A. R. Adamantidis, F. Zhang, A. M. Aravanis, K. Deisseroth, and L. De-lecea, Neural substrates of awakening probed with optogenetic control of hypocretin neurons, Nature, vol.23, issue.7168, pp.420-424, 2007.
DOI : 10.1038/nature06310

B. Bonnard and I. Kupka, Théories des singularités de l'application entrée/sortie et optimalité des trajectoires singulières dans le problème du temps minimal, Forum Math, vol.5, pp.111-159, 1993.

E. S. Boyden, Optogenetics and the future of neuroscience, Nature Neuroscience, vol.18, issue.9, pp.1200-1201, 2015.
DOI : 10.1126/scitranslmed.3003101

E. S. Boyden, F. Zhang, E. Bamberg, G. Nagel, and K. Deisseroth, Millisecond-timescale, genetically targeted optical control of neural activity, Nature Neuroscience, vol.72, issue.9, pp.1263-1268, 2005.
DOI : 10.1016/S0896-6273(04)00266-1

E. Brown, J. Moehlis, and P. Holmes, On the Phase Reduction and Response Dynamics of Neural Oscillator Populations, Neural Computation, vol.14, issue.4, pp.673-715, 2004.
DOI : 10.1007/BF02339491

Y. Chen, M. Xiong, and S. C. Zhang, Illuminating Parkinson's therapy with optogenetics, Nature Biotechnology, vol.78, issue.2, pp.149-150, 2015.
DOI : 10.1073/pnas.0700293104

K. Deisseroth, Optogenetics, Nature Methods, vol.8, issue.1, pp.26-29, 2011.
DOI : 10.1126/science.1190897

K. Deisseroth, Optogenetics: 10 years of microbial opsins in neuroscience, Nature Neuroscience, vol.257, issue.9, pp.1213-1225, 2015.
DOI : 10.1038/311756a0

S. Ditlevsen and P. Greenwood, The Morris???Lecar neuron model embeds a leaky integrate-and-fire model, Journal of Mathematical Biology, vol.14, issue.6, pp.239-259, 2013.
DOI : 10.1007/s00285-012-0552-7

J. Feng and H. C. , Optimal Control of Neuronal Activity, Physical Review Letters, vol.91, issue.1, 2003.
DOI : 10.1103/PhysRevLett.91.018101

R. Fitzhugh, Impulses and Physiological States in Theoretical Models of Nerve Membrane, Biophysical Journal, vol.1, issue.6, pp.445-466, 1961.
DOI : 10.1016/S0006-3495(61)86902-6

R. Fourer, D. M. Gay, and B. W. Kernighan, AMPL: A Modeling Language for Mathematical Programming, 2002.

T. J. Foutz, R. L. Arlow, and C. C. Mcintyre, Theoretical principles underlying optical stimulation of a channelrhodopsin-2 positive pyramidal neuron, Journal of Neurophysiology, vol.107, issue.12, pp.3235-3245, 2012.
DOI : 10.1152/jn.00501.2011

B. M. Gaub, A. E. Berry, E. Y. Holt, J. G. Isacoff, and . Flannery, Optogenetic Vision Restoration Using Rhodopsin for Enhanced Sensitivity, Molecular Therapy, vol.23, issue.10, pp.1562-1571, 2015.
DOI : 10.1038/mt.2015.121

P. Hegemann, S. Ehlenbeck, and D. Gradmann, Multiple Photocycles of Channelrhodopsin, Biophysical Journal, vol.89, issue.6, pp.3911-3918, 2005.
DOI : 10.1529/biophysj.105.069716

A. L. Hodgkin and A. F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve, The Journal of Physiology, vol.117, issue.4, pp.500-544, 1952.
DOI : 10.1113/jphysiol.1952.sp004764

H. Lecar and C. Morris, Voltage oscillations in the barnacle giant muscle fiber, Biophysical J, vol.35, pp.193-213, 1981.

M. K. Lobo, E. J. Nestler, and H. E. Covington, Potential Utility of Optogenetics in the Study of Depression, Biological Psychiatry, vol.71, issue.12, pp.711068-1074, 2012.
DOI : 10.1016/j.biopsych.2011.12.026

A. Lolov, S. Ditlevsen, and A. Longtin, Stochastic optimal control of single neuron spike trains, J. Neural. Eng, vol.11, 2014.

A. Nabi and J. Moehlis, Single input optimal control for globally coupled neuron networks, Journal of Neural Engineering, vol.8, issue.6, pp.3911-3918, 2011.
DOI : 10.1088/1741-2560/8/6/065008

J. Nagumo, S. Arimoto, and S. Yoshizawa, An Active Pulse Transmission Line Simulating Nerve Axon, Proceedings of the IRE, vol.50, issue.10, pp.2061-2070, 1962.
DOI : 10.1109/JRPROC.1962.288235

K. Nikolic, P. Degenaar, and C. Toumazou, Modeling and engineering aspects of channel- rhodopsin2 system for neural photostimulation, Proc. 28th, pp.1626-1629, 2006.

K. Nikolic, N. Grossman, M. S. Grubb, J. Burrone, C. Toumazou et al., Photocycles of Channelrhodopsin-2, Photochemistry and Photobiology, vol.78, issue.1, pp.400-411, 2009.
DOI : 10.1111/j.1751-1097.2008.00460.x

J. T. Paz and J. R. Huguenard, Optogenetics and Epilepsy: Past, Present and Future, Epilepsy Currents, vol.15, issue.1, pp.34-38, 2015.
DOI : 10.5698/1535-7597-15.1.34

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320957

L. Pontryagin, V. Boltyanski, R. Gamkrelidze, and E. Michtchenko, Théorie mathématique des processus optimaux, Editions Mir, 1974.

J. Rubin and M. Wechselberger, The selection of mixed-mode oscillations in a Hodgkin-Huxley model with multiple timescales, Chaos: An Interdisciplinary Journal of Nonlinear Science, vol.18, issue.1, p.15105, 2008.
DOI : 10.1063/1.2789564

T. J. Ryan, D. S. Roy, M. Pignatelli, A. Arons, and S. Tonegawa, Engram cells retain memory under retrograde amnesia, Science, vol.348, issue.6238, pp.3481007-1013, 2015.
DOI : 10.1126/science.aaa5542

M. Saint-hilaire and A. Longtin, Comparison of Coding Capabilities of Type I and Type II Neurons, Journal of Computational Neuroscience, vol.16, issue.3, pp.299-313, 2004.
DOI : 10.1023/B:JCNS.0000025690.02886.93

E. Trélat, Contrôle optimal : théorie et applications, Vuibert, 2008.

E. Trélat, Optimal Control and Applications to Aerospace: Some Results and Challenges, Journal of Optimization Theory and Applications, vol.21, issue.1, pp.713-758, 2012.
DOI : 10.1007/s10957-012-0050-5

J. Wong, O. J. Abilez, and E. Kuhl, Computational optogenetics: A novel continuum framework for the photoelectrochemistry of living systems, Journal of the Mechanics and Physics of Solids, vol.60, issue.6, pp.1158-1178, 2012.
DOI : 10.1016/j.jmps.2012.02.004

A. Wächter and L. T. Biegler, On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Mathematical Programming, vol.10, issue.1, pp.25-27, 2006.
DOI : 10.1007/s10107-004-0559-y