Literature DB >> 24381233

Brain network dysfunction in late-life depression: a literature review.

Reza Tadayonnejad1, Olusola Ajilore.   

Abstract

As a common psychiatric disorder in the growing geriatric population, late-life depression (LLD) has a negative impact on the cognitive, affective, and somatic domains of the lives of the elderly individuals. Accumulating evidence from the structural and functional imaging studies on LLD supports a "network dysfunction model" rather than a "lesion pathology model" for understanding the underlying biological mechanism in this mental disorder. In this work, we used network dysfunction model as a conceptual framework for reviewing recent neuroimaging findings in LLD. Our focus was on 4 major neurocircuits that have been shown to be involved in LLD: default mood network, cognitive control network, affective/frontolimbic network, and corticostriatal circuits. Findings of LLD-related gray and white matter structural abnormalities and resting-state and task-based functional changes were discussed for each network separately. We extended our review by summarizing the latest works that apply graph theory-based network analysis techniques for testing alterations in whole-brain network properties associated with LLD.

Entities:  

Keywords:  late-life depression; neurocircuits; neuroimaging

Mesh:

Year:  2013        PMID: 24381233     DOI: 10.1177/0891988713516539

Source DB:  PubMed          Journal:  J Geriatr Psychiatry Neurol        ISSN: 0891-9887            Impact factor:   2.680


  36 in total

1.  Amygdala network dysfunction in late-life depression phenotypes: Relationships with symptom dimensions.

Authors:  Wenjun Li; B Douglas Ward; Chunming Xie; Jennifer L Jones; Piero G Antuono; Shi-Jiang Li; Joseph S Goveas
Journal:  J Psychiatr Res       Date:  2015-09-09       Impact factor: 4.791

2.  Intrinsic Functional Network Connectivity Is Associated With Clinical Symptoms and Cognition in Late-Life Depression.

Authors:  Jason A Gandelman; Kimberly Albert; Brian D Boyd; Jung Woo Park; Meghan Riddle; Neil D Woodward; Hakmook Kang; Bennett A Landman; Warren D Taylor
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2018-09-21

3.  Lifetime major depression and grey-matter volume

Authors:  Marie-Laure Ancelin; Isabelle Carrière; Sylvaine Artero; Jerome Maller; Chantal Meslin; Karen Ritchie; Joanne Ryan; Isabelle Chaudieu
Journal:  J Psychiatry Neurosci       Date:  2019-01-01       Impact factor: 6.186

4.  Disrupted small world topology and modular organisation of functional networks in late-life depression with and without amnestic mild cognitive impairment.

Authors:  Wenjun Li; B Douglas Ward; Xiaolin Liu; Gang Chen; Jennifer L Jones; Piero G Antuono; Shi-Jiang Li; Joseph S Goveas
Journal:  J Neurol Neurosurg Psychiatry       Date:  2014-11-28       Impact factor: 10.154

5.  Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression.

Authors:  Wenjun Li; Yang Wang; B Douglas Ward; Piero G Antuono; Shi-Jiang Li; Joseph S Goveas
Journal:  J Psychiatr Res       Date:  2016-12-12       Impact factor: 4.791

6.  The relationship between hippocampal volume, chronic pain, and depressive symptoms in older adults.

Authors:  Ali Ezzati; Andrea R Zammit; Michael L Lipton; Richard B Lipton
Journal:  Psychiatry Res Neuroimaging       Date:  2019-05-15       Impact factor: 2.376

7.  Frontal-executive and corticolimbic structural brain circuitry in older people with remitted depression, mild cognitive impairment, Alzheimer's dementia, and normal cognition.

Authors:  Benoit H Mulsant; Aristotle N Voineskos; Neda Rashidi-Ranjbar; Tarek K Rajji; Sanjeev Kumar; Nathan Herrmann; Linda Mah; Alastair J Flint; Corinne E Fischer; Meryl A Butters; Bruce G Pollock; Erin W Dickie; John A E Anderson
Journal:  Neuropsychopharmacology       Date:  2020-05-18       Impact factor: 7.853

8.  Grey matter volume increase following electroconvulsive therapy in patients with late life depression: a longitudinal MRI study.

Authors:  Filip Bouckaert; François-Laurent De Winter; Louise Emsell; Annemieke Dols; Didi Rhebergen; Martien Wampers; Stefan Sunaert; Max Stek; Pascal Sienaert; Mathieu Vandenbulcke
Journal:  J Psychiatry Neurosci       Date:  2016-03       Impact factor: 6.186

9.  Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

Authors:  Meenal J Patel; Carmen Andreescu; Julie C Price; Kathryn L Edelman; Charles F Reynolds; Howard J Aizenstein
Journal:  Int J Geriatr Psychiatry       Date:  2015-02-17       Impact factor: 3.485

10.  Resilience and amygdala function in older healthy and depressed adults.

Authors:  Amber M Leaver; Hongyu Yang; Prabha Siddarth; Roza M Vlasova; Beatrix Krause; Natalie St Cyr; Katherine L Narr; Helen Lavretsky
Journal:  J Affect Disord       Date:  2018-04-25       Impact factor: 4.839

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