Efficient modular system identification provides a high-resolution assay of temporal processing and reveals the multilevel effects of attention along the human auditory pathway

Human studies of auditory temporal processing and the effects therein of aging, hearing loss, musicianship, and other auditory processing disorders have conventionally employed brainstem evoked potentials (e.g., FFRs/EFRs targeting specific modulation frequencies). Studies of temporal processing in forebrain structures are fewer and are often restricted to the 40 Hz steady-state response. One factor contributing to the limited investigation is the lack of a fast and reliable method to characterize temporal processing non-invasively in humans over a wide range of modulation frequencies. Here, we use a system-identification approach where white noise, modulated using an extended maximum-length sequence (em-seq), is employed to target stimulus energy toward a modulation-frequency range of interest and efficiently obtain a robust auditory modulation-temporal response function or mod-TRF. The mod-TRF can capture activity from sources in the early processing pathway (5-7 ms latency), middle-latency region (MLR), and late latency region (LLR). The mod-TRF is a high-resolution, modular assay of the temporal modulation transfer function (tMTF) in that the distinct neural components contributing to the tMTF can be separated on the basis of their latency, modulation frequency band, and scalp topography. This decomposition provides the insight that the seemingly random individual variation in the shape of the tMTF can be understood as arising from individual differences in the weighting and latency of similar underlying neural sources in the composite scalp response. We measured the mod-TRF under different states of attention and found a reduction in latency or enhancement of amplitude of the response from specific sources. Surprisingly, we found that attention effects can extend to the earliest parts of the processing pathway (5ms) in highly demanding tasks. Taken together, the mod-TRF is a promising tool for dissecting auditory temporal processing and obtain further insight into a variety of phenomenon such as aging, hearing loss, and neural pathology.