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基于动态因果建模和指数排序的耳鸣异常脑区检测。

Tinnitus Abnormal Brain Region Detection Based on Dynamic Causal Modeling and Exponential Ranking.

机构信息

School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China.

Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.

出版信息

Biomed Res Int. 2018 Jul 9;2018:8656975. doi: 10.1155/2018/8656975. eCollection 2018.

DOI:10.1155/2018/8656975
PMID:30105255
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6076911/
Abstract

Dynamic Causal Modeling (DCM) has been extended for the analysis of electroencephalography (EEG) based on a specific biophysical and neurobiological generative model for EEG. Comparing to methods that summarize neural activities with linear relationships, the generative model enables DCM to better describe how signals are generated and better reveal the underlying mechanism of the activities occurring in human brains. Since DCM provides us with an approach to the effective connectivity between brain areas, with exponential ranking, the abnormality of the observed signals can be further located to a specific brain region. In this paper, a combination of DCM and exponential ranking is proposed as a new method aiming at searching for the abnormal brain regions which are associated with chronic tinnitus.

摘要

动态因果建模 (DCM) 已经扩展到基于特定的生物物理和神经生物学 EEG 生成模型的脑电图 (EEG) 分析。与使用线性关系总结神经活动的方法相比，生成模型使 DCM 能够更好地描述信号是如何产生的，并更好地揭示人类大脑中活动的潜在机制。由于 DCM 为我们提供了一种研究大脑区域之间有效连接的方法，通过指数排名，可以将观察到的信号的异常进一步定位到特定的脑区。在本文中，提出了一种将 DCM 和指数排名相结合的新方法，旨在寻找与慢性耳鸣相关的异常脑区。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/098d1761892b/BMRI2018-8656975.alg.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/7cbb738110c3/BMRI2018-8656975.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/c1a1bccc975e/BMRI2018-8656975.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/28915f0d0cd1/BMRI2018-8656975.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/09840d5d8f20/BMRI2018-8656975.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/069bdfe4cd3a/BMRI2018-8656975.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/fdad8274af50/BMRI2018-8656975.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/3ce6e20070e9/BMRI2018-8656975.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/59c95084400c/BMRI2018-8656975.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/3d3cbd1575b6/BMRI2018-8656975.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/098d1761892b/BMRI2018-8656975.alg.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/7cbb738110c3/BMRI2018-8656975.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/c1a1bccc975e/BMRI2018-8656975.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/28915f0d0cd1/BMRI2018-8656975.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/09840d5d8f20/BMRI2018-8656975.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/069bdfe4cd3a/BMRI2018-8656975.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/fdad8274af50/BMRI2018-8656975.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/3ce6e20070e9/BMRI2018-8656975.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/59c95084400c/BMRI2018-8656975.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/3d3cbd1575b6/BMRI2018-8656975.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa8/6076911/098d1761892b/BMRI2018-8656975.alg.001.jpg

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本文引用的文献

1
Resting-State Brain Abnormalities in Chronic Subjective Tinnitus: A Meta-Analysis.慢性主观性耳鸣的静息态脑异常：一项荟萃分析。
Front Hum Neurosci. 2017 Jan 24;11:22. doi: 10.3389/fnhum.2017.00022. eCollection 2017.
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Deafferentation-based pathophysiological differences in phantom sound: Tinnitus with and without hearing loss.基于去传入的幻听病理生理差异：伴有和不伴有听力损失的耳鸣
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Evaluation of tinnitus patients by audiometric configuration.
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通过听力图形态对耳鸣患者进行评估。
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Disentangling tinnitus distress and tinnitus presence by means of EEG power analysis.通过脑电图功率分析区分耳鸣困扰和耳鸣存在情况。
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