A FPGA real-time model of single and multiple visual cortex neurons

Using a biologically realistic model of a single neuron can be very beneficial for visual physiologists to test their electrophysiology setups, train students in the laboratory, or conduct classroom-teaching demonstrations. Here we present a Field Programmable Gate Array (FPGA)-based spiking model of visual cortex neurons, which has the ability to simulate three independent neurons and output analog spike waveform signals in four channels. To realistically simulate multi-electrode (tetrode) recordings, the independently generated spikes of each simulated neuron has a distinct waveform, and each channel outputs a differentially weighted sum of these waveforms. The model can be easily constructed from a small number of inexpensive commercially available parts, and is straightforward to operate. In response to sinewave grating stimuli, the neurons exhibit biologically realistic simple-cell-like response properties, including highly modulated Poisson spike trains, orientation selectivity, spatial/temporal frequency selectivity, and space-time receptive fields. Users can customize their model neurons by downloading modifications to the FPGA with varying parameter values, particularly desired features, or qualitatively different models of their own design. The source code and documentation are provided to enable users to modify or extend the model's functionality according to their individual needs.

Research highlights▶ A new FPGA model simulates tetrode recordings of multiple visual cortex neurons. ▶ Useful to test recording setups, train students, or conduct demonstrations. ▶ Inexpensive to construct, easy to operate, and fully customizable. ▶ Simple-cell-like responses, grating tuning curves and spatial RF structure.