Fractional order modified Treves model: Simulation and Learning

First spike latency is an important code for the brain that conveys information in sensory systems [1]. Fractional-order models can generate shorter or longer first spike latency that strongly depends on the spiking history of a neuron. We studied a fractional Treves model and analyzed spiking patterns as a result of fractional dynamics. With fractional-order between 0 and 1, the model produces longer first spike latency that depends on memory and retains the downward spike frequency adaptation present in the classical Treves model. We qualitatively compared experimental data from a Primary visual cortical neuron of a mouse and fitted the fractional-order in the fractional modified Treves model using a differential evolution algorithm and L1 scheme.