Arnaud Delorme, PhD
Arnaud Delorme, PhD, is a CNRS principal investigator in Toulouse, France, a member faculty at the University of California, San Diego, and a Scientist at the Institute of Noetic Sciences. In 2000, Dr. Delorme completed his PhD thesis on visual categorization in humans, monkeys, and machines. Dr. Delorme then moved to the Salk Institute for a postdoc in Terry Sejnowski and Francis Crick’s laboratory where he focused on statistical analysis of electroencephalographic (EEG) signals recorded during various cognitive tasks. He developed the free EEGLAB software for advanced analysis of EEG signals, software which is now amongst the most used in EEG research worldwide. He was awarded a Brettencourt-Schueller young investigator award and a 10-year anniversary ANT young investigator award for his contributions to the field of EEG research.
Turner, MD, BCN, qEEG-D for several years providing neurofeedback and neuromodulation to a varied patient population before moving to the Nashville Child and Family Wellness Center in November of 2017."
Presenting: ”Artificial Intelligence”
Artificial intelligence is rapidly reshaping neurotherapy by enabling scalable, data driven analysis of electroencephalography through the emergence of EEG foundation models trained on large, heterogeneous datasets. These models promise to learn transferable representations of brain activity that support robust biomarker discovery across disorders and interventions, potentially overcoming long standing limitations related to small sample sizes, site effects, and handcrafted features. In parallel, conversational AI systems are beginning to act as interactive scientific assistants that can support neurotherapy research by helping design preprocessing and analysis pipelines, documenting methodological choices, and assisting with transparent reporting and interpretation of results. When appropriately constrained and validated, such tools may improve reproducibility and accessibility without replacing expert judgment. Together, EEG foundation models and scientifically grounded chatbots point toward a new generation of neurotherapy workflows in which biomarker development, methodological rigor, and human expertise are jointly augmented by artificial intelligence.
Education Level: INTERMEDIATE
Content builds upon the learner's foundational knowledge, familiarity with the literature and/or experience in a content area. Programming at this level includes more depth than at a beginning level program. It could also serve as a refresher course for individuals who have a background in a content area and are interested in learning more contemporary applications. The primary goal of this particular program is to broaden the clinical, consultative, and research knowledge bases of attendees and was deemed intermediate, by the definition above. For those psychologists using the modality of biofeedback and interested in efficacy, science, and latest clinical applications. This conference presents research relevant to psychological practice, education, and science; (2) it is our intention to host an offering to help psychologists to keep up with the most current scientific evidence regarding assessment, intervention, and education; and (3) we believe that this program would allow psychologists to increase competencies to improve services to patients. This conference is IN NO WAY a substitute for the basic academic education and training needed for entry into the field of psychology.