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Abstract: Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper presents a unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The weighted spherical harmonic representation is used to parameterize, smooth out, and normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using the SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects. [Copyright &y& Elsevier]

Abstract: Temporal lobe epilepsy (TLE) is considered primarily a limbic disorder. Our purpose was to map limbic network organization in TLE and to statistically relate it to neocortical atrophy. We performed MRI-based cortical thickness analysis in 110 TLE patients (including 68 patients with hippocampal atrophy and 42 patients with normal hippocampal volume) and 46 healthy controls. Limbic connectivity was statistically inferred by correlating mean thickness of the entorhinal cortex (EC) with thickness at each vertex across the entire neocortex. The EC was chosen as seed region since it is the link between the neocortex and the hippocampal formation. Patients showed cortical thinning mainly in temporal and fronto-central neocortices, with a prevalence of atrophy in up to 35%. In controls, EC networks corresponded closely to known anatomical connections. In TLE the pattern of correlations was similar to controls, suggesting that pathological processes in the EC affect the same networks that co-vary with the EC in the healthy brain. Nevertheless, we found decreases in correlations mainly in the temporal lobe and increases mainly in orbitofrontal cortices. Although our analysis indicated alterations in the temporo-limbic network in TLE, there was no association between mesiotemporal connectivity and atrophy across the entire cortical surface. This divergence underlines the complexity of the pathophysiological mechanisms leading to neocortical atrophy in TLE. [Copyright &y& Elsevier]

Abstract: We introduce MACACC-Mapping Anatomical Correlations Across Cerebral Cortex-to study correlated changes within and across different cortical networks. The principal topic of investigation is whether the thickness of one area of the cortex changes in a statistically correlated fashion with changes in thickness of other cortical regions. We further extend these methods by introducing techniques to test whether different population groupings exhibit significantly varying MACACC patterns. The methods are described in detail and applied to a normal childhood development population (n = 292), and show that association cortices have the highest correlation strengths. Taking Brodmann Area (BA) 44 as a seed region revealed MACACC patterns strikingly similar to tractography maps obtained from diffusion tensor imaging. Furthermore, the MACACC map of BA 44 changed with age, older subjects featuring tighter correlations with BA 44 in the anterior portions of the superior temporal gyri. Lastly, IQ-dependent MACACC differences were investigated, revealing steeper correlations between BA 44 and multiple frontal and parietal regions for the higher IQ group, most significantly (t = 4.0) in the anterior cingulate. [Copyright &y& Elsevier]

We present a unified statistical approach to deformation-based morphometry applied to the cortical surface. The cerebral cortex has the topology of a 2D highly convoluted sheet. As the brain develops over time, the cortical surface area, thickness, curvature, and total gray matter volume change. It is highly likely that such age-related surface changes are not uniform. By measuring how such surface metrics change over time, the regions of the most rapid structural changes can be localized. We avoided using surface flattening, which distorts the inherent geometry of the cortex in our analysis and it is only used in visualization. To increase the signal to noise ratio, diffusion smoothing, which generalizes Gaussian kernel smoothing to an arbitrary curved cortical surface, has been developed and applied to surface data. Afterward, statistical inference on the cortical surface will be performed via random fields theory. As an illustration, we demonstrate how this new surface-based morphometry can be applied in localizing the cortical regions of the gray matter tissue growth and loss in the brain images longitudinally collected in the group of children and adolescents. [Copyright &y& Elsevier]

We report new random field theory P values for peaks of canonical correlation SPMs for detecting multiple contrasts in a linear model for multivariate image data. This completes results for all types of univariate and multivariate image data analysis. All other known univariate and multivariate random field theory results are now special cases, so these new results present a true unification of all currently known results. As an illustration, we use these results in a deformation-based morphometry (DBM) analysis to look for regions of the brain where vector deformations of nonmissile trauma patients are related to several verbal memory scores, to detect regions of changes in anatomical effective connectivity between the trauma patients and a group of age- and sex-matched controls, and to look for anatomical connectivity in cortical thickness. [Copyright &y& Elsevier]

