Publications by authors named "P Chavarria-Elizondo"
Research on anxiety faces challenges due to the wide range of symptoms, making it difficult to determine if different aspects of anxiety are linked to distinct neurobiological processes. Both alterations in functional brain connectivity (FC) and monoaminergic neurotransmitter systems are implicated as potential neural bases of anxiety. We aimed to investigate whole-brain FC involving monoaminergic nuclei and its association with anxiety dimensions in 178 non-clinical participants.
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- Scientists studied how brain changes in older people could cause problems with thinking and feeling, particularly in those with mild cognitive issues and depression.
- They looked at 12 people with mild cognitive impairment, 24 people with late-life depression, and 26 healthy individuals using brain scans and tests over 2 years.
- The results showed that specific brain activity patterns could help doctors understand and spot early signs of thinking and mood problems that might lead to Alzheimer's disease.
Trait anxiety is a well-established risk factor for anxiety and depressive disorders, yet its neural correlates are not clearly understood. In this study, we investigated the neural correlates of trait anxiety in a large sample (n = 179) of individuals who completed the trait and state versions of the State-Trait Anxiety Inventory and underwent resting-state functional magnetic resonance imaging. We used independent component analysis to characterize individual resting-state networks (RSNs), and multiple regression analyses to assess the relationship between trait anxiety and intrinsic connectivity.
View Article and Find Full Text PDFIntroduction: We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs).
Participants: 23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs.
Material And Methods: Participants were assessed in two time-points, 2 years apart.
Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA.
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