SBIR/STTR Research Award

Live spike sorting for multichannel and high-channel recordings

Award identifier f60a60027d95c062946d973012b0ece27309b62a8f5dae781c7f93c0667d674fAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$698,289

Program and phase

STTR · Phase I

Award year

2023

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
POPNEURON LLC
Proposal award date
2023-09-22
Contract end date
2025-08-31
UEI
VVGNMXCD9T17
Solicitation number
PA22-178
Topic code
106

Research abstract

Project Summary: The goal of this project is to create two prototypes of a novel live spike sorting system which can be used by investigators to spike sort streams of neural data recorded by multi-channel, high channel and ultra-high channel probes. In most in-vivo extracellular recording conditions, an electrode can pick up neural spikes from several nearby neurons resulting in so-called “multi-unit” activity in the recording trace. Spike sorting algorithms are then used to separate this multi-unit activity into several sets of “single-unit” activities, each of which represents the action potential firing pattern of a single neuron. This sorting process is typically a computationally intensive process and is growing into a critical technology gap with the advent of multi and high channel count hardware. Live spike sorting of a complete set of multichannel data has been challenging if not impossible. On the other hand, there is a demand for live spike sorting during an experiment, especially by those investigators who record from functionally heterogenous brain areas such as, for example, all cortical regions. If an investigator had the ability to review live single cell data, he/she could determine the quality of the data and adjust the electrode position or decide on next experimental steps based on the incoming results. We recently developed the GEMsort algorithm, which, compared to existing spike sorting algorithms, was designed to sort neural spikes from multichannel probes with immediate sorting outcomes. These algorithms provide powerful, accurate yet computationally inexpensive spike sorting due to a different mathematical approach. As a result, these algorithms can spike sort complete streams of complex data, including data recorded with high channel and ultra-high channel electrodes virtually in real time. In this proposal, we will develop two tabletop-sized systems based on Field-Programmable Gate Array (FPGA) technology for laboratory use. These systems will be based on the GEMsort algorithm and add live spike sorting capabilities to an investigator's existing recording setup.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

2 SBIR/STTR records share this UEI (2020–2023). Reported award amounts total $950,249. Reported amounts are not federal obligations.

Phases: Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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