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Quantitative Biology > Neurons and Cognition

arXiv:2003.01385 (q-bio)
[Submitted on 3 Mar 2020 (v1), last revised 24 Mar 2020 (this version, v2)]

Title:Models Currently Implemented in MIIND

Authors:Hugh Osborne, Yi Ming Lai, Marc de Kamps
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Abstract:This is a living document that will be updated when appropriate. MIIND [1, 2] is a population-level neural simulator. It is based on population density techniques, just like DIPDE [3]. Contrary to DIPDE, MIIND is agnostic to the underlying neuron model used in its populations so any 1, 2 or 3 dimensional model can be set up with minimal effort. The resulting populations can then be grouped into large networks, e.g. the Potjans-Diesmann model [4]. The MIIND website this http URL contains training materials, and helps to set up MIIND, either by using virtual machines, a DOCKER image, or directly from source code.
Subjects: Neurons and Cognition (q-bio.NC); Computational Physics (physics.comp-ph)
Cite as: arXiv:2003.01385 [q-bio.NC]
  (or arXiv:2003.01385v2 [q-bio.NC] for this version)
  https://doi.org/10.48550/arXiv.2003.01385

Submission history

From: Marc de Kamps [view email]
[v1] Tue, 3 Mar 2020 08:21:58 UTC (5,584 KB)
[v2] Tue, 24 Mar 2020 11:26:24 UTC (5,585 KB)
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