Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis Challenges

The hybrid EEG-fNIRS (electroencephalogram - functional near-infrared spectroscopy) modality provides a comprehensive understanding of brain activity by simultaneously capturing electrical and hemodynamic responses. It takes advantage of the temporal resolution in EEG with the good spatial resolution of fNIRS. This hybrid system is non-invasive, portable, and relatively affordable compared to functional magnetic resonance imaging (fMRI). Despite its inherent limitations, EEG-fNIRS systems can be a valuable tool in neuroimaging, suitable for cognitive and clinical research that requires temporal and spatial information about brain function. They are well-suited in naturalistic experimental settings, brain-computer interface applications, and disease diagnosis. This paper also explores electro-metabolic interactions in the motor cortex during left- and right-hand grip tasks. We analyzed cross-frequency coupling (CFC) between delta rhythms (0–4Hz) and oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentrations calculated from fNIRS. CFC was estimated as the correlation between HbO, HbR, and the instantaneous amplitude of delta signals. CFC cannot be studied with non-synchronous measurements and is not directly related to activation amplitudes. Based on previous fMRI-EEG studies, some categories of oscillations denote a negligible correlation with fNIRS signals. However, our results showed a contra-lateral coupling between delta-EEG and HbO with significant pattern differences in the left motor cortex.

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Publication Details

Journal
Data Science in Science
Published
2024-12-06
DOI
https://doi.org/10.1080/26941899.2024.2426785
Citations
7
Primary Topic
Optical Imaging and Spectroscopy Techniques
Type
article
Field-Weighted Citation Impact
2.83
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article

Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis Challenges

Haroon Khan, Hernando Ombao, Marco Antonio Pinto-Orellana, Peyman Mirtaheri
7 citations
Data Science in Science
Optical Imaging and Spectroscopy Techniques
2.83
article

Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis Challenges

Haroon Khan, Hernando Ombao, Marco Antonio Pinto-Orellana, Peyman Mirtaheri
article en
7 citations

Abstract

The hybrid EEG-fNIRS (electroencephalogram - functional near-infrared spectroscopy) modality provides a comprehensive understanding of brain activity by simultaneously capturing electrical and hemodynamic responses. It takes advantage of the temporal resolution in EEG with the good spatial resolution of fNIRS. This hybrid system is non-invasive, portable, and relatively affordable compared to functional magnetic resonance imaging (fMRI). Despite its inherent limitations, EEG-fNIRS systems can be a valuable tool in neuroimaging, suitable for cognitive and clinical research that requires temporal and spatial information about brain function. They are well-suited in naturalistic experimental settings, brain-computer interface applications, and disease diagnosis. This paper also explores electro-metabolic interactions in the motor cortex during left- and right-hand grip tasks. We analyzed cross-frequency coupling (CFC) between delta rhythms (0–4Hz) and oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentrations calculated from fNIRS. CFC was estimated as the correlation between HbO, HbR, and the instantaneous amplitude of delta signals. CFC cannot be studied with non-synchronous measurements and is not directly related to activation amplitudes. Based on previous fMRI-EEG studies, some categories of oscillations denote a negligible correlation with fNIRS signals. However, our results showed a contra-lateral coupling between delta-EEG and HbO with significant pattern differences in the left motor cortex.

Data Science in ScienceVol. 3(1)
OsloMet – Oslo Metropolitan University (NO), University of California, Irvine (US), King Abdullah University of Science and Technology (SA)
Openalex Percentile: Top 9%
Optical Imaging and Spectroscopy Techniques
2.83
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