Brain Activation Changes During Balance- and Attention-Demanding Tasks in Middle- and Older-Aged Adults With Multiple Sclerosis

Motor Control ◽  
2019 ◽  
Vol 23 (4) ◽  
pp. 498-517 ◽  
Author(s):  
Manuel E. Hernandez ◽  
Erin O’Donnell ◽  
Gioella Chaparro ◽  
Roee Holtzer ◽  
Meltem Izzetoglu ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Older Adults ◽  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Motor Task ◽  
Brain Activation ◽  
Functional Near Infrared Spectroscopy ◽  
Healthy Older Adults

Functional near-infrared spectroscopy was used to evaluate prefrontal cortex activation differences between older adults with multiple sclerosis (MS) and healthy older adults (HOA) during the performance of a balance- and attention-demanding motor task. Ten older adults with MS and 12 HOA underwent functional near-infrared spectroscopy recording while talking, virtual beam walking, or virtual beam walking while talking on a self-paced treadmill. The MS group demonstrated smaller increases in prefrontal cortex oxygenation levels than HOA during virtual beam walking while talking than talking tasks. These findings indicate a decreased ability to allocate additional attentional resources in challenging walking conditions among MS compared with HOA. This study is the first to investigate brain activation dynamics during the performance of balance- and attention-demanding motor tasks in persons with MS.

scholarly journals Prefrontal Cortex Control of Walking: Functional Near-Infrared Spectroscopy and Beyond

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 791-791
Author(s):  
Andrea Rosso ◽  
Roee Holtzer
Keyword(s):  
Older Adults ◽  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Cognitive Control ◽  
Near Infrared Spectroscopy ◽  
Fall Risk ◽  
Near Infrared ◽  
Stair Climbing ◽  
Functional Near Infrared Spectroscopy ◽  
Primary Means

Abstract Cognitive control of walking may change with aging and is associated with poorer mobility and greater fall risk. The prefrontal cortex function is important for cognitive control of walking, and functional near-infrared spectroscopy (fNIRS) provides the primary means for assessing prefrontal activation during walking. Growing interest in fNIRS to assess cognitive control of walking has led to advancements in the methodologies for processing and analyzing the data, a greater sophistication of experimental protocols and participant samples, and implementation within intervention studies. These advancements will be highlighted in five presentations from an international group of researchers at the forefront of the field. First, Meltem Izzetoglu will provide direct comparisons of various data processing methodologies, demonstrating comparability across approaches. Three talks will demonstrate the range of applications of fNIRS to studying walking in older adults. Nemin Chen will present data on task-related patterns of prefrontal activation across walking tasks in relation to performance, cognitive function, and structural brain health. Sarah Fraser will present results from stair climbing, a critical task for daily function which also presents a fall risk. Inbal Maidan will examine how individual differences affect prefrontal activity during walking across older adults, younger adults, and patients with Parkinson’s disease or multiple sclerosis. Finally, David Clark will demonstrate the use of fNIRS in assessing outcomes from an intervention that combined walking with non-invasive frontal brain stimulation. Roee Holtzer will lead a discussion of the results and the future of fNIRS in assessing cognitive control of walking in older adults.

scholarly journals Inter-Session Reliability of Functional Near-Infrared Spectroscopy at the Prefrontal Cortex While Walking in Multiple Sclerosis

2020 ◽  
Vol 10 (9) ◽  
pp. 643
Author(s):  
Kim-Charline Broscheid ◽  
Dennis Hamacher ◽  
Juliane Lamprecht ◽  
Michael Sailer ◽  
Lutz Schega
Keyword(s):  
Multiple Sclerosis ◽  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Area Under The Curve ◽  
Functional Near Infrared Spectroscopy ◽  
Brodmann Areas ◽  
The Mean ◽  
Almost All

Many established technologies are limited in analyzing the executive functions in motion, especially while walking. Functional near-infrared spectroscopy (fNIRS) fills this gap. The aim of the study is to investigate the inter-session reliability (ISR) of fNIRS-derived parameters at the prefrontal cortex while walking in people with multiple sclerosis (MS) and healthy control (HC) individuals. Twenty people with MS/HC individuals walked a 12 m track back and forth over 6 min. The primary outcomes were the absolute and relative reliability of the mean, slope coefficient (SC), and area under the curve (A) of the oxy-/deoxyhemoglobin concentrations (HbO/HbR) in the Brodmann areas (BA) 9/46/10. The SC and the A of HbO exhibited a fair ISR in BA10 in people with MS. For the mean and A of the HbR, almost all areas observed revealed a fair ISR. Overall, the ISR was better for HbR than HbO. A fair to excellent ISR was found for most BA of the prefrontal cortex in HC individuals. In total, the ISR of the analyzed fNIRS-derived parameters was limited. To improve the ISR, confounders such as fatigue and mind wandering should be minimized. When reporting the ISR, the focus should be on the mean/A rather than SC.