Abstract: Epileptic activity underlying idiopathic generalized epilepsy (IGE) is related to abnormal thalamo–cortical interactions. Our purpose was to map in vivo the organization of the thalamo–cortical network in IGE. We measured cortical thickness and thalamic volumes on MRI in 23 IGE patients with generalized tonic–clonic seizures only and 46 healthy controls. Significant correlations between thalamic volumes and cortical thickness were interpreted as thalamo–cortical network connections. In controls, thickness of frontal, limbic, and occipital regions was positively correlated with the thalamic volumes, corresponding to known anatomical connections from sacrificial tracer studies in primates and human in vivo DTI data. In patients, thalamo–cortical network correlations increased in fronto-central and parietal regions, but decreased in limbic areas. Group analysis revealed that, compared to controls, IGE patients had bilateral thalamic atrophy and widespread cortical thinning that was most prominent in fronto-central areas, with a prevalence of up to 40%. Duration of epilepsy affected negatively thalamic volumes and thickness of fronto-central and limbic cortices. These effects were significantly different from aging in controls. Patients with poorly controlled seizures showed an even faster progression in these neocortical regions. Fronto-centro-parietal atrophy in IGE is likely the effect of generalized seizure activity inducing thalamo–cortical network remodeling. On the other hand, limbic abnormalities may take place secondary to thalamic disconnection. [Copyright &y& Elsevier]

Abstract: Contradictory reports regarding the detection of neuronal currents have left the feasibility of neuronal current MRI (ncMRI) an open question. Most previous ncMRI studies in human subjects are suspect due to their inability to separate or eliminate hemodynamic effects. In this study, we used a bloodless turtle brain preparation that eliminates hemodynamic effects, to explore the feasibility of detecting visually-evoked ncMRI signals at 9.4 T. Intact turtle brains, with eyes attached, were dissected from the cranium and placed in artificial cerebral spinal fluid. Light flashes were delivered to the eyes to evoke neuronal activity. Local field potential (LFP) and MRI signals were measured in an interleaved fashion. Robust visually-evoked LFP signals were observed in turtle brains, but no significant signal changes synchronized with neuronal currents were found in the ncMRI images. In this study, detection thresholds of 0.1% and 0.1° were set for MRI magnitude and phase signal changes, respectively. The absence of significant signal changes in the MRI images suggests that visually-evoked ncMRI signals in the turtle brain are below these detectable levels. [Copyright &y& Elsevier]

Abstract: Previous studies of cortical asymmetry have relied mainly on voxel-based morphometry (VBM), or manual segmentation of regions of interest. This study uses fully automated, surface-based techniques to analyse position and surface area asymmetry for the mid-surfaces of 112 right-handed subjects'' cortical hemispheres from a cohort of young adults. Native space measurements of local surface area asymmetry and vertex position asymmetry were calculated from surfaces registered to a previously validated hemisphere-unbiased surface-based template. Our analysis confirms previously identified hemispheric asymmetries (Yakovlevian torque, frontal and occipital petalia) in enhanced detail. It does not support previous findings of gender/asymmetry interactions or rightward planum parietale areal increase. It reveals several new findings, including a striking leftward increase in surface area of the supramarginal gyrus (peak effect 18%), compared with a smaller areal increase in the left Heschl''s gyrus and planum temporale region (peak effect 8%). A second finding was rightward increase in surface area (peak effect 10%) in a band around the medial junction between the occipital lobe, and parietal and temporal lobes. By clearly separating out the effects of structural translocation and surface area change from those of thickness and curvature, this study resolves the confound of these variables inherent in VBM studies. [Copyright &y& Elsevier]

Abstract: In this editorial, we outline a set of guidelines for the reporting of methods and results in functional magnetic resonance imaging studies and provide a checklist to assist authors in preparing manuscripts that meet these guidelines. [Copyright &y& Elsevier]

Abstract: Multiple sclerosis (MS) is thought to predominantly affect white matter (WM). Recently, however, loss of cortical gray matter has also been described. Little is known about the cause of cortical atrophy in MS, whether it occurs early in the disease course, and whether it affects all cortical regions equally or if there is a preferential pattern of focal cortical atrophy. An automated method was used to compute the thickness at every vertex of the cortical surface of the brains of 425 early relapsing–remitting MS patients. We correlated cortical thickness with the WM lesion load and the Expanded Disability Status Scale score. Mean cortical thickness correlated with WM lesion load and disability. The correlations of cortical thickness with total lesion load and disability were most significant in cingulate gyrus, insula, and associative cortical regions. Conversely, primary sensory, visual, and motor areas showed a less significant relationship. The highest amount of atrophy per lesion volume or disability scale unit was in the anterior cingulate cortex. This study confirms the relation between cortical atrophy, WM lesion load, and disability in MS, and suggests that cortical atrophy occurs even in MS patients with only mild disability. Most interestingly, we show a specific regional pattern of focal atrophy in MS that is distinctively different from the one in normal aging. The predilection of the atrophic process for areas that are heavily inter-connected with other brain regions suggests that interruption of WM tracts by MS plaques contributes, at least in part, to the development of cortical atrophy. [Copyright &y& Elsevier]

