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This wiki is the developer's wiki of Metaneva. If you are more of an end-user, check our main website of the project.
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What is Metaneva?
Metaneva is a neuroinformatics project, focusing on data management, retrieval and analysis of bulk neuroscience data sets. We focus on monkey and rat data, with a clear emphasis on single unit recordings and reaction times. In other words: we store experiments and try to analyze these in order to gain insights in 'how the brain works':
- Data management: designing a database allowing to store a wide variety of rat/monkey experiments. Various experimental paradigms are targeted, amongst which are visual recognition, memory, decision, reward... We are able to store various sensory modi (auditory, visual, tactile, motor...). This is complemented by the development of a neuroscience ontology, and various other ontologies allowing to create standardized reports.
- Retrieval: storing various detailed data sets allows to retrieve more precise and relevant sets. Retrieval is one of those core tasks.
- Analysis: with the growing number of experiments, we target to perform analysis across multiple data sets in order to define functional mechanisms in a very detailed manner.
We create a database able to store and retrieve behavioral experiments. Behavioral experiments are those experiments where one tests how the brain processes e.g. 'an emotional response' or 'should I eat an apple or an orange?'. Neuroscience tries to unravel such behavioral responses, both 'simple' and higher order processes, for further application in e.g. neurosurgery or therapy. In order to gain insight we must gather as much experiments as we can and conduct various meta-analysis. This requires the storage of experiments, which is done using relational databases.
However, many experiment use 'worldly' terminology e.g.: a ball, a chair, a room, a red light on a computer screen... and as we know there are quite a few synonyms for many of these worldly terms. This could cause our database to be very messy since everyone could use whatever synonym they prefer. To avoid such a messy database, we control our terminology by designing an ontology. Each exerpiment that is uploaded to the database is therefore described using a fixed/controlled vocabulary. Such a standardized terminology strongly improves the accessibility (data retrieval and analysis) of the tool.
Once uploaded to the database, these data sets will be used to perform detailed analysis of functional brain mechanisms. Our scope therefore is
- to provide a database design suitable for the storage of animal behavioral experiments
- using a controlled vocabulary/terminology/ontology to create standardized reports/annotation
- leading to the analysis of functional brain processes.
Data Structure and Annotation
We structure each experiment using our generic data structure, where each experiment has one or more conditions. Each of these conditions consists of 'set-ups', being are the combination of various stimuli, tasks and effect sizes. The subject is part of a condition and not of the entire experiment, to allow multi-species experiments being uploaded to the database. For a full description of the data structure and annotation process, check the data structure and annotation page.
Strategy
Strategy for first built (v1)
Metaneva has developed a test bench, which can be downloaded here. Do note that this built was an experimental built, to test the possibilities and to evaluate what is required for highly complex field of cognitive neuroscience. The difficulty of designing and implementing cognitive science concerns both the various ambiguous terms, the variety of paradigms deployed in the field as the lack of a standardized ontology. The results of this test case can be found in this section.
Strategy for second built (v2)
The successive built will be a far more flexible, powerful and scalable solution relying on the highly regarded CMS Drupal. The strategy of this successive built (v2) will be described in detail for its goals, technical details and results. One can follow the progress here.
Where do I start?
If you are new to this project, but would like to know more on why and how the project is being developed, you are recommended to check the Introduction for developers, check the various resources to get familiar with the project, check out our roadmap or learn about the overall aims of the project.
To see what we're actually building we recommend to check our documentation of the various modules.
For further information, check the overview of this wiki. If there are any further questions, you can always contact us.
What can you find on this wiki?
- Developers information: anything a developer should know or get familiar with when interested in the project
- An introduction: an introduction to the scope of the project, a short overview of 'databasing the brain' and everything else you need to know about neuroscience in order to get started
- Developers guidelines: information on how to use the mailinglists, SVN...
- Contact us: wel euhm....
- Project Management
- Project Objectives: Metaneva overall project objectives
- Requirements: Functional and Non Functional Requirements
- Roadmap: an overview of the roadmap, including links to the fully detailed roadmap
- Feature list: overview of the features of the workbench
- Documentation
- Documentation version 2 (v2)
- Documentation version 1
- Documentation guide: an overview on what kind of documents we produced so far and more specific the docs for the various modules of the tool
- Data Management v1: documentation with regards to the Data Management Module v1
- Data Management v1: documentation with regards to the Visualization Module v1
- Data Management v1: documentation with regards to the Search Module v1
- Further Information
- We have some video tutorials, mainly targeted at developers with no or limited background on neuroscience and/or ontology design
