Background: Dimensional frameworks of psychopathology call for multivariate approaches to map co-occurring disorders to index what symptoms emerge when and for whom. Ecological momentary assessment (EMA) offers a method for assessing and differentiating the dynamics of co-occurring symptoms with greater temporal granularity and naturalistic context. The present study used multivariate mixed effects location-scale modeling to characterize the time-varying dynamics of depressed mood and anxiety for women diagnosed with social anxiety disorder (SAD) and major depression (MDD).
Methods: Women completed five daily EMA surveys over 30 days (150 EMA surveys/woman, T ≈ 5250 total observations) and two clinical diagnostic and retrospective self-report measures administered approximately two months apart.
Results: There was evidence of same-symptom lagged effects (bs = 0.08-0.09), but not cross-symptom lagged effects (bs < 0.01) during EMA. Symptoms co-varied such that momentary spikes from one's typical level of anxiety were associated with increases in momentary depressed mood (b = 0.19) and greater variability of depressed mood (b = 0.06). Similarly, spikes from one's typical levels of depressed mood were associated with increases in momentary anxiety (b = 0.19). Furthermore, the presence and magnitude of effects demonstrated person-specific heterogeneity.
Limitations: Our findings are constrained to the dynamics of depressed and anxious mood among cisgender women with primary SAD and current or past MDD.
Conclusions: Findings from this work help to characterize how daily experiences of co-occurring mood and anxiety fluctuate and offer insight to aid the development of momentary, person-specific interventions designed to regulate symptom fluctuations.
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http://dx.doi.org/10.1016/j.jad.2024.06.064 | DOI Listing |
Chaos
January 2025
School of Mathematical & Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom.
Time-evolving graphs arise frequently when modeling complex dynamical systems such as social networks, traffic flow, and biological processes. Developing techniques to identify and analyze communities in these time-varying graph structures is an important challenge. In this work, we generalize existing spectral clustering algorithms from static to dynamic graphs using canonical correlation analysis to capture the temporal evolution of clusters.
View Article and Find Full Text PDFSoft Matter
January 2025
Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana, Slovenia.
We demonstrate the generation of diverse material flow regimes in nematic liquid cells as driven by time-variable active surface anchoring, including no-net flow, oscillatory flow, steady flow, and pulsating flow. Specifically, we numerically simulate a passive nematic fluid inside a cell bounded with two flat solid boundaries at which the time-dependent anchoring is applied with the dynamically variable surface anchoring easy axis. We show that different flow regimes emerge as the result of different anchoring driving directions ( co-rotating or counter-rotating) and relative phase of anchoring driving.
View Article and Find Full Text PDFPsychiatry Res
December 2024
Department of Psychiatry, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, PR China. Electronic address:
Background: Auditory verbal hallucinations (AVHs) in schizophrenia (SCZ) are linked to brain network abnormalities. Resting-state fMRI studies often assume stable networks during scans, yet dynamic changes related to AVHs are not well understood.
Methods: We analyzed resting-state fMRI data from 60 SCZ patients with persistent AVHs (p-AVHs), 39 SCZ patients without AVHs (n-AVHs), and 59 healthy controls (HCs), matched for demographics.
ISA Trans
December 2024
National Key Laboratory of Aerospace Flight Dynamics, School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China; Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China. Electronic address:
This paper investigates an integrated model-control scheme for large-scale spacecraft, focusing on orbit-attitude-vibration dynamics subject to strong time-varying coupling characteristics. The proposed scheme aims to achieve cooperative modeling and control for orbit maintenance, attitude stabilization and vibration suppression simultaneously. An integrated dynamic model is established using the Absolute Nodal Coordinate Formulation and Lagrangian mechanics, where time-varying coupling terms are preserved to enhance model integrity, contrasting with the reduction and decoupling methods commonly adopted in existing literature.
View Article and Find Full Text PDFCell Rep
January 2025
Western Institute for Neuroscience, Western University, London, ON, Canada; Department of Clinical Neurological Sciences, London Health Sciences Centre, Western University, London, ON, Canada; Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada. Electronic address:
Neuronal populations expand their information-encoding capacity using mixed selective neurons. This is particularly prominent in association areas such as the lateral prefrontal cortex (LPFC), which integrate information from multiple sensory systems. However, during conditions that approximate natural behaviors, it is unclear how LPFC neuronal ensembles process space- and time-varying information about task features.
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