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.

Plasticity After Hearing Rehabilitation in the Aging Brain.

Age-related hearing loss, presbycusis, is an unavoidable sensory degradation, often associated with the progressive decline of cognitive and social functions, and dementia. It is generally considered a natural consequence of the inner-ear deterioration. However, presbycusis arguably conflates a wide array of peripheral and central impairments. Although hearing rehabilitation maintains the integrity and activity of auditory networks and can prevent or revert maladaptive plasticity, the extent of such neural plastic changes in the aging brain is poorly appreciated. By reanalyzing a large-scale dataset of more than 2200 cochlear implant users (CI) and assessing the improvement in speech perception from 6 to 24 months of use, we show that, although rehabilitation improves speech understanding on average, age at implantation only minimally affects speech scores at 6 months but has a pejorative effect at 24 months post implantation. Furthermore, older subjects (>67 years old) were significantly more likely to degrade their performances after 2 years of CI use than the younger patients for each year increase in age. Secondary analysis reveals three possible plasticity trajectories after auditory rehabilitation to account for these disparities: Awakening, reversal of deafness-specific changes; Counteracting, stabilization of additional cognitive impairments; or Decline, independent pejorative processes that hearing rehabilitation cannot prevent. The role of complementary behavioral interventions needs to be considered to potentiate the (re)activation of auditory brain networks.

Acoustic features drive event segmentation in speech.

While our perceptual experience seems to unfold continuously over time, episodic memory preserves distinct events for storage and recollection. Previous work shows that stability in encoding context serves to temporally bind individual items into sequential composite events. This phenomenon has been almost exclusively studied using visual and spatial memory paradigms. Here we adapt these paradigms to test the role of speaker regularity for event segmentation of complex auditory information. The results of our auditory paradigm replicate the findings in other sensory modalities-finding greater within-event temporal memory for items within speaker-bound events and greater source memory for items at speaker or event transitions. The task we use significantly extends the ecological validity of past paradigms by allowing participants to encode the stimuli without any suggestions on the part of the experimenter. This unique property of our design reveals that, while memory performance is strongly dependent on self-reported mnemonic strategy, behavioral effects associated with event segmentation are robust to changes in mnemonic strategy. Finally, we consider the effect of serial position on segmentation effects during encoding and present a modeling approach to estimate the independent contribution of event segmentation. These findings provide several lines of evidence suggesting that contextual stability in perceptual features drives segmentation during word listening and supports a modality-independent role for mechanisms involved in event segmentation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neural oscillations are a start toward understanding brain activity rather than the end.

Does rhythmic neural activity merely echo the rhythmic features of the environment, or does it reflect a fundamental computational mechanism of the brain? This debate has generated a series of clever experimental studies attempting to find an answer. Here, we argue that the field has been obstructed by predictions of oscillators that are based more on intuition rather than biophysical models compatible with the observed phenomena. What follows is a series of cautionary examples that serve as reminders to ground our hypotheses in well-developed theories of oscillatory behavior put forth by theoretical study of dynamical systems. Ultimately, our hope is that this exercise will push the field to concern itself less with the vague question of "oscillation or not" and more with specific biophysical models that can be readily tested.

An oscillator model better predicts cortical entrainment to music.

A body of research demonstrates convincingly a role for synchronization of auditory cortex to rhythmic structure in sounds including speech and music. Some studies hypothesize that an oscillator in auditory cortex could underlie important temporal processes such as segmentation and prediction. An important critique of these findings raises the plausible concern that what is measured is perhaps not an oscillator but is instead a sequence of evoked responses. The two distinct mechanisms could look very similar in the case of rhythmic input, but an oscillator might better provide the computational roles mentioned above (i.e., segmentation and prediction). We advance an approach to adjudicate between the two models: analyzing the phase lag between stimulus and neural signal across different stimulation rates. We ran numerical simulations of evoked and oscillatory computational models, showing that in the evoked case,phase lag is heavily rate-dependent, while the oscillatory model displays marked phase concentration across stimulation rates. Next, we compared these model predictions with magnetoencephalography data recorded while participants listened to music of varying note rates. Our results show that the phase concentration of the experimental data is more in line with the oscillatory model than with the evoked model. This finding supports an auditory cortical signal that (i) contains components of both bottom-up evoked responses and internal oscillatory synchronization whose strengths are weighted by their appropriateness for particular stimulus types and (ii) cannot be explained by evoked responses alone.

