A Model for the Diffusive Filling-In Algorithm Operating in Spike Mode

Abstract

To run cortical circuit simulations in spike mode, i.e. taking into account the neural representation of information in terms of sequences of electrical pulses (also known as spikes), the use of customized hardware, which is specific for this purpose, is recommended. Simulations using more traditional hardware can be prohibitive. In this context, theoretical predictions are important for customized hardware design. For example, theoretical predictions lead to an adequate neuron model choice. To make such theoretical predictions, the cortical circuit simulations are carried out in amplitude mode. Differently from the spike mode, in amplitude mode information is represented by sequences of scalar values that describe neural input and output spike rates. In this paper, it was proposed amplitude and spike mode simulations of a cortical algorithm, namely the diffusive filling-in algorithm, to investigate whether predictions based on the amplitude-mode results approximate well the behavior of the customized hardware (spike mode results). The diffusive filling-in algorithm was chosen because it is simple enough for spike-mode simulation in a conventional computer, but the proposed amplitude-mode prediction method is the same for more complex algorithms or circuits. We provide a highly realistic comparison between amplitude-mode and spike-mode in the diffusive filling-in case, which suggests that the amplitude mode is reliable for theoretical predictions useful for customized hardware design for cortical circuit simulation. The goal of this paper is not to bring closure to these discussions but to suggest a way of avoiding possible issues that could compromise the success of the customized device design.