Biology subjects

Maye, A.

Publications and source records attributed to Maye, A..

6 recordsLinked to original sources

bioRxiv2026

Oscillatory sensory stimulation in the delta-band enhancestemporal prediction performance

Predicting the time point when an event will occur is fundamental for adaptive behavior, yet it remains unresolved whether temporal prediction can be influenced by low-frequency rhythmic modulation of sensory stimuli. Here, we tested whether external rhythmic sensory stimulation at a frequency in the delta range (0.5 - 3 Hz) alters performance in a visual temporal prediction task. Participants judged whether a moving visual stimulus reappeared too early or too late after disappearing behind an occluder, while the temporal structure of crossmodal sensory input was manipulated across two behavioral sessions. Results indicated that in the visual-auditory conditions, oscillatory stimulation in either the visual or auditory modality improved performance, whereas decaying sensory intensity over time impaired performance. In visual-tactile conditions, oscillatory visual stimulation also enhanced sensitivity, but rhythmic tactile stimulation did not produce a comparable benefit in performance. Critically, tactile stimulation improved performance only when aligned to the expected disappearance of the visual stimulus, demonstrating that the phase relationship between sensory input and intrinsic delta oscillations is behaviorally relevant. Together, these findings indicate that temporal prediction depends on the temporal structure of sensory input and support the relevance of delta-band oscillations in predictive behavior across and within sensory modalities. Hence, rhythmic modulation of sensory stimuli may provide a tool to enhance temporal prediction accuracy by stimulating oscillatory neural dynamics.

neuroscience↗

bioRxiv2025

The sensorimotor basis of subjective experience in social synchronization behavior

1.The sensorimotor contingency (SMC) theory addresses action and perception as constitutive factors to one another - what is being perceived depends on what we do and vice versa. Accordingly, perception is seen as an active process of probing the environment and receiving feedback from it. These action-effect patterns may also be a predominant factor in social interactions. They can manifest in the phenomenon of synchronization, for example, when applause, gait, or posture in conversations synchronize unintentionally and form the basis of the concept of socially deployed sensorimotor contingencies (socSMCs). In this study, we introduce and compare measures used to study complex systems in order to quantify the information-theoretic basis of socSMCs. Two human participants had to synchronize arm movements in a full body virtual reality (VR) environment with each other. We aimed to evaluate the information-theoretic measures transfer entropy and mutual information in this complex motion synchronization task. Furthermore, in our experiment participants shared a mutual sensation of synchronicity and creativity for their interaction solely based on their movements. These subjective ratings of synchronicity and creativity can be predicted using transfer entropy and mutual information, showing that informational coupling between agents is relevant to subjective experience of interaction as described by the concept of socSMCs.

neuroscience↗

bioRxiv2024

Delta phase-dependent modulation of temporal predictions by parietal transcranial alternating current stimulation

BackgroundPrevious research has shown that temporal prediction processes are associated with phase resets of low-frequency delta oscillations in a network of parietal, sensory and frontal areas during non-rhythmic sensory stimulation. Transcranial alternating current stimulation (tACS) modulates perceptually relevant brain oscillations in a frequency and phase-specific manner, allowing the assessment of their functional qualities in certain cognitive functions like temporal prediction. ObjectiveWe addressed the relation between oscillatory activity and temporal prediction by using tACS to manipulate brain activity in a sinusoidal manner. This enables the investigation of the relevance of low-frequency oscillations phase for temporal prediction. MethodsDelta tACS was applied over the left and right parietal cortex in two separate unimodal and crossmodal experiments. Participants judged either the visual or the tactile reappearance of a uniformly moving visual stimulus, which shortly disappeared behind and occluder. Using an intermittent electrical stimulation protocol, tACS was applied with six different phase shifts relative to sensory stimulation in both experiments while participants performed a temporal prediction task. Additionally, a computational model was developed and analysed to elucidate oscillation-based functional principles for the generation of temporal predictions. ResultsOnly in the unimodal experiment, the application of delta tACS resulted in a phase-dependent modulation of temporal prediction performance. By considering the effect of sustained tACS in the computational model, we demonstrate that the entrained dynamics can phase-specifically modulate temporal prediction accuracy. ConclusionOur findings suggest that phase-specific neuromodulation through delta tACS can influence temporal prediction accuracy in a unimodal context. This provides support to the notion that low-frequency delta oscillations are of causal relevance for temporal prediction.

neuroscience↗

bioRxiv2019

Dynamic Predictions: Oscillatory Mechanisms Underlying Multisensory Sequence Processing

Neural oscillations have been proposed to be involved in predictive processing, however less addressed in the multisensory context. In the present study, we recorded cortical activity using magnetoencephalography during an audiovisual serial prediction task in which participants had to acquire stimulus sequences and to monitor whether subsequent probe items complied with the sequence. In a given trial, either visual or auditory features of the bimodal stimuli were task-relevant. Task-related changes of power and coupling of neural oscillations were analyzed using a data-driven clustering approach. We observed prediction-related theta-band (5-7 Hz) coupling in a network involving the cingulate, premotor, prefrontal, and superior temporal regions. The behavioral performance of participants varied as a function of the phase delay of the coupling between different regions in this network. . Two additional spectro-temporal clusters were detected in which beta power (11-16 Hz and 16-22 Hz, respectively) was stronger if the previous or the following stimuli were the same as the current one in the sequence. These clusters spatially overlapped with the theta-band prediction cluster, and interacted with it through cross-frequency coupling. Our results offer novel insights into the multi-timescale neural dynamics underlying multisensory predictions, suggesting that oscillations in multiple frequency ranges, as well as coupling within and across frequencies, may be critical for multisensory sequence processing.

neuroscience↗

bioRxiv2019

An oscillator ensemble model of sequence learning

Learning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral fingerprint which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this fingerprint by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of complexity of the sequence to be memorized. Finally, we suggest an extension of the model for processing sequences that extend over several sensory modalities.

neuroscience↗

bioRxiv2019

Delta phase resetting mediates non-rhythmic temporal prediction

The phase of neural oscillatory activity aligns to the predicted onset of upcoming stimulation. Whether such phase alignments represent phase resets of underlying neural oscillations or just rhythmically evoked activity, and whether they can be observed in a rhythm-free visual context, however, remains unclear. Here, we recorded the magnetoencephalogram while participants were engaged in a temporal prediction task judging the visual or tactile reappearance of a uniformly moving stimulus. The prediction conditions were contrasted with a control condition to dissociate phase adjustments of neural oscillations from stimulus-driven activity. We observed stronger delta band inter-trial phase consistency (ITPC) in a network of sensory, parietal and frontal brain areas, but no power increase reflecting stimulus-driven or prediction-related processes. Delta ITPC further correlated with prediction performance in the cerebellum and visual cortex. Our results provide evidence that phase alignments of low-frequency neural oscillations underlie temporal predictions in a non-rhythmic visual and crossmodal context.

neuroscience↗