A retrofitted neural recording system with a novel stimulation IC to monitor early neural responses from a stimulating electrode.

Extracellular electrical stimulation is increasingly used for in vitro neural experimentation, including brain slices and cultured cells. Although it is desirable to record directly from the stimulating electrode, relatively high stimulation levels make it extremely difficult to record immediately after the stimulation. We have shown that this is feasible by a stimulation system (analog IC) that includes the feature of active electrode discharge.

A parameter-space search algorithm tested on a Hodgkin-Huxley model.

We demonstrate a parameter-space search algorithm using a computational model of a single-compartment neuron with conductance-based Hodgkin-Huxley dynamics. To classify bursting (the desired behavior), we use a simple cost function whose inputs are derived from the frequency content of the neural output. Our method involves the repeated use of a stochastic gradient descent-type algorithm to locate parameter values that allow the neural model to produce bursting within a specified tolerance.

A comparative analysis of multi-conductance neuronal models in silico.

We demonstrate that a previously presented flexible silicon-neuron architecture can implement three disparate conductance-based neuron models with both fast and slow dynamics. By exploiting the real-time nature of this physical implementation, we mapped the model dynamics across a large region of parameter space. We also found that two of these dynamically different models represent points in a contiguous bursting space that spans between the two models.