2-related factor 2 (Nrf2). Finally, optogenetic boosting of astrocytic Ca2+ influx using MonSTIM1 mimicked the therapeutic effects of the rASSR at 40 Hz. Our findings suggest that 40-Hz rASSR ameliorates Aβ pathology and sleep disturbances by neuron-astrocyte interaction. Tue, 31 Dec 2024 15:00:00 GMT https://scholar.gist.ac.kr/handle/local/19818 2024-12-31T15:00:00Z https://scholar.gist.ac.kr/handle/local/32668 Title: The utilization of a fNIRS system to investigate brain function under different cognitive conditions: from a single modal to a multimodal system Author(s): Thien Nguyen Thi Abstract: Since the first study on cerebral oxygenation in 1985, fNIRS system has been widely applied on various research areas, from the basic understanding of the brain to the complicated applications, and on various subjects, from infants to normal adults and to brain disorder elderly. Though fNIRS has been drawing attention from many people and thousands of papers related to this technique have been published, currently, it is still just being used in the research. The reason which makes fNIRS far away from being used in the clinic is that it has a low spatial resolution and it cannot measure deep brain signal. On the other hands, the low temporal resolution hampers its capability to be used in many real-life and online applications. However, fNIRS is simple, portable, and especially cost effective. Hence, further investigation on this technique may help to explore its appropriate applications in both the clinic and daily life. This work examines the potential of the fNIRS system as a single modal and also when combined with the EEG system to study the cognitive functions in different conditions and with different subject groups. Firstly, the single fNIRS system was used to identify the biomarker of the mild cognitive impairment (MCI) patients. Secondly, with the help of the EEG system, the fNIRS system was utilized to explore the cerebral functional connectivity in the rest and sleep states. Lastly, the fNIRS system was combined with the EEG system to find the physiological signals that can be used to predict driver drowsiness. In chapter 1, a brief description of fNIRS, the principle of this technique and how to calculate the cerebral hemodynamic responses from the measured light intensity, is introduced. In addition, current applications of this technique on the study of the cognitive functions are presented. In chapter 2, we examine the brain functional connectivity in both normal, healthy elders (HC) and mild cognitive impairment patients (MCI) to identify a typical feature to distinguish these two groups. A homemade four-channel fNIRS system is employed to measure the hemodynamic responses in the subjects’ prefrontal cortex during a resting state, an oddball task, a 1-back task, and a verbal fluency task. The brain connectivity is calculated as the Pearson correlation coefficients among fNIRS channels. The results reveal that MCI presents a significantly weaker connection in the inter-hemispheric connectivity than the left and right hemisphere connectivity. In addition, the connectivity in MCI exhibits a substantial decline along the performance time. Furthermore, comparison between MCI and HC connectivity establishes a statistically higher connection in the right hemisphere connectivity of MCI during the oddball task. These findings demonstrate potential of fNIRS as a promising avenue to study MCI brain functional connectivity. In chapter 3, we investigate the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases using a commercial LABNIRS system. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states. In chapter 4, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG, and NIRS signals have been measured during a simulated driving task, in which subjects underwent both awake and drowsy states. Heart rate, blinking rate, alpha band power, and eye closure were used to identify each subject’s condition. EEG band power and hemodynamic responses were investigated in the awake and drowsy states. The oxy-hemoglobin change and the beta band power in the frontal lobe were found to differ the most significantly between the two states. In addition, the time course of these two parameters correspond well to the awake-drowsy transition. As a result, the beta band power and oxy-hemoglobin concentration change were used to derive a drowsiness detection index, which enabled the combined EEG/NIRS system to predict drowsiness earlier than a camera based method. From our study, we found that the fNIRS system itself can provide adequate information to study the cognitive functions of the brain. However, the additional information from the EEG system helps to add up the functions that are currently not available to the fNIRS system such as the sleep stage verification and also it helps to increase the accuracy such as the classification accuracy. Mon, 31 Dec 2018 15:00:00 GMT https://scholar.gist.ac.kr/handle/local/32668 2018-12-31T15:00:00Z https://scholar.gist.ac.kr/handle/local/19833 Title: The roles of nutritional factors and gut-brain axis in the pathogenesis of psychiatric disorders: Implications on Alzheimer’s disease and ADHD Author(s): Jiseung Kang Abstract: This dissertation aims to investigate the potential links between metabolic dysregulation, the gut-brain axis, and neurodegenerative diseases. It comprises three chapters that focus on exploring the effects of vitamin D deficiency on Alzheimer's disease (AD) amyloidopathy and gliopathy, examining the impact of a high-fat diet (HFD) on dopaminergic dysregulation, REM sleep fragmentation, and attention-deficit hyperactivity disorder (ADHD)-like behaviors and the causal relationship between slow gut transition and AD pathology. In Chapter 1, I explored the role of vitamin D in AD pathology. Lower serum vitamin D levels have been associated with higher AD risk, but the underlying mechanisms remain unclear. My findings suggested that vitamin D plays a crucial role in modifying the course of AD by regulating amyloid pathology. Vitamin D deficiency led to an increase in brain amyloid-beta (Aβ) levels and changes in gene expression, while vitamin D supplementation reduced Aβ levels and improved memory function. Furthermore, I found that vitamin D deficiency exacerbated Aβ pathology and increased GABA-positive reactive astrocytes, whereas vitamin D supplementation ameliorated these effects. These results suggested that vitamin D could be a potential preventive and therapeutic nutritional approach for AD. In Chapter 2, I examined the effects of a high-fat diet (HFD) on dopaminergic dysregulation and behavioral deficits in male mice. The HFD group showed decreased ii wakefulness, fragmented REM sleep, ADHD-like behaviors, including anxiety, anhedonia, hyperactive-like behaviors, and impaired visuospatial memory. Additionally, the HFD group had decreased mRNA levels of dopamine-related genes in the brain regions of dopaminergic reward circuits. My findings suggest that HFD-induced behavioral deficits and disturbed REM sleep are associated with dysregulation of the dopaminergic system. Chapter 3 focused on the relationship between slow gut transition and AD pathology. Epidemiological studies have suggested a high prevalence of constipation in neurodegenerative disorders, including AD. My findings supported the notion that slow gut transition leads to a leaky gut, resulting in systemic inflammation and accelerated amyloidopathy. Importantly, this study also found that loperamide-induced slow gut transition caused memory impairment in wildtype mice. The study provided critical insights into the potential role of maintaining gut health in AD prevention and treatment. This dissertation investigated the links between metabolic dysregulation, the gut-brain axis, and neurodegenerative diseases, focusing on the effects of vitamin D deficiency, high-fat diets, and slow gut transition on various pathological aspects. The findings suggest that vitamin D plays a crucial role in modifying AD progression by regulating amyloid pathology and gliopathy, while high-fat diets lead to dopaminergic dysregulation, disturbed REM sleep, and ADHD-like behaviors. Additionally, the slow gut transition was found to exacerbate AD pathology through systemic inflammation and accelerated amyloidopathy. These results highlight the potential of nutritional interventions and maintaining gut health as preventive and therapeutic approaches for AD and other neurodegenerative disorders. Sat, 31 Dec 2022 15:00:00 GMT https://scholar.gist.ac.kr/handle/local/19833 2022-12-31T15:00:00Z