Zhiwen Ye, Andrew M. Shelton, Jordan R Shaker, Julien Boussard, Jennifer Colonell, Daniel Birman, Sahar Manavi, Susu Chen, Charlie Windolf, Cole Hurwitz, Yu Han, Tomoyuki Namima, Federico Pedraja, Shahaf Weiss, Bogdan Raducanu, Torbjørn V. Ness, Xiaoxuan Jia, Giulia Mastroberardino, L. Federico Rossi, Matteo Carandini, Michael Häusser, Gaute T. Einevoll, Gilles Laurent, Nathaniel B. Sawtell, Wyeth Bair, Anitha Pasupathy, Carolina Mora López, B. Dutta, Liam Paninski, Joshua H. Siegle, Christof Koch, Shawn R. Olsen, T.D. Harris, Nicholas A. Steinmetz
To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single-neuron and single-spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). Using NP Ultra, neuronal yield in mouse visual cortex recordings increased by more than 2-fold. With ultra-high spatial resolution, we discovered that a feature of extracellular waveforms, the spatial extent or "footprint," distinguished axonal from somatic recordings. In addition, three genetically identified cortical cell types could be discriminated from one another with ∼80% accuracy and from other neurons with ∼85% accuracy. NP Ultra improves yield, detection of subcellular compartments, and cell type identification to enable a more powerful dissection of neural circuit activity during behavior.