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Updated: Jun 28, 2025

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat
Published on: September 12, 2014
Brain dynamics and spatiotemporal trajectories during threat processing
Joyneel Misra1, Luiz Pessoa1,2,3
1Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, United States of America.
Abstract:
In the past decades, functional MRI research has investigated task processing in a largely static fashion based on evoked responses during blocked and event-related designs. Despite some progress in naturalistic designs, our understanding of threat processing remains largely limited to those obtained with standard paradigms with limited dynamics. In the present paper, we applied Switching Linear Dynamical Systems to uncover the dynamics of threat processing during a continuous threat-of-shock paradigm. First, we demonstrated that the SLDS model learned the regularities of the experimental paradigm, such that states and state transitions estimated from fMRI time series data from 85 regions of interest reflected threat proximity and threat approach vs. retreat. After establishing that the model captured key properties of threat-related processing, we characterized the dynamics of the states and their transitions. Importantly, we characterized both endogenous and exogenous contributions to dynamics. The results revealed how threat processing can be viewed in terms of dynamic multivariate patterns whose trajectories are a combination of intrinsic and extrinsic factors that jointly determine how the brain temporally evolves during dynamic threat. Furthermore, we developed a measure of region importance that quantifies the contributions of an individual brain region to system dynamics, which complements the system-level characterization that is obtained with the state-space SLDS formalism. Finally, we investigated the generalizability of the modelling approach. The successful application of the SLDS model trained on one paradigm to a separate experiment illustrates the potential of this approach to capture fMRI dynamics that generalize across related but distinct threat-processing tasks. We propose that viewing threat processing through the lens of dynamical systems offers important avenues to uncover properties of the dynamics of threat that are not unveiled with standard experimental designs and analyses.
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