NIH VideoCast - Prediction of clinical outcomes after CNS injury using cognitive neuroscience and computational linguistics

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Prediction of clinical outcomes after CNS injury using cognitive neuroscience and computational linguistics

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Air date:	Thursday, December 16, 2021, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 113 (31 Live, 82 On-demand)
Category:	Special
Runtime:	00:57:37
Closed captioning:	Check box to display CC outside of the video Note: You can drag the captioning window around and resize it
Description:	NIH Natural Language Processing Special Interest Group We seek to develop a computational framework that combines ultrasensitive functional noninvasive brain imaging techniques, neural networks and linguistics to investigate the neural basis of auditory language comprehension. We intend to use this information to develop neurocomputational predictive AI based algorithms that reliably prediction clinical outcomes following CNS injury. Initially, we seek to develop computational models in healthy individual and then in pre and post-surgical epilepsy patients. In this report, we present preliminary data in which our methodology enables us to assess the auditory processing network in health individuals. We describe a tightly interactive bilateral neural network located in the temporal parietal lobes. This network is recruited independent of hearing and handedness. It is our intention to use this data to predict the 1, 2 and 3 year postsurgical language mediated neural network alterations following specific surgical interventions. Although we are primarily focused on auditory language processing networks, the same methodology can be used to assess all other aspects of language processing as well as the attentional and memory networks that subserve cognition. Dr. Biassou is a board-certified radiologist at the NIH Clinical Center for the last 15years and holds a joint appointment as staff clinician in the Radiology and Imaging Sciences Department at the NIH Clinical Center and Chief of the Integrative Neuroscience of Communication Research Unit at NIDCD. She obtained her training in clinical general diagnostic radiology from Georgetown University Hospital with subspecialty fellowship training in neuroradiology from the Hospital of the University of Pennsylvania. She also holds a Bachelor of Arts Degree in English Literature from Amherst College, a Masters of Arts and PhD in applied linguistics and cognitive science from the University of Pennsylvania and a medical degree from the University of Chicago-Pritzker School of Medicine. The scope of her research spans from applied computational neuroscience to neuropsychology and applied linguistics.

NLM Title:	Prediction of clinical outcomes after CNS injury using cognitive neuroscience and computational linguistics / Dr. Nadia Biassou.
Author:	Biassou, Nadia. National Institutes of Health (U.S). Natural Language Processing Special Interest Group.
Publisher:
Abstract:	(CIT): NIH Natural Language Processing Special Interest Group We seek to develop a computational framework that combines ultrasensitive functional noninvasive brain imaging techniques, neural networks and linguistics to investigate the neural basis of auditory language comprehension. We intend to use this information to develop neurocomputational predictive AI based algorithms that reliably prediction clinical outcomes following CNS injury. Initially, we seek to develop computational models in healthy individual and then in pre and post-surgical epilepsy patients. In this report, we present preliminary data in which our methodology enables us to assess the auditory processing network in health individuals. We describe a tightly interactive bilateral neural network located in the temporal parietal lobes. This network is recruited independent of hearing and handedness. It is our intention to use this data to predict the 1, 2 and 3 year postsurgical language mediated neural network alterations following specific surgical interventions. Although we are primarily focused on auditory language processing networks, the same methodology can be used to assess all other aspects of language processing as well as the attentional and memory networks that subserve cognition. Dr. Biassou is a board-certified radiologist at the NIH Clinical Center for the last 15years and holds a joint appointment as staff clinician in the Radiology and Imaging Sciences Department at the NIH Clinical Center and Chief of the Integrative Neuroscience of Communication Research Unit at NIDCD. She obtained her training in clinical general diagnostic radiology from Georgetown University Hospital with subspecialty fellowship training in neuroradiology from the Hospital of the University of Pennsylvania. She also holds a Bachelor of Arts Degree in English Literature from Amherst College, a Masters of Arts and PhD in applied linguistics and cognitive science from the University of Pennsylvania and a medical degree from the University of Chicago-Pritzker School of Medicine. The scope of her research spans from applied computational neuroscience to neuropsychology and applied linguistics.
Subjects:	Auditory Perception Nerve Net--physiology Neurosciences Psychoacoustics Psycholinguistics Speech Acoustics
Publication Types:	Lecture Webcast

NLM Classification:	WV 501
NLM ID:	9918332579006676
CIT Live ID:	44302
Permanent link:	https://videocast.nih.gov/watch=44302

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