scholarly journals Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

2021 ◽  
Vol 11 (6) ◽  
pp. 701
Author(s):  
Cheng-Hsuan Chen ◽  
Kuo-Kai Shyu ◽  
Cheng-Kai Lu ◽  
Chi-Wen Jao ◽  
Po-Lei Lee
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Kernel Functions ◽  
Olfactory Stimulation ◽  
Support Vector ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy ◽  
Data Set

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

Social hyperscanning with fNIRS

Gesture ◽  
2020 ◽  
Vol 19 (2-3) ◽  
pp. 196-222
Author(s):  
Michela Balconi ◽  
Angela Bartolo ◽  
Giulia Fronda
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Dorsolateral Prefrontal Cortex ◽  
Near Infrared ◽  
Brain Connectivity ◽  
Gestural Communication ◽  
Functional Near Infrared Spectroscopy ◽  
Dorsolateral Prefrontal ◽  
Posterior Parietal

Abstract The interest of neuroscience has been aimed at the investigation of the neural bases underlying gestural communication. This research explored the intra- and inter-brain connectivity between encoder and decoder. Specifically, adopting a “hyperscanning paradigm” with the functional Near-infrared Spectroscopy (fNIRS) cerebral connectivity in oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin levels were revealed during the reproduction of affective, social, and informative gestures of different valence. Results showed an increase of intra- and inter-brain connectivity in dorsolateral prefrontal cortex for affective gestures, in superior frontal gyrus for social gestures and in frontal eyes field for informative gestures. Moreover, encoder showed a higher intra-brain connectivity in posterior parietal areas more than decoder. Finally, an increasing of inter-brain connectivity more than intra-brain (ConIndex) was observed in left regions for positive gestures. The present research has explored how the individuals neural tuning mechanisms turn out to be strongly influenced by the nature of specific gestures.

scholarly journals What Does Sleeping Brain Tell About Stress? A Pilot Functional Near-Infrared Spectroscopy Study Into Stress-Related Cortical Hemodynamic Features During Sleep

2021 ◽  
Vol 3 ◽  
Author(s):  
Zilu Liang
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Pilot Study ◽  
Near Infrared Spectroscopy ◽  
Dorsolateral Prefrontal Cortex ◽  
Near Infrared ◽  
Functional Near Infrared Spectroscopy ◽  
Stress Indicators ◽  
Measured Stress ◽  
Dorsolateral Prefrontal

People with mental stress often experience disturbed sleep, suggesting stress-related abnormalities in brain activity during sleep. However, no study has looked at the physiological oscillations in brain hemodynamics during sleep in relation to stress. In this pilot study, we aimed to explore the relationships between bedtime stress and the hemodynamics in the prefrontal cortex during the first sleep cycle. We tracked the stress biomarkers, salivary cortisol, and secretory immunoglobulin A (sIgA) on a daily basis and utilized the days of lower levels of measured stress as natural controls to the days of higher levels of measured stress. Cortical hemodynamics was measured using a cutting-edge wearable functional near-infrared spectroscopy (fNIRS) system. Time-domain, frequency-domain features as well as nonlinear features were derived from the cleaned hemodynamic signals. We proposed an original ensemble algorithm to generate an average importance score for each feature based on the assessment of six statistical and machine learning techniques. With all channels counted in, the top five most referred feature types are Hurst exponent, mean, the ratio of the major/minor axis standard deviation of the Poincaré plot of the signal, statistical complexity, and crest factor. The left rostral prefrontal cortex (RLPFC) was the most relevant sub-region. Significantly strong correlations were found between the hemodynamic features derived at this sub-region and all three stress indicators. The dorsolateral prefrontal cortex (DLPFC) is also a relevant cortical area. The areas of mid-DLPFC and caudal-DLPFC both demonstrated significant and moderate association to all three stress indicators. No relevance was found in the ventrolateral prefrontal cortex. The preliminary results shed light on the possible role of the RLPCF, especially the left RLPCF, in processing stress during sleep. In addition, our findings echoed the previous stress studies conducted during wake time and provides supplementary evidence on the relevance of the dorsolateral prefrontal cortex in stress responses during sleep. This pilot study serves as a proof-of-concept for a new research paradigm to stress research and identified exciting opportunities for future studies.

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