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dandiset.yaml 3.6 KB

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  1. '@context': https://raw.githubusercontent.com/dandi/schema/master/releases/0.6.4/context.json
  2. about: []
  3. access:
  4. - schemaKey: AccessRequirements
  5. status: dandi:EmbargoedAccess
  6. assetsSummary:
  7. numberOfBytes: 0
  8. numberOfFiles: 0
  9. schemaKey: AssetsSummary
  10. citation: Dias-Ferreira, Eduardo; Maimon, Gaby (2023) Identifying neurons required
  11. for visually-driven reward predictions in Drosophila (Version draft) [Data set].
  12. DANDI archive. https://dandiarchive.org/dandiset/000471/draft
  13. contributor:
  14. - contactPoint: []
  15. identifier: https://ror.org/0420db125
  16. includeInCitation: false
  17. name: The Rockefeller University
  18. roleName:
  19. - dcite:Affiliation
  20. schemaKey: Organization
  21. - affiliation:
  22. - identifier: https://ror.org/0420db125
  23. name: The Rockefeller University
  24. schemaKey: Affiliation
  25. - identifier: https://ror.org/006w34k90
  26. name: Howard Hughes Medical Institute
  27. schemaKey: Affiliation
  28. awardNumber: EMBO Long-Term Fellowship (ALTF 160-2014), Marie Curie Actions, European
  29. Comission. Mohapatra Fellowship in Vision Research at The Rockefeller University.
  30. email: eferreira@rockefeller.edu
  31. identifier: 0009-0008-3787-5456
  32. includeInCitation: true
  33. name: Dias-Ferreira, Eduardo
  34. roleName:
  35. - dcite:Author
  36. - dcite:Conceptualization
  37. - dcite:ContactPerson
  38. - dcite:DataCollector
  39. schemaKey: Person
  40. - affiliation:
  41. - identifier: https://ror.org/0420db125
  42. name: The Rockefeller University
  43. schemaKey: Affiliation
  44. - identifier: https://ror.org/006w34k90
  45. name: Howard Hughes Medical Institute
  46. schemaKey: Affiliation
  47. email: maimon@rockefeller.edu
  48. identifier: 0000-0003-1219-5856
  49. includeInCitation: true
  50. name: Maimon, Gaby
  51. roleName:
  52. - dcite:Author
  53. - dcite:Conceptualization
  54. - dcite:ContactPerson
  55. - dcite:Supervision
  56. schemaKey: Person
  57. url: https://maimonlab.rockefeller.edu/
  58. - contactPoint: []
  59. identifier: https://ror.org/006w34k90
  60. includeInCitation: false
  61. name: Howard Hughes Medical Institute
  62. roleName:
  63. - dcite:Affiliation
  64. - dcite:Funder
  65. schemaKey: Organization
  66. - awardNumber: 1 R01 NS 121904-01
  67. name: National Institutes of Health (NIH)
  68. roleName:
  69. - dcite:Funder
  70. schemaKey: Organization
  71. dateCreated: '2023-04-03T16:05:28.189225+00:00'
  72. description: This dataset presents the results of a hypothesis-driven screen to identify
  73. neurons in Drosophila that are necessary for visual learning in an appetitive conditioning
  74. paradigm. To achieve this, we silenced electrical activity in various subtypes of
  75. Kenyon cells using UAS-Kir(human) in a new, trial-based, visual learning paradigm
  76. in head-fixed Drosophila. During the experiment, small drops of sugar-water were
  77. delivered to the fly's proboscis in coordination with the presentation of a moving
  78. visual grating. We monitored the reflexive movements of the proboscis in anticipation
  79. of sugar-reward to follow the dynamics of conditioning for hundreds of trials. For
  80. more information about this dataset, including different download options and various
  81. raw/processed data formats, please contact Eduardo Dias-Ferreira and/or Gaby Maimon.
  82. ethicsApproval: []
  83. id: DANDI:000471/draft
  84. identifier: DANDI:000471
  85. keywords:
  86. - Drosophila
  87. - associative learning
  88. - visual
  89. - appetitive
  90. - reward prediction
  91. - mushroom body
  92. - Kenyon cells
  93. license:
  94. - spdx:CC-BY-4.0
  95. manifestLocation:
  96. - https://api.dandiarchive.org/api/dandisets/000471/versions/draft/assets/
  97. name: Identifying neurons required for visually-driven reward predictions in Drosophila.
  98. protocol: []
  99. relatedResource: []
  100. repository: https://dandiarchive.org
  101. schemaKey: Dandiset
  102. schemaVersion: 0.6.4
  103. studyTarget: []
  104. url: https://dandiarchive.org/dandiset/000471/draft
  105. version: draft
  106. wasGeneratedBy: []
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