Bridging large-scale neuronal recordings and large-scale network models using dimensionality reduction.

Bridging large-scale neuronal recordings and large-scale network models using dimensionality reduction. Curr Opin Neurobiol. 2019 Jan 21;55:40-47 Authors: Williamson RC, Doiron B, Smith MA, Yu BM Abstract A long-standing goal in neuroscience has been to bring together neuronal recordings and neural network modeling to understand brain function. Neuronal recordings can inform the development of network models, and network models can in turn provide predictions for subsequent experiments. Traditionally, neuronal recordings and network models have been related using single-neuron and pairwise spike train statistics. We review here recent studies that have begun to relate neuronal recordings and network models based on the multi-dimensional structure of neuronal population activity, as identified using dimensionality reduction. This approach has been used to study working memory, decision making, motor control, and more. Dimensionality reduction has provided common ground for incisive comparisons and tight interplay between neuronal recordings and network models. PMID: 30677702 [PubMed - as supplied by publisher]
Source: Current Opinion in Neurobiology - Category: Neurology Authors: Tags: Curr Opin Neurobiol Source Type: research
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