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- W4385466225 abstract "Artificial intelligence (AI) is a fast-growing field focused on modeling and machine implementation of various cognitive functions with an increasing number of applications in computer vision, text processing, robotics, neurotechnology, bio-inspired computing and others. In this chapter, we describe how AI methods can be applied in the context of intracranial electroencephalography (iEEG) research. IEEG data is unique as it provides extremely high-quality signals recorded directly from brain tissue. Applying advanced AI models to this data carries the potential to further our understanding of many fundamental questions in neuroscience. At the same time, as an invasive technique, iEEG lends itself well to long-term, mobile brain-computer interface applications, particularly for communication in severely paralyzed individuals. We provide a detailed overview of these two research directions in the application of AI techniques to iEEG. That is, (1) the development of computational models that target fundamental questions about the neurobiological nature of cognition (AI-iEEG for neuroscience) and (2) applied research on monitoring and identification of event-driven brain states for the development of clinical brain-computer interface systems (AI-iEEG for neurotechnology). We explain key machine learning concepts, specifics of processing and modeling iEEG data and details of state-of-the-art iEEG-based neurotechnology and brain-computer interfaces." @default.
- W4385466225 created "2023-08-02" @default.
- W4385466225 creator A5004865135 @default.
- W4385466225 creator A5020704424 @default.
- W4385466225 creator A5051870567 @default.
- W4385466225 creator A5054638114 @default.
- W4385466225 date "2023-01-01" @default.
- W4385466225 modified "2023-10-03" @default.
- W4385466225 title "How Does Artificial Intelligence Contribute to iEEG Research?" @default.
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