MNI Space Research Articles

Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty

A widely used technique for coordinate-based meta-analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors present a revised ALE algorithm addressing drawbacks associated with former implementations. The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, the authors analyzed fMRI data of 21 subjects, each normalized into MNI space using nine different approaches. This analysis provided quantitative estimates of between-subject and between-template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above-chance clustering between foci, the revised algorithm assesses above-chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a null-distribution of random spatial association between experiments. Critically, this modification entails a change from fixed- to random-effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors showed that the revised ALE-algorithm overcomes conceptual problems of former meta-analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate-based meta-analyses on functional imaging data.

Neuroscientific literature search based on the location coordinates in brain - BredeQuery plugin for SPM environment

Event Abstract Back to Event Neuroscientific literature search based on the location coordinates in brain - BredeQuery plugin for SPM environment Bartlomiej Wilkowski1* 1 Technical University of Denmark, DTU Informatics, Denmark Current research in neuroscience, specifically neuroimaging, is based on the functional localization paradigm. New, state-of-the-art scanning techniques allow to detect haemodynamic response (dynamically regulated blood flow in brain) relating directly to neuronal activity in brain, hence to define functional localization of specific human behavior. There is a vast amount of new studies and publications about various human behaviours which are being mapped to specific brain regions where the significant change in activity occurs. The BredeQuery software [1] proposed herein, enables the user to search for related neuroscientific literature which reports various phenomena in similar brain regions. The search is done in a coordinate-based (not ordinary keyword-based) way and can be performed directly from the SPM (Statistical Parametric Mapping) - software platform run in Matlab and used inter alia in analysis of brain images.The BredeQuery plugin is written in Matlab and Java and it runs directly from SPM. The coordinate-based search for publications is offered in the plugin using the Brede Database [2] http://neuro.imm.dtu.dk/services/brededatabase/. The graphical user interface of the BredeQuery plugin can be seen in the Figure 1.The activation coordinates are grabbed from the SPM results window. Since the Brede Database is based on Talairach space coordinates, the BredeQuery plugin offers two MNI-to-Talairach (MTT) transformations. The grabbed coordinates can be then transformed from MNI space to Talairach using Mathew Brett's piece-wise affine transformation (brett) or Jack Lancaster et al.'s transformation (with three subtypes: SPM, FSL and pooled). The Lancaster's MTT-SPM transformation is set as default in the BredeQuery plugin.The grabbed and optionally transformed coordinates can then be used for querying the Brede Database. The query results (related publications) can be shown in the internal Matlab web browser or can be automatically exported to one of the following bibliographic formats: BibTeX, Reference Manager, RefWorks, EndNote. It should be mentioned that the user is also able to perform the Brede Database query manually, without using the grabbed coordinates. The plugin was released on March 12, 2009. It can be found on the SPM community list of toolboxes: http://www.fil.ion.ucl.ac.uk/spm/ext/#BredeQuery/ or can be directly downloaded from: http://neuroinf.imm.dtu.dk/BredeQuery/. Since the Brede Database is a relatively small database, the future development of the plugin is directed towards automatic retrieval of the articles also from huge, updated databases like PubMed. Integration with SKEEPMED (Semantic KEyword Extraction Pipeline for MEdical Documents) [3] is planned. This pipeline can be used for extracting relevant keywords from abstracts, mapping to ontological terms and constructing logical queries to other databases.

P2-080: Mapping of amyloid deposition in early- and late-onset Alzheimer's disease

Previous PET studies have demonstrated that there are differences in cerebral metabolic impairment and acetylcholinesterase activity between early- (EOAD) and late-onset Alzheimer's disease (LOAD).1, 2 Sixteen healthy volunteers (HV: 8M and 8F, 65 ± 10 y.o.), 7 patients with EOAD (4M and 3F, 61 ± 5 y.o., Mini-mental state examination score 15 ± 5), and 10 patients with LOAD (2M and 8F, 75 ± 5 y.o., MMSE score 20 ± 3) took part in this study. [11C]PIB -PET acquisition was a dynamic sequence of 19 PET scans over a 90-minute period. Regions of interest (ROI) were placed in the frontal, temporal, parietal , and occipital cortices, posterior cingulate, striatum and cerebellar cortex. Logan graphical analysis was employed to yield estimates of distribution volume (DV) in each regions using the arterial input function, and DV ratios were calculated in each regions with the cerebellar cortex as a reference tissue. PET images were spatially normalized to the MNI space and voxel-by-voxel DVR in the whole brain was also calculated. Group comparisons of DVR in HVs and two patient groups were performed using ANOVA in SPM5 (uncorrected p<0.0001, cluster extent K50 voxels). DVRs were remarkably increased in the frontal (+49%), lat. temporal (+54%) and lateral parietal cortices (+55%), posterior cingulate (+43%), striatum (+40%) in the EOAD group compared with HVs (Fig. 1a). DVRs were also remakably increased in the frontal (+49%), lateral temporal (+48%), and lateral parietal cortices (+55%), posterior cingulate (+52%), striatum (+35%) in the LOAD group compared with HVs (Fig. 1b). There was no significant difference in DVR in the brain between EOAD and LOAD groups. The results suggest that the degrees and distributions of amyloid deposition in the brain are similar in EOAD and LOAD.

