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Sound meets meaning: An orchestration of coupled non-linear systems to incorporate transient dynamics with oscillatory inter-areal cortical communication.

Project description

Harmonising brain and machine speech processing

Supported by the Marie Skłodowska-Curie Actions programme, the ORCHESTRAS project explores how the human brain effortlessly processes and predicts speech by synthesising two traditional scientific views into one model: oscillatory rhythms and evoked neural responses. At its core is phase-amplitude coupling, a biological mechanism where brain waves synchronise, hypothesised to underlie the brain's ability to track linguistic hierarchies, from sounds to syntax and meaning. Using oscillatory models and brain connectivity data, the project simulates dynamic 'blueprints' during speech processing. ORCHESTRAS aims to identify language processing markers and integrate them as neural architectural priors into models such as Transformers to create faster, more efficient language systems. This research bridges cognitive science and next-generation AI, revolutionising our understanding of both natural and artificial communication.

Objective

ORCHESTRAS posits a new a theoretical framework for a mechanistic understanding of neural tracking of speech by synthesizing views from both the oscillatory and evoked-like paradigms. It builds upon work from computational neuroscience on whole-brain modelling together with the emergent field of NeuroAI where artificial neural networks are augmented with neural architectural priors which serves in bringing inductive biases to AI models that allow for faster learning and more efficient inference. ORCHESTRAS’ oscillator-based model naturally aligns with the concept of neural oscillations as a mechanism for prediction and expectation. The core hypothesis lies in the idea that event-based predictions (e.g. after hearing a context leading to a strong word or phoneme prediction) elicit a transient response which synchronises slow-phase signal between areas. In turn, that phase modulates higher frequency oscillations reflected in power increase observed in sentence building or upon unexpected words. The interplay between transient and oscillatory dynamic via phase-amplitude coupling is the key linkage of the proposed modelling approach. In other words, we are looking at integrating evoked potentials dynamically with oscillatory activity, a synergic interaction allowing to map linguistic predictions to oscillatory brain activity. The project will be developed along two main approaches: (1) consolidating our theoretical understanding of neural tracking of speech using whole-brain modelling of non-linear oscillators and (2) bridging with AI systems for language modelling such as Transformers by enhancing them with novel attention mechanism based on phase-ampltidude coupling akin to the biological brain. The findings are expected to have significant impact in both our theoretical understanding of speech processing in the human brain and in our practical usage of large language models in AI systems.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
Net EU contribution
€ 209 914,56
Address
PASEO MIKELETEGI 69 2
20009 San Sebastian
Spain
Region
Noreste País Vasco Gipuzkoa
Activity type
Research Organisations
Links
Total cost
No data