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基于太赫兹超材料对不同脑功能区识别研究

张娟 陈宇 穆宁 周萌 郑靖民

太赫兹科学与电子信息学报2025,Vol.23Issue(2):116-122,7.
太赫兹科学与电子信息学报2025,Vol.23Issue(2):116-122,7.DOI:10.11805/TKYDA2024548

基于太赫兹超材料对不同脑功能区识别研究

Research on the identification of different brain functional regions based on terahertz metamaterials

张娟 1陈宇 2穆宁 3周萌 2郑靖民4

作者信息

  • 1. 陆军军医大学第一附属医院 医学心理科,重庆 400038
  • 2. 陆军军医大学第一附属医院 神经外科,重庆 400038
  • 3. 陆军军医大学第一附属医院 神经外科,重庆 400038||重庆大学,重庆 400044
  • 4. 陆军军医大学第一附属医院 医务处,重庆 400038
  • 折叠

摘要

Abstract

Precise diagnosis and personalized treatment of neurological diseases are crucial for improving patient outcomes.Terahertz(THz)metamaterials,due to their unique spectral properties,have become essential tools for studying different functional areas of brain tissue.THz metamaterials are employed to detect brain tissue sections,with a focus on analyzing key functional areas such as the amygdala,motor cortex,auditory cortex,hippocampus,hypothalamus,and thalamus.By measuring the resonant frequencies and amplitude changes in each area,the ability of THz metamaterials to identify different brain regions is verified.The resonant frequencies and amplitudes in each brain functional area have undergone significant changes.Among them,the hippocampus shows the largest change in resonance peak amplitude(ΔA),increasing from 7.62%to 20.35%.The motor cortex,auditory cortex,and amygdala show significant resonance frequency shifts,with a shift amount(Δf)reaching(369±4.4)GHz,while the hypothalamus shows a shift of 23.77 GHz.These differences are closely related to the biophysical properties of each brain area.The study indicates that THz metamaterials can effectively distinguish the spectral characteristics of brain functional areas.

关键词

脑功能区/THz超材料/共振频率/传输振幅

Key words

brain functional areas/terahertz metamaterials/resonant frequency/transmission amplitude

分类

临床医学

引用本文复制引用

张娟,陈宇,穆宁,周萌,郑靖民..基于太赫兹超材料对不同脑功能区识别研究[J].太赫兹科学与电子信息学报,2025,23(2):116-122,7.

基金项目

国家自然科学基金资助项目(82173388) (82173388)

重庆市自然科学基金资助项目(CSTB2023NSCQ-MSX0524) (CSTB2023NSCQ-MSX0524)

国家教育部光电信息技术科学重点实验室基金资助项目(2024KFKT003) (2024KFKT003)

太赫兹科学与电子信息学报

2095-4980

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