1. The Physiologists FriendChip A product of the Institute of Neuroinformatics The only FriendChip youll ever need

3. A Typical Visual Physiology Setup Several communicating machines, custom software. Months of development and debugging… Stimulus

4. Goal To make a practical chip that acts as a substitute animal for experiment design or demonstration. It should provide spiking neurons from retina and early visual cortex. It should be plug and play: battery power no computer no knobs.

5. Chip + Lens BNC connector Volumecontrol Onboard speaker Output selector External speaker jack

6. Chip schematic Photoreceptors Horizontal/Bipolar Ganglion Synapses Photodiodes Bias generator 34 1 2 5 6 7 8 On Off Excitatory Inhibitory Average Brighter than average Darker than average Simple cells

7. Layout Photoreceptors Bipolar/Horizontal cells Ganglion & Simple cells Synapses Photodiodes 2.2mm Biases

8. Photoreceptor layer

9. Photoreceptor has low DC gain, high transient gain

10. Adaptive Photoreceptor Circuit

11. VpVp V fb I photo log I V VpVp V fb -U T /e-fold

12. log I V VpVp V fb V out IbIb VpVp V out transient V fb In steady state (DC) V=0 C2C2 C1C1 Long term history of brightness

13. Bipolar and Horizontal Layer

14. Horizontal cell Averages photoreceptor output V avg V photo

15. Horizontal cell Using Deweerths follower aggegrator V photo V avg Averages photoreceptor output Transconductance amplifiers

16. Bipolar Cell Rectifies into ON and OFF currents Steals center part of diff pair current

17. Ganglion cell layer

18. Ganglion/Simple cells have integrate and fire somas with spike adaptation (Mead/Boahen)

19. Dendritic Trees of Simple Cells Excitatory Inhibitory Are arranged to make orientation tuned simple cells with push-pull inputs

20. Simple cell synapses ExcitatoryInhibitory Inject slow pulses of charge with each spike

21. Receptive fields of outputs Photoreceptor (1) Horizontal cell ON center ganglion (3) OFF center ganglion (4) V mem ODD simple (5) V mem ON EVEN simple (6) ODD simple (7) ON EVEN simple (8) V mem Ganglion cell (2) produces maximal response (average photoreceptor value) Chip output

22. PCB Chip + Lens BNC connector Volumecontrol Onboard speaker Output selector External speaker jack

26. Representative responses to drifting grating with varying orientation

27. Spatial RFs of simple cells Measured by reverse spike correlation using random orientation stimuli Thanks to Matteo Carrandini

28. Temporal and spatial frequency tunings of a simple cell Thanks to Matteo Carrandini

29. Chip design notes Chip simulation: 1s real time takes about 10h on P3 866MHz (TSPICE) –Simulations are very stiff numerically Cost: Chip ~$220, system ~$360. (dominated by cost of small quantity chip prototypes)

30. Specifications Power supply9V battery 9V DC supply (- on inside) Power consumptionExternal speaker: 2.5mA Internal Speaker: 5 to 20mA Lens8mm focal length Neutral density filter1 decade filter behind lens temporally lowpass filters signal so chip can be used with monitor input Tripod mountStandard 1/4 by 20 tripod thread

31. Quick user guide 1 Cell #Cell TypeOutput type 3ON ganglion cellSpike 4OFF ganglion cellSpike 7ODD simple cellSpike 8EVEN simple cellSpike 5ODD simple cellV mem 6EVEN simple cellV mem 1Center PhotoreceptorV mem 2Side Ganglion cellV mem

32. Quick user guide 2 Things to be careful about: –Watch out for static electricity (ground yourself before picking up the friendchip). Static can kill the chip! –Store the friendchip in an anti-static bag –The lens holder is only attached with double stick tape, it can be pulled off.

33. What we plan Complex cells Direction selective cells Production of ~100 systems for no-profit distribution to labs and teachers (We have orders for about 30)

34. Collaborators and Helpers From INI Matteo Carandini Kevan Martin Tobe Freeman Jorg Kramer Giacomo Indiveri From Telluride Workshop, July 2000 Jeff Dean, Cleveland State, USA Barbara Claas, Cleveland State, USA Elana Grassi, Univ. of Maryland, Inst. for Systems Research, USA Joaquin Sitte, Queensland University of Technology, Australia Richard Reeve, Stirling University, Scotland Daljeet Gill, Leicester, UK Bias circuits Andre Van Schaik, Univ. of Sydney Oliver Landolt, Agilent Bic Schediwy, Synaptics Supported by the Swiss National Science Foundation