: Transcranial magnetic stimulation (TMS) research has suggested dysfunction in cortical glutamatergic systems in adolescent depression, while proton magnetic resonance spectroscopy (H-MRS) studies have demonstrated deficits in concentrations of glutamatergic metabolites in depressed individuals in several cortical regions, including the anterior cingulate cortex (ACC). However, few studies have combined TMS and MRS methods to examine relationships between glutamatergic neurochemistry and excitatory and inhibitory neural functions, and none have utilized TMS-MRS methodology in clinical populations or in youth. This exploratory study aimed to examine relationships between TMS measures of cortical excitability and inhibition and concentrations of glutamatergic metabolites as measured by H-MRS in depressed adolescents. : Twenty-four adolescents (aged 11-18 years) with depressive symptoms underwent TMS testing, which included measures of the resting motor threshold (RMT), cortical silent period (CSP), short-interval intracortical inhibition (SICI), and intracortical facilitation (ICF). Fourteen participants from the same sample also completed H-MRS in a 3 T MRI scanner after TMS testing. Glutamate + glutamine (Glx) concentrations were measured in medial ACC and left primary motor cortex voxels with a TE-optimized PRESS sequence. Metabolite concentrations were corrected for cerebrospinal fluid (CSF) after tissue segmentation. Pearson product-moment and Spearman rank-order correlations were calculated to assess relationships between TMS measures and [Glx]. : In the left primary motor cortex voxel, [Glx] had a significant positive correlation with the RMT. In the medial ACC voxel, [Glx] had significant positive correlations with ICF at the 10-ms and 20-ms interstimulus intervals (ISIs). : These preliminary data implicate glutamate in cortical excitatory processes measured by TMS. Limitations included small sample size, lack of healthy control comparators, possible age- and sex-related effects, and observational nature of the study. Further research aimed at examining the relationship between glutamatergic metabolite concentrations measured through MRS and the excitatory and inhibitory physiology measured through TMS is warranted. Combined TMS-MRS methods show promise for future investigations of the pathophysiology of depression in adults as well as in children and adolescents.
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http://dx.doi.org/10.3389/fncir.2016.00098 | DOI Listing |
JMIR Form Res
December 2024
Department of Communication, Stanford University, Stanford, US.
Background: Contrary to popular concerns about the harmful effects of media use on mental health, research on this relationship is ambiguous, stalling advances in theory, interventions, and policy. Scientific explorations of the relationship between media and mental health have mostly found null or small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health.
Objective: This exploratory empirical demonstration aimed to answer whether mental health effects are associated with media use experiences by (1) redirecting research investments to granular and intensive longitudinal recordings of digital experiences to build models of media use and mental health for single individuals over the course of one entire year, (2) using new metrics of fragmented media use to propose explanations of mental health effects that will advance person-specific theorizing in media psychology, and (3) identifying combinations of media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders.
J Med Internet Res
January 2025
Graduate School of Health Science and Technology, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
Background: Artificial intelligence (AI) social chatbots represent a major advancement in merging technology with mental health, offering benefits through natural and emotional communication. Unlike task-oriented chatbots, social chatbots build relationships and provide social support, which can positively impact mental health outcomes like loneliness and social anxiety. However, the specific effects and mechanisms through which these chatbots influence mental health remain underexplored.
View Article and Find Full Text PDFPLoS One
January 2025
Institute of Psychiatry, Psychology & Neuroscience at King's College London, London, United Kingdom.
Fluctuation-related pain (FRP) affects more than one third of people with Parkinson's disease (PwP, PD) and has a harmful effect on health-related quality of life (HRQoL), but often remains under-reported by patients and neglected by clinicians. The National Institute for Health and Care Excellence (NICE) recommends The Parkinson KinetiGraphTM (the PKGTM) for remote monitoring of motor symptoms. We investigated potential links between the PKGTM-obtained parameters and clinical rating scores for FRP in PwP in an exploratory, cross-sectional analysis of two prospective studies: "The Non-motor International Longitudinal, Real-Life Study in PD-NILS" and "An observational-based registry of baseline PKG™ in PD-PKGReg".
View Article and Find Full Text PDFPLoS One
January 2025
Department of Medical Sciences, Cancer Epidemiology Unit, University of Turin and CPO-Piemonte, Turin, Italy.
Objectives: Maternal occupational exposures during early pregnancy can be detrimental to foetus health and have short- and long-term health effects on the child. This study examined their association with adverse birth outcomes.
Methods: The study included 3938 nulliparous women from the Italian NINFEA mother-child cohort.
PLoS One
January 2025
Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi, Università di Genova, Genova, Italy.
In this paper, we explore the application of Artificial Intelligence and network science methodologies in characterizing interdisciplinary disciplines, with a specific focus on the field of Italian design, taken as a paradigmatic example. Exploratory data analysis and the study of academic collaboration networks highlight how the field is evolving towards increased collaboration. Text analysis and semantic topic modelling identified the evolution of research interest over time, defining a ranking of pairs of keywords and three prominent research topics: User-Centric Experience Design, Innovative Product Design and Sustainable Service Design.
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