EyeWire

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Cs Portal > List of citizen science projects > EyeWire - (2013/09/25)

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IDENTIFICATION

Participant's homepage
  • Infrastructure:
  • Developed with:
Start date : 2012/12/10
  • Beta start date : N/A
  • End date : Still open.
Subject

Description EyeWire is a game where volounteers map the 3D structure of neurons. By playing EyeWire, they help map the retinal connectome and contribute to the neuroscience research conducted by Sebastian Seung's Computational Neuroscience Lab at MIT. The connectome is a map of all the connections between cells in the brain. Rather than mapping an entire brain, we’re starting with a retina. Purpose Identify and Maps all the neurons in the retina. ? Research question

TEAM

MAIN TEAM LOCATION
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Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis

Project team page http://wiki.eyewire.org/en/Who we are and what we do. Leader: Sebastian Seung's Institution: Partner institutions: Contact: support@eyewire.org

USER TASKS

CONTRIBUTION TYPE: data analysis
PARTICIPATION TYPOLOGY: crowdsourcing


GAMING GENRE NONE
GAMING ELEMENTS: NONE

COMPUTING
THINKING
SENSING
GAMING

Tasks description The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task. Interaction with objects

Interface

  • Data type to manipulate: 3D manipulation
  • interface enjoyment: cool/attractive
  • Interface usability: somewhat difficult to use

GUIDANCE

GUIDANCE
  • Tutorial:
  • Peer to peer guidance:
  • Training sequence: Somewhat
FEEDBACK ON
  • Individual performance:
  • Collective performance: Somewhat
  • Research progress: Somewhat

Feedback and guidance description

COMMUNITY

COMMUNITY TOOLS
  • Communication: website, blog, forum, wiki
  • Social Network: Twitter, Facebook, Linkedin
  • Member profiles:: minimal
  • Member profile elements: badges, activity metrics
NEWS & EVENTS

Community description

  • Community size (volounteers based) 80 000
  • Role:
  • Interaction form:
  • Has official community manager(s): N/A
  • Has team work N/A
  • Other: Community can make suggestions in threads on the discussion forum which project staff look at and respond to accordingly.
  • Community led additions:


Other information

PROJECT

Url:http://eyewire.org/
Start date: 2012/12/10
End date: Still open


TEAM

Official team page:http://wiki.eyewire.org/en/Who_we_are_and_what_we_do.
Leader: Sebastian Seung's


Contact: support@eyewire.org
Main location: Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis

PROJECT DEFINITION


Subject

Natural sciences > Neurology (biology/medicine/neuroscience)

Description

EyeWire is a game where volounteers map the 3D structure of neurons. By playing EyeWire, they help map the retinal connectome and contribute to the neuroscience research conducted by Sebastian Seung's Computational Neuroscience Lab at MIT. The connectome is a map of all the connections between cells in the brain. Rather than mapping an entire brain, we’re starting with a retina.

Purpose.

Identify and Maps all the neurons in the retina.

.

ABOUT PARTICIPANT TASKS


Tasks description.

The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task.

.

Grey typology Participation typology Contribution type:
Computing: NO Thinking: YES
Sensing: NO Gaming: YES
Crowdsourcing Distributed intelligence
Participatory science Extreme citizen science
Science outreach
Data collection
Data analysis
Data interpretation --------
Gaming
Genre: other Gaming elements:
Interface
Data type to manipulate: 3D manipulation interface enjoyment: cool/attractive
Interface usability: somewhat difficult to use
Member profiles::minimal
Member profile elements: badges, activity metrics


ABOUT GUIDANCE AND FEEDBACK


Guidance Feedback on
Tutorial and documentation: YES
Training sequence: SOMEWHAT
Peer to peer guidance: YES
individual performance: YES
collective performance: Somewhat
research progress: YES

.

COMMUNITY


Tools News & Events

Communication: website, blog, forum, wiki
Social Network: Twitter, Facebook, Linkedin

Main news site: http://blog.eyewire.org/
Frequency of project news updates: less than weekly
Type of events: MeetUps, other
Frequency of events : 4

Community description

Community size (volounteers based): 80 000
Role: Interaction form:
Has official community manager(s): N/A
Has team work N/A

Other information about community: Community can make suggestions in threads on the discussion forum which project staff look at and respond to accordingly.
Community led additions:

OTHER PROJECT INFORMATION




Photo.jpg Yes [[has completion level::Medium]

http://wiki.eyewire.org/en/Who we are and what we do.

Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis support@eyewire.org

Yes Neurology Natural sciences biology/medicine/neuroscience Identify and Maps all the neurons in the retina.


EyeWire The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task. data analysis

crowdsourcing 3D manipulation, other: Thinking: yes Computing: no Sensing: no Gaming: yes

other

cool/attractive somewhat difficult to use yes yes strong yes somewhat yes

minimal badges, activity metrics N/A website, blog, forum, wiki Twitter, Facebook, Linkedin MeetUps, other 4 http://blog.eyewire.org/ 80 000 less than weekly Community can make suggestions in threads on the discussion forum which project staff look at and respond to accordingly.


N/A


Medium

Assessment:

Progression isn’t very clear, overall neurone you’ve mapped isn’t shown. Accuracy isn’t clear either as users don’t know if they’ve gotten it right. Volunteers don’t feel like part of the team but like unpaid interns.

Other Info:

Since President Obama announced the BRAIN initiative, the project have used this very well in their marketing to stress the importance of their aims. They use bold statements like “Obama wants to map the brain. You can help by playing EyeWire.”

Artificial Intelligence (AI) is used in the game to help volunteers complete it.


Bibliography

BIBLIOGRAPHY