2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDBIO-4.5
Paper Title Decentralized motion inference and registration of Neuropixel data
Authors Erdem Varol, Julien Boussard, Nishchal Dethe, Columbia University, United States; Olivier Winter, Champalimaud Centre for the Unknown, Portugal; Anne Urai, Leiden University, Netherlands; Anne Churchland, University of California, Los Angeles, United States; Nick Steinmetz, University of Washington, United States; Liam Paninski, Columbia University, United States
SessionBIO-4: Machine Learning and Signal Processing for Neural Signals
LocationGather.Town
Session Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Poster
Topic Biomedical Imaging and Signal Processing: [BIO] Biomedical signal processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Multi-electrode arrays such as “Neuropixels” probes enable the study of neuronal voltage signals at high temporal and single-cell spatial resolution. However, in vivo recordings from these devices often experience some shifting of the probe (due e.g. to animal movement), resulting in poorly localized voltage readings that in turn can corrupt estimates of neural activity. We introduce a new registration method to partially correct for this motion. In contrast to previous template-based registration methods, the proposed approach is decentralized, estimating shifts of the data recorded in mul- tiple timebins with respect to one another, and then extracting a global registration estimate from the resulting estimated shift matrix. We find that the resulting decentralized regis- tration is more robust and accurate than previous template- based approaches applied to both simulated and real data, but nonetheless some significant non-stationarity in the recovered neural activity remains that should be accounted for by down- stream processing pipelines. Open source code is available at https://github.com/evarol/NeuropixelsRegistration.