Brain dynamics that correlate with effects of learning on auditory distance perception

Abstract

Accuracy in auditory distance perception can improve with practice and varies for sounds differing in familiarity. Here, listeners were trained to judge the distances of English, Bengali, and backwards speech sources pre-recorded at near (2-m) and far (30-m) distances. Listeners' accuracy was tested before and after training. Improvements from pre-test to post-test were greater for forward speech, demonstrating a learning advantage for forward speech sounds. Independent component (IC) processes identified in electroencephalographic (EEG) data collected during pre- and post-testing revealed three clusters of ICs across subjects with stimulus-locked spectral perturbations related to learning and accuracy. One cluster exhibited a transient stimulus-locked increase in 4–8 Hz power (theta event-related synchronization; ERS) that was smaller after training and largest for backwards speech. For a left temporal cluster, 8–12 Hz decreases in power (alpha event-related desynchronization; ERD) were greatest for English speech and less prominent after training. In contrast, a cluster of IC processes centered at or near anterior portions of the medial frontal cortex showed learning-related enhancement of sustained increases in 10–16 Hz power (upper-alpha/low-beta ERS). The degree of this enhancement was positively correlated with the degree of behavioral improvements. Results suggest that neural dynamics in non-auditory cortical areas support distance judgments. Further, frontal cortical networks associated with attentional and/or working memory processes appear to play a role in perceptual learning for source distance.

Theta‐ and alpha‐power enhancements in the electroencephalogram as an auditory delayed match‐to‐sample task becomes impossibly difficult

“…Enhancements of alpha power appear strongest at occipital sites, but these enhancements tend to be more widespread across the scalp than theta‐power enhancements (cf. Wisniewski et al, ). Traces of relative theta and alpha power extracted from ERSPs for each difficulty condition are depicted below their respective ERSP images in Figure .…”

“…Note that this time window starts a sufficient length of time past the onset and offset of A and B stimuli (at least 500 ms) in order to minimize the influence of transient responses to those sounds (cf. Wisniewski et al, ). Frequencies of theta and alpha selected for analysis were within canonical bands, 4–8 Hz and 8–13 Hz, respectively.…”

“…If easy listening conditions show a stronger suppression in mu rhythm power (see Figure 4), this could be interpreted as a weaker enhancement in alpha-band power in the channel data when the mu rhythm is mixed by scalp conduction with other rhythms that show relative increases in power (cf. Wisniewski et al, 2014). One study found that presentations of speech sounds in noise were accompanied by suppression of the mu rhythm (Bowers, Saltuklaroglu, Harkrider, & Cuellar, 2013).…”

“…As with channel activities, activities of independent components (ICs) can be examined in the time‐frequency domain for theta‐ and alpha‐power enhancements. ICs identified by ICA are often found to account for a significant amount of variability in both frontal midline theta (e.g., Onton et al, ; Scheeringa et al, ; Wisniewski et al, ) and alpha rhythms (e.g., Gramann et al, ; Makieg & Onton, ; Wisniewski, Mercado, Church, Gramann, & Makeig, ; Wisniewski, Mercado, Gramann, & Makeig, ). The ICA approach is especially useful for the current research because analyses of ICs have the potential to disentangle the contributions of multiple brain sources to theta‐ and alpha‐power effects seen at channels.…”

Learning-related improvements in auditory detection sensitivities correlate with neural changes observable during active and passive sound processing

“…Independent component (IC) processes identified as eye-or muscle-movement artifacts (based on scalp projections, spectra, and time courses) were removed from the data (i.e., the data were corrected for artifacts; cf. Wisniewski et al 27 ). Epochs were extracted from -0.5 to 1.0 seconds surrounding onsets of tones.…”