John Ashburner

Correlation between structural and functional changes in brain in an idiopathic headache syndrome

Fundamental to the concept of idiopathic or primary headache, including migraine, tension-type headache and cluster headache, is the currently accepted view that these conditions are due to abnormal brain function with completely normal brain structure. Cluster headache is one such idiopathic headache with many similarities to migraine, including normal brain structure on magnetic resonance imaging and abnormal function in the hypothalamic grey matter by positron emission tomography. Given the consistency of the positron emission tomography findings with the clinical presentation, we sought to assess whether the brains of such patients were structurally normal. We used voxel-based morphometry, an objective and automated method of analyzing changes in brain structure, to study the structure of the brains of patients with cluster headache. We found a co-localization of structural changes and changes in local brain activity with positron emission tomography in the same area of the brain in the same patients. The results indicate that the current view of the neurobiology of cluster headache requires complete revision and that this periodic headache is associated with a hitherto unrecognized brain abnormality in the hypothalamic region. We believe that voxel-based morphometry has the potential to change in the most fundamental way our concept of primary headache disorders, requiring a radical reappraisal of the tenet of structural normality.

Kallmann’s syndrome Mirror movements associated with bilateral corticospinal tract hypertrophy

Objective: To investigate the etiology of mirror movements in patients with X-linked Kallmann’s syndrome (xKS) through statistical analysis of pooled white matter data from structural MR images. Background: Mirror movements occur in 85% of xKS patients. Previous electrophysiologic studies have suggested an abnormal ipsilateral corticospinal tract projection in xKS patients exhibiting mirror movements. However, an alternative hypothesis has proposed a functional lack of transcallosal inhibitory fibers. Methods: T1-weighted brain scans were normalized into stereotaxic space with segregation of gray and white matter to allow comparison of pooled white matter data on a voxel-by-voxel basis using SPM-96 software. Nine xKS patients were compared with two age-matched groups of nonmirroring individuals: nine patients with autosomal Kallmann’s syndrome (aKS) and nine age-matched normal (healthy) men. Results: Hypertrophy of the corpus callosum was found in both Kallmann’s syndrome groups: the anterior and midsection in xKS, and the genu and posterior section in aKS. Bilateral hypertrophy of the corticospinal tract was found only in the group of xKS patients exhibiting mirror movements. SPM analysis was validated by an independent region of interest analysis of corpus callosum size. Conclusion: Although morphometry on its own cannot determine the cause of mirror movements, the specific finding of a hypertrophied corticospinal tract in xKS is consistent with electrophysiologic evidence suggesting that mirror movements in xKS result from abnormal development of the ipsilateral corticospinal tract fibers.

The Critical Relationship between the Timing of Stimulus Presentation and Data Acquisition in Blocked Designs with fMRI

This paper concerns the experimental design and statistical models employed by fMRI activation studies which block presentation of linguistic stimuli. In particular, we note that the relationship between the timing of stimulus presentation and data acquisition can have a substantial impact on the ability to detect activations in critical language areas, even when the stimuli are presented in blocks. Using a blocked word rhyming paradigm and repeated investigations on a single subject, activation was observed in Brocas area (left inferior frontal cortex) and Wernickes area (left posterior temporoparietal cortex) when (i) the timing of data acquisition was distributed throughout the peristimulus time and (ii) an event-related analysis was used to model the phasic nature of the hemodynamic response within each block of repeated word stimuli. In contrast, when the timing of data acquisition relative to stimulus presentation was fixed, activation was detected in Brocas area but not consistently in Wernickes area. Our results indicate that phasic responses to stimuli occur even in a blocked design and that the sampling and proper modeling of these responses can have profound effects on their detection. Specifically, distributed sampling over peristimulus time is essential in order to detect small activations particularly when they are transient. These findings are likely to generalize to the detection of transient signals in any cognitive paradigm.

The Precision of Anatomical Normalization in the Medial Temporal Lobe Using Spatial Basis Functions

We investigated the accuracy of spatial basis function normalization using anatomical landmarks to determine how precisely homologous regions are colocalized. We examined precision in terms of: (1) the number of nonlinear basis functions used by the normalization procedure; (2) the degree of (Bayesian) regularization; and (3) the effect of substituting different templates and how this interacted with the number of basis functions. The face validity of spatial normalization was assessed as a function of these parameters, using the colocalization of homologous landmarks in a test sample of 20 normally developing children and 5 children with bilateral hippocampal pathology. Our results suggest that when optimal normalization parameters are used, anatomical landmarks in the medial temporal lobes are colocalized to within a standard deviation of about 1 mm. When suboptimal parameters are used this standard deviation can increase up to 3 mm. Interestingly the optimal parameters are those that provide a rather constrained normalization as opposed to those that optimize intensity matching at the expense of rendering the warps unlikely. The implications of our results, for users of voxel-based morphometry, are discussed.

