Timothee LEVI, Dr.

limms_Levi.jpg Host Laboratory FUJII LAB.
Position in LIMMS CNRS Senior Researcher

Main Research Topic in LIMMS

Bio-MEMS - Microfluidic neurons

Keywords

Microfluidic, Neuron, Hybrid experiments
Contact LIMMS/CNRS-IIS (UMI 2820)
Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
Phone:+81 (0)3 5452 6036 / Fax:+81 (0)3 5452 6088
E-mail levi at iis.u-tokyo.ac.jp  |  timothee.levi at ims-bordeaux.fr
Download icon_pdf.gifAbstract2015_TLevi.pdf

Resume

Timothée Levi was born in Talence, France in 1981. He received the Ph.D. degree in Electrical, from the University of Bordeaux 1 in 2007. His dissertation was about the reuse methodology applied on neuromorphic engineering. In 2008, he was a post-doctoral researcher at CEA-LETI in Grenoble, France, about real-time signal processing of spike sorting. In 2009, he was post-doctoral researcher at the University of Tokyo (LIMMS/CNRS-IIS), Japan, about silicon neural network for smart MEMS systems. He is currently Associate Professor at Laboratory IMS (CNRS / ENSEIRB – University Bordeaux 1) since 2010. His main research is focused on architecture of silicon neural networks and reuse methodologies. From September 2013, he is visiting research fellow at the University of Tokyo, LIMMS/CNRS-IIS, dealing with microfluidic neurons and biomimetic artificial neural networks.

Short resume :
2013-now CNRS Researcher (Délégation CNRS) at LIMMS/CNRS-IIS, University of Tokyo, Japan (Host Lab: T. Fujii)
2009-2013 Associate Professor at University of Bordeaux, IMS Lab., France
2009

LIMMS/CNRS-IIS, University of Tokyo, Japan

(Host Lab: T. Kohno) - JSPS Post-Doc – Silicon neural network circuits for smart-MEMS system

2008 CEA LETI lab., Grenoble, France - Post-Doc position – Real-time embedded processing for spike sorting
2004-2007 IMS lab., University of Bordeaux, France - PhD student - Design flow improvement of AMS neuromorphic systems: Development of an IP-based library: application on neuromorphic engineering.          icon_pdf.gifThesis
2004

Engineering diploma in electronics at ENSEIRB, Bordeaux

University of Bordeaux, Master in Microelectronics

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Research Projects in Limms

1- Microfluidic neurons

 

   This project deals with the design of a new device which reproduces the electrical behavior of one biological neuron. To reach it, microfluidic techniques will be used to design microsystems with the same scale as biological ones (about 10 µm). This microfluidic neuron will simplify the interaction with biological neurons (Fig. 1). It exists in the state of the art some hybrid interactions between silicium neurons and biological ones [1], [2], [3] but there is nothing about microfluidic neuromorphic devices. The neuromorphic engineering using silicon neurons is a field which becomes more and more useful for the study and treatment of neuronal diseases.

Specific Background and Goal:
My previous and current work deals with the design of silicon neurons which mimic the electrical activity of biological neurons. The main goal is to allow some hybrid experiments like the communication between biological neurons and electronic ones. This could reach to the design of tools for biomedical applications like neuroprosthesis and for the understanding of the human nervous system.
Nevertheless my experience in this field shows me the difficulties of doing these hybrid experiments due to compatibility problems. Then I would like to develop this microfluidic neuron project which will reduce these compatibility issues, like keeping the same ionic currents than in biology. The modeling will be nearly similar as the electronic one but the use of aqueous solutions of Sodium, Potassium and Calcium will make the connection with the living neural network easier. Furthermore, the design of this device in PDMS will allow in the same device the culture of real neurons.
State of the art and Originality:
The best advantage of this microfluidic neuron is its modeling which is very close to the nature and then the hybrid connection with a living neuron could be done. This neuron is a deal with biological neurons and silicium ones. It exists in the state of the art some hybrid interactions between silicium neurons and biological ones but there is nothing about microfluidic neuromorphic devices. The neuromorphic enginnering using silicon neurons is a field which becomes more and more useful for the study and treatment of neuronal diseases. Our microfluidic neuron could easier communicate than the silicium one thanks to its modeling closer to the nature and with the use of real ionic channels. The neuromorphic engineering using microfluidic devices doesn’t exist in the literature. An interaction with the silicium neuron could also be done for robotic applications.

