Recent Advances in Neurocognitive Analysis Based on EEG Signal Processing
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 17582
Special Issue Editors
Interests: neurocognitive deficits; brain stimulation; electroencephalography; brain computer interface; machine learning; deep learning; neural networks; signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: neurocognitive deficits; autobiographical recall; aging; schizophrenia; depression; neurofeedback; psychopathology; brain stimulation
Special Issue Information
Dear Colleagues,
The study of data derived from electroencephalography (EEG) can yield exhaustive information related to the physiological, functional, and pathological status of the brain. As a result, this information can be extremely useful for the identification of brain rhythms. The latest developments in signal processing and machine learning applied to EEG analysis have provided notable advancements in basic and clinical neuroscience. Hence, the combination of both, complete brain monitoring together with novel and improved signal processing, makes noninvasive EEG analysis a promising clinical tool for the diagnosis and treatment of brain disorders and/or impairments.
This Special Issue invites original research papers that report on recent advancements in EEG signal processing for neurocognitive analysis and its applications. Prospective authors are invited to submit high-quality contributions and reviews. Potential topics include, but are not limited to the following:
- EEG signal processing
- EEG Data analytics
- BCI applications
- Machine learning
- Neural networks
- Neural signal processing techniques (EEG, MEG, MRI/fMRI, PET, fNIRS)
- Neurofeedback
- Neurostimulation
Dr. Alejandro L. Borja
Dr. Jorge J. Ricarte
Guest Editors
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