Searching across hundreds of databases
Size and location of activated cortical areas are often identified in relation to their surrounding macro-anatomical landmarks such as gyri and sulci. The sulcal pattern, however, is highly variable. In addition, many cortical areas are not linked to well defined landmarks, which in turn do not have a fixed relationship to functional and cytoarchitectonic boundaries. Therefore, it is difficult to unambiguously attribute localized neuronal activity to the corresponding cortical areas in the living human brain. Here we present new methods that are implemented in a toolbox for the objective anatomical identification of neuromagnetic activity with respect to cortical areas. The toolbox enables the platform independent integration of many types of source analysis obtained from magnetoencephalography (MEG) together with probabilistic cytoarchitectonic maps obtained in postmortem brains. The probability maps provide information about the relative frequency of a given cortical area being located at a given position in the brain. In the new software, the neuromagnetic data are analyzed with respect to cytoarchitectonic maps that have been transformed to the individual subject brain space. A number of measures define the degree of overlap between and distance from the activated areas and the corresponding cytoarchitectonic maps. The implemented algorithms enable the investigator to quantify how much of the reconstructed current density can be attributed to distinct cortical areas. Dynamic correspondence patterns between the millisecond-resolved MEG data and the static cytoarchitectonic maps are obtained. We show examples for auditory and visual activation patterns. However, size and location of the postmortem brain areas as well as the inverse method applied to the neuromagnetic data bias the anatomical classification. Therefore, the adaptation to the respective application and a combination of the objective quantities are discussed.
Pubmed ID: 17187996 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
View all literature mentionsCenter dedicated to understanding and treatment of neurological diseases by creating and using imaging methods to study human nervous system. Dedicated to research imaging of human brain. Brain structure is imaged using anatomical Magnetic Resonance Imaging (aMRI) while brain physiology is imaged using Positron Emission Tomography (PET), Magnetic Resonance Spectroscopy (MRS), functional MRI (fMRI) and magnetoencephalography (MEG). BIC maintains linkages with clinical, clinical research and basic research communities within Montreal Neurological Institute (MNI), McGill University and has collaborations across Quebec, Canada, USA and internationally.
View all literature mentionsA MATLAB toolbox which uses three dimensional probabilistic cytoarchitechtonic maps to correlate microscopic, anatomic and functional data of the cerebral cortex. Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
scicrunch.org