Fig1_Levi.jpg

 

Fig. 1 « Microfluidic » neuron position and Hybrid experiment between real neurons and microfluidic neurons.

Fig2_Levi.jpg

Fig. 2 PDMS Platform for hybrid experiments with biological cell culture and microfluidic neurons.

Objectives & Methods:
Our microfluidic neuron could easier communicate than the silicium one thanks to its modeling closer to the nature. Microfluidic techniques are used to design microsystems with the same scale as biological ones: Quake valves, deposit of Nafion selective membrane and culture of living neurons into PDMS.
 
Results:
We obtain an electrical behavior similar to the biological neuron. The main parameter for controlling the shape of the action potential is the difference of ion concentration between the two chambers. We could also control the spike frequency with the programmed time sequence of the quake valve controller. The next step of our work is to make hybrid experiments in the same chip: neuron culture in one part of the PDMS device and the artificial neurons in the other part.
These hybrid experiments will allow a better understanding of the neural network and will be a first step for microfluidic neuroprosthesis studies. The microfluidic neurons could also be used in robotic field reducing the electronic part and then the different issues like marine robots.
References:
[1] R. Jung, et al., IEEE Transactions on Neural Systems and Rehabilitation Engineering, 9, 319-326, 2001.
[2] G. Le Masson, et al., Nature, 417, 854–858, 2002.
[3] RJ. Vogelstein, et al., Biological Cybernetics, 95, 555-566, 2006.

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Main publication List (papers, conferences and patent)

2016

Journals
  1. Levi T and Fujii T, "Microfluidic neurons: a new way in neuromorphic engineering?," Micromachines, 7:146, August 2016
  2. Joucla S, Ambroise M, Levi T, Lafon T, Chauvet P, Saïghi S, Bornat Y, Lewis N, Renaud S and Yvert B, "Generation of Locomotor-Like Activity in the Isolated Rat Spinal Cord Using Intraspinal Electrical Microstimulation Driven by a Digital Neuromorphic CPG," Frontiers in Neurosciences, 10:67 February 2016
Conferences
  1. Buccelli S, Tessadori J, Bornat Y, Pasquale V, Ambroise M, Levi T, Massobrio P, Chiappalone M, "Connecting biological and artificial neural networks," MEA 2016, Reutlingen, Germany, July 2016
  2. Levi T, "Biomimetic Spiking Neural Network for Neurological Studies," Neurogune 2016, Bilbao, Spain, June 2016

 

2015

Book chapters
  1. Ambroise M, Levi T and Saïghi S, Biomimetic CPG, "Biomimetic technologies Principles and Applications," edited by Dr Trung Dung Ngo, Elsevier, Chapter 15, August 2015
  2. Baccar S, Levi T, Dallet D and Barbara F, "Optimizing Models Precision in High Temperature for an Efficient Analogue and Mixed-Signal Circuits Design by Using Modern Behavioral Modeling Technique: an Industrial Case Study," Computational Intelligence in Analog and Mixed-Signal (AMS) and Radio-Frequency (RF) Circuit Design, Springer, Chapter 7, August 2015
Conferences
  1. Levi T, "Biomimetic neural network for the new neuromorphic roadmap," Beyond CMOS, Munich, Germany, October 2015
  2. Levi T, Tixier-Mita A, Ségard B-D, Toshiyoshi H, Fujita H, Fujii T, "Biomimetic microfluidic neuron for hybrid experiments," MicroTAS 2015, Gyeongju, South Korea, October 2015
  3. Levi T, Araki A, Fujii T, "Artificial biomimetic neuron on a microfluidic device, 2015 Bridging Biomedical Worlds, from neural circuitry to neurotechnology," Tokyo, Japan, May 2015

