Intracellular Dynamics as a Computational Substrate in Neural and Neuromorphic Systems

Biological neurons perform extensive computation not only through spikes and synaptic interactions but also through rich internal dynamics unfolding across multiple spatial and temporal scales. Processes such as subthreshold integration, dendritic and compartmental computation, adaptation, and state retention shape how inputs are filtered, transformed, and transmitted. These within-neuron mechanisms form a computational substrate that works alongside spike-mediated communication to support learning, memory, and robust information processing. In neuromorphic computing, analog and hybrid circuits can emulate similar subthreshold and internal-state behaviors, potentially extending beyond purely spike-based abstractions toward more efficient and context-sensitive computation. Recognizing intracellular and internal-state dynamics as active computational elements opens new possibilities for designing neuromorphic systems that better mirror biological efficiency and flexibility.This Research Topic aims to explore the role of intracellular — or more generally internal-state — dynamics as substrates for computation in both neural and neuromorphic systems. It seeks to unify perspectives from theoretical neuroscience, computational modeling, and hardware design to understand how subthreshold, dendritic, and compartmental mechanisms interact with spike generation and synaptic signaling. The goal is to elucidate the forms of computation such dynamics enable, identify their organizing principles, and demonstrate their realizations in neuromorphic circuits and device-level architectures. Of particular interest are studies that quantify computational advantages, reveal mechanistic parallels between biological and synthetic systems, or propose abstractions that inform hardware implementation. By bringing together insights from biology and engineering, this Topic aims to establish intracellular computation and state dynamics as a guiding principle for neuromorphic design.To gather further insights into internal-state computation in neural and neuromorphic contexts, we welcome contributions addressing, but not limited to, the following themes:• Theoretical and computational models of subthreshold and pre-spike processing• Dendritic and multicompartment mechanisms for within-neuron computation• Analog and mixed-signal circuit implementations of subthreshold or adaptive dynamics• Emerging device platforms (e.g., memristive, ferroelectric, or spintronic systems) enabling internal-state computing• Functional roles of subthreshold dynamics in learning, memory, temporal coding, robustness, and energy efficiencyThis Research Topic welcomes Original Research, Reviews, and Perspectives that examine how internal-state and intracellular dynamics serve as active computational substrates in neuromorphic and neural systems. Submissions focused solely on device physics, materials, or theoretical neuroscience without a clear link to neuromorphic implementation or design principles will fall outside the scope of this Topic. Topic editors: G. William Chapman, FRANCES CHANCE, Jean Anne Incorvia Source: https://www.frontiersin.org/research-topics/82534/intracellular-dynamics-as-a-computational-substrate-in-neural-and-neuromorphic-systems