Abstract
Acute acoustic (sound) stimuli prompt a state of defensive motivation in which unconscious muscle responses are activated in humans. The neuronal arcade of this acoustic startle reflex (ASR) is comprised of unconsciously regulated brainstem and cerebral structures that are susceptible to influences from a variety of physiological and/or psychological conditions. The orbicularis oculi (OO) muscle of the eye is an easily accessed muscle that is commonly utilized to measure the ASR. To date, OO readings have involved electromyographic (EMG) measurements, as measured using electro-oculo-graphic (EOG) electrodes with adhesives and wires. While effective, such measures require specialized equipment and expertise, and can be influenced by factors such as posture (sitting versus (vs) standing). As such, although the ASR can provide insights about numerous clinical conditions, existing methodologies of OO and ASR measurements using the EMG limit the utility of the method in clinical conditions.
In an effort to overcome challenges associated with standard EMG/EOG measures of the ASR, we have developed a novel application (app) that can be run on an iPhoneX and later model. The app, the Mobile Acoustic startle Reflex-monitoring System (MARS) delivers specific sound stimuli and independently detects the blink reflex response outcomes of both eyes in millisecond resolution. MARS permits measurements of responses to various acute acoustic sounds of different frequencies and amplitudes in both standing and sitting postures, outside of clinical settings.
In the present study, we aimed to correlate variables of blink latency, velocity, amplitude, and gradient with PTSD severity and PTSD predictor symptoms of first responder populations with (PTSD).
55 MARS intakes were performed in conjunction with standard PTSD behavioural health assessments on male fire fighters at the International Association of Fire Fighters Center of Excellence (IAFF COE). Data from MARS, PTSD severity, and PTSD predictor symptoms were analysed using Pearson’s correlation and backward stepwise regression statistical methodology to describe outcomes of standing and sitting postures, and PTSD severity with ASR OO response measures. Our conclusions reveal a very strong correlation (r=0.82, P=<2e-16 ***) between blink velocity and amplitude which encourage substitutions of EMG amplitude with MARS velocity for ASR OO measurements. Additionally, significant (but weak) correlations with ASR blink latency and PTSD severity (beta = 9.867, SE 3.081, P=0.00153) were reported. While statistically significant, the overall prediction for ASR OO latency response and PTSD severity was weak (P=0.001, Adjusted R squared = 0.03425). PTSD severity and PTSD symptomology measures from the CAPS-5 reported no significant correlations to response measures: latency, amplitude, velocity, or gradient. Response differences for sitting and standing postures reported no significant differences but there were visual observations of potential sensitization across stimulus order and repeated measures in both postures. Results from this experiment show that the MARS app reliably induces and records the ASR in OO muscles with specific stimulus parameters. Response measures from ASR OO amplitude and velocity are interchangeable. There was a weak, but statistically significant predictive model of PTSD severity and ASR OO Latency.