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Master MSR (2017-2018)

Archives

The organization of movement (E. Guigon)   (6.1Mo)
Computational motor control (E. Guigon)   (8.1Mo)
Biological motor control (E. Guigon)   (6.7Mo)
Models and theories (E. Guigon)   (11.6Mo)
Bibliography (E. Guigon)   (4.5Mo)
Functional motor anatomy (E. Guigon)   (7.3Mo)
Methods & advanced data processing (E. Guigon)   (14.5Mo)
Stroke and rehabilitation (E. Guigon)   (8.1Mo)
Movement disorders and nervous disease (E. Guigon)   (2.7Mo)
Bibliography (E. Guigon)   (0.1Mo)


Courses 5AH13 Part 2

1. Functional motor anatomy (E. Guigon)   (7.3Mo)
2. Methods & advanced data processing (E. Guigon)   (14.5Mo)
3. Stroke and rehabilitation (E. Guigon)   (8.1Mo)
4. Movement disorders and nervous disease (E. Guigon)   (2.7Mo)
5. Bibliography (E. Guigon)   (0.1Mo)

Assignments

Date: Tuesday 5 November 2017 | 8h30-12h45
Please choose one of the following articles (3 students/article) and indicate your choice by email to emmanuel.guigon at upmc.fr. If the article is still available, you will receive an acknowledgement of your choice.
Prepare a 10-min presentation (in english) to describe the work reported in the article. Please use some slides as a support to present the article (with a maximum of 6-7 slides). Use the following plan:
- Introduction (involving the research question and its relevance for the field)
- Procedure
- Main results (you can do several times procedure and results if there are several studies)
- Discussion (involving explaining what did the results specifically showed).
The presentation will be followed by questions (10-min). An evaluation mark will be given based on the clarity of the presentation and the depth of understanding. The intrinsic difficulty of each article will be taken into account. Please respect the timing.
The presentations (ppt or pdf) can be sent in advance to emmanuel.guigon at upmc.fr (preferred), brought on a USB key (good), or on your own computer (less preferred).

FREE ALREADY CHOSEN

1. Maravita A, Spence C, Kennett S, Driver J (2002) Tool-use changes multimodal spatial interactions between vision and touch in normal humans. Cognition 83(2):B25-B34.
2. Palmeri TJ, Blake R, Marois R, Flanery MA, Whetsell W (2002) The perceptual reality of synesthetic colors. Proc Natl Acad Sci USA 99(6):4127-4131.
3. Longo MR, Lourenco SF (2006) On the nature of near space: effects of tool use and the transition to far space. Neuropsychologia 44(6):977-981.
4. Lenggenhager B, Tadi T, Metzinger T, Blanke O (2007) Video ergo sum: manipulating bodily self-consciousness. Science 317(5841):1096-1099.
5. Held R, Ostrovsky Y, de Gelder B, Gandhi T, Ganesh S, Mathur U, Sinha P (2011) The newly sighted fail to match seen with felt. Nat Neurosci 14(5):551-553.
6. Levy-Tzedek S, Novick I, Arbel R, Abboud S, Maidenbaum S, Vaadia E, Amedi A (2012) Cross-sensory transfer of sensory-motor information: visuomotor learning affects performance on an audiomotor task, using sensory-substitution. Sci Rep 2:949.
7. Striem-Amit E, Guendelman M, Amedi A (2012) 'Visual' acuity of the congenitally blind using visual-to-auditory sensory substitution. PLoS One 7(3):e33136.
8. Bremner AJ, Caparos S, Davidoff J, de Fockert J, Linnell KJ, Spence C (2013) "Bouba" and "Kiki" in Namibia? A remote culture make similar shape-sound matches, but different shape-taste matches to Westerners. Cognition 126(2):165-172.
9. Hartcher-O'Brien J, Auvray M, Hayward V (2015) Perception of distance-to-obstacle through time-delayed tactile feedback. In: Proc IEEE World Haptics Conference, pp 7-12.



