Open science: redefining operant conditioning; PKC and motorneurons

462 views
381 views

Published on

Presentation introducing the need for a new definition of operant conditioning, and presenting data suggesting an action of PKC in motorneurons during self-learning in Drosophila. Finally, some slides about our attempt in working using open science as a default mode

Published in: Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
462
On SlideShare
0
From Embeds
0
Number of Embeds
19
Actions
Shares
0
Downloads
5
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Open science: redefining operant conditioning; PKC and motorneurons

  1. 1. OPEN NEUROSCIENCE VIA AUTOMATIC PUBLICATION OF DIGITAL DATA:
 FROM LOCOMOTION TO OPERANT "SELF-LEARNING" IN DROSOPHILA Julien Colomb Freie Universität Berlin
  2. 2. PLAN
  3. 3. PLAN • World- and self-learning: redefining operant learning
  4. 4. PLAN • World- and self-learning: redefining operant learning • PKC, motorneurons and self-learning
  5. 5. PLAN • World- and self-learning: redefining operant learning • PKC, motorneurons and self-learning • Open science: philosophy and practice
  6. 6. PLAN • World- and self-learning: redefining operant learning • PKC, motorneurons and self-learning • Open science: philosophy and practice Figshare and Rfigshare
  7. 7. PLAN • World- and self-learning: redefining operant learning • PKC, motorneurons and self-learning • Open science: philosophy and practice Figshare and Rfigshare Locomotion data and self-learning data
  8. 8. OPERANT CONDITIONING: DISSOCIABLE LEARNING TYPES “A process of behavior modification in which the likelihood of a specific behavior is increased or decreased through positive or negative reinforcement” ?
  9. 9. OPERANT CONDITIONING: DISSOCIABLE LEARNING TYPES “A process of behavior modification in which the likelihood of a specific behavior is increased or decreased through positive or negative reinforcement” ? Tolman, 1946
  10. 10. Response learning Place learning
  11. 11. METHOD Brembs and Plendel, 2008
  12. 12. PROTOCOL • 7 blocks of 2 minutes • PI = proportion of time spent performing the “safe” behavior • self-learning assessed during the last test period • statistics = for each group, nonparametric, higher than 0 ?
  13. 13. SELF-LEARNING ONLY Dissecting world- and self-learning Colomb and Brembs, 2010
  14. 14. DROSOPHILA FLIGHT SIMULATOR Dissecting world- and self-learning Colomb and Brembs, 2010
  15. 15. Mendoza et al., unpublished
  16. 16. THE WHAT AND WHERE OF 
 SELF-LEARNING • Which PKC is involved • In which neurons is PKC involved
  17. 17. GENETIC TOOLS
  18. 18. UAS-GAL4 SYSTEM: SPATIAL AND TEMPORAL CONTROL
  19. 19. UAS-GAL4 SYSTEM: SPATIAL AND TEMPORAL CONTROL
  20. 20. UAS-GAL4 SYSTEM: SPATIAL AND TEMPORAL CONTROL • PKCi
  21. 21. UAS-GAL4 SYSTEM: SPATIAL AND TEMPORAL CONTROL • PKCi • RNAi
  22. 22. RESULTS
  23. 23. WHICH PKC ? No conclusive results
  24. 24. LOCALISATION OF PKC ACTION PKC inhibition: only during test only in certain neurons
  25. 25. POSITIVE CONTROL heat shock protocol for the TARGET system using a pan-neuronal Gal4
  26. 26. FIRST SCREEN not in central brain, in glutamatergic neurons
  27. 27. MOTORNEURONS
  28. 28. ANATOMICAL CONFIRMATION: IN PROGRESS Gal4 lines crossed to a UAS-CD8GFP antibody staining: anti-GFP , anti-dvGlut
  29. 29. DISCUSSION
  30. 30. DISCUSSION • Motorneurons as probable site of plasticity for self-learning
  31. 31. DISCUSSION • Motorneurons as probable site of plasticity for self-learning • Interaction self-/world-learning: probably different neuronal site
  32. 32. DISCUSSION • Motorneurons as probable site of plasticity for self-learning • Interaction self-/world-learning: probably different neuronal site • Then why different molecular substrate? Different cellular correlates?
  33. 33. INVOLVES MOTORNEURON INTRINSIC PLASTICITY Aiko K. Thompson,, Xiang Yang Chen, and Jonathan R. Wolpaw, 2009
