ArticleCommunications engineering2025
Neural spike compression through salient sample extraction and curve fitting dedicated to high-density brain implants.
Article in Communications engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
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Authors and funding
2 authors.
Funding
Abstract
As brain implants evolve towards higher channel density, efficient on-implant processing of the acquired signals becomes essential to overcome constraints in power, area, and data transmission. Here we propose a data reduction framework, specific to extra-cellular neuronal action potentials. This approach picks a small number of salient spike samples, using which the spike waveshape is interpolated. Attributes of salient samples are sent off the implant to reconstruct the spike waveshape on the external side of the system. In addition to exhibiting high data compression capability, this technique is highly hardware efficient, hence well suits for brain-implantable neural recording microsystems with high channel counts. Based on the proposed framework, a 128-channel neural signal compressor was implemented using a 130-nm CMOS technology, and measured 1.05 × 0.35 mm
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Registered trials
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