Abstract

In this paper, we present: (i) a novel analog silicon retina featuring auto-adaptive pixels that obey the Michaelis-Menten law, i.e. V=VmInIn+σn; (ii) a method of characterizing silicon retinas, which makes it possible to accurately assess the pixels’ response to transient luminous changes in a ±3-decade range, as well as changes in the initial steady-state intensity in a 7-decade range. The novel pixel, called M2APix, which stands for Michaelis-Menten Auto-Adaptive Pixel, can auto-adapt in a 7-decade range and responds appropriately to step changes up to ±3 decades in size without causing any saturation of the Very Large Scale Integration (VLSI) transistors. Thanks to the intrinsic properties of the Michaelis-Menten equation, the pixel output always remains within a constant limited voltage range. The range of the Analog to Digital Converter (ADC) was therefore adjusted so as to obtain a Least Significant Bit (LSB) voltage of 2.35mV and an effective resolution of about 9 bits. The results presented here show that the M2APix produced a quasi-linear contrast response once it had adapted to the average luminosity. Differently to what occurs in its biological counterparts, neither the sensitivity to changes in light nor the contrast response of the M2APix depend on the mean luminosity (i.e. the ambient lighting conditions). Lastly, a full comparison between the M2APix and the Delbrück auto-adaptive pixel is provided.

© 2015 Optical Society of America

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References

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2014 (1)

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

2013 (4)

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

J. Carneiro, S.-H. Ieng, C. Posch, and R. Benosman, “Event-based 3D reconstruction from neuromorphic retinas,” Neural Networks 45, 27–38 (2013).
[Crossref] [PubMed]

C. Pacoret and S. Régnier, “A review of haptic optical tweezers for an interactive microworld exploration,” Rev. Sci. Instrum. 84, 081301 (2013).
[Crossref]

2012 (1)

F. Expert, S. Viollet, and F. Ruffier, “Outdoor field performances of insect-based visual motion sensors,” J. Field Robot. 28, 529–541 (2012).
[Crossref]

2011 (3)

D. Drazen, P. Lichtsteiner, P. Häfliger, T. Delbrück, and A. Jensen, “Toward real-time particle tracking using an event-based dynamic vision sensor,” Exp. Fluids 51, 1465–1469 (2011).
[Crossref]

K. Shimonomura, S. Kameda, A. Iwata, and T. Yagi, “Wide-dynamic-range APS-based silicon retina with brightness constancy,” IEEE Trans. Neural Networks 22, 1482–93 (2011).
[Crossref]

S. Ferradans, M. Bertalmio, E. Provenzi, and V. Caselles, “An analysis of visual adaptation and contrast perception for tone mapping,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2002–2012 (2011).
[Crossref]

2009 (1)

A. Spivak, A. Belenky, A. Fish, and O. Yadid-Pecht, “Wide-Dynamic-Range CMOS Image Sensors - Comparative Performance Analysis,” IEEE Trans. Electron Devices 56, 2446–2461 (2009).
[Crossref]

2008 (1)

P. Lichtsteiner, C. Posch, and T. Delbrück, “A 128×128 120 dB 15 μs Latency Asynchronous Temporal Contrast Vision Sensor,” IEEE J. Solid-State Circuits 43, 566–576 (2008).
[Crossref]

2007 (1)

2006 (1)

K. A. Zaghloul and K. Boahen, “A silicon retina that reproduces signals in the optic nerve,” J. Neural Eng. 3, 257–267 (2006).
[Crossref] [PubMed]

2005 (1)

E. Reinhard and K. Devlin, “Dynamic range reduction inspired by photoreceptor physiology,” IEEE Trans. Vis. Comput. Graphics 11, 13–24 (2005).
[Crossref]

2002 (1)

E. Zrenner, “Will Retinal Implants Restore Vision?,” Science 295, 1022–1025 (2002).
[Crossref] [PubMed]

1997 (1)

P. Venier and X. Arreguit, “Réseau de cellules photosensibles et capteur d’images comportant un tel réseau,” French Patent, Patent No.: EP0792063A1 (1997).