  34. 34. HAS THERAPEUTIC APPLICATION IN HUMAN Thompson AK, Pomerantz FR, Wolpaw JR., 2013
  35. 35. OPEN SCIENCE BY DEFAULT Making scientific research, data and dissemination accessible to all levels of an inquiring society, amateur or professional.
  36. 36. BURIDAN’S PARADIGM Assess locomotor behavior
  37. 37. 12 VARIABLES CALCULATED Median speed Speed of the animal while walking (median) Mean distance travelled Distance travelled during the experiment divided by the length of the experiment. Turning angle median of the angle difference between two movement Meander median of the turning angle divided by instantaneous speed thigmotaxis while moving proportion of time spent moving on the edge of the platform versus the center of the platform (equal surfaces) proportion of time spent not moving on the edge of the platform versus the center of the thigmotaxis while sitting platform (equal surfaces) Stripe deviation Median deviation angle between walking direction and direction toward the stripes Number of walks number of times a fly walk between the two stripes during the experiment number of pauses number of times a fly made a pause (longer than 1s) during the experiment activity bouts duration Median length of activity phases pause length Median length of pauses total time active sum of the length of activity phases during the experiment
  38. 38. DIFFERENT SUB-STRAINS OF CS 
 (WILD TYPE) FLIES.
  39. 39. DIFFERENT SUB-STRAINS OF CS 
 (WILD TYPE) FLIES.
  40. 40. DIFFERENT SUB-STRAINS OF CS 
 (WILD TYPE) FLIES.
  41. 41. CENTROID TRAJECTORY ANALYSIS
  42. 42. CENTROID TRAJECTORY ANALYSIS Automatic publication
  43. 43. API The figshare API allows you to push data to figshare, or pull data out. This first version is a basic implementation that allows you to manage your figshare account or build applications on top of the figshare platform and public research.
  44. 44. Rfigshare from Ropensci team http://ropensci.org/ : ! 2013 RopenSci challenge
  45. 45. DIFFICULTIES • Metadata format: include more types of trajectory data • Is Figshare the right platform for this, wouldn't be a git based solution better?
  46. 46. OPEN SCIENCE AND
 THE SELF-LEARNING SETUP
  47. 47. DATA PUBLICATION • Get all data on the same format • all results in one file • link metadata and raw torque data • Publish on Figshare http://dx.doi.org/10.6084/m9.figshare.830423
  48. 48. DATA PUBLICATION • Get all data on the same format • all results in one file • link metadata and raw torque data • Publish on Figshare http://dx.doi.org/10.6084/m9.figshare.830423
  49. 49. DATA PUBLICATION One metadata
 file • Get all data on the same format • all results in one file • link metadata and raw torque data • Publish on Figshare http://dx.doi.org/10.6084/m9.figshare.830423
  50. 50. DATA PUBLICATION One metadata
 file • Get all data on the same format • all results in one file • link metadata and raw torque data • Publish on Figshare http://dx.doi.org/10.6084/m9.figshare.830423
  51. 51. CONCLUSION: 
 R AND DATA ANALYSIS
  52. 52. CONCLUSION: 
 R AND DATA ANALYSIS 1. Graphical representation and statistics
  53. 53. CONCLUSION: 
 R AND DATA ANALYSIS 1. Graphical representation and statistics 2. Reproducible data analysis
  54. 54. CONCLUSION: 
 R AND DATA ANALYSIS 1. Graphical representation and statistics 2. Reproducible data analysis 3. Graphs & data publishable on Figshare
  55. 55. CONCLUSION: 
 R AND DATA ANALYSIS 1. Graphical representation and statistics 2. Reproducible data analysis 3. Graphs & data publishable on Figshare 4. Automatic publication/archivage of the data and results, during analysis
  56. 56. ACKNOWLEDGMENTS Direct collaborators: Bjoern Brembs Axel Gorostiza ! Reagents, machine, software and flies: M. Heisenberg, H. Aberle, C. Duch, T. Preat, H. Scholz, J. Wessnitzer, T. Colomb, S. Sigrist, B.v.Swinderen. FoxP project: H.J. Pflüger, C. Scharff, A. Mendoza, T. Zars

×