Large-scale neural model of visual short-term memory (Ulloa, Horwitz 2016; Horwitz, et al. 2005,...)

Large-scale neural model of visual short term memory embedded into a 998-node connectome. The model simulates electrical activity across neuronal populations of a number of brain regions and converts that activity into fMRI and MEG time-series. The model uses a neural simulator developed at the Brain Imaging and Modeling Section of the National Institutes of Health.

Model Type: Realistic Network

Region(s) or Organism(s): Prefrontal cortex (PFC)

Model Concept(s): Working memory

Simulation Environment: Python

Implementer(s): Ulloa, Antonio [antonio.ulloa at]


Tagamets MA, Horwitz B. (1998). Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral cortex (New York, N.Y. : 1991). 8 [PubMed]

Ulloa A, Horwitz B. (2016). Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex. Frontiers in neuroinformatics. 10 [PubMed]

Horwitz B et al. (2005). Investigating the neural basis for functional and effective connectivity. Application to fMRI. Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 360 [PubMed]

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