Individualized Assays of Temporal Coding in the Ascending Human Auditory System

Abstract

Neural phase-locking to temporal fluctuations is a fundamental and unique mechanism by which acoustic information is encoded by the auditory system. The perceptual role of this metabolically expensive mechanism, the neural phase-locking to temporal fine structure (TFS) in particular, is debated.Although hypothesized, it is unclear if auditory perceptual deficits in certain clinical populations are attributable to deficits in TFS coding. Efforts to uncover the role of TFS have been impeded by the fact that there are no established assays for quantifying the fidelity of TFS coding at the individual level. While many candidates have been proposed, for an assay to be useful, it should not only intrinsically depend on TFS coding, but should also have the property that individual differences in the assay reflect TFS coding per se over and beyond other sources of variance. Here, we evaluate a range of behavioral and electroencephalogram (EEG)-based measures as candidate individualized measures of TFS sensitivity. Our comparisons of behavioral and EEG-based metrics suggest that extraneous variables dominate both behavioral scores and EEG amplitude metrics, rendering them ineffective. After adjusting behavioral scores using lapse rates, and extracting latency or percent-growth metrics from EEG, interaural timing sensitivity measures exhibit robust behavior-EEG correlations. Together with the fact that unambiguous theoretical links can be made relating binaural measures and phase-locking to TFS, our results suggest that these "adjusted" binaural assays may be well-suited for quantifying individual TFS processing.

Individual Differences Elucidate the Perceptual Benefits Associated with Robust Temporal Fine-Structure Processing

“…The left panel compares online measurement of binaural FM detection with in-person results from Grose and Mamo (2012); Whiteford and Oxenham (2015); Whiteford et al (2017); Lelo de Larrea-Mancera et al (2020). The right panel includes a sample of in-person studies that measured ITD discrimination (Henning, 1983; Dye, 1990; Brughera et al, 2013; Borjigin et al, 2022). Borjigin et al (2022) is our previous in-person study.…”

“…The right panel includes a sample of in-person studies that measured ITD discrimination (Henning, 1983; Dye, 1990; Brughera et al, 2013; Borjigin et al, 2022). Borjigin et al (2022) is our previous in-person study. These results further validate our choice of TFS sensitivity measures.…”

“…We previously established that binaural behavioral and electrophysiological (EEG) measurements of ITD sensitivity can reliably reflect individual differences in TFS processing (Borjigin et al, 2022). Therefore, in this study, we adopted the behavioral ITD detection and added a binaural version of the frequency-modulation (FM) detection.…”

“…Therefore, in this study, we adopted the behavioral ITD detection and added a binaural version of the frequency-modulation (FM) detection. Importantly, our previous study also showed that the binaural metrics were effective in capturing individual TFS processing only if the contributions of extraneous “non-sensory” factors that are irrelevant to TFS processing, such as engagement, were measured and adjusted for (Borjigin et al, 2022). In the present study, we implemented a stand-alone measure that will also be influenced by extraneous non-sensory factors, but unaffected by individual TFS-processing fidelity.…”

“…The individual differences approach has been successfully used to address other fundamental questions in the neuroscience of audition (McDermott et al, 2010; Bharadwaj et al, 2015; Whiteford et al, 2020). However, this approach has not been used to investigate the role of TFS given that robust measures of TFS sensitivity at the individual level were only recently established by comparing behavioral and electrophysiological assays (Borjigin et al, 2022).…”