The consciousness debate is often trapped between two extremes: either the brain is “just software” (computational functionalism) or consciousness is uniquely biological (biological naturalism). Our paper proposes a third view: biological computationalism. This means that brains do compute, but not like standard digital machines.

We argue that the classical computational picture doesn’t fit the brain, because biological computation has three key traits: it’s hybrid (discrete events inside continuous dynamics), scale-inseparable (no clean split between software and hardware), and metabolically grounded (energy constraints shape how intelligence is organized). In this framework, the brain isn’t merely running an abstract algorithm. Rather, the algorithm is the substrate, unfolding in physical time through fields, flows, and multi-scale dynamics.

This doesn’t mean consciousness belongs only to biology. But it may require biology-like computation, potentially in new non-biological materials. So the challenge of synthetic consciousness isn’t just finding a better algorithm to run—it’s building the kind of matter that matters.

The development of artificial synapses aimed at creating neuromorphological computing systems that are anticipated to fundamentally address the performance bottleneck issues in von Neumann architecture systems. Two-dimensional (2D) materials, with their atomic-scale thickness and van der Waals contact surfaces, offer exceptional optoelectronic properties, making them potential candidates for artificial synapse fabrication.