Beta power encodes contextual estimates of temporal event probability in the human brain

Overt Oculomotor Behavior Reveals Covert Temporal Predictions

Our eyes move in response to stimulus statistics, reacting to surprising events, and adapting to predictable ones. Cortical and subcortical pathways contribute to generating context-specific eye-movement dynamics, and oculomotor dysfunction is recognized as one the early clinical markers of Parkinson's disease (PD). We asked if covert computations of environmental statistics generating temporal expectations for a potential target are registered by eye movements, and if so, assuming that temporal expectations rely on motor system efficiency, whether they are impaired in PD. We used a repeating tone sequence, which generates a hazard rate distribution of target probability, and analyzed the distribution of blinks when participants were waiting for the target, but the target did not appear. Results show that, although PD participants tend to produce fewer and less temporally organized blink events relative to healthy controls, in both groups blinks became more suppressed with increasing target probability, leading to a hazard rate of oculomotor inhibition effects. The covert generation of temporal predictions may reflect a key feature of cognitive resilience in Parkinson's Disease.

Dynamics underlying auditory-object-boundary detection in primary auditory cortex

Auditory object analysis requires the fundamental perceptual process of detecting boundaries between auditory objects. However, the dynamics underlying the identification of discontinuities at object boundaries are not well understood. Here, we employed a synthetic stimulus composed of frequency-modulated ramps known as 'acoustic textures', where boundaries were created by changing the underlying spectrotemporal statistics. We collected magnetoencephalographic (MEG) data from human volunteers and observed a slow (<1 Hz) post-boundary drift in the neuromagnetic signal. The response evoking this drift signal was source localised close to Heschl's gyrus (HG) bilaterally, which is in agreement with a previous functional magnetic resonance imaging (fMRI) study that found HG to be involved in the detection of similar auditory object boundaries. Time-frequency analysis demonstrated suppression in alpha and beta bands that occurred after the drift signal.

Neural correlates of speech and limb motor timing deficits revealed by aberrant beta band desynchronization in Parkinson's disease

OBJECTIVE

We used a classical motor reaction time paradigm to examine the effects of Parkinson's disease (PD) on the mechanisms of speech production and upper limb movement.

METHODS

Electro-encephalography (EEG) signals were recorded in PD and control groups during speech vowel production and button press tasks in response to temporally predictable and unpredictable visual stimuli.

RESULTS

Motor reaction times were slower in PD vs. control group independent of stimulus timing and movement modality. This effect was accompanied by stronger desynchronizations of low beta (13-18 Hz) and high beta (18-25 Hz) band neural oscillations in PD vs. control prior to the onset of speech and hand movement. In addition, pre-movement desynchronization of beta band oscillations were correlated with motor reaction time in control subjects with faster responses associated with weaker beta band desynchronizations during the planning phase of movement. However, no such effect was found in the PD group.

CONCLUSIONS

We suggest that the aberrant pattern of beta band desynchronization is a neural correlate of speech and upper limb motor timing deficits as a result of cortico-striatal pathology in PD.

SIGNIFICANCE

These findings motivate interventions targeted toward normalizing beta band activities for improving speech and upper limb movement timing in PD.

Expectancy-based rhythmic entrainment as continuous Bayesian inference

When presented with complex rhythmic auditory stimuli, humans are able to track underlying temporal structure (e.g., a "beat"), both covertly and with their movements. This capacity goes far beyond that of a simple entrained oscillator, drawing on contextual and enculturated timing expectations and adjusting rapidly to perturbations in event timing, phase, and tempo. Previous modeling work has described how entrainment to rhythms may be shaped by event timing expectations, but sheds little light on any underlying computational principles that could unify the phenomenon of expectation-based entrainment with other brain processes. Inspired by the predictive processing framework, we propose that the problem of rhythm tracking is naturally characterized as a problem of continuously estimating an underlying phase and tempo based on precise event times and their correspondence to timing expectations. We present two inference problems formalizing this insight: PIPPET (Phase Inference from Point Process Event Timing) and PATIPPET (Phase and Tempo Inference). Variational solutions to these inference problems resemble previous "Dynamic Attending" models of perceptual entrainment, but introduce new terms representing the dynamics of uncertainty and the influence of expectations in the absence of sensory events. These terms allow us to model multiple characteristics of covert and motor human rhythm tracking not addressed by other models, including sensitivity of error corrections to inter-event interval and perceived tempo changes induced by event omissions. We show that positing these novel influences in human entrainment yields a range of testable behavioral predictions. Guided by recent neurophysiological observations, we attempt to align the phase inference framework with a specific brain implementation. We also explore the potential of this normative framework to guide the interpretation of experimental data and serve as building blocks for even richer predictive processing and active inference models of timing.