1993 (1)

S. Laughlin and M. Weckstrom, “Fast and slow photoreceptors - a comparative study of the functional diversity of coding and conductances in the Diptera,” J. Comp. Physiol., A 172, 593–609 (1993).
[Crossref]

1988 (1)

C. A. Mead and M. Mahowald, “A silicon model of early visual processing,” Neural Networks 1, 91–97 (1988).
[Crossref]

1983 (1)

J. M. Valeton, “Photoreceptor light adaptation models: an evaluation,” Vision Res. 23, 1549–1554 (1983).
[Crossref] [PubMed]

1981 (1)

W. S. Geisler, “Effects of bleaching and backgrounds on the flash response of the cone system,” J. Physiol. 50, 413–434 (1981).
[Crossref]

1979 (1)

R. A. Normann and I. Perlman, “The effects of background illumination on the photoresponses of red and green cones,” J. Physiol. 286, 491–507 (1979).
[Crossref] [PubMed]

1978 (1)

S. B. Laughlin and R. C. Hardie, “Common strategies for light adaptation in the peripheral visual systems of fly and dragonfly,” J. Comp. Physiol., A 128, 319–340 (1978).
[Crossref]

1975 (2)

J. Kleinschmidt and J. E. Dowling, “Intracellular Recordings from Gecko Photoreceptors during Light and Dark Adaptation,” J. Gen. Physiol. 66, 617–648 (1975).
[Crossref] [PubMed]

D. C. Hood and P. A. Hock, “Light adaptation of the receptors: Increment threshold functions for the frog’s rods and cones,” Vision Res. 15, 545–553 (1975).
[Crossref] [PubMed]

1974 (1)

F. S. Werblin, “Control of Retinal Sensitivity II: Lateral Interactions at the Outer Plexiform Layer,” J. Gen. Physiol. 63, 62–87 (1974).
[Crossref] [PubMed]

1971 (1)

F. S. Werblin, “Adaptation in a vertebrate retina: intracellular recording in Necturus,” J. Neurophysiol. 34, 228–241 (1971).
[PubMed]

1970 (2)

D. A. Baylor and M. G. F. Fuortes, “Electrical responses of single cones in the retina of the turtle,” J. Physiol. 207, 77–92 (1970).
[Crossref] [PubMed]

R. M. Boynton and D. N. Whitten, “Visual Adaptation in Monkey Cones: Recordings of Late Receptor Potentials,” Science 170, 1423–1426 (1970).
[Crossref] [PubMed]

1966 (1)

K. I. Naka and W. A. H. Rushton, “S-potentials from luminosity units in the retina of fish (Cyprinidae),” J. Physiol. 185, 536–555 (1966).
[Crossref] [PubMed]

1959 (1)

T. Oikawa, T. Ogawa, and K. Motokawa, “Origin of so-called cone action potential,” J. Neurophysiol. 22, 102– 111 (1959).
[PubMed]

1953 (1)

G. Svaetichin, “The cone action potential,” Acta Physiol. 29, 565–600 (1953).

1913 (1)

L. Michaelis and M. L. Menten, “The Kinetics of Invertase Action (Die Kinetik der Invertinwirkung),” Biochemische Zeitschrift 49, 333–369 (1913).

Abbas, H.

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Alleysson, D.

L. Meylan, D. Alleysson, and S. Süsstrunk, “Model of retinal local adaptation for the tone mapping of color filter array images,” J. Opt. Soc. Am. A 24, 2807–2816 (2007).
[Crossref]

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Amhaz, H.

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Andreou, A. G.

