Perceptual Temporal Asymmetry Associated with Distinct ON and OFF Responses to Time-Varying Sounds with Rising versus Falling Intensity: A Magnetoencephalography Study

Abstract

This magnetoencephalography (MEG) study investigated evoked ON and OFF responses to ramped and damped sounds in normal-hearing human adults. Two pairs of stimuli that differed in spectral complexity were used in a passive listening task; each pair contained identical acoustical properties except for the intensity envelope. Behavioral duration judgment was conducted in separate sessions, which replicated the perceptual bias in favour of the ramped sounds and the effect of spectral complexity on perceived duration asymmetry. MEG results showed similar cortical sites for the ON and OFF responses. There was a dominant ON response with stronger phase-locking factor (PLF) in the alpha (8–14 Hz) and theta (4–8 Hz) bands for the damped sounds. In contrast, the OFF response for sounds with rising intensity was associated with stronger PLF in the gamma band (30–70 Hz). Exploratory correlation analysis showed that the OFF response in the left auditory cortex was a good predictor of the perceived temporal asymmetry for the spectrally simpler pair. The results indicate distinct asymmetry in ON and OFF responses and neural oscillation patterns associated with the dynamic intensity changes, which provides important preliminary data for future studies to examine how the auditory system develops such an asymmetry as a function of age and learning experience and whether the absence of asymmetry or abnormal ON and OFF responses can be taken as a biomarker for certain neurological conditions associated with auditory processing deficits.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

“…Given that multiple analysis techniques (for example, waveform analysis, source localization, time-frequency analysis) can be applied to the same neurophysiological data in cognitive neuroscience research [54,57,58,59], a cautionary note against the convenient use of the simple Pearson correlation test is necessary when selecting and applying statistical models to interpret brain-behavior correlations (e.g., biomarkers of various diseases and disorders) or correlations among the various brain measures with prior distributions and covariance structure for repeated measures. …”

Oscillations in the auditory system and their possible role

“…In these cases, as stated before, it is difficult to disentangle neural oscillations from the spectral content of typical evoked potentials. For instance, AEPs or inter-trial phase locking lasting only one or two cycles were possibly misinterpreted as "alpha-beta" activity (Fritz et al, 2010) or "theta" activity (Musacchia et al, 2017;Zhang et al, 2016). More importantly, it questions the accuracy of the conclusions based on very few cycles of oscillations.…”

Sound Change Integration Error: An Explanatory Model of Tinnitus

“…As stated above, the auditory N1 is a prominent cortical electroencephalographic response to both the onset (On-response; On-N1) and offset (Off-response; Off-N1) of an auditory stimulus (Zhang et al, 2016 ). An auditory N1 can also be elicited by infrequent changes in pitch or timbre of a continuous complex tone (Vaz Pato and Jones, 1999 ; Change-N1).…”

“…The model further postulates that the auditory cortex recognizes sound inputs by comparing it to the input of the previous instant, and thus acts as a detector of input changes. In this model, the auditory N1, a prominent electromagnetic response of the auditory cortex that is elicited ~100 ms after the onset and offset of a discrete tone or after an alteration of a continuous tone (Zhang et al, 2016 ), serves as a marker of this change detection process within auditory cortex. Indeed, recent studies have revealed that the auditory N1 detects change by comparing the information of a preceding stimulus with that of a subsequent stimulus (Inui et al, 2010 ).…”