Adaptive Cognitive Prosthetic to Treat Neurological and Neuropsychiatric Disorders and Traumatic Brain Injuries
Princeton Docket # 14-3031
A researcher in the Princeton Neuroscience Institute and the Department of Psychology at Princeton University is developing a novel treatment approach for neurological and neuropsychiatric disorders. These neural disorders severely reduce the quality of life for those affected and carry significant societal and economic costs. The CDC estimates over 600,000 individuals in the United States experience a stroke each year, and over 275,000 individuals suffer traumatic head injuries requiring hospitalization. Many individuals never fully recover from these injuries and exhibit limited function due to one or more cognitive disabilities. Currently, there is no effective treatment for these neural disorders.
To address this issue, researchers at Princeton are developing an “Adaptive Cognitive Prosthetic,” which can learn to replace the neural function lost to a brain injury or neural disorder. For example, to bypass a damaged region in the brain, the prosthetic will mimic the lost functionality by recording the neural activity from other brain regions, transforming this activity according to the lost cognitive function, and then stimulating unaffected brain regions to convey the result. Crucially, this mapping from inputs to outputs must be learned for each individual and for each lost cognitive function. This is supported by a novel hierarchical learning algorithm that allows the prosthetic to produce the neural stimulation patterns needed to facilitate exactly those behaviors that are disrupted.
• Recover function of damaged brain regions either through traumatic brain injury (TBI) or stroke
• Neurological and neurodegenerative disorders (e.g. Alzheimer’s, Parkinson’s, epilepsy, migraines)
• Neuropsychiatric and mental health disorders (e.g. obsessive-compulsive disorder, schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism)
• Device adapts to the brain, learning optimal stimulation patterns for each individual
• Device matches the spatiotemporal precision of the brain, allowing for the dynamic interaction between ongoing neural activity and treatment
• Learning algorithm works with specially designed tasks that can target specific cognitive deficits
Keywords: Neurological disorder, neuropsychiatric disorder, mental health, neural stimulation, brain damage, traumatic brain injury, neural tissue, algorithm, prosthetic
Timothy J. Buschman, Ph.D., Assistant Professor of Psychology
The Buschman laboratory studies the mechanisms by which the brain controls behaviors, internally guiding ones actions towards a goal. In particular, the lab aims to understand how cognition arises from the complex interactions between brain regions. To this end, the lab pursues a unique, multidisciplinary approach that combines the design of innovative behavioral tasks with large-scale, multiple-electrode electrophysiology and direct stimulation of neural circuits. The lab’s goal is to understand the neural mechanisms of executive control in order to develop novel treatments for neuropsychiatric and neurodegenerative diseases.
Dr. Timothy Buschman received a B.S. from the California Institute of Technology in 2001 and a Ph.D. from Massachusetts Institute of Technology in 2008. His graduate work with Dr. Earl Miller investigated how networks of neurons support cognitive flexibility. As a graduate student, he pioneered the development and use of large-scale multiple-electrode electrophysiological techniques. Using this approach, one can, for the first time, simultaneously observe large populations of neurons within and across brain regions. This has led to novel insights into fundamental aspects of our cognition, including how we control attention, what underlies our limited capacity to hold things in mind, and what neural mechanisms support flexible thinking. This work has been widely recognized, including in the awarding of a NIH Director’s New Innovator award supporting the development of the current technology.
Sina Tafazoli et al 2020 J.. Neural Eng. 17 056007
Intellectual Property and Licensing Status
Issued US (10,994,141) and EU (UK, Germany, and France: EP3203904) patents. Princeton is seeking industrial collaborators for further development and commercialization of this technology.
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