Event Abstract

A versatile technology approach for high-resolution implantable CMOS-probes

  • 1 Fondazione Istituto Italiano di Technologia, Neuroscience and Brain Technologies (NBT), Italy

Active multielectrode arrays (MEAs) based on CMOS technology enable large-scale electrophysiological recordings at sub-millisecond temporal resolution from up to several thousands of densely spaced microelectrodes. This allows monitoring a large number of single neurons while mapping signal propagations over large fields of view. Furthermore, innovative opportunities to advance spike detection and sorting methods on large arrays [1-3] originate from taking advantage of spatial and temporal correlations among the spiking signals recorded by multiple and closely spaced electrodes. Initially proposed and validated for in-vitro and ex-vivo applications [4-12], this neurotechnology was also recently demonstrated to realize implantable micro-structured CMOS probes for in-vivo large-scale recordings [13-18]. However, the implementation of implantable CMOS-probes is a young and emerging field of research and several challenges on the probe and hardware design, data analysis and experimental application still need to be addressed. To do so and to be in the position to evaluate the performances of different probe’s layouts for different experimental needs, our approach focused on developing a versatile and scalable CMOS-probe technology that exploits a modular on-probe circuit solution for signal conditioning and read-out as well as micro-/nano-structuring processes that can be easily adapted to different probe’s layouts, electrode materials and 2D/3D morphologies and system configurations. Our circuit architecture radically differs from other CMOS-probes and builds from the Active Pixel Sensor concept (APS) that we have previously demonstrated for sub-millisecond whole-array recordings on planar CMOS-MEAs with 4096 electrodes [19]. To adapt these concepts for implantable probes, we entirely re-designed and optimized the on-probe circuits to meet three distinct, yet intimately correlated constraints: i) low-noise performances, ii) small area integration and iii) sufficiently low power consumption to avoid thermal issues. As a first step to demonstrate our approach we designed in standard 0.18 μm CMOS process a 512 single-shaft probe for acute electrophysiological recordings in mice. Each electrode-pixel integrates a DC-coupled amplifier (pixel area of 26 x 26 µm2) underneath each electrode (16 x 16 µm2). On-chip time-division multiplexing circuits allow sampling the whole-array on 16 output channels and achieving 25kHz sampling frequency for each electrode. An active feedback loop for the auto-zeroing circuit, shared among multiple electrode-pixels, permits the cancellation of DC offsets without the need of large input capacitors, thus minimizing the in-pixel circuit size. Further, our circuit solution permits electrical recordings during light-stimulation thus making it suitable for experimental protocols involving optogenetics or optical imaging. Post-processing of the CMOS devices consists in thinning the devices down to 30-40 µm; shaping the probe’s shafts (100 µm and 6 mm in length) using micro-structuring processes and in post-processing the electrodes by electrodeposition of PEDOT:PSS or Pt. Finally, we have realized an interfacing hardware, based on a low-cost FPGA board, that allows for the synchronous sampling from up to three different active devices and a conventional passive probe with 36 electrodes [20]. Experimental performances of a first generation of these CMOS-probes demonstrate the capability of recording both LFPs and spiking signals in head-fixed anesthetized or behaving mice. Low-noise performances down to 12µVrms (full bandwidth up to 10kHz) can be achieved with optimized in-pixel circuit designs. Further, the integrated circuit solution allows constant recordings during light-stimulation. In perspective, the proposed approach allows to investigate optimizations of the probe-shaft geometry for chronic recordings and the integration of these CMOS-probes with ultra-low power wireless circuits that we have recently reported [21].

Acknowledgements

This work was partially supported by the NIH BRAIN program (USA), project number 2015/2018 - NIH 1U01NS094190.

References


1. G Hilgen et al. Cell Reports 18(10), 2521–2532, doi: 10.1016/j.celrep.2017.02.038 (2017).
2. JE Chung et al. Neuron 95 (6), 1381-1394.e6, doi: 10.1016/j.neuron.2017.08.030 (2017).
3. P Yeger et al. eLife 7:e34518, doi: 10.7554/eLife.34518 (2018).
4. L Berdondini et al. Biosensors Bioelectronics 21, 167–74, doi:10.1016/j.bios.2004.08.011 (2005).
5. L Berdondini et al. Lab Chip 9, 2644–51, doi:10.1039/b907394a (2009).
6. E Ferrea et al. Frontiers in Neural Circuits 6(80), doi: 10.3389/fncir.2012.00080 (2012).
7. A Maccione et al. J Physiology 15, 592(Pt 16): 3697, doi: 10.1113/jphysiol.2013.262840 (2014).
8. H Amin et al. Sci Rep. 16 7(1):15752, doi: 10.1038/s41598-017-15793-9 (2017).
9. B Eversmann et al. IEEE J. Solid-State Circuits 38, 2306–2317, doi:10.1109/JSSC.2003.819174 (2003).
10. M Hutzler et al. J. Neurophysiology 96, 1638–45, doi:10.1152/jn.00347.2006 (2006).
11. U Frey et al. J. Solid-State Circuits IEEE 45, 467–482, doi:10.1109/JSSC.2009.2035196 (2010).
12. M Ballini et al. IEEE J. Solid-State Circuits 49, 1–15, doi:10.1109/JSSC.2014.2359219 (2014).
13. CM Lopez et al. IEEE Journal of Solid-State Circuits 49(1), doi: 0.1109/JSSC.2013.2284347 (2014).
14. CM Lopez et al. IEEE Transactions on Biomedical Circuits and Systems 11(3), doi: 10.1109/TBCAS.2016.2646901, (2017).
15. P Ruther and O Paul. Current Opinion Neurobiology 32, 31–37. (2015).
16. JJ Jun, Nature 551, 232–236, doi:10.1038/nature24636 (2017).
17. GN Angotzi et al. “A 512-channels whole array readout, CMOS implantable probe for acute recordings from the brain”, in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, pp. 877–880, doi: 10.1109/EMBC.2015.7318502 (2015).
18. GN Angotzi and L. Berdondini, “A low-power, low-area modular architecture for high density neural probes”, in Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference, pp. 521–524, doi: 10.1109/NER.2015.7146674 (2015).
19. K Imfeld et al. IEEE Transactions on Biomedical Engineering 55(8), 2064–2073, doi: 10.1109/TBME.2008.919139 2008.
20. GN Angotzi et al. IEEE Transactions on Biomedical Circuits and Systems (early access), doi: 10.1109/TBCAS.2018.2792046 (2018).
21. M Crepaldi et al. IEEE Transactions on Circuits and Systems I: Regular Papers 65 (3), doi: 10.1109/TCSI.2017.2762159 (2018).

Keywords: CMOS-probes, extracellular recordings, high-resolution MEAs, Implantable devices, neuroscience methods

Conference: MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays, Reutlingen, Germany, 4 Jul - 6 Jul, 2018.

Presentation Type: Oral Presentation

Topic: In vivo applications of MEAs

Citation: Angotzi GN, Boi F, Miele E, Lecomte A and Berdondini L (2019). A versatile technology approach for high-resolution implantable CMOS-probes. Conference Abstract: MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays. doi: 10.3389/conf.fncel.2018.38.00063

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 22 Apr 2018; Published Online: 17 Jan 2019.

* Correspondence: Dr. Luca Berdondini, Fondazione Istituto Italiano di Technologia, Neuroscience and Brain Technologies (NBT), Genoa, 16163, Italy, Luca.Berdondini@iit.it