This file describes in short both the goals as the IT requirements. As such, it is a summary and is always in need for improvement.

If there is a question, do not hesitate to contact us.

This paper represents one of our prototypes of articles/papers/experiments we want to encode in the database. This paper describes a monkey performing a decision task.

This allow you to get an idea of what we are trying to encode and what type of data we are trying to analyze. 

Primary author: Jan Lauwereyns.

These files are the first two in a series of 12 reviews of reviews.

In this analysis we do NOT target individual reviewers, NOR the quality of the reviews. We strongly state that all the reviews used in this analysis are chosen on the basis of their recognized high quality. We only want to indicate a trend within the field which allows for similar data sets to be neglected on the basis of their semantic labels (e.g. functional attribution). It's this trend and this trend only which is the subject of this analysis.

More information and reporst will be available soon. These files are 2 pdf's and are zipped for your convenience.

Method: We queried the ISI Web of Knowledge and gathered 12 reviews using the query “TI=([term]) AND ts=(neuro* or (cognit* and scien*))” where “[term]” stands for the term used for the query (cf. decision, reward and attention) and the symbol ‘*’ stands for a wildcard in ISI representing zero to multiple characters and in this case used to auto complete our search terms.
All reviews date from 2004 or later (timespan=2004-2009), and selected 12 papers out of which 7 had “decision” in their title, 3 had “attention” and 2 had “reward”. With 7 reviews directly labeled as “decision”, the main focus lies on decision processing. We integrated the terms “attention” and “reward” since they are often a crucial aspect in the functional attribution as reported in the field. We used this distribution to gather semantically similar articles so the result should be a consistent data set.
We ‘annotated’ all primary resources and checked which species, stimulus, task, functional attribution, brain area, recording method and stimulus modus they used. We then checked the reviews on how they combine the wide variety of data and if they systematically connect highly similar data on the data level (cf. species, stimulus, task, brain area, recording method and stimulus modus) or used semantic attributions (e.g. functional attribution) to connect data sets. Current results are based on 2 reviews and total of +40 close readings of primary sources.

This document gives an overview for developers who would like to contribute and those who want to know how we upload/structure our data sets.

This document will soon be accompanied by a video tutorial further explaining the upload form.

 Update:

2008-12-18

- Introduction to the document updated

- Stimulus description