Integrating neural cultures developed through synthetic biology methods with digital
computing has enabled the early development of Synthetic Biological Intelligence (SBI) …

Highlights•The three-factor framework describes various learning rules in a unified
way.•Third factors can encode reward, attention, summary statistics, or supervised …

Integrating neurons into digital systems may enable performance infeasible with silicon
alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive …

Biological computing (or biocomputing) offers potential advantages over silicon-based
computing in terms of faster decision-making, continuous learning during tasks, and greater …

Spiking neural networks (SNNs) have shown clear advantages over traditional artificial
neural networks (ANNs) for low latency and high computational efficiency, due to their event …

This work considers a class of canonical neural networks comprising rate coding models,
wherein neural activity and plasticity minimise a common cost function—and plasticity is …

Empirical applications of the free-energy principle are not straightforward because they
entail a commitment to a particular process theory, especially at the cellular and synaptic …

Neuronal computations rely upon local interactions across synapses. For a neuronal
network to perform inference, it must integrate information from locally computed messages …

This paper considers the emergence of a generalised synchrony in ensembles of coupled
self-organising systems, such as neurons. We start from the premise that any self-organising …

In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based
neurorobotic systems, can interact with the external world, so that they can present some …