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Projekt Druckansicht

Integrierte magnetische Sensoren zur Bildgebung neuronaler Ströme

Fachliche Zuordnung Mikrosysteme
Elektronische Halbleiter, Bauelemente und Schaltungen, Integrierte Systeme, Sensorik, Theoretische Elektrotechnik
Molekulare Biologie und Physiologie von Nerven- und Gliazellen
Förderung Förderung von 2017 bis 2022
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 391912302
 
Erstellungsjahr 2021

Zusammenfassung der Projektergebnisse

The overall goal of the NeuroTMR project was to contribute to the understanding of the mechanisms of neuronal information transmission by developing and applying a new generation of implantable magnetic field sensors. Here, the key advantage of using magnetic sensors rather than electrodes is that the magnetic fields pass through tissues without significant distortion and allow for contactless detection that avoids problems related to electrode degradation. Especially the latter property makes the measurement of neural information using magnetic field sensors particularly attractive for the design of durable implants for human-machine interfaces. The project utilizes spin-based magneto resistors, namely tunneling magneto resistors (TMRs) and giant magneto resistors (GMRs) provided by the French project partner CEA-SPEC as highly sensitive magnetic field sensors that can be implemented in a miniaturized fashion on implantable probes in the form of so-called magnetrodes. Since the magnetic fields associated with neuronal activity are tiny, even very close to their place of origin, the key to reading out such signals is to use highly sensitive sensors with integrated interface electronics in very close proximity in order to minimize pickup noise. Therefore, one central goal of the NeuroTMR project was to research and prototypically design very low-noise readout electronics that can be integrated in standard CMOS and that maximally preserve the intrinsic signal-to-noise ratio (SNR) of the neuronal signals. As a major outcome of the project, this has been achieved by designing a novel current source that can effectively bias resistive sensors with record low noise floors. Moreover, an amplifier chain has been designed and manufactured that, in combination with a biasing circuit built around the new low-noise current source, allows to readout the neuronal signals with minimum SNR degradation. Although the integration of the interface electronics into the magnetrodes could not be completed during the runtime of the project due to delays introduced by the COVID pandemic and the closure of labs and manufacturing sites, all individual components were successfully designed and manufactured, allowing for the completion of the new active magnetrode generation soon after the official project end. For the in vivo testing of the probe, we have optimized the recording environment and applied spike sorting methods to treat the data (electrical and magnetic recordings) free of artifacts. The obtained neural probe is thin, 2-dimensional, integrates electrical recordings, and has demonstrated the possibility of measuring signals in the 400 pT range during in-vivo experiments. The in-vivo experiments performed on a rat’s hippocampus highlight the resistance and the long lasting of the probe in biologic liquids, and also its reduced damage to the brain. Currently, the only actual limitation for magnetrode use in neuroscience is its limit of detection, which leads to the necessity of averaging for neuronal spike detection. Moreover, thanks to their versatility and programmability, the ASICs originating from the NeuroTMR project were also successfully tested in combination TMR sensors for the detection of biomolecules in point-of-care (PoC) diagnostic platforms. Thanks to their small form factor, low price, and excellent performance, the interface electronics originating from the NeuroTMR project can pave the way to widespread use of PoC platforms based on magneto resistors in personalized medicine.

Projektbezogene Publikationen (Auswahl)

  • (2019) Human visual cortical gamma reflects natural image structure. Neuroimage 200: 635-643
    Brunet, N. M. and P. Fries
    (Siehe online unter https://doi.org/10.1016/j.neuroimage.2019.06.051)
  • “FIR Feedback in Continuous- Time Incremental Sigma-Delta ADCs,” 2019 17th IEEE International New Circuits and Systems Conference (NEWCAS), 2019, pp. 1-4
    A. Mohamed, A. Sakr and J. Anders
    (Siehe online unter https://doi.org/10.1109/NEWCAS44328.2019.8961214)
  • (2020) Magnetoresistive Sensor in Two-Dimension on a 25 μ m Thick Silicon Substrate for In Vivo Neuronal Measurements. ACs Sens.
    Chopin, C., Torrejon, J., Solignac, A., Fermon, C., Jendritza, P., Fries, P. and Pannetier-Lecoeur, M.
    (Siehe online unter https://doi.org/10.1021/acssensors.0c01578)
  • Stability Analysis of Incremental ΣΔ Modulators using Mixed-Logic Dynamical Systems and Optimal Control Theory,” 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020, pp. 1-5
    A. Mohamed and J. Anders,
    (Siehe online unter https://doi.org/10.1109/ISCAS45731.2020.9180952)
  • “A Low Noise CMOS Sensor Frontend for a TMR-based Biosensing Platform,” 2020 IEEE SENSORS, 2020, pp. 1-4
    A. Mohamed, M. Schmid, A. Tanwear, H. Heidari and J. Anders
    (Siehe online unter https://doi.org/10.1109/SENSORS47125.2020.9278826)
  • "A readout circuit for tunnel magnetoresistive sensors employing an ultra-low-noise current source," ESSCIRC 2021 - IEEE 47th European Solid State Circuits Conference (ESSCIRC), 2021, pp. 331-334
    A. Mohamed, H. Heidari and J. Anders
    (Siehe online unter https://doi.org/10.1109/ESSCIRC53450.2021.9567752)
  • (2021) Cortical gamma-band resonance preferentially transmits coherent input. Cell. Rep. 35:109083
    Lewis, C. M., Ni, J., Wunderle, T., Jendritza, P., Diester, I. and Fries, P.
    (Siehe online unter https://doi.org/10.1016/j.celrep.2021.109083)
  • (2021) Visual Neuroscience Methods for Marmosets: Efficient Receptive Field Mapping and Hand-Free Eye Tacking. eNeuro 8:ENEURO.0489-20.2021et
    Jendritza, P., Klein, F. J., Rohenkohl, G. and Fries, P.
    (Siehe online unter https://doi.org/10.1523/ENEURO.0489-20.2021)
  • (2021). Brain rhythms define distinct interaction networks with differential dependence on anatomy. Neuron. S0896-6273(21)00725-X
    Vezoli, J., Vinck, M., Bosman, C. A, Bastos, A. M., Lewis, C. M, Kennedy H., Fries P.
    (Siehe online unter https://doi.org/10.1016/j.neuron.2021.09.052)
 
 

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