 

 2014

Journals
  1. F. GRASSIA, T. LEVI, T. KOHNO, S. SAIGHI, "Silicon neuron: digital hardware implementation of the quartic model", Journal of Artificial Life and Robotics, Springer, vol. 19, Issue 3, pp. 215-219, November 2014.
Conferences
  1. T. LEVI, A. ARAKI,T. FUJII, "Microfluidic neuron: a Neuromimetic Approach to Interact with Biological Neurons", IEEE EMBS Micro and Nanotechnology in Medecine conference, Hawaii, US, December 2014.
  2. T. LEVI, M. AMBROISE, F. GRASSIA, O. MALOT, S. SAIGHI, Y. BORNAT, J. TOMAS, S. RENAUD, "Biomimetic neural networks for hybrid experiments", International Symposium on Neuromorphic and Non-linear Engineering, ISNNE 2014, Tokyo, Japan, February 2014.
  3. M. AMBROISE, T. LEVI, S. SAIGHI, "Biomimetic CPG on FPGA for hybrid experiments", International Symposium on Neuromorphic and Non-linear Engineering, ISNNE 2014, Tokyo, Japan, February 2014
  4. S. BACCAR, T. LEVI, D. DALLET, F. BARBARA, "Modeling and Simulation of an Instrumentation Amplifier in High Temperature Using a VHDL-AMS Op-Amp Model", NEWCAS 2014, Trois-Rivières, Canada, June 2014.
  5. T. LEVI, M. AMBROISE, F. GRASSIA, S. SAIGHI, T. KOHNO, T. FUJII, "Biomimetic CPGs for robotic applications", 19th International Symposium on Artificial Life and Robotics, pp. 355-358, Beppu, Japan, January 2014, Best paper award.
  6. F. GRASSIA, T. LEVI, T. KOHNO, S. SAIGHI, "Silicon neuron: digital hardware implementation of the quartic model", 19th International Symposium on Artificial Life and Robotics, pp. 359-362, Beppu, Japan, January 2014.

 

 2013

Journals
  1. M. Ambroise, T. Levi, S. Joucla, B. Yvert, S. Saighï, Real-time biomimetic Central Pattern Generators into FPGA for hybrid experiments, Frontiers in Neurosciences, 7:215, November 2013
  2. P. Bonifazi, F. Difato, G. L. Breschi, P. Massobrio, T. Levi, M. Goldin, J. Tessadori, V. Pasquale, Y. Bornat, S. Taverna, M. Chiappalone, In vitro large-scale experimental and theoretical studies for the realization of bi-directional brain-prostheses, Frontiers in Neural Circuits, 7:40, March 2013. 
Conferences
  1. M. Ambroise, T. Levi, S. Saighï, "Leech Heartbeat Neural Network on FPGA", Biomimetic and biohybrid systems, Lecture notes in computer science, Vol. 8064, pp. 347-349, Living Machines 2013, London, UK, July 29 – August 2 2013.
  2. S. Baccar, T. Levi, D. Dallet, F. Barbara, "Modeling and Simulation of a Wheatstone Bridge Pressure Sensor in High Temperature with VHDL-AMS", 19th symposium IMEKO, Barcelona, Spain, July 2013.
  3. M. Ambroise, T. Levi, Y. Bornat, S. Saighï, "Biorealistic Spiking Neural Network on FPGA", IEEE CISS 2013, Baltimore, US, March 2013.
  4. S. Joucla, M. Ambroise, T. Levi, T. Lafon, P. Chauvet, L. Rousseau, G. Lissorgues, S. Saighi, Y. Bornat, N. Lewis, S. Renaud, B. Yvert, "Generation of Locomotor-Like Activity in the Isolated Rat Spinal Cord by Electrical Microstimulations Driven by an Artificial CPG", 6th International IEEE EMBS Conference on Neural Engineering, San Diego, US, November 2013. 
  5. P. Bonifazi, P. Massobrio, T. Levi, F. Difato, G. Breschi, V. Pasquale, M. Goldin, M. Ambroise, Y. Bornat, M. Tedesco, M. Bisio, M. Frega, J. Tessadori, P. Nowak, F. Grassia, S. Kanner, G. Ronit, S. Renaud, S. Martinoia, S. Taverna, M. Chiappalone, "In vitro experimental and theoretical studies to restore lost neuronal functions: the Brain Bow experimental framework", 6th International IEEE EMBS Conference on Neural Engineering, San Diego, US, November 2013.
  6. T. Levi, "Conception de reseau de neurones du coeur de sangsue", JFR13, Maison Franco-Japonaise, Tokyo (29-12-2013).

