Prominence of delta oscillatory rhythms in the motor cortex and their relevance for auditory and speech perception

In the motor cortex, beta oscillations (∼12-30 Hz) are generally considered a principal rhythm contributing to movement planning and execution. Beta oscillations cohabit and dynamically interact with slow delta oscillations (0.5-4 Hz), but the role of delta oscillations and the subordinate relationship between these rhythms in the perception-action loop remains unclear. Here, we review evidence that motor delta oscillations shape the dynamics of motor behaviors and sensorimotor processes, in particular during auditory perception. We describe the functional coupling between delta and beta oscillations in the motor cortex during spontaneous and planned motor acts. In an active sensing framework, perception is strongly shaped by motor activity, in particular in the delta band, which imposes temporal constraints on the sampling of sensory information. By encoding temporal contextual information, delta oscillations modulate auditory processing and impact behavioral outcomes. Finally, we consider the contribution of motor delta oscillations in the perceptual analysis of speech signals, providing a contextual temporal frame to optimize the parsing and processing of slow linguistic information

Terrifying film music mimics alarming acoustic feature of human screams

One way music is thought to convey emotion is by mimicking acoustic features of affective human vocalizations [Juslin and Laukka (2003). Psychol. Bull. 129(5), 770-814]. Regarding fear, it has been informally noted that music for scary scenes in films frequently exhibits a "scream-like" character. Here, this proposition is formally tested. This paper reports acoustic analyses for four categories of audio stimuli: screams, non-screaming vocalizations, scream-like music, and non-scream-like music. Valence and arousal ratings were also collected. Results support the hypothesis that a key feature of human screams (roughness) is imitated by scream-like music and could potentially signal danger through both music and the voice

Entrained delta oscillations reflect the subjective tracking of time

The ability to precisely anticipate the timing of upcoming events at the time-scale of seconds is essential to predict objects' trajectories or to select relevant sensory information. What neurophysiological mechanism underlies the temporal precision in anticipating the occurrence of events? In a recent article, we demonstrated that the sensori-motor system predictively controls neural oscillations in time to optimize sensory selection. However, whether and how the same oscillatory processes can be used to keep track of elapsing time and evaluate short durations remains unclear. Here, we aim at testing the hypothesis that the brain tracks durations by converting (external, objective) elapsing time into an (internal, subjective) oscillatory phase-angle. To test this, we measured magnetoencephalographic oscillatory activity while participants performed a delayed-target detection task. In the delayed condition, we observe that trials that are perceived as longer are associated with faster delta-band oscillations. This suggests that the subjective indexing of time is reflected in the range of phase-angles covered by delta oscillations during the pre-stimulus period. This result provides new insights into how we predict and evaluate temporal structure and support models in which the active entrainment of sensori-motor oscillatory dynamics is exploited to track elapsing time

Cortical oscillations and sensory predictions

Many theories of perception are anchored in the central notion that the brain continuously updates an internal model of the world to infer the probable causes of sensory events. In this framework, the brain needs not only to predict the causes of sensory input, but also when they are most likely to happen. In this article, we review the neurophysiological bases of sensory predictions of "what' (predictive coding) and 'when' (predictive timing), with an emphasis on low-level oscillatory mechanisms. We argue that neural rhythms offer distinct and adapted computational solutions to predicting 'what' is going to happen in the sensory environment and 'when'

Adaptive oscillators support Bayesian prediction in temporal processing.

Humans excel at predictively synchronizing their behavior with external rhythms, as in dance or music performance. The neural processes underlying rhythmic inferences are debated: whether predictive perception relies on high-level generative models or whether it can readily be implemented locally by hard-coded intrinsic oscillators synchronizing to rhythmic input remains unclear and different underlying computational mechanisms have been proposed. Here we explore human perception for tone sequences with some temporal regularity at varying rates, but with considerable variability. Next, using a dynamical systems perspective, we successfully model the participants behavior using an adaptive frequency oscillator which adjusts its spontaneous frequency based on the rate of stimuli. This model better reflects human behavior than a canonical nonlinear oscillator and a predictive ramping model-both widely used for temporal estimation and prediction-and demonstrate that the classical distinction between absolute and relative computational mechanisms can be unified under this framework. In addition, we show that neural oscillators may constitute hard-coded physiological priors-in a Bayesian sense-that reduce temporal uncertainty and facilitate the predictive processing of noisy rhythms. Together, the results show that adaptive oscillators provide an elegant and biologically plausible means to subserve rhythmic inference, reconciling previously incompatible frameworks for temporal inferential processes