Toward an Objective Assessment of Fight-or-Flight System Function in Anxiety Disorders: Startle Reflex Modulation in Threat Coping Contexts as a Candidate Neurophysiological Marker of Disrupted Defense System Operation
Gertler, J. H.; Marsicano, C.; George, M. S.; McTeague, L. M.; Sege, C. T.
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Background: As a key mechanism of disorder, clinical anxiety changes how a defensive motivation system functions in active threat coping contexts. Building on initial evidence that a lab-based escape/avoid preparation task is sensitive to disruptions in underlying defensive activation, current research moved toward implementation as a clinical assessment by testing if task responding predicts symptoms in anxiety treatment seekers. Methods: In our escape/avoid task, unpleasant images are shown after 5.5-second cues that indicate if the upcoming image can be prevented (avoid context), terminated after onset (escape context), or not controlled (no-control comparator). To assess defensive activation during response preparation/threat anticipation, a startle reflex indicator of such activation is probed during each cue. Guided by prior data, 125 individuals were classified into groups based on whether startle was enhanced 1) in a no-control, relative to avoid, context, and 2) in an escape, relative to avoid, context. To test clinical correlates, anxiety (State-Trait Anxiety Inventory), depression (Beck Depression Inventory), and worry (Penn State Worry Questionnaire) were then compared across response groups. Results: Anxiety and worry were higher in participants with enhanced no-control and escape startle than in participants with enhanced no-control but not escape startle. Further, depression was higher in participants with under-enhancement of no-control startle than other groups. Finally, when comparing startle-based profiles to canonical questionnaire cut-off score-based groups, ~54-63% convergence emerged. Conclusions: Defensive profiling in escape/avoid contexts shows promise as a prognostic indicator, but a need to continue improving is also indicated. Possibilities to improve predictiveness and reliability are discussed.
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