Because of their increased sensitivity to spatially extended signals, cluster-size tests are widely used to detect changes and activations in brain images. However, when images are nonstationary, the cluster-size distribution varies depending on local smoothness. Clusters tend to be large in smooth regions, resulting in increased false positives, while in rough regions, clusters tend to be small, resulting in decreased sensitivity. Worsley et al. proposed a random field theory (RFT) method that adjusts cluster sizes according to local roughness of images [Worsley, K.J., 2002. Nonstationary FWHM and its effect on statistical inference of fMRI data. Presented at the 8th International Conference on Functional Mapping of the Human Brain, June 2–6, 2002, Sendai, Japan. Available on CD-ROM in NeuroImage 16 (2) 779–780; Hum. Brain Mapp. 8 (1999) 98]. In this paper, we implement this method in a permutation test framework, which requires very few assumptions, is known to be exact [J. Cereb. Blood Flow Metab. 16 (1996) 7] and is robust [NeuroImage 20 (2003) 2343]. We compared our method to stationary permutation, stationary RFT, and nonstationary RFT methods. Using simulated data, we found that our permutation test performs well under any setting examined, whereas the nonstationary RFT test performs well only for smooth images under high df. We also found that the stationary RFT test becomes anticonservative under nonstationarity, while both nonstationary RFT and permutation tests remain valid under nonstationarity. On a real PET data set we found that, though the nonstationary tests have reduced sensitivity due to smoothness estimation variability, these tests have better sensitivity for clusters in rough regions compared to stationary cluster-size tests. We include a detailed and consolidated description of Worsley nonstationary RFT cluster-size test. [Copyright &y& Elsevier]

In multiple sclerosis (MS), the correlation between disability and the volume of white matter lesions on magnetic resonance imaging (MRI) is usually weak. This may be because lesion location also influences the extent and type of functional disability. We applied an automatic lesion-detection algorithm to 452 MRI scans of patients with relapsing-remitting MS to identify the regions preferentially responsible for different types of clinical deficits. Statistical parametric maps were generated by performing voxel-wise linear regressions between lesion probability and different clinical disability scores. There was a clear distinction between lesion locations causing physical and cognitive disability. Lesion likelihood correlated with the Expanded Disability Status Scale (EDSS) in the left internal capsule and in periventricular white matter mostly in the left hemisphere. Pyramidal deficits correlated with only one area in the left internal capsule that was also present in the EDSS correlation. Cognitive dysfunction correlated with lesion location at the grey-white junction of associative, limbic, and prefrontal cortex. Coordination impairment correlated with areas in interhemispheric and pyramidal periventricular white matter tracts, and in the inferior and superior longitudinal fascicles. Bowel and bladder scores correlated with lesions in the medial frontal lobes, cerebellum, insula, dorsal midbrain, and pons, areas known to be involved in the control of micturition. This study demonstrates for the first time a relationship between the site of lesions and the type of disability in large scale MRI data set in MS. [Copyright &y& Elsevier]

We present a general method—denoted MoDef—to help specify (or define) the model used to analyze brain imaging data. This method is based on the use of the multivariate linear model on a training data set. We show that when the a priori knowledge about the expected brain response is not too precise, the method allows for the specification of a model that yields a better sensitivity in the statistical results. This obviously relies on the validity of the a priori information, in our case the representativity of the training set, an issue addressed using a cross-validation technique. We propose a fast implementation that allows the use of the method on large data sets as found with functional Magnetic Resonance Images. An example of application is given on an experimental fMRI data set that includes nine subjects who performed a mental computation task. Results show that the method increases the statistical sensitivity of fMRI analyses. [Copyright &y& Elsevier]