Courses 5AH13 Part 1

1. Reinforcement learning: From the basics to Deep RL (O. Sigaud)   (8.4Mo)
2. Bio-inspired / bio-mimetic action selection & reinforcement learning (M. Khamassi)   (13.9Mo)
3. The organization of movement (E. Guigon)   (6.1Mo)
4. Computational motor control (E. Guigon)   (8.1Mo)
5. Regression (O. Sigaud)   (8.6Mo)
6. Architecture and models of the brain eye saccadic movement circuitry (B. Girard)   (6.8Mo)
7. Biological motor control (E. Guigon)   (6.7Mo)
8. Models and theories (E. Guigon)   (11.6Mo)
4. Bibliography (E. Guigon)   (4.5Mo)

Assignments

Date: Tuesday 10 October 2017 | 13h45-18h00
Please choose one of the following articles (3 students/article) and indicate your choice by email to emmanuel.guigon at upmc.fr. If the article is still available, you will receive an acknowledgement of your choice.
Prepare a 10-min presentation (in english) to describe the work reported in the article, as if you were the authors (introduction&question, methods, results, discussion, general implications in relation to the course). The presentation will be followed by questions (10-min). An evaluation mark will be given based on the clarity of the presentation and the depth of understanding. The intrinsic difficulty of each article will be taken into account. Please respect the timing.
The presentations (ppt or pdf) can be sent in advance to emmanuel.guigon at upmc.fr (preferred), brought on a USB key (good), or on your own computer (less preferred).

FREE ALREADY CHOSEN

1. Sing GC, Joiner WM, Nanayakkara T, Brayanov JB, Smith MA (2009) Primitives for motor adaptation reflect correlated neural tuning to position and velocity. Neuron 64(4):575-589. Supplementary
2. Izawa J, Shadmehr R (2011) Learning from sensory and reward prediction errors during motor adaptation. PLoS Comput Biol 7(3):e1002012.
3. Geijtenbeek T, van de Panne M, van der Stappen AF (2013) Flexible muscle-based locomotion for bipedal creatures. ACM Trans Graph 32(6):206.
4. Saeb S, Weber C, Triesch J (2011) Learning the optimal control of coordinated eye and head movements. PLoS Comput Biol 7(11):e1002253.
5. Verstynen T, Sabes PN (2011) How each movement changes the next: An experimental and theoretical study of fast adaptive priors in reaching. J Neurosci 31(27):10050-10059.
6. Nagengast AJ, Braun DA, Wolpert DM (2010) Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty. PLoS Comput Biol 6(7):e1000857.
7. Braun DA, Aertsen A, Wolpert DM, Mehring C (2009) Learning optimal adaptation strategies in unpredictable motor tasks. J Neurosci 29(20):6472-6478.
8. Nagengast AJ, Braun DA, Wolpert DM (2009) Optimal control predicts human performance on objects with internal degrees of freedom. PLoS Comput Biol 5(6):e1000419.
9. Flanagan JR, Vetter P, Johansson RS, Wolpert DM (2003) Prediction precedes control in motor learning. Curr Biol 13(2):146-150.
10. Smith MA, Ghazizadeh A, Shadmehr R (2006) Interacting adaptive processes with different timescales underlie short-term motor learning. PLoS Biol 4(6):e179.
11. Hwang EJ, Donchin O, Smith MA, Shadmehr R (2003) A gain-field encoding of limb position and velocity in the internal model of arm dynamics. PLoS Biol 1(2):209-220.
12. Selen LP, Franklin DW, Wolpert DM (2009) Impedance control reduces instability that arises from motor noise. J Neurosci 29(40):12606-12616.
13. Tamosiunaite M, Asfour T, Worgotter F (2009) Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions. Biol Cybern 100(3):249-260.
14. Groh JM (2001) Converting neural signals from place codes to rate codes. Biol Cybern 85(3):159-165.
15. Shadmehr R, Orban de Xivry JJ, Xu-Wilson M, Shih TY (2010) Temporal discounting of reward and the cost of time in motor control. J Neurosci 30(31):10507-10516.
16. Charlesworth JD, Warren TL, Brainard MS (2012) Covert skill learning in a cortical-basal ganglia circuit. Nature 486(7402):251-255. Supplementary
17. Pekny SE, Izawa J, Shadmehr R (2015) Reward-dependent modulation of movement variability. J Neurosci 35(9):4015-4024.
18. Berniker M, Körding KP (2015) Deep networks for motor control functions. Front Comput Neurosci 9:32.
19. Cashaback JG, McGregor HR, Gribble PL (2015) The human motor system alters its reaching movement plan for task-irrelevant, positional forces. J Neurophysiol 113(7):2137-2149.
20. Galea JM, Mallia E, Rothwell J, Diedrichsen J (2015) The dissociable effects of punishment and reward on motor learning. Nat Neurosci 18(4):597-602.