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Cross-Modal Alignment for Semantic Processing and Effective Representation

Project description

Integrating neuroscience and AI to advance understanding of human cognition

Understanding how the brain processes and integrates information across different senses is crucial for neuroscience and AI. Advancing understanding could unlock groundbreaking applications in neural decoding, assistive technologies and conversational AI. With the support of the Marie Skłodowska-Curie Actions programme, the CASPER project will merge cognitive neuroscience with cutting-edge AI techniques. It will employ graph neural networks and large language models to integrate and represent diverse data types, including text, audio, speech, images and neural signals (fMRI, EEG and MEG). CASPER’s goal is to push the boundaries of multimodal learning and neural representation recording, facilitating speech reconstruction, cross-modal content generation and zero-shot learning. By aligning AI with neural activity patterns, CASPER should help redefine cross-modal representation and neural signal interpretation.

Objective

Cross-Modal Alignment for Semantic Processing and Effective Representation (CASPER) project is pioneering a novel framework that synergizes cognitive neuroscience with advanced artificial intelligence methodologies. By employing Graph Neural Networks (GNNs) and Large Language Models (LLMs), CASPER enables seamless integration and representation of diverse modalities, such as text, audio, speech, images, and neural signals, including fMRI, EEG, and MEG. The project’s core aim is to push the frontier of multimodal learning and neural representation decoding, facilitating complex tasks like speech reconstruction, cross-modal content generation, and zero-shot learning. Through the alignment of AI systems with neural activity patterns, CASPER strives to enhance our understanding of human cognition while unlocking groundbreaking applications in neural decoding, assistive technologies, and conversational AI. This transformative approach is poised to redefine the standards of cross-modal representation and neural signal interpretation, marking a significant advancement in the field.

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Keywords

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-2024-PF-01

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Coordinator

UNIVERSITA CA' FOSCARI VENEZIA
Net EU contribution
€ 209 483,28
Address
DORSODURO 3246
30123 Venezia
Italy
Region
Nord-Est Veneto Venezia
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Partners (2)