Simulation Environment: NCS

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https://www.cse.unr.edu/brain/ncs

NCS is a brain simulator that allows large networks of many biologically realistic neurons to be constructed. These networks are synaptically connected using an integrate-and-fire technique as described by the Hodkin-Huxley model. Recent experimental data suggests that spike-timing and membrane dynamics of biological neurons may encode information in a way not achievable using artificial neural networks (ANNs) or machine learning algorithms ( Mass, Bishop, et al. 1999). NCS has been used to study multiple sensory pathways (audio and visual) simultaneously in order to cull out the synergistic properties common across modalities. It has been used with the goal in mind of achieving some understanding of the organization principles of brain physiology that underlie human behavior, looking for insight about the sensory integration needed for higher-level processing. Using multimodal investigations may take researchers a step closer to determining the high-level processes that occur in the brain, where higher-level processes include processes beyond the primary sensory areas (Maciokas, 2003).
Top authors for NCS:
Top concepts studied with NCS:
Top neurons studied with NCS:
Top references cited by these models:
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