1. 1 Neuromath kickoff meeting 2009-01-23 É. Tlapale 1, G.S. Masson 2, P. Kornprobst 1 1 : Équipe Odyssée (INRIA, ENS, INPC) 2 : Équipe DyVA (INCM/CNRS)

2. 2 Current work We design a bio-inspired model of motion integration. – Functional model (V1/MT) – Feedbacks (MT => V1) – Form modulation (V2) Why ? – To reproduce motion perception – And its dynamic

3. 3 Influence of form Chopstick illusions

4. 4 Influence of form Chopstick illusions

5. 5 Influence de la forme Jonctions intrinsèques vs extrinsèques

6. 6 Multi-layer feedback model Input : grey-level sequence

7. 7 Multi-layer feedback model Local motion detectors: correlation or energy models

8. 8 Multi-layer feedback model

9. 9 Lateral inhibition => winner-take-all

10. 10 Un modèle multi-couche rétroactif Feedback (Bayerl & Neumann, 2004)

11. 11 Multi-layer feedback model Anisotropic diffusion

12. 12 Form-modulated diffusion We only use luminosity for now

13. 13 Reproducing the perception Wallach (1935)

14. 14 Wallace, Stone et Masson (2005) Reproducing the dynamic Eye-movement like read-out

15. 15 Reproducing the neurobiology Huang, Albright et Stoner (2007) Notion of objects

16. 16 Future work Reformulate our model in a neural field formalism And using a multi-layer variational formalism Propose our form-motion interaction as a synchronisation mechanism

17. 17 Journal clubs Biology: Barthelemy et al. (2008) Models: Cesmely & Wang (2000) Technologies: Python, GPGPU