Differential activation of frontal and parietal regions during visual word recognition: An optical topography study

The present study examined cortical oxygenation changes during lexical decision on words and pseudowords using functional Near-Infrared Spectroscopy (fNIRS). Focal hyperoxygenation as an indicator of functional activation was compared over three target areas over the left hemisphere. A 52-channel Hitachi ETG-4000 was used covering the superior frontal gyrus (SFG), the left inferior parietal gyrus (IPG) and the left inferior frontal gyrus (IFG). To allow for anatomical inference a recently developed probabilistic mapping method was used to determine the most likely anatomic locations of the changes in cortical activation [Tsuzuki, D., Jurcak, V., Singh, A.K., Okamoto, M., Watanabe, E., Dan, I., 2007. Virtual spatial registration of stand-alone fNIRS data to MNI space. NeuroImage 43 (4), 1506–1518.Subjects made lexical decisions on 50 low and 50 high frequency words and 100 pseudowords. With respect to the lexicality effect, words elicited a larger focal hyperoxygenation in comparison to pseudowords in two regions identified as the SFG and left IPG. The SFG activation difference was interpreted to reflect decision-related mechanisms according to the Multiple Read-Out Model [Grainger, J., Jacobs, A.M., 1996. Orthographic processing in visual word recognition: A multiple read-out model. Psychological Review 103, 518–565]. The greater oxygenation response to words in the left IPG suggests that this region connects orthographic, phonological and semantic representations. A decrease of deoxygenated hemoglobin was observed to low frequency in comparison to high frequency words in a region identified as IFG. This region’s sensitivity to word frequency suggests its involvement in grapheme–phoneme conversion, or its role during the selection of pre-activated semantic candidates.

3D Probabilistic map of cytoarchitectonically defined human thalamic nuclei in standard MRI

Event Abstract Back to Event 3D Probabilistic map of cytoarchitectonically defined human thalamic nuclei in standard MRI Harry B. Uylings1*, Katrin Amunts2, H. Mohlberg3, C. W. Pool1, K. Zilles3 and W. J. Smeets4 1 VU Univ. Med. Ctr./ Univ.Maastricht, Netherlands 2 Research Ctr Juelich, RWTH Aachen Univ, Netherlands 3 Research Ctr Juelich, GERMANY, Germany 4 Netherlands Institute for Brain Research, Netherlands Introduction: The parcellation of the human thalamus has been the subject of several studies (Morel et al., 1997; Jones, 2006). Apart from geometric variability of macroscopic anatomical features, there is a very large variability in microscopically defined brain areas even after the application of the full non-linear deformation method (Amunts et al., 1999; Uylings et al, 2005). For the interpretation of functional imaging data it is essential to know the extent of interindividual variability of the different thalamic nuclei. Some indications for variability in thalamic nuclei are reported by Niemann et al., 2000, and Johansen-Berg et al, 2005. Data on the variability in cytoarchitectonically defined thalamic nuclei displayed in the stereotactic format of the MNI brain are here provided for the first time. Methods: The thalamus of ten control human brains (5 males) has been studied. Postmortem MRIs , scanned in a 1.5 T Siemens Magnetom, were taken before the brains were embedded, cut in the frontal plane and stained for cell bodies. Cytoarchitectonic criteria as cell density, cell size and shape, and arrangement of cells were used to delineate about 30 thalamic nuclei in these sections taken at an interval of about 1 mm. The cytoarchitectonic delineations were 3D-reconstructed and then transformed to the reference MNI brain by elastic deformation. 3D probabilistic maps were calculated which describe, for each voxel of the reference space, the relative frequency with which a nucleus was present at this particular position. Results and Conclusion: The thalamic nuclei show a smaller inter-individual variability after transformation into MNI space than the cortical areas studied. Still the inter-individual variability in cytoarchitectonically defined thalamic nuclei is considerable. Intersubject variability differs between nuclei within the thalamus. The mediodorsal nucleus (MD), e.g., Fig.1, has a low variability, whereas the variability of ventral posterior lateral nucleus (VPL), Fig2, and medial geniculate nucleus (MGN), Fig3, is higher. These maps will open new perspective for the interpretation of functional imaging data for thalamic structural-functional analyses in the human brain, where many techniques are not available.

