Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.

Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Peng Fang, Ling-Li Zeng, Hui Shen, Lubin Wang, Baojuan Li, Li Liu, Dewen Hu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/16a195b37782451eab3c59bc551463cf
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:16a195b37782451eab3c59bc551463cf
record_format	dspace
spelling	oai:doaj.org-article:16a195b37782451eab3c59bc551463cf2021-11-18T08:13:52ZIncreased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.1932-620310.1371/journal.pone.0045972https://doaj.org/article/16a195b37782451eab3c59bc551463cf2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23049910/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001) of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.Peng FangLing-Li ZengHui ShenLubin WangBaojuan LiLi LiuDewen HuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 9, p e45972 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Peng Fang Ling-Li Zeng Hui Shen Lubin Wang Baojuan Li Li Liu Dewen Hu Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
description	Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001) of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.
format	article
author	Peng Fang Ling-Li Zeng Hui Shen Lubin Wang Baojuan Li Li Liu Dewen Hu
author_facet	Peng Fang Ling-Li Zeng Hui Shen Lubin Wang Baojuan Li Li Liu Dewen Hu
author_sort	Peng Fang
title	Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
title_short	Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
title_full	Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
title_fullStr	Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
title_full_unstemmed	Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
title_sort	increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/16a195b37782451eab3c59bc551463cf
work_keys_str_mv	AT pengfang increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT linglizeng increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT huishen increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT lubinwang increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT baojuanli increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT liliu increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging AT dewenhu increasedcorticallimbicanatomicalnetworkconnectivityinmajordepressionrevealedbydiffusiontensorimaging
_version_	1718422028626690048

Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.

Ejemplares similares