Abstract
Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. New advances in high density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here we propose a neuron tracking method that can identify the same cells independent of firing statistics, which are used by most existing methods. Our method is based on between-day non-rigid alignment of spike sorted clusters. We verified the same cell identify using measured visual receptive fields. This method succeeds on datasets separated from one to 47 days, with an 84% average recovery rate.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
We have added material to discuss the applicability to other brain areas outside mouse visual cortex. sorter (Methods section 4.2, Supplement section 8.4, figure S9, paragraphs 7-10 of the Discussion section). To address the concern of overfitting, we have also added discussion covering adjustment of the two parameters in the procedure (the relative weight of waveform distance vs. physical distance, and the threshold for accepting matches as real) to the Discussion section. Since the posting of this manuscript, another method for tracking neurons has been introduced: Enny H. van Beest, Celian Bimbard, Julie M. J. Fabre, Flora Takacs, Philip Coen, Anna Lebedeva, Kenneth Harris, Matteo Carandini, Tracking neurons across days with high-density probes, bioRxiv 2023.10.12.562040; doi: https://doi.org/10.1101/2023.10.12.562040