The neural basis of attention bias toward mood-congruent information in people with major depressive disorder

2008 ◽  
Author(s):  
Kwok-keung Leung
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Attention Bias ◽  
Neural Basis ◽  
Major Depressive

MF.09 The neural basis of self-blaming bias in major depressive disorder

2011 ◽  
Vol 82 (8) ◽  
pp. e2-e2
Author(s):  
R. Zahn ◽  
M. L. Ralph ◽  
J. Moll ◽  
B. Deakin ◽  
S. Green
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Neural Basis ◽  
Major Depressive

scholarly journals Neural basis of major depressive disorder: Beyond monoamine hypothesis

2017 ◽  
Vol 72 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Shuken Boku ◽  
Shin Nakagawa ◽  
Hiroyuki Toda ◽  
Akitoyo Hishimoto
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Neural Basis ◽  
Major Depressive

scholarly journals Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts

2021 ◽  
Vol 12 ◽  
Author(s):  
Ayumu Yamashita ◽  
Yuki Sakai ◽  
Takashi Yamada ◽  
Noriaki Yahata ◽  
Akira Kunimatsu ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Prediction Model ◽  
Resting State ◽  
Validation Dataset ◽  
Depression Symptoms ◽  
Resting State Functional Connectivity ◽  
Neural Basis ◽  
Major Depressive

Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.

scholarly journals The neural basis of conceptual–emotional integration and its role in major depressive disorder

2013 ◽  
Vol 8 (5) ◽  
pp. 417-433 ◽  
Author(s):  
Sophie Green ◽  
Matthew A. Lambon Ralph ◽  
Jorge Moll ◽  
Jessica Zakrzewski ◽  
John F. William Deakin ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Neural Basis ◽  
Major Depressive
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