Biology subjects

Guilleminot, P. H.

Publications and source records attributed to Guilleminot, P. H..

3 recordsLinked to original sources

bioRxiv2026

Cortical encoding of probabilistic temporal predictions during speech perception

The temporal structure of speech has traditionally been characterized by the rhythmicity of its canonical linguistic units (phonemes, syllables, words), each summarized by a mean occurrence rate. While valid, this view overlooks whether speech carries a finer, context-dependent and probabilistic temporal structure that could support temporal predictive coding during listening. Using large French and English speech corpora, we trained models of increasing complexity to predict the onsets of linguistic units. Recurrent neural networks (RNNs) outperform mean-rate and hazard-rate models, showing that the variability around these rates is not noise but a temporal structure shaped by local context, statistically predictable across phonemes, syllables and words. Recording from 7,698 intracerebral electrodes in 53 neurosurgical patients listening to natural speech, we next show that the models' output), the continuous probability of an upcoming onset (when), explains neural activity beyond acoustic and linguistic content (what) features, with markedly stronger effects for RNNs than for mean- or hazard-rate models. This dynamic neural prediction of when an onset will occur is dissociable from the encoding of linguistic content, relying on largely distinct channel populations. Temporal predictions engage a distributed cortical network extending from bilateral temporal cortex into left frontal and sensorimotor regions. Together, these results establish temporal prediction in speech as a dynamic, context-dependent and probabilistic process in its own right.

neuroscience↗

bioRxiv2025

Two forms of uncertainty hierarchically shape lexical predictions during natural speech processing

Prediction under uncertainty is a hallmark of human cognition(Friston, 2010), yet how the brain represents uncertainty remains unresolved(Bach and Dolan, 2012). Speech provides a powerful test case: lexical predictions involve thou-sands of alternatives, making classical Shannon entropy an ambiguous measure of uncertainty. Here we explored a generalization of Shannon entropy, the Renyi entropy family (Renyi, 1961), combined with information-theoretic tools and whole-brain intracranial EEG during naturalistic listening. Word-related neural activity was best explained by two complementary forms of uncertainty: dis-persion, reflecting the number of plausible alternatives, and strength, reflecting the probability of the most likely word. These uncertainties were consistently encoded in each participant by distinct neural populations, with opposing com-putational goals. Dispersion shapes anticipatory sensory activity and dampens responses to unexpected inputs, consistent with Bayesian optimization(Pouget et al., 2013). Strength instead emerges only for surprising words in lexical circuits, amplifying prediction errors and promoting information seeking. Despite bidirec-tional exchange between these two populations, their dynamics are dominated by local computations(Heilbron et al., 2022), challenging purely hierarchical models of predictive processing. Our findings reveal that the brain approximates large lexical probability distributions using multiple summary statistics, providing a flexible, low-dimensional representation of uncertainty in complex cognitive tasks and advancing principles of predictive processing across cognition.

neuroscience↗

bioRxiv2023

Audiotactile stimulation can improve syllable discrimination through multisensory integration in the theta frequency band

Syllables are an essential building block of speech. We recently showed that tactile stimuli linked to the perceptual centers of syllables in continuous speech can improve speech comprehension. The rate of syllables lies in the theta frequency range, between 4 and 8 Hz, and the behavioural effect appears linked to multisensory integration in this frequency band. Because this neural activity may be oscillatory, we hypothesized that a behavioural effect may also occur not only while but also after this activity has been evoked or entrained through vibrotactile pulses. Here we show that audiotactile integration regarding the perception of single syllables, both on the neural and on the behavioural level, is consistent with this hypothesis. We first stimulated subjects with a series of vibrotactile pulses and then presented them with a syllable in background noise. We show that, at a delay of 200 ms after the last vibrotactile pulse, audiotactile integration still occurred in the theta band and syllable discrimination was enhanced. Moreover, the dependence of both the neural multisensory integration as well as of the behavioral discrimination on the delay of the audio signal with respect to the last tactile pulse was consistent with a damped oscillation. In addition, the multisensory gain is correlated with the syllable discrimination score. Our results therefore evidence the role of the theta band in audiotactile integration and provide evidence that these effect may involve oscillatory activity that still persists after the tactile stimulation.

neuroscience↗