The bio-digital nexus: Exploring the fusion of biological neural networks and artificial intelligence

For decades, neuroscience and artificial intelligence (AI) have shared a symbiotic history, with biological neural networks (BNNs) serving as the foundational blueprint for early computational models. While AI has since evolved into a powerhouse of data processing and pattern recognition, it often lacks the energy efficiency, plastic adaptability, and high-level generalization inherent in biological systems. Conversely, the complexity of the living brain presents a challenge that traditional analytical methods struggle to unravel. With all of this, today, we have entered the "Bio-Digital Nexus," a frontier where the boundaries between carbon-based cognition and silicon-based computation are increasingly blurred. Advances in neuroengineering, high-resolution neural recording, and deep learning now allow us to not only simulate biological processes but to directly interface artificial systems with living tissue. This convergence represents a pivotal shift from merely mimicking intelligence to actively integrating biological and synthetic architectures.The primary goal of this Research Topic is to bridge the persistent gap between the flexible, resilient nature of biological intelligence and the specialized efficiency of computational systems. Despite the success of modern AI, current architectures remain rigid and energy-intensive compared to the human brain, and furthermore, our ability to restore lost neurological functions or enhance cognitive processes remains limited by our understanding of neural decoding and circuit dynamics.To address these challenges, this collection aims to foster a multi-disciplinary dialogue that leverages AI to model complex neural interactions while using biological insights to refine computational frameworks. We seek to explore how "bio-hybridity" can solve grand challenges in motor restoration, cognitive augmentation, and adaptive robotics. By synthesizing these diverse perspectives, this Research Topic intends to establish a foundational framework for "Hybrid Intelligence," ensuring that the next generation of AI is not only inspired by the brain but is capable of working in seamless concert with it.We invite contributors to submit articles that explore the interface between biological and artificial intelligence, the scope of this topic is broad, yet focused on the functional and theoretical integration of these two domains. Contributors are encouraged to address the following themes:- Bio-Inspired AI and Algorithms: Architectures and memory consolidation mechanisms informed by brain connectivity and plasticity.- Computational Neuroscience: Mathematical models of biological neurons, synaptic dynamics, and large-scale neural circuits.- Neural Interfaces and Robotics: Brain-computer interfaces (BCIs) and AI-driven decoding for motor or cognitive restoration.- Neuromorphic Engineering: Hardware and software designed to emulate the efficiency of biological nervous systems.- Cognitive Modeling: AI-based simulations of learning, perception, and human decision-making processes.- Bio-Hybrid Systems: The integration of living neural cultures or organoids with computational platforms.- Ethical and Theoretical Frameworks: The future of hybrid intelligence and the ethical implications of synthetic-biological integration. Topic editors: Tamara Zhukabayeva, Qurat-ul-ain Mastoi, Fadia Ali Khan Source: https://www.frontiersin.org/research-topics/80159/the-bio-digital-nexus-exploring-the-fusion-of-biological-neural-networks-and-artificial-intelligence