Exercise effects on depression: Possible neural mechanisms.

Gen Hosp Psychiatry

University of Pittsburgh, Department of Psychology, United States; Center for Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, United States.

Published: November 2017

Depression is a syndrome of stress- and emotion-dysregulation, involving compromised structural integrity of frontal-limbic networks. Meta-analytic evidence indicates that volumetric reductions in the hippocampus, anterior cingulate cortex, prefrontal cortex, striatum, and amygdala, as well as compromised white matter integrity are frequently observed in depressed adults. Exercise has shown promise as an effective treatment for depression, but few studies have attempted to characterize or identify the neural mechanisms of these effects. In this review, we examined the overlap between structural brain abnormalities in depression and the effects of exercise on brain structure in adults, to highlight possible neural mechanisms that may mediate the positive effects of exercise on depressive symptoms. The prefrontal cortex, anterior cingulate cortex, hippocampus, and corpus callosum emerged as structural neural markers that may serve as targets for exercise-based treatments for depression. These findings highlight the need for randomized exercise interventions to test these proposed neurobiological mechanisms of exercise on depression.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437683PMC
http://dx.doi.org/10.1016/j.genhosppsych.2017.04.012DOI Listing

Publication Analysis

Top Keywords

neural mechanisms
12
anterior cingulate
8
cingulate cortex
8
prefrontal cortex
8
effects exercise
8
exercise
6
depression
6
exercise effects
4
effects depression
4
neural
4

Similar Publications

EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer.

Sci Rep

December 2024

School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, 434100, Hubei, China.

Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effectiveness. In this paper, we propose a novel end-to-end emotion recognition method from EEG signals, called MSDCGTNet, which is based on the Multi-Scale Dynamic 1D CNN and the Gated Transformer.

View Article and Find Full Text PDF

The study aims to address the critical issue of toxic side effects resulting from drug combinations, which can significantly increase health risks, clinical complications, and lead to drug being withdrawn from the market. A model named TSEDDI (toxic side effects of drug-drug interaction) has been developed to improve the identification of drug pairs that may induce toxicity or adverse reactions. By utilizing drug chemical structures and diverse proteins, we employ a convolutional neural network (CNN) to extract features from molecular images, enzyme proteins, transporter proteins, and target proteins.

View Article and Find Full Text PDF

This study seeks to improve urban supply chain management and collaborative governance in the context of public health emergencies (PHEs) by integrating fuzzy theory with the Back Propagation Neural Network (BPNN) algorithm. By combining these two approaches, an early warning mechanism for supply chain risks during PHEs is developed. The study employs Matlab software to simulate supply chain risks, incorporating fuzzy inference techniques with the adaptive data modeling capabilities of neural networks for both training and testing.

View Article and Find Full Text PDF

High density laminar recordings reveal cell type and layer specific responses to infrared neural stimulation in the rat neocortex.

Sci Rep

December 2024

Research Group for Implantable Microsystems, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 50/a, Budapest, 1083, Hungary.

Infrared neural stimulation has consistently shown that temperature is a critical neuronal state variable. However, a comprehensive understanding of the biophysical background is essential. In this study, using high-density laminar electrode recordings, we investigated the impact of pulsed and continuous-wave infrared illumination on cortical neurons in anesthetized rats ([Formula: see text]).

View Article and Find Full Text PDF

Chronic ischemia in moyamoya disease (MMD) impaired white matter microstructure and neural functional network. However, the coupling between cerebral blood flow (CBF) and functional connectivity and the association between structural and functional network are largely unknown. 38 MMD patients and 20 sex/age-matched healthy controls (HC) were included for T1-weighted imaging, arterial spin labeling imaging, resting-state functional MRI and diffusion tensor imaging.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!