Mariana Lazar

Diffusion tensor imaging of the corpus callosum in Autism.

The corpus callosum is the largest commissural white matter pathway that connects the hemispheres of the human brain. In this study, diffusion tensor imaging (DTI) was performed on subject groups with high-functioning autism and controls matched for age, handedness, IQ, and head size. DTI and volumetric measurements of the total corpus callosum and subregions (genu, body and splenium) were made and compared between groups. The results showed that there were significant differences in volume, fractional anisotropy, mean diffusivity, and radial diffusivity between groups. These group differences appeared to be driven by a subgroup of the autism group that had small corpus callosum volumes, high mean diffusivity, low anisotropy, and increased radial diffusivity. This subgroup had significantly lower performance IQ measures than either the other individuals with autism or the control subjects. Measurements of radial diffusivity also appeared to be correlated with processing speed measured during the performance IQ tests. The subgroup of autism subjects with high mean diffusivity and low fractional anisotropy appeared to cluster with the highest radial diffusivities and slowest processing speeds. These results suggest that the microstructure of the corpus callosum is affected in autism, which may be related to nonverbal cognitive performance.

Longitudinal changes in patients with traumatic brain injury assessed with diffusion-tensor and volumetric imaging ☆

Traumatic brain injury (TBI) is associated with brain volume loss, but there is little information on the regional gray matter (GM) and white matter (WM) changes that contribute to overall loss. Since axonal injury is a common occurrence in TBI, imaging methods that are sensitive to WM damage such as diffusion-tensor imaging (DTI) may be useful for characterizing microstructural brain injury contributing to regional WM loss in TBI. High-resolution T1-weighted imaging and DTI were used to evaluate regional changes in TBI patients compared to matched controls. Patients received neuropsychological testing and were imaged approximately 2 months and 12.7 months post-injury. Paradoxically, neuropsychological function improved from Visit 1 to Visit 2, while voxel-based analyses of fractional anisotropy (FA), and mean diffusivity (MD) from the DTI images, and voxel-based analyses of the GM and WM probability maps from the T1-weighted images, mainly revealed significantly greater deleterious GM and WM change over time in patients compared to controls. Cross-sectional comparisons of the DTI measures indicated that patients have decreased FA and increased MD compared to controls over large regions of the brain. TBI affected virtually all of the major fiber bundles in the brain including the corpus callosum, cingulum, the superior and inferior longitudinal fascicules, the uncinate fasciculus, and brain stem fiber tracts. The results indicate that both GM and WM degeneration are significant contributors to brain volume loss in the months following brain injury, and also suggest that DTI measures may be more useful than high-resolution anatomical images in assessment of group differences.

Diffusion tensor imaging of white matter in the superior temporal gyrus and temporal stem in autism.

Recent MRI studies have indicated that regions of the temporal lobe including the superior temporal gyrus (STG) and the temporal stem (TS) appear to be abnormal in autism. In this study, diffusion tensor imaging (DTI) measurements of white matter in the STG and the TS were compared in 43 autism and 34 control subjects. DTI measures of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were compared between groups. In all regions, fractional anisotropy was significantly decreased and both mean diffusivity and radial diffusivity were significantly increased in the autism group. These results suggest that white matter microstructure in autism is abnormal in these temporal lobe regions, which is consistent with theories of aberrant brain connectivity in autism.

Reduced evoked gamma oscillations in the frontal cortex in schizophrenia patients: a TMS/EEG study.

OBJECTIVE Transcranial magnetic stimulation (TMS) combined with high-density electroencephalography (EEG) can be used to directly examine the properties of thalamocortical circuits in the brain without engaging an individual in cognitive or motor tasks. The authors investigated EEG responses in schizophrenia patients and healthy comparison subjects following the application of TMS to the premotor cortex. METHOD Sixteen schizophrenia patients and 14 healthy comparison subjects were recruited to participate in the study. Participants underwent three to five TMS/high-density EEG sessions at various TMS doses. The following three aspects of TMS-evoked responses were analyzed: amplitude, synchronization, and source localization. RESULTS Relative to healthy comparison subjects, schizophrenia patients had a marked decrease in evoked gamma oscillations that occurred within the first 100 msec after TMS, particularly in a cluster of electrodes located in a fronto-central region. These oscillations were significantly reduced in amplitude (calculated using global-mean field power and event-related spectral perturbation analysis) and synchronization (measured using intertrial coherence). Furthermore, source modeling analysis revealed that the TMS-evoked brain activation underlying these gamma oscillations in patients with schizophrenia did not propagate (as it did in healthy comparison subjects) and was mostly confined to the stimulated brain region. CONCLUSIONS Schizophrenia patients showed a decrease in EEG-evoked responses in the gamma band when TMS was applied to directly stimulate the frontal cortex while these responses were recorded. Since EEG responses to direct cortical stimulation are not affected by an individuals motivation, attention, or cognitive capacity and are not relayed through peripheral afferent pathways, these findings suggest that there might be an intrinsic dysfunction in frontal thalamocortical circuits in individuals with schizophrenia.

