A recent article on the BBC (and the highly recommended MIT news) breaks the news on an innovative silicone chip that models neuronal architecture and neuronal communication. The chip’s 400 transistors mimic the head of a neuron: they summate the analog signals received from other chips. When such signals reach an adjustable limit, they cascade into an action potential, just as in neurons. Depending on their arrangement and organization, these action potentials can have an excitatory, or inhibitory effect on their neighbours, analogous to their biological counterparts.
This kind of modelling is exciting and interesting – for it is profoundly different from other contemporary methods of modelling brain activity. While a great overgeneralization, most other programmes model the brain’s circuitry – the neurons, the synaptic connections, the action potentials – in a virtual space. They exist as computer code, or interacting objects created by such code. These coded objects, whatever existence they have, model the function of neurons. These chips, in comparison, are an actual model of a neuron. And this is the important difference between the two paradigms: that between modelling function and form.