AI/ML-Readiness for Neuroimaging of Language

语言神经影像的 AI/ML 准备

• 批准号: 10412576
• 负责人: Rutvik H Desai
• 金额: $ 28.74万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10412576
• 关键词: Affect; Anatomy; Anterior; Aphasia; Artificial Intelligence; Behavioral; Brain; Code; Cognitive; Communication; Communities; Complex; Crude Extracts; Data; Data Set; Decision Making; Dementia; Dimensions; Distributed Systems; Electrophysiology (science); FAIR principles; Functional Magnetic Resonance Imaging; Goals; Impairment; Individual; Inferior; Knowledge; Language; Language Disorders; Lesion; Life; Light; Machine Learning; Measures; Mental disorders; Metadata; Methodology; Methods; Modernization; Motor; Motor Cortex; Nature; Noise; Parietal Lobe; Participant; Patients; Pattern; Process; Property; Psycholinguistics; Quality of life; Readiness; Recovery; Research; Rest; Role; Scanning; Schizophrenia; Semantic memory; Semantics; Sensory; Series; Social Interaction; Stimulus; Stroke; Structure; Structure of middle temporal gyrus; Symptoms; System; Techniques; Temporal Lobe; Temporal Lobe Epilepsy; Time; United States National Institutes of Health; Variant; angular gyrus; autism spectrum disorder; deep learning; feature selection; frontal lobe; insight; language comprehension; language processing; learning strategy; lexical; machine learning method; nervous system disorder; neuroimaging; neuropathology; neurotransmission; open data; parent grant; phrases; rehabilitation strategy; relating to nervous system; repository; segregation; semantic processing; social cognition; stroke recovery; stroke survivor; support vector machine; treatment strategy

Project Summary/Abstract Conceptual or semantic knowledge refers to information about objects, actions, relations, self, culture, and includes meanings of words and phrases. The use of this knowledge is pervasive and automatic in daily life. Everyday activities such as communication, recognition and use of objects, social interactions, and decision making are crucially reliant on conceptual knowledge. Impairment of this complex and widely distributed system has serious consequences for quality of life. Several neurological and psychiatric disorders are associated with the impairment of this system, including stroke with aphasia, dementias, temporal lobe epilepsy, schizophrenia, and autism. Understanding the structure and organization of this system, and the specific ways it is disrupted in these individuals, is critical for developing better treatments and rehabilitation strategies. The goal of this research is to understand the structure and use of this information, its neural basis, and the ways in which it can be impaired by neuropathology. This project pertains to three neuroimaging datasets — two functional MRI and one from stroke survivors — that speak to the neural basis of concepts and language processing in the brain. We aim to transform these data and associated metadata to a “machine learning ready” format and make them easily accessible. This will enable application of powerful modern machine learning techniques, such as Deep Learning, for their analysis. We expect that these analyses will shed new light on the organization and function of this core semantic region in the healthy and impaired brain.

项目总结/文摘