K. A. Boahen and A. G. Andreou, “A Contrast Sensitive Silicon Retina with Reciprocal Synapses,” in Adv. Neural Inf. Process. Syst. 4, D. S. Touretzky, ed. (Morgan Kaufmann, 1991), pp. 764–772.

Arreguit, X.

P. Venier and X. Arreguit, “Réseau de cellules photosensibles et capteur d’images comportant un tel réseau,” French Patent, Patent No.: EP0792063A1 (1997).

Aryan, N. P.

L. Liu, J. Wiinschmann, N. P. Aryan, A. Zohny, M. Fischer, S. Kibbel, and A. Rothermel, “An ambient light adaptive subretinal stimulator,” in Proc. ESSCIRC ’09 (IEEE, 2009), pp. 420–423.
[Crossref]

Bartz-Schmidt, K. U.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Baylor, D. A.

D. A. Baylor and M. G. F. Fuortes, “Electrical responses of single cones in the retina of the turtle,” J. Physiol. 207, 77–92 (1970).
[Crossref] [PubMed]

Belenky, A.

A. Spivak, A. Belenky, A. Fish, and O. Yadid-Pecht, “Wide-Dynamic-Range CMOS Image Sensors - Comparative Performance Analysis,” IEEE Trans. Electron Devices 56, 2446–2461 (2009).
[Crossref]

Benosman, R.

J. Carneiro, S.-H. Ieng, C. Posch, and R. Benosman, “Event-based 3D reconstruction from neuromorphic retinas,” Neural Networks 45, 27–38 (2013).
[Crossref] [PubMed]

Bertalmio, M.

S. Ferradans, M. Bertalmio, E. Provenzi, and V. Caselles, “An analysis of visual adaptation and contrast perception for tone mapping,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2002–2012 (2011).
[Crossref]

Besch, D.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Boahen, K.

K. A. Zaghloul and K. Boahen, “A silicon retina that reproduces signals in the optic nerve,” J. Neural Eng. 3, 257–267 (2006).
[Crossref] [PubMed]

Boahen, K. A.

K. A. Boahen and A. G. Andreou, “A Contrast Sensitive Silicon Retina with Reciprocal Synapses,” in Adv. Neural Inf. Process. Syst. 4, D. S. Touretzky, ed. (Morgan Kaufmann, 1991), pp. 764–772.

Boynton, R. M.

R. M. Boynton and D. N. Whitten, “Visual Adaptation in Monkey Cones: Recordings of Late Receptor Potentials,” Science 170, 1423–1426 (1970).
[Crossref] [PubMed]

Braun, A.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Breugnon, P.

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

Bruckmann, A.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Brückner, A.

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

Buss, W.

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

Caplier, A.

N.-S. Vu and A. Caplier, “Illumination-robust face recognition using retina modeling,” in IEEE Int. Conf. Image Process. (ICIP ’09), (IEEE, 2009), pp. 3289–3292.

Carneiro, J.

J. Carneiro, S.-H. Ieng, C. Posch, and R. Benosman, “Event-based 3D reconstruction from neuromorphic retinas,” Neural Networks 45, 27–38 (2013).
[Crossref] [PubMed]

Caselles, V.

S. Ferradans, M. Bertalmio, E. Provenzi, and V. Caselles, “An analysis of visual adaptation and contrast perception for tone mapping,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2002–2012 (2011).
[Crossref]

Chavent, P.

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S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
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D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
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S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
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S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
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D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
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J. Carneiro, S.-H. Ieng, C. Posch, and R. Benosman, “Event-based 3D reconstruction from neuromorphic retinas,” Neural Networks 45, 27–38 (2013).
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[Crossref]

Recktenwald, F.

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

Régnier, S.

C. Pacoret and S. Régnier, “A review of haptic optical tweezers for an interactive microworld exploration,” Rev. Sci. Instrum. 84, 081301 (2013).
[Crossref]

Reinhard, E.

