Evidence map›Paper›PMID 41676620›Full record

ArticlebioRxiv : the preprint server for biology2026

Live Spike Sorting of Large-scale Neural Recordings.

Shreyas Muralidharan, Calvin Leng, Lucas Orts, Ethan Trepka, Shude Zhu, Matthew Panichello, Donatas Jonikaitis, Frank Lanfranchi, Jacob Pennington, Marius Pachitariu and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Shreyas MuralidharanDepartment of Electrical Engineering, Stanford University School of Engineering, Stanford CA, USA.
Calvin LengDepartment of Neurobiology, Stanford University School of Medicine, Stanford CA, USA.
Lucas OrtsDepartment of Electrical Engineering, Stanford University School of Engineering, Stanford CA, USA.
Ethan TrepkaDepartment of Neurobiology, Stanford University School of Medicine, Stanford CA, USA.
Shude ZhuDepartment of Neurobiology, Stanford University School of Medicine, Stanford CA, USA.ORCID 0000-0002-8674-9607
Matthew PanichelloDepartment of Neurobiology, Stanford University School of Medicine, Stanford CA, USA.ORCID 0000-0003-0270-782X
Donatas JonikaitisHoward Hughes Medical Institute, Stanford CA, USA.
Frank LanfranchiHoward Hughes Medical Institute, Stanford CA, USA.
Jacob PenningtonDepartment of Mathematics, Washington State University, Vancouver, WA, USA.
Marius PachitariuHoward Hughes Medical Institute, Ashburn, VA, USA.
Tirin MooreDepartment of Neurobiology, Stanford University School of Medicine, Stanford CA, USA.

Funding

Interaction of Visual and Oculomotor Signals in CortexR01EY014924 · NEI · STANFORD UNIVERSITY · PI MOORE, TIRIN · 2004 to 2024
$7.3M
Interaction of Visual and Oculomotor Signals in CortexR56EY014924 · NEI · STANFORD UNIVERSITY · PI MOORE, TIRIN · 2009 to 2009
$398k
NEI NIH HHS R01 EY014924NEI NIH HHS R56 EY014924
6 · The paper itself

Abstract

Online monitoring of neuronal activity has tremendous value for closed-loop control in both experimental and clinical settings, yet established methods rely primarily on thresholded neural activity, rather than sorted single-neuron spikes. The recent introduction of large-scale electrophysiological tools has greatly expanded single-neuron recording capacity in animals and humans highlighting the need to sort spikes during data collection. Here, we describe a system for live spike sorting (LSS) populations of hundreds of neurons with millisecond-scale latency. Using neurophysiological recordings from macaque visual cortex with Neuropixels probes, we show that LSS closely replicates the temporal responses and tuning of single neurons obtained using offline sorting. We further show that decoding neural signals with LSS achieves the same performance as that obtained from offline sorting. Lastly, we demonstrate the capacity of LSS to enable closed-loop interventions based on the activity of specific neuronal subclasses.

Identifiers

PMID41676620
PMCPMC12889464

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.