NRT Spike Sorting Project

Spring 2019 • University of Rochester

Overview

Spike sorting is a crucial step to extract information from extracellular recordings and even a prerequisite for studying many types of brain function. This project aims at investigating several existing spike sorting methods, which include both offline and real-time processing and use either supervised or unsupervised learning algorithms, and at comparing their performances with different types and scales of neural data.

Members

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Hayden Scott (BCS)

hscott5@ur.rochester.edu

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Zhen Chen (BCS)

zchen87@ur.rochester.edu

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Yingping Lu (DS)

ylu63@ur.rochester.edu

Sponsors

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Where

University of Rochester

When

Spring 2019

Email

Email: xxx