Current Research
Machine Learning Methods for Mapping Neuronal Circuits

Srinivas Turaga seeks to develop new machine learning methods for use in mapping the structure and function of neural circuits. Turaga and his team apply machine learning algorithms to map neural connectivity – for example, reconstructing connectomes from electron microscopic images. They also develop statistical models to characterize neural activity, and to relate activity to connectivity. Their aim is to advance understanding of how the structure of a neural circuit gives rise to its function – how networks of neurons are connected, how cells are organized into cell types, and what activity and computation they produce.

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