Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits
Fig 6
The biophysical and point-neuron V1 models.
(A) Visualizations of the biophysical and point-neuron models. The 230,000-neuron models emulate the central portion of the mouse V1, across the full cortical depth, containing layers 1, 2/3, 4, 5, and 6 (layer boundaries are indicated). In the top model, the core portion, ~50,000 neurons, is simulated using biophysically detailed compartmental neuronal models, and the annulus around the core using leaky integrate-and-fire (LIF) point-neuron models. In the bottom model, both core and the annulus employ the generalized LIF neuronal models. Neurons are colored by cell class: hues of red for excitatory cells in layers 2/3, 4, 5, and 6, and blue, cyan and green for Parvalbumin- (Pvalb), Somatostatin- (SST), and 5-hydroxytryptamine receptor 3A- (Htr3a) expressing inhibitory cells classes. (B) Summary of firing rates and direction selectivity index (DSI) obtained from the biophysical and point-neuron simulations, vs. experimental extracellular electrophysiology recordings, by cell class. The data were obtained from 2.5-second long presentations of drifting gratings at 8 different directions, 10 trials each. “RS” and “FS” are experimentally determined regular- and fast-spiking cells, roughly corresponding to excitatory and Pvalb inhibitory neurons; the SST and Htr3a neurons could not be identified from experiments. (C) Performance benchmarks and scaling of simulations and setup (including disk I/O) of the biophysical version of the V1 model using BMTK’s BioNet. The simulation involved 0.5 s presentation of gray screen and 2.5 s of a drifting grating. The time shown is the wallclock time it took to obtain 1 second of simulated time, averaged over 3 s of simulation. The dashed lines indicate ideal scaling (relative to 125 cores, which is a typical choice for simulation of such scale).