Karl Zilles

A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data.

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.

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. Hum Brain Mapp 2009.

Bias between MNI and talairach coordinates analyzed using the ICBM-152 brain template

MNI coordinates determined using SPM2 and FSL/FLIRT with the ICBM‐152 template were compared to Talairach coordinates determined using a landmark‐based Talairach registration method (TAL). Analysis revealed a clear‐cut bias in reference frames (origin, orientation) and scaling (brain size). Accordingly, ICBM‐152 fitted brains were consistently larger, oriented more nose down, and translated slightly down relative to TAL fitted brains. Whole brain analysis of MNI/Talairach coordinate disparity revealed an ellipsoidal pattern with disparity ranging from zero at a point deep within the left hemisphere to greater than 1‐cm for some anterior brain areas. MNI/Talairach coordinate disparity was generally less for brains fitted using FSL. The mni2tal transform generally reduced MNI/Talairach coordinate disparity for inferior brain areas but increased disparity for anterior, posterior, and superior areas. Coordinate disparity patterns differed for brain templates (MNI‐305, ICBM‐152) using the same fitting method (FSL/FLIRT) and for different fitting methods (SPM2, FSL/FLIRT) using the same template (ICBM‐152). An MNI‐to‐Talairach (MTT) transform to correct for bias between MNI and Talairach coordinates was formulated using a best‐fit analysis in one hundred high‐resolution 3‐D MR brain images. MTT transforms optimized for SPM2 and FSL were shown to reduced group mean MNI/Talairach coordinate disparity from a 5‐13 mm to 1‐2 mm for both deep and superficial brain sites. MTT transforms provide a validated means to convert MNI coordinates to Talairach compatible coordinates for studies using either SPM2 or FSL/FLIRT with the ICBM‐152 template. Hum Brain Mapp 2007.

Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps.

The statistical inference on functional imaging data is severely complicated by the embedded multiple testing problem. Defining a region of interest (ROI) where the activation is hypothesized a priori helps to circumvent this problem, since in this case the inference is restricted to fewer simultaneous tests, rendering it more sensitive. Cytoarchitectonic maps obtained from postmortem brains provide objective, a priori ROIs that can be used to test anatomically specified hypotheses about the localization of functional activations. We here analyzed three methods for the definition of ROIs based on probabilistic cytoarchitectonic maps. (1) ROIs defined by the volume assigned to a cytoarchitectonic area in the summary map of all areas (maximum probability map, MPM), (2) ROIs based on thresholding the individual probabilistic maps and (3) spherical ROIs build around the cytoarchitectonic center of gravity. The quality with which the thus defined ROIs represented the respective cytoarchitectonic areas as well as their sensitivity for detecting functional activations was subsequently statistically evaluated. Our data showed that the MPM method yields ROIs, which reflect most adequately the underlying anatomical hypotheses. These maps also show a high degree of sensitivity in the statistical analysis. We thus propose the use of MPMs for the definition of ROIs. In combination with thresholding based on the Gaussian random field theory, these ROIs can then be applied to test anatomically specified hypotheses in functional neuroimaging studies.

Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45

We investigated neural activations underlying a verbal fluency task and cytoarchitectonic probabilistic maps of Brocas speech region (Brodmanns areas 44 and 45). To do so, we reanalyzed data from a previous functional magnetic resonance imaging (fMRI) [Brain 125 (2002) 1024] and from a cytoarchitectonic study [J. Comp. Neurol. 412 (1999) 319] and developed a method to combine both data sets. In the fMRI experiment, verbal fluency was investigated in 11 healthy volunteers, who covertly produced words from predefined categories. A factorial design was used with factors verbal class (semantic vs. overlearned fluency) and switching between categories (no vs. yes). fMRI data analysis employed SPM99 (Statistical Parametric Mapping). Cytoarchitectonic maps of areas 44 and 45 were derived from histologic sections of 10 postmortem brains. Both the in vivo fMRI and postmortem MR data were warped to a common reference brain using a new elastic warping tool. Cytoarchitectonic probability maps with stereotaxic information about intersubject variability were calculated for both areas and superimposed on the functional data, which showed the involvement of left hemisphere areas with verbal fluency relative to the baseline. Semantic relative to overlearned fluency showed greater involvement of left area 45 than of 44. Thus, although both areas participate in verbal fluency, they do so differentially. Left area 45 is more involved in semantic aspects of language processing, while area 44 is probably involved in high-level aspects of programming speech production per se. The combination of functional data analysis with a new elastic warping tool and cytoarchitectonic maps opens new perspectives for analyzing the cortical networks involved in language.

