Consistent spectro-spatial features of human ECoG successfully decode naturalistic behavioral states

• Published in: Frontiers in human neuroscience Vol. 18; p. 1388267
• Main Authors: Alasfour, Abdulwahab, Gilja, Vikash
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 30.05.2024
• Subjects: brain-computer interfaces; ECoG; Human Neuroscience; naturalistic behavior; neural decoding; neural signal processing; neural decoding; brain-computer interfaces; naturalistic behavior; neural signal processing; ECoG
• DOI: 10.3389/fnhum.2024.1388267
• ISSN: 1662-5161

Understanding the neural correlates of naturalistic behavior is critical for extending and confirming the results obtained from trial-based experiments and designing generalizable brain-computer interfaces that can operate outside laboratory environments. In this study, we aimed to pinpoint consistent spectro-spatial features of neural activity in humans that can discriminate between naturalistic behavioral states. We analyzed data from five participants using electrocorticography (ECoG) with broad spatial coverage. Spontaneous and naturalistic behaviors such as "Talking" and "Watching TV" were labeled from manually annotated videos. Linear discriminant analysis (LDA) was used to classify the two behavioral states. The parameters learned from the LDA were then used to determine whether the neural signatures driving classification performance are consistent across the participants. Spectro-spatial feature values were consistently discriminative between the two labeled behavioral states across participants. Mainly, , , and low and high in the postcentral gyrus, precentral gyrus, and temporal lobe showed significant classification performance and feature consistency across participants. Subject-specific performance exceeded 70%. Combining neural activity from multiple cortical regions generally does not improve decoding performance, suggesting that information regarding the behavioral state is non-additive as a function of the cortical region. To the best of our knowledge, this is the first attempt to identify specific spectro-spatial neural correlates that consistently decode naturalistic and active behavioral states. The aim of this work is to serve as an initial starting point for developing brain-computer interfaces that can be generalized in a realistic setting and to further our understanding of the neural correlates of naturalistic behavior in humans.