Fig. 5: DHS enables spine-level modeling.
From: A GPU-based computational framework that bridges neuron simulation and artificial intelligence
a Experiment setup. We examine two major types of models: few-spine models and full-spine models. Few-spine models (two on the left) are the models that incorporated spine area globally into dendrites and only attach individual spines together with activated synapses. In full-spine models (two on the right), all spines are explicitly attached over whole dendrites. We explore the effects of clustered and randomly distributed synaptic inputs on the few-spine models and the full-spine models, respectively. b Somatic voltages recorded for cases in a. Colors of the voltage curves correspond to a, scale bar: 20 ms, 20 mV. c Color-coded voltages during the simulation in b at specific times. Colors indicate the magnitude of voltage. d Somatic spike probability as a function of the number of simultaneously activated synapses (as in Eyal et al.’s work) for four cases in a. Background noise is attached. e Run time of experiments in d with different simulation methods. NEURON: conventional NEURON simulator running on a single CPU core. CoreNEURON: CoreNEURON simulator on a single GPU. DeepDendrite: DeepDendrite on a single GPU.