E. Reinhard and K. Devlin, “Dynamic range reduction inspired by photoreceptor physiology,” IEEE Trans. Vis. Comput. Graphics 11, 13–24 (2005).
[Crossref]

Rolland, R.

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Rothermel, A.

L. Liu, J. Wiinschmann, N. P. Aryan, A. Zohny, M. Fischer, S. Kibbel, and A. Rothermel, “An ambient light adaptive subretinal stimulator,” in Proc. ESSCIRC ’09 (IEEE, 2009), pp. 420–423.
[Crossref]

Ruffier, F.

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

F. Expert, S. Viollet, and F. Ruffier, “Outdoor field performances of insect-based visual motion sensors,” J. Field Robot. 28, 529–541 (2012).
[Crossref]

G. Sabiron, P. Chavent, T. Raharijaona, P. Fabiani, and F. Ruffier, “Low-speed optic-flow sensor onboard an unmanned helicopter flying outside over fields,” in IEEE Int. Conf. Robot. Autom. (ICRA ’13), (IEEE, 2013), pp. 1742–1749.
[Crossref]

F. Expert and F. Ruffier, “Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers,” Bioinspir. Biomim. (to be published in February 2015).

Rushton, W. A. H.

K. I. Naka and W. A. H. Rushton, “S-potentials from luminosity units in the retina of fish (Cyprinidae),” J. Physiol. 185, 536–555 (1966).
[Crossref] [PubMed]

Sabiron, G.

G. Sabiron, P. Chavent, T. Raharijaona, P. Fabiani, and F. Ruffier, “Low-speed optic-flow sensor onboard an unmanned helicopter flying outside over fields,” in IEEE Int. Conf. Robot. Autom. (ICRA ’13), (IEEE, 2013), pp. 1742–1749.
[Crossref]

Sachs, H.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Schatz, A.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Shimonomura, K.

K. Shimonomura, S. Kameda, A. Iwata, and T. Yagi, “Wide-dynamic-range APS-based silicon retina with brightness constancy,” IEEE Trans. Neural Networks 22, 1482–93 (2011).
[Crossref]

Sicard, G.

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Spivak, A.

A. Spivak, A. Belenky, A. Fish, and O. Yadid-Pecht, “Wide-Dynamic-Range CMOS Image Sensors - Comparative Performance Analysis,” IEEE Trans. Electron Devices 56, 2446–2461 (2009).
[Crossref]

Stingl, K.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Stingl, K. T.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

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G. Svaetichin, “The cone action potential,” Acta Physiol. 29, 565–600 (1953).

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J. M. Valeton, “Photoreceptor light adaptation models: an evaluation,” Vision Res. 23, 1549–1554 (1983).
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Venier, P.

P. Venier and X. Arreguit, “Réseau de cellules photosensibles et capteur d’images comportant un tel réseau,” French Patent, Patent No.: EP0792063A1 (1997).

Viollet, S.

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
[Crossref]

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

F. Expert, S. Viollet, and F. Ruffier, “Outdoor field performances of insect-based visual motion sensors,” J. Field Robot. 28, 529–541 (2012).
[Crossref]

Vu, N.-S.

N.-S. Vu and A. Caplier, “Illumination-robust face recognition using retina modeling,” in IEEE Int. Conf. Image Process. (ICIP ’09), (IEEE, 2009), pp. 3289–3292.

Weckstrom, M.

S. Laughlin and M. Weckstrom, “Fast and slow photoreceptors - a comparative study of the functional diversity of coding and conductances in the Diptera,” J. Comp. Physiol., A 172, 593–609 (1993).
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Werblin, F. S.

F. S. Werblin, “Control of Retinal Sensitivity II: Lateral Interactions at the Outer Plexiform Layer,” J. Gen. Physiol. 63, 62–87 (1974).
[Crossref] [PubMed]

F. S. Werblin, “Adaptation in a vertebrate retina: intracellular recording in Necturus,” J. Neurophysiol. 34, 228–241 (1971).
[PubMed]

Whitten, D. N.

