Frequency Selectivity of Persistent Cortical Oscillatory Responses to Auditory Rhythmic Stimulation.

Abstract

Cortical oscillations have been proposed to play a functional role in speech and music perception, attentional selection, and working memory, via the mechanism of neural entrainment. One of the properties of neural entrainment that is often taken for granted is that its modulatory effect on ongoing oscillations outlasts rhythmic stimulation. We tested the existence of this phenomenon by studying cortical neural oscillations during and after presentation of melodic stimuli in a passive perception paradigm. Melodies were composed of ∼60 and ∼80 Hz tones embedded in a 2.5 Hz stream. Using intracranial and surface recordings in male and female humans, we reveal persistent oscillatory activity in the high-γ band in response to the tones throughout the cortex, well beyond auditory regions. By contrast, in response to the 2.5 Hz stream, no persistent activity in any frequency band was observed. We further show that our data are well captured by a model of damped harmonic oscillator and can be classified into three classes of neural dynamics, with distinct damping properties and eigenfrequencies. This model provides a mechanistic and quantitative explanation of the frequency selectivity of auditory neural entrainment in the human cortex.SIGNIFICANCE STATEMENT It has been proposed that the functional role of cortical oscillations is subtended by a mechanism of entrainment, the synchronization in phase or amplitude of neural oscillations to a periodic stimulation. One of the properties of neural entrainment that is often taken for granted is that its modulatory effect on ongoing oscillations outlasts rhythmic stimulation. Using intracranial and surface recordings of humans passively listening to rhythmic auditory stimuli, we reveal consistent oscillatory responses throughout the cortex, with persistent activity of high-γ oscillations. On the contrary, neural oscillations do not outlast low-frequency acoustic dynamics. We interpret our results as reflecting harmonic oscillator properties, a model ubiquitous in physics but rarely used in neuroscience.