bioRxivNeurosciencePreprint
Linear superposition of responses evoked by individual glottal pulses explain over 80% of the frequency following response to human speech in the macaque monkey
Tobias TeichertiD, G. Nike GnanatejaiD, Srivatsun SadagopaniD, Bharath ChandrasekaraniD
Abstract
The frequency-following response (FFR) is a scalp-recorded electrophysiological potential that closely follows the periodicity of complex sounds such as speech. It has been suggested that FFRs reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses) and sequentially propagate through auditory processing stages in brainstem, midbrain, and cortex. However, this conceptualization of the FFR is debated, and it remains unclear if and how well a simple linear superposition can capture the spectro-temporal complexity of FFRs that are generated within the highly recurrent and non-linear auditory system. To address this question, we used a deconvolution approach to compute the hypothetical F0 responses that best explain the FFRs in rhesus monkeys to human speech and click trains with time-varying pitch patterns. The linear superposition of F0 responses explained well over 90% of the variance of click train steady state FFRs and well over 80% of mandarin tone steady state FFRs. The F0 responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (<5ms; 200-1000 Hz), midbrain (5-15 ms; 100-250 Hz) and cortex (15-35 ms; ~90 Hz). In summary, our results in the monkey support the notion that FFRs arise as the superposition of F0 responses by showing for the first time that they can capture the bulk of the variance and spectro-temporal complexity of FFRs to human speech with time-varying pitch. These findings identify F0 responses as a potential diagnostic tool that may be useful to reliably link altered FFRs in speech and language disorders to altered F0 responses and thus to specific latencies, frequency bands and ultimately processing stages.
- organism: rat
- organism: mouse
- organism: non-human primate
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 2
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