BRyBI

Our ability to perceive speech remains resilient to variations in voice, rate, and temporal interruptions. While inference models addressed the first two [1], the computational principles by which speech understanding remains impervious to temporal restructuring are largely unexplored. Previous studies indicated intriguing recoveries in comprehension when speech is temporally modulated [2-4]. We show that predictive coding, constrained by endogenous rhythms, accounts for these quizzical results and enables robust lexical speech recovery. We build upon the major hypotheses that the rhythmic st

Speech processing, with its temporal cadence and multi-scale syntactic invariants (syllables, words), is a paradigmatic example where rhythms have been proposed to play a key role [1], with a speech-modulated hierarchical structure of intercoupled cortical oscillations correlating with successful comprehension. Experiments show that speech recognition remains largely intact when compressed up to a certain temporal factor [2] and the re-spacing of chunks of incomprehensible compressed speech with silences recovers comprehension. We hypothesize that rhythm-based top-down semantic context inferen

Rhythms stretching across multiple interacting frequencies and spatial scales are ubiquitous in brain activity during complex cognitive tasks. Yet their functional significance is hotly debated between a structural epiphenomenon of brain activity and mechanisms implementing computations. Speech processing, with its temporal cadence and multi-scale of syntactic invariants (syllables, words), is a paradigmatic example where rhythms have been proposed to play a key role [1], with a speech-modulated hierarchical structure of intercoupled cortical oscillations correlating with successful comprehens