R. M. Boynton and D. N. Whitten, “Visual Adaptation in Monkey Cones: Recordings of Late Receptor Potentials,” Science 170, 1423–1426 (1970).
[Crossref] [PubMed]

Wiinschmann, J.

L. Liu, J. Wiinschmann, N. P. Aryan, A. Zohny, M. Fischer, S. Kibbel, and A. Rothermel, “An ambient light adaptive subretinal stimulator,” in Proc. ESSCIRC ’09 (IEEE, 2009), pp. 420–423.
[Crossref]

Wilhelm, B.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Yadid-Pecht, O.

A. Spivak, A. Belenky, A. Fish, and O. Yadid-Pecht, “Wide-Dynamic-Range CMOS Image Sensors - Comparative Performance Analysis,” IEEE Trans. Electron Devices 56, 2446–2461 (2009).
[Crossref]

Yagi, T.

K. Shimonomura, S. Kameda, A. Iwata, and T. Yagi, “Wide-dynamic-range APS-based silicon retina with brightness constancy,” IEEE Trans. Neural Networks 22, 1482–93 (2011).
[Crossref]

Zaghloul, K. A.

K. A. Zaghloul and K. Boahen, “A silicon retina that reproduces signals in the optic nerve,” J. Neural Eng. 3, 257–267 (2006).
[Crossref] [PubMed]

Zimouche, H.

G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

Zohny, A.

L. Liu, J. Wiinschmann, N. P. Aryan, A. Zohny, M. Fischer, S. Kibbel, and A. Rothermel, “An ambient light adaptive subretinal stimulator,” in Proc. ESSCIRC ’09 (IEEE, 2009), pp. 420–423.
[Crossref]

Zrenner, E.

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

E. Zrenner, “Will Retinal Implants Restore Vision?,” Science 295, 1022–1025 (2002).
[Crossref] [PubMed]

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L. Michaelis and M. L. Menten, “The Kinetics of Invertase Action (Die Kinetik der Invertinwirkung),” Biochemische Zeitschrift 49, 333–369 (1913).

Bioinspir. Biomim. (1)

F. Expert and F. Ruffier, “Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers,” Bioinspir. Biomim. (to be published in February 2015).

Exp. Fluids (1)

D. Drazen, P. Lichtsteiner, P. Häfliger, T. Delbrück, and A. Jensen, “Toward real-time particle tracking using an event-based dynamic vision sensor,” Exp. Fluids 51, 1465–1469 (2011).
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IEEE J. Solid-State Circuits (1)

P. Lichtsteiner, C. Posch, and T. Delbrück, “A 128×128 120 dB 15 μs Latency Asynchronous Temporal Contrast Vision Sensor,” IEEE J. Solid-State Circuits 43, 566–576 (2008).
[Crossref]

IEEE Trans. Electron Devices (1)

A. Spivak, A. Belenky, A. Fish, and O. Yadid-Pecht, “Wide-Dynamic-Range CMOS Image Sensors - Comparative Performance Analysis,” IEEE Trans. Electron Devices 56, 2446–2461 (2009).
[Crossref]

IEEE Trans. Neural Networks (1)

K. Shimonomura, S. Kameda, A. Iwata, and T. Yagi, “Wide-dynamic-range APS-based silicon retina with brightness constancy,” IEEE Trans. Neural Networks 22, 1482–93 (2011).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

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IEEE Trans. Vis. Comput. Graphics (1)

E. Reinhard and K. Devlin, “Dynamic range reduction inspired by photoreceptor physiology,” IEEE Trans. Vis. Comput. Graphics 11, 13–24 (2005).
[Crossref]

