Saved in:
Bibliographic Details
Main Authors: Wang, Yuejiao, Gong, Xianmin, Meng, Lingwei, Wu, Xixin, Meng, Helen
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.10376
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916323339010048
author Wang, Yuejiao
Gong, Xianmin
Meng, Lingwei
Wu, Xixin
Meng, Helen
author_facet Wang, Yuejiao
Gong, Xianmin
Meng, Lingwei
Wu, Xixin
Meng, Helen
contents Functional magnetic resonance imaging (fMRI) is essential for developing encoding models that identify functional changes in language-related brain areas of individuals with Neurocognitive Disorders (NCD). While large language model (LLM)-based fMRI encoding has shown promise, existing studies predominantly focus on healthy, young adults, overlooking older NCD populations and cognitive level correlations. This paper explores language-related functional changes in older NCD adults using LLM-based fMRI encoding and brain scores, addressing current limitations. We analyze the correlation between brain scores and cognitive scores at both whole-brain and language-related ROI levels. Our findings reveal that higher cognitive abilities correspond to better brain scores, with correlations peaking in the middle temporal gyrus. This study highlights the potential of fMRI encoding models and brain scores for detecting early functional changes in NCD patients.
format Preprint
id arxiv_https___arxiv_org_abs_2407_10376
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Large Language Model-based FMRI Encoding of Language Functions for Subjects with Neurocognitive Disorder
Wang, Yuejiao
Gong, Xianmin
Meng, Lingwei
Wu, Xixin
Meng, Helen
Neurons and Cognition
Computation and Language
Functional magnetic resonance imaging (fMRI) is essential for developing encoding models that identify functional changes in language-related brain areas of individuals with Neurocognitive Disorders (NCD). While large language model (LLM)-based fMRI encoding has shown promise, existing studies predominantly focus on healthy, young adults, overlooking older NCD populations and cognitive level correlations. This paper explores language-related functional changes in older NCD adults using LLM-based fMRI encoding and brain scores, addressing current limitations. We analyze the correlation between brain scores and cognitive scores at both whole-brain and language-related ROI levels. Our findings reveal that higher cognitive abilities correspond to better brain scores, with correlations peaking in the middle temporal gyrus. This study highlights the potential of fMRI encoding models and brain scores for detecting early functional changes in NCD patients.
title Large Language Model-based FMRI Encoding of Language Functions for Subjects with Neurocognitive Disorder
topic Neurons and Cognition
Computation and Language
url https://arxiv.org/abs/2407.10376