Use of Remote Surface Based Tools for Visualizing Integrated Brain Imaging Data

We describe a surface-based approach to 3D visualization of integrated neuroimaging data. Our web-enabled software allows researchers to use these visualization tools over the Internet. We present examples of brain imaging studies where such remote surface-based visualization techniques have proven to be quite effective

Brain Visualization in Java3D

BrainJ3D is a cross-platform Java/Java3D software toolkit for processing and visualizing brain imaging data, which 1) contains general purpose tools for reconstructing, mapping and visualizing integrated structural and functional images and 2) leverages Java's Remote Method Invocation to provide both a standalone and a client/server mode

Unobtrusive Integration of Data Management with fMRI Analysis

We describe a plugin for SPM, a popular fMRI statistical processing package, which interfaces to the Dartmouth Experiment lab book, an ontologybased tool to help researchers manage metadata and maintain it in a uniform format. The SPM plugin permits the creation of batch processing scripts that automatically populate the lab book, thereby hiding the details of data management while permitting researchers to continue using an analysis tool with which they are familiar

Anatomical Parcellation of Cortical Language Sites

Anatomical labeling of cerebral cortical stimulation (CSM) sites is necessary for intelligent computer querying of a rich and unique experimental database examining neural substrates underlying human language production. To this end, we have developed a parcellation scheme for the lateral surface of the human cerebral cortex. We then compared results generated utilizing this approach to those generated using an alternative method implemented in the Talairach Daemon

Dissociation of Action and Object Naming: Evidence From Cortical Stimulation Mapping

This cortical stimulation mapping study investigates the neural representation of action and object naming. Data from 13 neurosurgical subjects undergoing awake cortical mapping is presented. Our findings indicate clear evidence of differential disruption of noun and verb naming in the context of this naming task. At the individual level, evidence was found for punctuate regions of perisylvian cortex subserving noun and verb function. Across subjects, however, the location of these sites varied. This finding may help explain discrepancies between lesion and functional imaging studies of noun and verb naming. In addition, an alternative coding of these data served to highlight the grammatical class vulnerability of the target response. The use of this coding scheme implicates a role for the supramarginal gyrus in verb-naming behavior. These data are discussed with respect to a functional-anatomical pathway underlying verb naming

Intrinsic Variability of GM Density Maps and its Implications to VBM Studies

Voxel Based Morphometry (VBM) has been gaining popularity as an unbiased objective neuroimaging technique for identifying structural changes in the brain. VBM involves a voxel-wise comparison of the local concentration of gray matter (GM) in whole brain MRI scans. Although it was originally devised to examine structural abnormalities in patients, the technique has also been used successfully with healthy subjects. Recent VBM studies have investigated the impact of learning and practice on brain structure. Unlike certain medical conditions that may cause dramatic structural changes, effects observed in healthy subjects are expected to be small, therefore imposing stringent requirements on the sensitivity of the technique. The success of such studies depends on high quality imaging and subsequent accurate segmentation of GM. Segmentation results are inevitably affected by the presence of other tissues with similar intensity (dura matter, large blood vessels etc.), imaging artifacts (blood flow and eye movement, susceptibility artifacts etc.). Since these factors are non-homogeneous throughout the brain, segmentation is highly reproducible in some areas of cortex while it is less reliable in other areas. This non-homogeneity makes VBM sensitivity selective to areas where segmentation happens to be more robust. We studied the intrinsic variability of GM density maps derived from scans obtained under identical conditions, i.e. the same subject, scanner and protocol. The data was acquired on GE Signa 1.5, (SPGR) and Philips Achieva 3T (MPRAGE) scanners. A distinction should be made between variability observed among scans acquired within the same session and that observed for different sessions, since the latter will also be affected by such factors as different head positioning and the somewhat altered state of both the subject and the scanner. The figure summarizes within-session variability of GM density maps observed using the GE Signa. Six SPGR scans were obtained in each of four subjects in one session, and the scan sessions were repeated nine weeks later as a part of longitudinal VBM study. Variability for one subject/session was estimated by computing the standard deviation of six GM density maps obtained using SPM5 unified segmentation/normalization framework and VBM5 toolkit. These were normalized by applying a transformation estimated as follows: all six scans were coregistered and averaged to obtain a low noise structural image volume and a single normalization transformation was estimated from it. Eight variability maps in standard (MNI) space corresponding to session/subject pairs were averaged to produce a map shown in the Figure. The color coded variability map is superimposed onto the GM probability density map (only the right hemisphere is shown in the figure). We will present the findings of within and between session variability analyses derived from our data and from data obtained in other laboratories, and discuss implications and methodological considerations for planning and interpreting VBM studies of GM density. Preliminary results indicate that although different scanners and protocols produce varying patterns of GM variability maps, certain areas (e.g. tip of the temporal lobe) may consistently show increased variability

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data

Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine

Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators

Second-language learning and changes in the brain

International audiencePresumably, second-language (L2) learning is mediated by changes in the brain. Little is known about what changes in the brain, how the brain changes, or when these changes occur during learning. Here, we illustrate by way of example how modern brain-based methods can be used to discern some of the changes that occur during L2 learning. Preliminary results from three studies indicate that classroom based L2 instruction can result in changes in the brain's electrical activity, in the location of this activity within the brain, and in the structure of the learners' brains. These changes can occur during the earliest stages of L2 acquisition

Unobtrusive Integration of Data Management With fMRI Analysis

This note describes a software utility, called X-batch which addresses two pressing issues typically faced by functional magnetic resonance imaging (fMRI) neuroimaging laboratories (1) analysis automation and (2) data management. The first issue is addressed by providing a simple batch mode processing tool for the popular SPM software package (http://www.fil.ion. ucl.ac.uk/spm/; Welcome Department of Imaging Neuroscience, London, UK). The second is addressed by transparently recording metadata describing all aspects of the batch job e.g., subject demographics, analysis parameters, locations and names of created files, date and time of analysis, and so on). These metadata are recorded as instances of an extended version of the Protégé-based Experiment Lab Book ontology created by the Dartmouth fMRI Data Center. The resulting instantiated ontology provides a detailed record of all fMRI analyses performed, and as such can be part of larger systems for neuroimaging data management, sharing, and visualization. The X-batch system is in use in our own fMRI research, and is available for download at http://X-batch.sourceforge.net/