TY - GEN
T1 - Enhancing Neuronal Coupling Estimation by NIRS/EEG Integration
AU - Gallego-Molina, Nicolás J.
AU - Ortiz, Andrés
AU - Formoso, Marco A.
AU - Martínez-Murcia, Francisco J.
AU - Woo, Wai Lok
PY - 2024/5/31
Y1 - 2024/5/31
N2 - Neuroimaging techniques have had a major impact on medical science, allowing advances in the research of many neurological diseases and improving their diagnosis. In this context, multimodal neuroimaging approaches, based on the neurovascular coupling phenomenon, exploit their individual strengths to provide complementary information on the neural activity of the brain cortex. This work proposes a novel method for combining electroencephalography (EEG) and functional near–infrared spectroscopy (fNIRS) to explore the functional activity of the brain processes related to low-level language processing of skilled and dyslexic seven-year-old readers. We have transformed EEG signals into image sequences considering the interaction between different frequency bands by means of cross-frequency coupling (CFC), and applied an activation mask sequence obtained from the local functional brain activity inferred from simultaneously recorded fNIRS signals. Thus, the resulting image sequences preserve spatial and temporal information of the communication and interaction between different neural processes and provide discriminative information that enables differentiation between controls and dyslexic subjects.
AB - Neuroimaging techniques have had a major impact on medical science, allowing advances in the research of many neurological diseases and improving their diagnosis. In this context, multimodal neuroimaging approaches, based on the neurovascular coupling phenomenon, exploit their individual strengths to provide complementary information on the neural activity of the brain cortex. This work proposes a novel method for combining electroencephalography (EEG) and functional near–infrared spectroscopy (fNIRS) to explore the functional activity of the brain processes related to low-level language processing of skilled and dyslexic seven-year-old readers. We have transformed EEG signals into image sequences considering the interaction between different frequency bands by means of cross-frequency coupling (CFC), and applied an activation mask sequence obtained from the local functional brain activity inferred from simultaneously recorded fNIRS signals. Thus, the resulting image sequences preserve spatial and temporal information of the communication and interaction between different neural processes and provide discriminative information that enables differentiation between controls and dyslexic subjects.
KW - Cross-Frequency Coupling
KW - Dyslexia
KW - Functional Brain Activation
KW - Integrated EEG-fNIRS Analysis
KW - Multimodal Neuroimaging
UR - http://www.scopus.com/inward/record.url?scp=85197173760&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-61140-7_3
DO - 10.1007/978-3-031-61140-7_3
M3 - Conference contribution
AN - SCOPUS:85197173760
SN - 9783031611391
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 24
EP - 33
BT - Artificial Intelligence for Neuroscience and Emotional Systems (IWINAC 2024)
A2 - Ferrández Vicente, José Manuel
A2 - Val Calvo, Mikel
A2 - Adeli, Hojjat
PB - Springer
CY - Cham, Switzerland
T2 - 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024
Y2 - 4 June 2024 through 7 June 2024
ER -