Prefrontal involvement in imitation learning of hand actions: Effects of practice and expertise

In this event-related fMRI study, we demonstrate the effects of a single session of practising configural hand actions (guitar chords) on cortical activations during observation, motor preparation and imitative execution. During the observation of non-practised actions, the mirror neuron system (MNS), consisting of inferior parietal and ventral premotor areas, was more strongly activated than for the practised actions. This finding indicates a strong role of the MNS in the early stages of imitation learning. In addition, the left dorsolateral prefrontal cortex (DLPFC) was selectively involved during observation and motor preparation of the non-practised chords. This finding confirms Buccino et al.s [Buccino, G., Vogt, S., Ritzl, A., Fink, G.R., Zilles, K., Freund, H.-J., Rizzolatti, G., 2004a. Neural circuits underlying imitation learning of hand actions: an event-related fMRI study. Neuron 42, 323-334] model of imitation learning: for actions that are not yet part of the observers motor repertoire, DLPFC engages in operations of selection and combination of existing, elementary representations in the MNS. The pattern of prefrontal activations further supports Shallices [Shallice, T., 2004. The fractionation of supervisory control. In: Gazzaniga, M.S. (Ed.), The Cognitive Neurosciences, Third edition. MIT Press, Cambridge, MA, pp. 943-956] proposal of a dominant role of the left DLPFC in modulating lower level systems and of a dominant role of the right DLPFC in monitoring operations.

Genetic contributions to human brain morphology and intelligence

Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images of 54 monozygotic and 58 dizygotic twin pairs and 34 of their siblings. For genetic analyses, we used structural equation modeling and voxel-based morphometry. To explore the common genetic origin of focal GM and WM areas with intelligence, we obtained cross-trait/cross-twin correlations in which the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0.55). Intelligence shared a common genetic origin with superior occipitofrontal, callosal, and left optical radiation WM and frontal, occipital, and parahippocampal GM (phenotypic correlations up to 0.35). These findings point to a neural network that shares a common genetic origin with human intelligence.

A Four-Dimensional Probabilistic Atlas of the Human Brain

The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype- phenotype-behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders.

Characterization of the temporo-parietal junction by combining data-driven parcellation, complementary connectivity analyses, and functional decoding

The right temporo-parietal junction (RTPJ) is consistently implicated in two cognitive domains, attention and social cognitions. We conducted multi-modal connectivity-based parcellation to investigate potentially separate functional modules within RTPJ implementing this cognitive dualism. Both task-constrained meta-analytic coactivation mapping and task-free resting-state connectivity analysis independently identified two distinct clusters within RTPJ, subsequently characterized by network mapping and functional forward/reverse inference. Coactivation mapping and resting-state correlations revealed that the anterior cluster increased neural activity concomitantly with a midcingulate-motor-insular network, functionally associated with attention, and decreased neural activity concomitantly with a parietal network, functionally associated with social cognition and memory retrieval. The posterior cluster showed the exact opposite association pattern. Our data thus suggest that RTPJ links two antagonistic brain networks processing external versus internal information.

Identifying Human Parieto-Insular Vestibular Cortex Using fMRI and Cytoarchitectonic Mapping

The parieto‐insular vestibular cortex (PIVC) plays a central role in the cortical vestibular network. Although this region was first defined and subsequently extensively studied in nonhuman primates, there is also ample evidence for a human analogue in the posterior parietal operculum. In this study, we functionally and anatomically characterize the putative human equivalent to macaque area PIVC by combining functional magnetic resonance imaging (fMRI) of the cortical response to galvanic vestibular stimulation (GVS) with probabilistic cytoarchitectonic maps of the human parietal operculum. Our fMRI data revealed a bilateral cortical response to GVS in posterior parieto‐insular cortex. Based on the topographic similarity of these activations to primate area PIVC, we suggest that they constitute the functionally defined human equivalent to macaque area PIVC. The locations of these activations were then compared to the probabilistic cytoarchitectonic maps of the parietal operculum (Eickhoff et al. [ 2005a ]: Cereb Cortex, in press; Eickhoff et al. [ 2005c ]: Cereb Cortex, in press), whereby the functionally defined PIVC matched most closely the cytoarchitectonically defined area OP 2. This activation of OP 2 by vestibular stimulation and its cytoarchitectonic features, which are similar to other primary sensory areas, suggest that area OP 2 constitutes the human equivalent of macaque area PIVC. Hum Brain Mapp, 2005.