scholarly journals Working Memory Decline in Alzheimer’s Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1380
Author(s):  
David Perpetuini ◽  
Antonio Maria Chiarelli ◽  
Chiara Filippini ◽  
Daniela Cardone ◽  
Pierpaolo Croce ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Working Memory ◽  
Near Infrared ◽  
Complexity Analysis ◽  
Brain Activity ◽  
Conditional Entropy ◽  
Functional Near Infrared Spectroscopy ◽  
Complex Figure ◽  
Raven's Progressive Matrices

Alzheimer’s disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey–Osterrieth complex figure and Raven’s progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

scholarly journals Evidence of Neurovascular Un-Coupling in Mild Alzheimer’s Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 337
Author(s):  
Antonio M. Chiarelli ◽  
David Perpetuini ◽  
Pierpaolo Croce ◽  
Chiara Filippini ◽  
Daniela Cardone ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Near Infrared ◽  
Area Under The Curve ◽  
Hemoglobin Concentration ◽  
Blood Perfusion ◽  
Ambulatory Setting ◽  
Functional Near Infrared Spectroscopy ◽  
Frequency Bands ◽  
Concentration Changes

Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10−5). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

scholarly journals Use of Virtual Reality Working Memory Task and Functional Near-Infrared Spectroscopy to Assess Brain Hemodynamic Responses to Methylphenidate in ADHD Children

2021 ◽  
Vol 11 ◽  
Author(s):  
Sooah Jang ◽  
JongKwan Choi ◽  
Jooyoung Oh ◽  
Jungyeon Yeom ◽  
Narae Hong ◽  
...  
Keyword(s):  
Working Memory ◽  
Virtual Reality ◽  
Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Memory Task ◽  
Real Life ◽  
Drug Effects ◽  
Functional Near Infrared Spectroscopy ◽  
Adhd Children

Virtual reality (VR) neuropsychological tests have emerged as a method to explore drug effects in real-life contexts in attention deficit hyperactivity disorder (ADHD) children. Functional near-infrared spectroscopy (fNIRS) is a useful tool to measure brain activity during VR tasks in ADHD children with motor restlessness. The present study aimed to explore the acute effects of methylphenidate (MPH) on behavioral performance and brain activity during a VR-based working memory task simulating real-life classroom settings in ADHD children. In total, 23 children with ADHD performed a VR n-back task before and 2 h after MPH administration concurrent with measurements of oxygenated hemoglobin signal changes with fNIRS. Altogether, 12 healthy control (HC) subjects participated in the same task but did not receive MPH treatment. Reaction time (RT) was shortened after MPH treatment in the 1-back condition, but changes in brain activation were not observed. In the 2-back condition, activation of the left dorsolateral prefrontal cortex (DLPFC) and bilateral medial prefrontal cortex (mPFC) was decreased alongside behavioral changes such as shorter RT, lower RT variability, and higher accuracy after MPH administration. Bilateral mPFC activation in the 2-back condition inversely correlated with task accuracy in the pre-MPH condition; this inverse correlation was not observed after MPH administration. In ADHD children, deactivation of the default mode network mediated by mPFC reduced during high working memory load, which was restored through MPH treatment. Our results suggest that the combination of VR classroom tasks and fNIRS examination makes it easy to assess drug effects on brain activity in ADHD children in settings simulating real-life.

Making social neuroscience less WEIRD: Using fNIRS to measure neural signatures of persuasive influence in a Middle East participant sample

2019 ◽  
Author(s):  
Shannon Burns ◽  
Lianne N. Barnes ◽  
Ian A. McCulloh ◽  
Munqith M. Dagher ◽  
Emily B. Falk ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Near Infrared ◽  
Brain Activity ◽  
Health And Safety ◽  
Social Neuroscience ◽  
Functional Near Infrared Spectroscopy ◽  
Future Directions ◽  
Neuroscience Research ◽  
Neuropsychological Functions ◽  
Arabic Speaking

The large majority of social neuroscience research uses WEIRD populations – participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sample. Participants were shown persuasive videos on various health and safety topics while their brain activity was measured using functional near infrared spectroscopy (fNIRS). Self-reported persuasiveness ratings for each video were then recorded. Consistent with previous research conducted with American subjects, this work found that activity in the dorsomedial and ventromedial prefrontal cortex predicted how persuasive participants found the videos and how much they intended to engage in the messages’ endorsed behaviors. Further, activity in the left ventrolateral prefrontal cortex was associated with persuasiveness ratings, but only in participants for whom the message was personally relevant. Implications for these results on the understanding of the brain basis of persuasion and on future directions for neuroimaging in diverse populations are discussed.

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