Cortical entrainment to music and its modulation by expertise.

Recent studies establish that cortical oscillations track naturalistic speech in a remarkably faithful way. Here, we test whether such neural activity, particularly low-frequency (<8 Hz; delta-theta) oscillations, similarly entrain to music and whether experience modifies such a cortical phenomenon. Music of varying tempi was used to test entrainment at different rates. In three magnetoencephalography experiments, we recorded from nonmusicians, as well as musicians with varying years of experience. Recordings from nonmusicians demonstrate cortical entrainment that tracks musical stimuli over a typical range of tempi, but not at tempi below 1 note per second. Importantly, the observed entrainment correlates with performance on a concurrent pitch-related behavioral task. In contrast, the data from musicians show that entrainment is enhanced by years of musical training, at all presented tempi. This suggests a bidirectional relationship between behavior and cortical entrainment, a phenomenon that has not previously been reported. Additional analyses focus on responses in the beta range (∼15-30 Hz)-often linked to delta activity in the context of temporal predictions. Our findings provide evidence that the role of beta in temporal predictions scales to the complex hierarchical rhythms in natural music and enhances processing of musical content. This study builds on important findings on brainstem plasticity and represents a compelling demonstration that cortical neural entrainment is tightly coupled to both musical training and task performance, further supporting a role for cortical oscillatory activity in music perception and cognition.

Delta-Beta Coupled Oscillations Underlie Temporal Prediction Accuracy.

The ability to generate temporal predictions is fundamental for adaptive behavior. Precise timing at the time-scale of seconds is critical, for instance to predict trajectories or to select relevant information. What mechanisms form the basis for such accurate timing? Recent evidence suggests that (1) temporal predictions adjust sensory selection by controlling neural oscillations in time and (2) the motor system plays an active role in inferring "when" events will happen. We hypothesized that oscillations in the delta and beta bands are instrumental in predicting the occurrence of auditory targets. Participants listened to brief rhythmic tone sequences and detected target delays while undergoing magnetoencephalography recording. Prior to target occurrence, we found that coupled delta (1-3 Hz) and beta (18-22 Hz) oscillations temporally align with upcoming targets and bias decisions towards correct responses, suggesting that delta-beta coupled oscillations underpin prediction accuracy. Subsequent to target occurrence, subjects update their decisions using the magnitude of the alpha-band (10-14 Hz) response as internal evidence of target timing. These data support a model in which the orchestration of oscillatory dynamics between sensory and motor systems is exploited to accurately select sensory information in time.

Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing.

A growing body of research suggests that intrinsic neuronal slow (<10 Hz) oscillations in auditory cortex appear to track incoming speech and other spectro-temporally complex auditory signals. Within this framework, several recent studies have identified critical-band temporal envelopes as the specific acoustic feature being reflected by the phase of these oscillations. However, how this alignment between speech acoustics and neural oscillations might underpin intelligibility is unclear. Here we test the hypothesis that the 'sharpness' of temporal fluctuations in the critical band envelope acts as a temporal cue to speech syllabic rate, driving delta-theta rhythms to track the stimulus and facilitate intelligibility. We interpret our findings as evidence that sharp events in the stimulus cause cortical rhythms to re-align and parse the stimulus into syllable-sized chunks for further decoding. Using magnetoencephalographic recordings, we show that by removing temporal fluctuations that occur at the syllabic rate, envelope-tracking activity is reduced. By artificially reinstating these temporal fluctuations, envelope-tracking activity is regained. These changes in tracking correlate with intelligibility of the stimulus. Together, the results suggest that the sharpness of fluctuations in the stimulus, as reflected in the cochlear output, drive oscillatory activity to track and entrain to the stimulus, at its syllabic rate. This process likely facilitates parsing of the stimulus into meaningful chunks appropriate for subsequent decoding, enhancing perception and intelligibility.