Research ReportMethodological optimization of tinnitus assessment using prepulse inhibition of the acoustic startle reflex
Introduction
For several decades pre-pulse inhibition of the startle reflex has been successfully used as a powerful tool to identify various psychiatric disorders in humans and the deficiencies associated with sensorimotor gating in laboratory animals (Braff et al., 2001). The basic parameters of the stimulus paradigm used for this testing have been well studied. The stimulus parameters have been optimized for accurate assessment (Carlson and Willott, 1996, Hoffman and Searle, 1965, Ison et al., 2002, Ison et al., 2005). The neural circuits that relate to this phenomenon have also been identified and intensively studied (Koch and Schnitzler, 1997).
Recently prepulse inhibition of the acoustic startle reflex (ASR) has been adapted and successfully tested as a powerful technique for tinnitus assessment in laboratory animals (Turner et al., 2006). This method confers a significant advantage over the previously used time-consuming behavioral approaches utilizing basic mechanisms of conditioning (Bauer et al., 1999, Guitton et al., 2003, Heffner and Harrington, 2002, Heffner and Koay, 2005, Lobarinas et al., 2004, Rüttiger et al., 2003). It does not require animal training. Tinnitus assessment can be done in animals within a single short testing session. This method relies on a reduction of the acoustic startle reflex by a preceding silent gap in an otherwise constant acoustic background. Animals with behavioral evidence of tinnitus cannot detect silence and therefore their reduction of the startle reflex is significantly less than in normal animals. This method has been successfully used to assess tinnitus induced by salicylate overdose or acoustic trauma in rats (Kraus et al. 2010; Turner et al., 2006, Wang et al., 2009, Yang et al., 2007, Zhang et al., 2011) and mice (Longenecker and Galazyuk, 2011; Middleton et al., 2011). Many of the finer details of this methodology, however, have not been described enough to be replicated, but are critical for tinnitus assessment. All these details can be roughly divided into four major categories: refinement of hardware for best performance, optimization of stimulus parameters, behavioral considerations, and identification of optimal strategies for data analysis. Thus, the purpose of this paper is to help newcomers with the typically painful process of learning to correctly apply gap detection techniques for tinnitus assessment in laboratory animals.
Section snippets
Hardware refinement
Any lab equipment requires tuning for the best performance including those designed to measure the behavioral response of an animal to sensory stimuli. Here we focus on refining a system aimed to assess gap detection performance. This method has recently become popular for tinnitus assessment in laboratory animals. Currently, such systems are commercially available and several labs have designed their own systems. All these systems share the same principals but vary slightly in design. Here we
Acknowledgments
We thank Dr. Merri Rosen for valuable comments on earlier versions of this manuscript and Marie Gadziola for technical assistance with acoustical assessments of mouse restrainers. The authors also thank Olga Galazyuk for developing software that allowed off-line data analysis and statistical evaluation. This study is supported by the Tinnitus Research Consortium (AVG).
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2020, Otolaryngologic Clinics of North AmericaCitation Excerpt :The GPIAS methodology has been improved on over the past decade.38,39 It has been shown that careful considerations of GPIAS parameters, such as the startle stimulus and background intensities, acoustical parameters of the gap of silence preceding the startle, and overall duration of a testing session, greatly improve results of GPIAS testing in laboratory animals.40 Recent research also demonstrated large variability in GPIAS measurements between different days of testing, especially in mice.41