Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Electroconvulsive Therapy01:30

Electroconvulsive Therapy

59
Electroconvulsive therapy (ECT), or shock therapy, remains a critical biomedical intervention for severe, treatment-resistant depression. While its origins can be traced back to Hippocrates' observations that malaria-induced convulsions alleviated mental illness, modern ECT has evolved significantly from its earlier, more primitive applications. First introduced in 1938 by Ugo Cerletti and his colleagues, ECT involves inducing controlled seizures using electrical currents. In its early...
59

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Impact of Vagus Nerve Stimulation on Suicidal Ideation in Markedly Treatment-Resistant Major Depression: A RECOVER Study Report.

The Journal of clinical psychiatry·2026
Same author

Structural and functional covariance architecture of major depressive disorder: A meta-analytic structural equation modeling approach to primary neuroimaging analysis.

Brain organoid & systems neuroscience journal·2026
Same author

Wearable sensing for quantifying cognitive and balance functions in naturalistic movements of older adults with mild cognitive impairment in therapeutic environments.

medRxiv : the preprint server for health sciences·2026
Same author

Lewy pathology largely absent in prefrontal cortices of Parkinson's disease patients undergoing deep brain stimulation.

NPJ Parkinson's disease·2026
Same author

Regional, functional and transcriptomic decoding of multidimensional brain structure alterations in obsessive-compulsive disorder.

Nature communications·2026
Same author

Corrigendum to "Revisiting subcallosal cingulate deep brain stimulation for depression: Long-term safety and effectiveness outcomes from a pooled analysis of 172 implanted patients" [Brain Stimul 18 (2025) 1632-1640].

Brain stimulation·2026

相关实验视频

Updated: Jul 16, 2025

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.3K

用深度大脑刺激来追踪抑郁症的恢复

Sankaraleengam Alagapan1, Ki Sueng Choi2,3,4, Stephen Heisig2

  • 1School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Nature
|September 21, 2023
PubMed
概括

对抗治疗抑郁症的深度大脑刺激 (DBS) 是有前途的. 来自SCC记录的新脑生物标志物有助于个性化治疗和预测康复,改善患者的结果.

更多相关视频

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.6K
Treating Clinical Depression with Repetitive Deep Transcranial Magnetic Stimulation Using the Brainsway H1-coil
09:30

Treating Clinical Depression with Repetitive Deep Transcranial Magnetic Stimulation Using the Brainsway H1-coil

Published on: October 4, 2016

22.4K

相关实验视频

Last Updated: Jul 16, 2025

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.3K
Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.6K
Treating Clinical Depression with Repetitive Deep Transcranial Magnetic Stimulation Using the Brainsway H1-coil
09:30

Treating Clinical Depression with Repetitive Deep Transcranial Magnetic Stimulation Using the Brainsway H1-coil

Published on: October 4, 2016

22.4K

科学领域:

  • 神经科学
  • 生物标志物
  • 人工智能

背景情况:

  • 在治疗耐药性抑郁症 (TRD) 中,深度大脑刺激 (DBS) 提供长期缓解.
  • 目前的治疗缺乏客观的生物标志物,依靠主观报告和试错调整.
  • 个人从TRD中恢复是不可预测的,需要个性化治疗策略.

研究的目的:

  • 开发和验证客观的基于大脑的生物标志物,以指导TRD中的SCC DBS.
  • 在接受DBS的TRD患者中确定可变恢复轨迹的预测因素.
  • 将电生理和行为标记与TRD中的临床状态相关联.

主要方法:

  • 在10名TRD参与者中实施新型电子生理记录装置.
  • 利用可解释的人工智能 (AI) 分析SCC局部场势 (LFP) 来检测临床状态.
  • 使用数据驱动的视频分析来检测客观的面部表情变化.

主要成果:

  • 90% 的参与者在 24 周内实现了临床反应和 70% 的缓解.
  • 由人工智能衍生的LFP生物标志物准确地反映了个体患者的康复状态,与刺激效应不同.
  • 手术前白质完整性和功能连接性预测了恢复的变化,面部表情的变化反映了这一点.

结论:

  • 来自SCCLFP的客观生物标志物可以为TRD个性化SCCDBS管理.
  • TRD病理的多方面 (功能,解剖学,行为) 特性影响治疗的可变性.
  • 需要进一步研究以了解抑郁症治疗变化的原因.