J. Comp. Physiol., A (2)

S. Laughlin and M. Weckstrom, “Fast and slow photoreceptors - a comparative study of the functional diversity of coding and conductances in the Diptera,” J. Comp. Physiol., A 172, 593–609 (1993).
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S. B. Laughlin and R. C. Hardie, “Common strategies for light adaptation in the peripheral visual systems of fly and dragonfly,” J. Comp. Physiol., A 128, 319–340 (1978).
[Crossref]

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F. Expert, S. Viollet, and F. Ruffier, “Outdoor field performances of insect-based visual motion sensors,” J. Field Robot. 28, 529–541 (2012).
[Crossref]

J. Gen. Physiol. (2)

F. S. Werblin, “Control of Retinal Sensitivity II: Lateral Interactions at the Outer Plexiform Layer,” J. Gen. Physiol. 63, 62–87 (1974).
[Crossref] [PubMed]

J. Kleinschmidt and J. E. Dowling, “Intracellular Recordings from Gecko Photoreceptors during Light and Dark Adaptation,” J. Gen. Physiol. 66, 617–648 (1975).
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K. A. Zaghloul and K. Boahen, “A silicon retina that reproduces signals in the optic nerve,” J. Neural Eng. 3, 257–267 (2006).
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T. Oikawa, T. Ogawa, and K. Motokawa, “Origin of so-called cone action potential,” J. Neurophysiol. 22, 102– 111 (1959).
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K. I. Naka and W. A. H. Rushton, “S-potentials from luminosity units in the retina of fish (Cyprinidae),” J. Physiol. 185, 536–555 (1966).
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J. Carneiro, S.-H. Ieng, C. Posch, and R. Benosman, “Event-based 3D reconstruction from neuromorphic retinas,” Neural Networks 45, 27–38 (2013).
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Proc. Nat. Acad. Sci. U. S. A. (1)

D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. a. Mallot, and N. Franceschini, “Miniature curved artificial compound eyes,” Proc. Nat. Acad. Sci. U. S. A. 110, 9267–72 (2013).
[Crossref]

Proc. R. Soc. London, Ser. B (1)

K. Stingl, K. U. Bartz-Schmidt, D. Besch, A. Braun, A. Bruckmann, F. Gekeler, U. Greppmaier, S. Hipp, G. Hörtdörfer, C. Kernstock, H. Koitschev, A. Kusnyerik, H. Sachs, A. Schatz, K. T. Stingl, T. Peters, B. Wilhelm, and E. Zrenner, “Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS,” Proc. R. Soc. London, Ser. B 280, (2013).
[Crossref]

Rev. Sci. Instrum. (1)

C. Pacoret and S. Régnier, “A review of haptic optical tweezers for an interactive microworld exploration,” Rev. Sci. Instrum. 84, 081301 (2013).
[Crossref]

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R. M. Boynton and D. N. Whitten, “Visual Adaptation in Monkey Cones: Recordings of Late Receptor Potentials,” Science 170, 1423–1426 (1970).
[Crossref] [PubMed]

E. Zrenner, “Will Retinal Implants Restore Vision?,” Science 295, 1022–1025 (2002).
[Crossref] [PubMed]

Sensors (1)

S. Viollet, S. Godiot, R. Leitel, W. Buss, P. Breugnon, M. Menouni, R. Juston, F. Expert, F. Colonnier, G. L’Eplattenier, A. Brückner, F. Kraze, H. Mallot, N. Franceschini, R. Pericet-Camara, F. Ruffier, and D. Floreano D., “Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye,” Sensors 110, 21702–21721 (2014).
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G. Sicard, H. Abbas, H. Amhaz, H. Zimouche, R. Rolland, and D. Alleysson, “A CMOS HDR Imager with an Analog Local Adaptation,” in Int. Image Sensor Workshop (IISW ’13), (2013), pp. 1–4.