 

 2012 and prior

Journals
  1. T. Levi, N. Lewis, J. Tomas, S. Renaud, Application of IP-based Analog Platforms in the design of Neuromimetic Integrated Circuits, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 31 , Issue 11, pp. 1629-1641, November 2012.
  2. F. Grassia, T. Levi, S. Saighï, T. Kohno, Bifurcation analysis in a silicon neuron, Journal of Artificial Life and Robotics, Springer, vol. 17, Issue 1, pp. 53-58, October 2012.
  3. S. Baccar, T. Levi, D. Dallet, S. Qaisar, V. Shitikov, F. Barbara, Modeling Methodology for Analog Front-End Circuits Dedicated to High-Temperature Instrumentation and Measurement applications, IEEE Transactions on Instrumentation and Measurement, vol. 60, pp. 1555-1564, May 2011.
  4. F. Grassia, L. Buhry, T. Levi, J. Tomas, A. Destexhe, S. Saighi, Tunable neuromimetic integrated system for emulating cortical neuron models, Frontiers in Neurosciences, 5:134, December 2011.
  5. Levi T.,Tomas J.,Lewis N. and Fouillat P., A CMOS Resizing Methodology for Analog Circuits, IEEE Design & Test of Computers, 26(1): 78-86, 2009.
Patents
  1. T. Levi, J.F. Beche, S. Bonnet, R. Escola, Methods and Devices for  processing pulse signals, and in particular Neural Action Potential Signals, European Patent Application EP2389103, filing date: December 12th 2008, publication date: November 2011.
Book Chapter
  1. J.F. Bêche, T. Levi, G. Charvet, O. Billoin, L. Rousseau, J.P. Rostaing, C. Condemine, S. Bonnet, R. Escola, T. Kauffmann, B. Yvert, R. Guillemaud, System Architecture for Neural–Electrical Interface and Processing, Integrated Microsystems Electronics, Photonics, and Biotechnology, Iniewski Editor, CRC Press, pp. 133-146, October 2011.
Conferences
  1. S. Baccar, T. Levi, D. Dallet, V. Shitikov, F. Barbara, "A Validity Study of an Industrial SPICE based Op-amp Macromodel for High-Temperature Simulation", IEEE I2MTC 2012, Graz, Austria,  May 2012. 
  2. F. Grassia, T. Levi, S. Saighï, T. Kohno, "Bifurcation analysis in a silicon neuron", International Symposium on Artificial Life and Robotics, Beppu, Japan, January 2012. 
  3. M. Chiappalone, F. Difato, G. Breschi, V. Pasquale, M. Bisio, Y. Bornat, P. Massobrio, T. Levi, S. Taverna, P. Bonifazi, "Linking biological and artificial neuronal assemblies to restore lost brain functions", Neuroscience 2012, New Orleans (LO, USA), October 13-17, 2012.
  4. F. Grassia, T. Levi, J. Tomas, S. Renaud, S. Saighi, A Neuromimetic Spiking Neural Network for Simulating Cortical Circuits, IEEE CISS 2011, Baltimore, US,  March 2011.
  5. Levi T. and Kohno T., Silicon neural network circuits for smart-MEMS systems, CMOS Emerging Technologies, Canada, 2009

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