Circuits that contain the Modeling Application : NeuroML (web link to model) (Home Page)

("Model Descriptions for Computational Neuroscience. Computational models based on detailed neuroanatomical and electrophysiological data have been used for many years as an aid for understanding the function of the nervous system. NeuroML is an international, collaborative initiative to develop a language for describing detailed models of neural systems. The aims of the NeuroML initiative are: To create specifications for a language in XML to describe the biophysics, anatomy and network architecture of neuronal systems at multiple scales To facilitate the exchange of complex neuronal models between researchers, allowing for greater transparency and accessibility of models To promote software tools which support NeuroML and support the development of new software and databases To encourage researchers with models within the scope of NeuroML to exchange and publish their models in this format. NeuroML is a free and open community effort developed with input from many contributors. We need your help as the language and tools continue to evolve. ... ")
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    Models   Description
1. Rapid desynchronization of an electrically coupled Golgi cell network (Vervaeke et al. 2010)
Electrical synapses between interneurons contribute to synchronized firing and network oscillations in the brain. However, little is known about how such networks respond to excitatory synaptic input. In addition to detailed electrophysiological recordings and histological investigations of electrically coupled Golgi cells in the cerebellum, a detailed network model of these cells was created. The cell models are based on reconstructed Golgi cell morphologies and the active conductances are taken from an earlier abstract Golgi cell model (Solinas et al 2007, accession no. 112685). Our results show that gap junction coupling can sometimes be inhibitory and either promote network synchronization or trigger rapid network desynchronization depending on the synaptic input. The model is available as a neuroConstruct project and can executable scripts can be generated for the NEURON simulator.
2. Spikes,synchrony,and attentive learning by laminar thalamocort. circuits (Grossberg & Versace 2007)
"... The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. ..."
3. The neocortical microcircuit collaboration portal (Markram et al. 2015)
"This portal provides an online public resource of the Blue Brain Project's first release of a digital reconstruction of the microcircuitry of juvenile Rat somatosensory cortex, access to experimental data sets used in the reconstruction, and the resulting models."

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