Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS
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arXiv
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| Natura: | Preprint |
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2025
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| author | Lemaire, William Koleibi, Esmaeil Ranjbar Benhouria, Maher Koua, Konin Ménard, Jérémy Gagnon, Keven Quesnel, Charles Gauthier, Louis-Philippe Omrani, Takwa Dridi, Montassar Majdoub, Mahdi Besrour, Marwan Roy, Sébastien Fontaine, Réjean |
| author_facet | Lemaire, William Koleibi, Esmaeil Ranjbar Benhouria, Maher Koua, Konin Ménard, Jérémy Gagnon, Keven Quesnel, Charles Gauthier, Louis-Philippe Omrani, Takwa Dridi, Montassar Majdoub, Mahdi Besrour, Marwan Roy, Sébastien Fontaine, Réjean |
| contents | Neural interfaces advance neuroscience research and therapeutic innovations by accurately measuring neuronal activity. However, recording raw data from numerous neurons results in substantial amount of data and poses challenges for wireless transmission. While conventional neural recorders consume energy to digitize and process the full neural signal, only a fraction of this data carries essential spiking information. Leveraging on this signal sparsity, this paper introduces a neural recording integrated circuit in TSMC 28nm CMOS. It features an event-driven ramp analog-to-digital converter, and a spike compression module based on principal component analysis. The circuit consists of 49 channels, each occupying an on-chip area of 50 $\times$ 60 $μ$m$^2$. The circuit measures 1370 $\times$ 1370 $μ$m$^2$ and consumes 534 $μ$W. Compression testing on a synthetic dataset demonstrated an 8.8-fold reduction compared to raw spikes and a 328-fold reduction relative to the raw signal. This compression approach maintained a spike sorting accuracy of 74.9%, compared to the 79.5% accuracy obtained with the raw signal. The paper details the architecture and performance outcomes of the neural recording circuit and its compression module. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_04128 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS Lemaire, William Koleibi, Esmaeil Ranjbar Benhouria, Maher Koua, Konin Ménard, Jérémy Gagnon, Keven Quesnel, Charles Gauthier, Louis-Philippe Omrani, Takwa Dridi, Montassar Majdoub, Mahdi Besrour, Marwan Roy, Sébastien Fontaine, Réjean Systems and Control Neural interfaces advance neuroscience research and therapeutic innovations by accurately measuring neuronal activity. However, recording raw data from numerous neurons results in substantial amount of data and poses challenges for wireless transmission. While conventional neural recorders consume energy to digitize and process the full neural signal, only a fraction of this data carries essential spiking information. Leveraging on this signal sparsity, this paper introduces a neural recording integrated circuit in TSMC 28nm CMOS. It features an event-driven ramp analog-to-digital converter, and a spike compression module based on principal component analysis. The circuit consists of 49 channels, each occupying an on-chip area of 50 $\times$ 60 $μ$m$^2$. The circuit measures 1370 $\times$ 1370 $μ$m$^2$ and consumes 534 $μ$W. Compression testing on a synthetic dataset demonstrated an 8.8-fold reduction compared to raw spikes and a 328-fold reduction relative to the raw signal. This compression approach maintained a spike sorting accuracy of 74.9%, compared to the 79.5% accuracy obtained with the raw signal. The paper details the architecture and performance outcomes of the neural recording circuit and its compression module. |
| title | Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2505.04128 |