Using frequency selectivity to examine category-informative dimension-selective attention

Abstract

In everyday situations, listeners may selectively attend to acoustic dimensions (e.g., frequency) within complex sounds and ignore other simultaneous dimensions. Speech sound categories are defined over multiple dimensions that vary in informativeness; thus, speech perception may demand selective attention to diagnostic dimensions. Here, we examine how selective attention affects cortical representations of informative acoustic dimensions during category learning. Participants completed a five-day training regimen wherein they learned four novel non-speech categories to criterion (Obasih et al., in prep). Crucially, stimuli were designed such that for two categories, categorization required reliance on – and perhaps selective attention to – acoustic patterns within high-frequency bands; the other two categories were differentiated by acoustic patterns in low-frequency bands. After training, listeners completed an fMRI session using the same non-speech categorization task. Best frequency for each auditory cortex voxel was obtained using tonotopic mapping. We hypothesized that when categorization depended on distinctions in certain frequency ranges (e.g., high frequencies), listeners would selectively attend to those frequencies, resulting in greater recruitment of voxels preferring those frequencies and possibly attenuation of signal in voxels preferring other frequencies. We present preliminary data from our study, with the goal of clarifying the cortical mechanisms supporting dimension-based auditory selective attention.