Statistical parametric mapping with 18F-dopa PET shows bilaterally reduced striatal and nigral dopaminergic function in early Parkinson's disease.

OBJECTIVE To apply statistical parametric mapping to 18F-dopa PET data sets, to examine the regional distribution of changes in dopaminergic metabolism in early asymmetric Parkinson’s disease. METHODS Thirteen normal volunteers (age 57.7 (SD 16.5) years; four women, nine men ) and six patients (age 50.3 (SD 13.5) years; three women, three men) with asymmetric (right sided) Parkinson’s disease were studied. Images from each dynamic dopa PET dataset were aligned and parametric images of18F-dopa influx (Ki) were created for each subject. The Ki images were transformed into standard stereotactic space. The Ki values of the caudate and putamen on spatially normalised images were compared with the Ki values before normalisation. The application of statistical parametric mapping (SPM) allowed statistical comparison of regional Ki values on a voxel by voxel basis between healthy volunteers and patients with Parkinson’s disease. RESULTS There was a strong correlation between the Ki values before and after spatial normalisation (r=0.898, p=0.0001). Significant decreases in the Ki values were found for the Parkinson’s desease group throughout the entire left putamen (p< 0.001) and focally in the dorsal right putamen (p< 0.001). Decreased Ki values were also shown bilaterally in the substantia nigra (p< 0.01). CONCLUSION Using (SPM) and 18F-dopa PET, reductions in both striatal and nigral brain dopaminergic function could be demonstrated in early Parkinson’s disease.

Assessing study-specific regional variations in fMRI signal.

In this paper, we present a post hoc method for identifying regions where functional MRI data are subject to signal reduction that may compromise sensitivity to activations. The motivation for developing this technique derives from recent language studies that showed responses in the inferior temporal lobe that could be detected by PET but not by fMRI. Reduced signal is due mostly to susceptibility artifacts and can be identified by comparing the T2* images (which are subject to susceptibility artifacts) with T2 images (which are not). However, T2 images are not usually acquired in fMRI studies. Therefore, we propose that areas with reduced signal can be identified by comparing T2* images that are corrected for nonuniformity with the original uncorrected images. The technique provides a voxel-wise characterization of signal reduction that pertains to the particular data that enter into a statistical model. It requires only the functional data and can thus be applied post hoc and without any additional scans.

CHAPTER 4 – Rigid Body Registration

This chapter opens with a discussion of how images are transformed via the process of resampling. This chapter is about rigid registration of images and therefore it describes the parameterization of rigid body transformations as a subset of the more general affine transformations. Image registration is important in many aspects of functional image analysis. In imaging neuroscience, particularly for fMRI, the signal changes due to any haemodynamic response can be small compared to apparent signal differences that can result from subject movement. Subject head movement in the scanner cannot be completely eliminated, so retrospective motion correction is performed as a preprocessing step. This is especially important for experiments where subjects may move in the scanner in a way that is correlated with the different conditions. It also focuses on the methods of rigid body registration, in both intra and intermodality contexts. Intramodality registration implies registration of images acquired using the same modality and scanning sequence or contrast agent, whereas intermodality registration allows the registration of different modalities.

Chapter 2 – Spatial Normalization

Publisher Summary nThis chapter addresses the problem of spatial normalization, namely, how to map a single subjects brain image into a standard space. The solution of this problem, assuming that the standard space adopted has a known relationship to other standard spaces, allows for a wide range of voxel-based analyses and facilitates the comparison of different subjects and databases. There are a variety of approaches to these types of spatial normalization. These include the use of spatial basis functions, viscous fluid models, elastic models, and multiresolution approaches. The mathematical foundations and ideas that are applied in a number of contexts include Gauss–Newton-like optimization algorithms and a Bayesian framework used to find maximum a posteriori (MAP) estimates of the deformation fields. The chapter describes methods for performing rapid and automatic nonlabel based nonlinear spatial normalizations. The method which is considered in detail in this chapter minimizes the residual squared difference between the image and a template image of the same modality. The first step of the registration is to correct for differences in position, orientation, and size by optimizing the parameters of an affine transformation. Knowledge of the variability in head size is incorporated into this optimization to obtain a more stable solution and rapid convergence.