MINI is intended to cover a wide range of electrophysiological protocols, but appears best suited for reporting on single-cell recordings, fty720 PP2a as opposed to far-field recordings, such as EEG Inhibitors,Modulators,Libraries and ERPs. In human neuroscience, Poldrack and associates have proposed a set of standards for reporting of fMRI data, called MIfMRI (see MIBBI portal and Appendix A in Ref [6].). MIfMRI specifies Inhibitors,Modulators,Libraries minimal information about human subjects, a useful complement to MINI, and categories such as Task and Behavioral performance, which are available in MINI and can be readily extended to other types of human neuroscience protocols (e.g., Inhibitors,Modulators,Libraries ERP experiments). Other categories, such as experimental design, appear more narrowly suited for description for fMRI experiments.

There are several publications on ERP research design, implementation, and reporting of results [7-9], but no minimal information checklists or similar resources for the ERP domain. In 2000, Picton and associates provided a detailed and highly influential set of guidelines [9]. In developing Inhibitors,Modulators,Libraries MINEMO, we have taken these guidelines under consideration. At the same time, we have tried to create a usable (i.e., relatively short) checklist, Inhibitors,Modulators,Libraries comprising no more than ~60 fields�� and no more than ~20 that must be completed before data are uploaded to the NEMO database. In this respect, we follow BrainMap and MIBBI researchers, who have discussed lessons learned in developing metadata tools and resources and then working to secure buy-in from users [4,10]. However good the resource, it is unlikely to find widespread use if it is clunky or time-consuming to use.

Controlled Vocabularies For the Dacomitinib NEMO project, we need consistent annotation of ERPdata, since we are aiming to conduct cross-lab meta-analysis. MI checklists can promote the use of consistent guidelines for reporting of studydata. However, there is no guarantee that different researchers will use the same terms for data mark-up. For this reason, researchers in several domains have created controlled vocabularies, or lexicons, for data annotation [11]1. In human neuroscience, the BrainMap lexicon has enjoyed widespread use, particularly in connection with their database [10,12]. The BrainMap database is an immense repository, resulting from more than 10 years of work curating results from thousands of functional brain imaging studies. Making such a collection reliably searchable requires consistent and precise naming of study information. To this end, the BrainMap team has created a portal called ��Sleuth�� that supports controlled entry of metadata. The BrainMap lexicon (aka the ��Meta-Data Coding Scheme��) covers a range of metadata, including stimuli, tasks (instructions), and protocols for measurement of behavioral and brain responses.