MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone

The past, present, and future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS

Dissociating Morpheme Form and Meaning: Evidence for Morphological Decomposition of Compound Words during Reading

Compound words have two free morphemes whose individual meanings can have a transparent (e.g., roadside) or opaque (e.g., butterfly) relationship to the overall meaning. It is unclear when meaning is accessed during lexical processing of compounds (and other morphologically complex words), with conflicting results from priming in lexical-decision studies and from reading-time studies that examine how the characteristics of a compound affect its processing. The present studies examined eye-movement measures on target words in a sentence as a function of their relation in form and meaning to a prime word that occurred earlier in the sentence. In Experiment 1 the primes were transparent or opaque compounds and the targets were the first constituent of the compound (e.g., doll preceded by dollhouse vs. container; and brief preceded by briefcase vs. portfolio). First-pass measures showed that target-word recognition was facilitated by prior processing of the compound but that the amount of facilitation was not affected by semantic transparency, a pattern that suggests that there is a stage of processing where compounds are decomposed into their constituent morphemes regardless of their composite meaning. Experiment 2 used first constituents as primes and compounds as targets. First-pass measures showed priming on recognition of both transparent and opaque compounds. Priming facilitation persisted on later measures of lexical processing for transparent compounds but became inhibitory for opaque compounds. These results show that compounds are initially decomposed into their constituent words independently of meaning, but that later in processing activation of the meaning of a constituent word facilitates comprehension of semantically consistent compounds but competes with comprehension of semantically inconsistent compounds

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEGBIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several dataanalytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone

MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis

Peer reviewe

Brain Imaging Data Structure Presentations

Collection of BIDS presentations given by researchers involved in BID

mne-tools/mne-python: v0.15

MNE : Magnetoencephalography (MEG) and Electroencephalography (EEG) in Pytho

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS