Empirically based comparisons of the reliability and validity of common quantification approaches for eyeblink startle potentiation in humans

Abstract

Startle potentiation is a well‐validated translational measure of negative affect. Startle potentiation is widely used in clinical and affective science, and there are multiple approaches for its quantification. The three most commonly used approaches quantify startle potentiation as the increase in startle response from a neutral to threat condition based on (1) raw potentiation, (2) standardized potentiation, or (3) percent‐change potentiation. These three quantification approaches may yield qualitatively different conclusions about effects of independent variables (IVs) on affect when within‐ or between‐group differences exist for startle response in the neutral condition. Accordingly, we directly compared these quantification approaches in a shock‐threat task using four IVs known to influence startle response in the no‐threat condition: probe intensity, time (i.e., habituation), alcohol administration, and individual differences in general startle reactivity measured at baseline. We confirmed the expected effects of time, alcohol, and general startle reactivity on affect using self‐reported fear/anxiety as a criterion. The percent‐change approach displayed apparent artifact across all four IVs, which raises substantial concerns about its validity. Both raw and standardized potentiation approaches were stable across probe intensity and time, which supports their validity. However, only raw potentiation displayed effects that were consistent with a priori specifications and/or the self‐report criterion for the effects of alcohol and general startle reactivity. Supplemental analyses of reliability and validity for each approach provided additional evidence in support of raw potentiation.

If or when? Uncertainty's role in anxious anticipation

“…Peak raw startle eyeblink amplitudes were the primary dependent variable, consistent with previous startle eyeblink investigations (Bradford et al, 2015; Grillon et al, 2004; Grillon et al, 2009; Nelson & Shankman, 2011; Nelson, Hajcak, & Shankman, 2015). Startle response data were measured using a BioNomadix® 2Ch EMG Receiver (Biopac Systems, Goleta, CA) from two 4-mm Ag/AgCl sensors placed below the left eye, over the orbicularis muscle.…”

“…These findings suggest that among individuals who are less tolerant of uncertainty, not knowing if a threat will occur provokes increases in anxiety. Overall, by examining the likelihood, probability, and reinforcement rate of threat, these studies provide some insight into the nuanced nature of uncertainty and anxiety and highlight the possible relevance of occurrence uncertainty (OU), the inability to determine if (i.e., the likelihood) an aversive stimulus will occur, for eliciting anxious states (Bradford, Starr, Shackman, & Curtin, 2015; Chin et al, 2016; Davies & Craske, 2015; Dunsmoor et al, 2007; Dunsmoor et al, 2008; Hsu et al, 2005; Monat et al, 1972; Williams et al, 2014). …”

Error-related brain activity is related to aversive potentiation of the startle response in children, but only the ERN is associated with anxiety disorders.

“…Previous work suggests that both the ERN (Meyer, Riesel et al, 2013; Olvet & Hajcak, 2009) and startle response (Bradford, Starr, Shackman, & Curtin, 2015; Larson, Ruffalo, Nietert, & Davidson, 2000) have good psychometric properties in adults; however, only the ERN has been established as a reliable indicator in children (Meyer, Bress et al, 2014). Future work should explore the psychometric properties of the affective modulation of the startle response in children.…”

Postauricular reflexes elicited by soft acoustic clicks and loud noise probes: Reliability, prepulse facilitation, and sensitivity to picture contents

“…Modulation scores appear to serve as more appropriate measures of broad appetitive and defensive processing with the postauricular and startle blink reflexes, respectively. This study appears to be one of the few that used coefficient α to assess the internal consistency of reflexive measures of emotion (e.g., Amodio, Harmon-Jones, & Devine, 2003); previous studies have typically assessed the reliability of emotion-modulated startle blink reflexes through test-retest correlations (e.g., Larson, Ruffalo, Nietert, & Davidson, 2000) or odd-even trial correlations (e.g., Bradford, Starr, Shackman, & Curtin, 2015). The coefficients α for emotional modulation compare favorably with ERP measures based on four trials per condition (Meyer, Riesel, & Proudfit, 2013), and the middling α s in this study belie the relatively acceptable ranges of interitem correlations for each emotional modulation.…”