TY - JOUR
T1 - Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings
T2 - Data Collection and Analysis Challenges
AU - Pinto-Orellana, Marco Antonio
AU - Khan, Haroon
AU - Ombao, Hernando
AU - Mirtaheri, Peyman
N1 - Publisher Copyright:
© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - cross-frequency coupling
KW - data pre-processing
KW - electrical-hemodynamic coupling
KW - Hybrid EEG-fNIRS
KW - statistical modeling
KW - synchronization
UR - http://www.scopus.com/inward/record.url?scp=105003407038&partnerID=8YFLogxK
U2 - 10.1080/26941899.2024.2426785
DO - 10.1080/26941899.2024.2426785
M3 - Article
AN - SCOPUS:105003407038
SN - 2694-1899
VL - 3
JO - Data Science in Science
JF - Data Science in Science
IS - 1
M1 - 2426785
ER -