L. Liu, J. Wiinschmann, N. P. Aryan, A. Zohny, M. Fischer, S. Kibbel, and A. Rothermel, “An ambient light adaptive subretinal stimulator,” in Proc. ESSCIRC ’09 (IEEE, 2009), pp. 420–423.
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[Crossref]

N.-S. Vu and A. Caplier, “Illumination-robust face recognition using retina modeling,” in IEEE Int. Conf. Image Process. (ICIP ’09), (IEEE, 2009), pp. 3289–3292.

S.-C. Liu, J. Kramer, G. Indiveri, T. Delbrück, and R. Douglas, Analog VLSI: Circuits and Principles (MIT Press, 2002).

P. Venier and X. Arreguit, “Réseau de cellules photosensibles et capteur d’images comportant un tel réseau,” French Patent, Patent No.: EP0792063A1 (1997).

G. Sabiron, P. Chavent, T. Raharijaona, P. Fabiani, and F. Ruffier, “Low-speed optic-flow sensor onboard an unmanned helicopter flying outside over fields,” in IEEE Int. Conf. Robot. Autom. (ICRA ’13), (IEEE, 2013), pp. 1742–1749.
[Crossref]

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Figures (13)

Fig. 5
Fig. 5 (a) Simulated example of the adaptive pixel’s response (blue line) to a step change in the light intensity (light to dark gray stripe). The red and magenta lines stand for the photodiode current and the average current, respectively. (b) Theoretical S-shaped curve based on equation (4), giving the peak values of the pixel’s response Vi to step changes in the photodiode current from Iph0 to Iphi.
Fig. 7
Fig. 7 (a) Pictures and (b) exploded view of the Lighting Box composed of a PCB with a red LED (λ ≈ 618nm) and an optical filter support. The direct control of the LED current makes the illuminance vary in a 3-decade range. Additional optical filters (neutral density filters) were used to drastically increase the mean luminosity range from 3 to 7 decades.
Fig. 1
Fig. 1 S-shaped curves corresponding to dark- and light-adapted response curves recorded in a red cone of the turtle. The peak of either the incremental or decremental response measured from the dark-adapted potential recorded before the background onset (dashed line) is plotted as a function of the log of the test pulse intensity which elicited each response. The steady hyperpolarization produced by each background lighting condition is given by the intersection between the intensity-response curve and the small horizontal line. The continuous curves were drawn from a single template which describes the function V = V m I I + σ. Adapted from [10].
Fig. 2
Fig. 2 (a) The silicon retina in its 9 × 9mm package; (b) Magnified view of the silicon retina composed of 12 Michaelis-Menten pixels presented in this study, and 12 additional Delbrück pixels; (c) Magnified view of 3 Michaelis-Menten pixels giving the photodiode’s dimensions and the inter-receptor distance.
Fig. 3
Fig. 3 Block diagram of the retina’s serial synchronous read-out interface (see [39]).
Fig. 4
Fig. 4 (a) Block diagram of the M2APix: Michaelis-Menten Auto-adaptive Pixel. The blocks in the dashed-line area, which are replicated 12 times, belong to a single pixel, whereas the two blocks outside the dashed-line area are common to all twelve pixels. (b) Hardware implementation in VLSI of an elementary auto-adaptive pixel (photodiode and current normalizer), the output signal of which is noted Iouti. A switch S can be used to select either I0i as the mean current Imeani provided by the built-in averaging circuit, or an external current Iexti provided by an external circuit. (c) Hardware implementation in VLSI of the filtering and averaging circuit computing the mean current of the 12 mirrored photodiode currents (I′phi) produced by the 12 normalizer circuits.
Fig. 6
Fig. 6 Root Mean Square (RMS) of the simulated output noise (blue) and corresponding minimum detectable contrast (red) with respect to the photodiode current. The RMS values are given by integrating in [10−5, 108]Hz the output noise obtained with an AC noise simulation which takes into account all the transistor noises and a white noise for the input photodiode. The minimum detectable contrast can be defined as the contrast that gives rise to a transient response of the output signal ±6-fold the RMS noise.
