Phonotopic Resonance Computing: A Bio-Inspired Framework for Audio-Visual Data Fusion Using Cortical Column Dynamics

Posted: Oct 28, 2025

• Dr. Elara Vance
• Prof. Kenji Tanaka
• Dr. Isabella Rossi

Abstract

Multimodal data fusion represents a fundamental challenge in artificial intelligence, with conventional approaches often treating different sensory modalities as independent streams to be combined through statistical methods. While techniques such as cross-attention and tensor fusion have shown promise, they fail to capture the dynamic, resonant nature of biological perception where auditory and visual information interact through complex oscillatory networks in the cortex. This paper introduces Phonotopic Resonance Computing (PRC), a radical departure from existing fusion paradigms. Inspired by the tonotopic organization of the auditory cortex and its integration with visual processing through thalamocortical loops, PRC models multimodal interaction as coupled dynamical systems rather than static feature combinations. Our approach addresses three key limitations of current methods: (1) the inability to capture temporal hierarchies in cross-modal relationships, (2) the computational inefficiency of exhaustive cross-modal attention, and (3) the lack of biological plausibility in fusion mechanisms. We formulate two research questions: (RQ1) Can cortical column dynamics provide a more effective foundation for multimodal fusion than statistical correlation methods? (RQ2) Does resonance-based computation offer advantages in robustness and efficiency for real-world audio-visual tasks?