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Models of the Mouse Primary Visual Cortex

Models of the Mouse Primary Visual Cortex

This webpage provides access to the code, data, and meta-data for a set of mouse V1 models developed by the Allen Institute for Brain Science. All code, data, and metadata for the V1 models are covered by these Terms of Use. The software package needed is the Brain Modeling ToolKit (BMTK), which can be found here on Github. The data files can be accessed here in Dropbox.

The Allen Institute for Brain Science developed data-driven models of the mouse primary visual cortex (area V1) for in silico visual physiology studies with arbitrary visual stimuli (Fig. 1). The models integrate information from extensive literature curation and large-scale experimental pipelines. They were constructed at two levels of granularity, using either biophysically-detailed or Generalized Leaky Integrate and Fire (GLIF) point-neuron models.

The models contain 17 cell classes (Fig. 1), represented by >100 unique neuron models. The biophysical and GLIF model networks use exactly the same graph, i.e. each neuron in one network has an exact counterpart in the other, with the same coordinates, presynaptic sources, and postsynaptic targets. The models span a 845 micron radius. For the biophysically detailed model, the “core” (400 micron radius) is composed of compartmental neuron models and is surrounded by an annulus of leaky-integrate-and-fire neurons, to avoid boundary artifacts. Also included is a LGN module that provides visual stimulation to V1 neurons in response to arbitrary visual stimuli.

For further details, please see the paper


Figure 1: Overview of the V1 models. Top: The models consist of one excitatory class and three inhibitory classes (Pvalb, Sst, Htr3a) in each of four layers - L2/3, L4, L5 and L6; L1 has a single Htr3a inhibitory class. Visual stimulation is conveyed by thalamocortical projections (from the LGN; see paper). Bottom: Visualization of the biophysically detailed network (1% of neurons shown). For each class, the total number of neurons is indicated, and one exemplary dendritic morphology is provided.