Fig. 8
Fig. 8 Block diagram of the hardware setup and communication flow involved in the pixel characterization procedure.
Fig. 9
Fig. 9 (a) Example of M2APix responses to step changes in the LED irradiance (ILEDi), starting with the same initial irradiance ( I LED 0 = 1 W m 2). (b) Zoom of the temporal pixel responses shown in Fig. 9(a) ranging between 0 and 50ms. To be able to distinguish more clearly between the steady-state responses and the transient responses, the step changes were delayed by 10ms (Ts) after the acquisition procedure had started. The black circles amount to 90% of the peak values Vouti and give qualitative information about the rise time (Tr). The contrast values are given by the Michelson formula c i = I LED i I LED 0 I LED i + I LED 0.
Fig. 10
Fig. 10 Average rise time with respect to luminous contrast. Each point corresponds to the time (Tr) required to reach 90% of the peak value Vouti, as depicted in Fig. 9(b). Each color refers to a different initial irradiance value ILED0: red about 0.001 W m 2, pink about 0.01 W m 2, dark blue about 0.1 W m 2, light blue about 1 W m 2, cyan about 10 W m 2, green about 100 W m 2.
Fig. 11
Fig. 11 (a) S-shaped curves and steady-state responses of the 12 pixels to LED irradiance changes in a 7-decade range. Each color refers to a different initial irradiance value ILED0 (red about 0.001 W m 2, pink about 0.01 W m 2, dark blue about 0.1 W m 2, light blue about 1 W m 2, cyan about 10 W m 2, green about 100 W m 2, same color and marker as Fig. 10), and the data points correspond to the average peak value Vouti reached by the 12 pixels in response to a step change in the irradiance ILEDi, as shown in Fig. 5. The steady-state response (black points) was obtained with ILEDi = ILED0 at several values of ILED0, whereas the initial values of the irradiance ILED0 are indicated by large black circles. The shaded areas were obtained by plotting the minimum to maximum values of the mean pixel output voltages. The average dispersion of each curve (σmean) ranged from 37.2mV in the case of the green one, to 85.4mV, in that of the red one. (b) Average peak response of the 12 pixels versus the contrast. The various curves correspond to the S-shaped curves in Fig. 11(a) (same colors and markers). The contrast is given by the Michelson formula: c i = I LED i I LED 0 I LED i + I LED 0.
Fig. 12
Fig. 12 Absolute value of the error between the M2APix responses measured and those predicted by the model with respect to the LED irradiance. As post-layout simulations of the circuit showed that the current-to-voltage converter gave a non-linear response at low current values, the theoretical values V out i * were computed by applying a look-up table of the current-to-voltage converter to (2), with Iph = ILED instead of using equation (4). (Same color and marker as previous figures)
Fig. 13
Fig. 13 (a) Two sequences of small contrasts in a 2-decade irradiance range. Time responses of (b) M2APix and (c) Delbrück pixel [16], implemented in the same silicon retina (see Fig. 2), when exposed to the irradiance sequences in Fig. 13(a). The sequences were obtained by repeating: ±2% and ±4% contrasts (blue line), ±6% and ±12% contrasts (red line). The steps in the sequence were triggered every 0.5 s and the changes in the average irradiance every 5s. For the sake of clarity, the timing of the sequence has been slightly shifted. (The spurious peaks, such as that which occurred at 10.5 s, may have been due to some error in the data transmission)

Tables (1)

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Table 1 Specifications of the M2APix and Delbrück pixels. The main advantage is that M2APix responds monotonically over very wide illuminance range without any loss of sensitivity and contrast resolution.

Equations (6)

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V = V m I n I n + σ n ,
I out i = I b I ph i I ph i + I mean i ,
V out = R f I out ,
V out = R f I b I ph I ph + I mean + V BG ,
V out 0 = R f I b 2 + V BG ,
V out i = R f I b c i + 1 2 + V BG .

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