Houghton’s method fills a clear need in the neuroinformatics field and
moves forward the possibilities for neuron modeling in in vivo
electrophysiology research. There exist many avenues for further
improvement, including models with more biologically interpretable
parameters and improved optimization algorithms.
In this paper, we propose a dynamical systems-based neuron model combined with an STRF filter that provides superior prediction accuracy with a computationally efficient optimization algorithm. This method is based on a Hindmarsh-Rose (HR) neuron model (Hindmarsh & Rose, 1984), which strikes a balance between the limited parameter sets of