A novel group analysis for functional MRI of the human brain based on a two-threshold correlation (TTC) method

This work presents a new group analysis for functional MRI of human brain activation. The two-threshold correlation (TTC) method determines two statistical thresholds by estimating the noise distribution underlying the summed histogram of correlation coefficients (CC) from all sections and subjects. The probabilistic CC thresholds ( p < 0.0001 for the identification of highly significant activation centers and p < 0.05 for limiting the iterative addition of directly neighboring voxels to these centers) are applied to the group CC maps for each section. These maps may be reconstructed by taking the maximum (MAX) or mean (MEAN) CC value of all subjects for a particular voxel. Experimental analyses involved functional echo-planar imaging of sequential finger-to-thumb opposition and silent word generation at 3 T (eight subjects). Preprocessing included motion correction, spatial filtering, and normalization to MNI space. While the results for the TTC MAX approach were very similar to those obtained for a standard SPM analysis, the TTC MEAN approach turned out to be more conservative emphasizing voxels that are activated in most rather than in only a few subjects. The new method is simple, fast, and robust by linking two thresholds in a physiologically meaningful manner.

A spatially unbiased atlas template of the human cerebellum

This article presents a new high-resolution atlas template of the human, cerebellum and brainstem, based on the anatomy of 20 young healthy individuals. The atlas is spatially unbiased, i.e., the location of each structure is equal to the expected location of that structure across individuals in MNI space, a result that is cross-validated with an independent sample of 16 individuals. At the same time, the new template preserves the anatomical detail of cerebellar structures through a nonlinear atlas generation algorithm. In comparison to current whole-brain templates, it allows for an improved voxel-by-voxel normalization for functional MRI and lesion analysis. Alignment to the template requires that the cerebellum and brainstem are isolated from the surrounding tissue, a process for which an automated algorithm has been developed. Compared to normalization to the MNI whole-brain template, the new method strongly improves the alignment of individual fissures, reducing their spatial spread by 60%, and improves the overlap of the deep cerebellar nuclei. Applied to functional MRI data, the new normalization technique leads to a 5–15% increase in peak t values and in the activated volume in the cerebellar cortex for movement vs. rest contrasts. This indicates that the new template significantly improves the overlap of functionally equivalent cerebellar regions across individuals. The template and software are freely available as an SPM-toolbox, which also allows users to relate the new template to the annotated volumetric (Schmahmann, J.D., Doyon, J., Toga, A., Petrides, M., Evans, A. (2000). MRI atlas of the human cerebellum. San Diego: Academic Press) and surface-based (Van Essen, D.C. (2002a) Surface-based atlases of cerebellar cortex in the human, macaque, and mouse. Ann. N. Y. Acad. Sci. 978:468–479.) atlas of one individual, the “colin27”-brain.

Modeling the current distribution during transcranial direct current stimulation

ObjectiveTo investigate the spatial distribution of the magnitude and direction of the current density in the human head during transcranial direct current stimulation (tDCS). MethodsThe current density distribution was calculated using a numerical method to implement a standard spherical head model into which current was injected by means of large electrodes. The model was positioned in ‘MNI space’ to facilitate the interpretation of spatial coordinates. ResultsThe magnitude and direction of the current density vector are illustrated in selected brain slices for four different electrode montages. Approximately half of the current injected during tDCS is shunted through the scalp, depending on electrode dimension and position. Using stimulating currents of 2.0mA, the magnitude of the current density in relevant regions of the brain is of the order of 0.1A/m2, corresponding to an electric field of 0.22V/m. ConclusionsCalculations based on a spherical model of the head can provide useful information about the magnitude and direction of the current density vector in the brain during tDCS, taking into account the geometry and position of the electrodes. Despite the inherent limitations of the spherical head model, the calculated values are comparable to those used in the most recent in vitro studies on modulation of neuronal activity. SignificanceThe methodology presented in this paper may be used to assess the current distribution during tDCS using new electrode montages, to help optimize montages that target a specific region of the brain or to preliminarily investigate compliance with safety guidelines.

An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets

Analysis and interpretation of functional MRI (fMRI) data have traditionally been based on identifying areas of significance on a thresholded statistical map of the entire imaged brain volume. This form of analysis can be likened to a “fishing expedition.” As we become more knowledgeable about the structure–function relationships of different brain regions, tools for a priori hypothesis testing are needed. These tools must be able to generate region of interest masks for a priori hypothesis testing consistently and with minimal effort. Current tools that generate region of interest masks required for a priori hypothesis testing can be time-consuming and are often laboratory specific. In this paper we demonstrate a method of hypothesis-driven data analysis using an automated atlas-based masking technique. We provide a powerful method of probing fMRI data using automatically generated masks based on lobar anatomy, cortical and subcortical anatomy, and Brodmann areas. Hemisphere, lobar, anatomic label, tissue type, and Brodmann area atlases were generated in MNI space based on the Talairach Daemon. Additionally, we interfaced these multivolume atlases to a widely used fMRI software package, SPM99, and demonstrate the use of the atlas tool with representative fMRI data. This tool represents a necessary evolution in fMRI data analysis for testing of more spatially complex hypotheses.