White Matter in Aging and Cognition: A Cross-sectional Study of Microstructure in Adults Aged Eighteen to Eighty-Three

Structural brain change and concomitant cognitive decline are the seemingly unavoidable escorts of aging. Despite accumulating studies detailing the effects of age on the brain and cognition, the relationship between white matter features and cognitive function in aging have only recently received attention and remain incompletely understood. White matter microstructure can be measured with diffusion tensor imaging (DTI), but whether DTI can provide unique information on brain aging that is not explained by white matter volume is not known. In the current study, the relationship between white matter microstructure, age, and neuropsychological function was assessed using DTI in a statistical framework that employed white matter volume as a voxel-wise covariate in a sample of 120 healthy adults across a broad age range (18–83). Memory function and executive function were modestly correlated with the DTI measures while processing speed showed the greatest extent of correlation. The results suggest that age-related white matter alterations underlie age-related declines in cognitive function. Mean diffusivity and fractional anisotropy in several white matter brain regions exhibited a nonlinear relationship with age, while white matter volume showed a primarily linear relationship with age. The complex relationships between cognition, white matter microstructure, and white matter volume still require further investigation.

A Study of Diffusion Tensor Imaging by Tissue-Specific, Smoothing-Compensated Voxel-Based Analysis

Voxel-based analysis (VBA) is commonly used for statistical analysis of image data, including the detection of significant signal differences between groups. Typically, images are co-registered and then smoothed with an isotropic Gaussian kernel to compensate for image misregistration, to improve the signal-to-noise ratio (SNR), to reduce the number of multiple comparisons, and to apply random field theory. Problems with typical implementations of VBA include poor tissue specificity from image misregistration and smoothing. In this study, we developed a new tissue-specific, smoothing-compensated (T-SPOON) method for the VBA of diffusion tensor imaging (DTI) data with improved tissue specificity and compensation for image misregistration and smoothing. When compared with conventional VBA methods, the T-SPOON method introduced substantially less errors in the normalized and smoothed DTI maps. Another confound of the conventional DTI-VBA is that it is difficult to differentiate between differences in morphometry and DTI measures that describe tissue microstructure. T-SPOON VBA decreased the effects of differential morphometry in the DTI VBA studies. T-SPOON and conventional VBA were applied to a DTI study of white matter in autism. T-SPOON VBA results were found to be more consistent with region of interest (ROI) measurements in the corpus callosum and temporal lobe regions. The T-SPOON method may be also applicable to other quantitative imaging maps such as T1 or T2 relaxometry, magnetization transfer, or PET tracer maps.

Mapping brain anatomical connectivity using white matter tractography

Integration of the neural processes in the human brain is realized through interconnections that exist between different neural centers. These interconnections take place through white matter pathways. White matter tractography is currently the only available technique for the reconstruction of the anatomical connectivity in the human brain noninvasively and in vivo. The trajectory and terminations of white matter pathways are estimated from local orientations of nerve bundles. These orientations are obtained using measurements of water diffusion in the brain. In this article, the techniques for estimating fiber directions from diffusion measurements in the human brain are reviewed. Methods of white matter tractography are described, together with the current limitations of the technique, including sensitivity to image noise and partial voluming. The applications of white matter tractography to the topographical characterization of the white matter connections and the segmentation of specific white matter pathways, and corresponding functional units of gray matter, are discussed. In this context, the potential impact of white matter tractography in mapping the functional systems and subsystems in the human brain, and their interrelations, is described. Finally, the applications of white matter tractography to the study of brain disorders, including fiber tract localization in brains affected by tumors and the identification of impaired connectivity routes in neurologic and neuropsychiatric diseases, are discussed. Copyright

White matter is altered with parental family history of Alzheimer’s disease

Brain alterations in structure and function have been identified in people with risk factors for sporadic type Alzheimers disease (AD), suggesting that alterations can be detected decades before AD diagnosis. Although the effect of apolipoprotein E (APOE) ɛ4 on the brain is well‐studied, less is known about the effect of family history of AD. We examined the main effects of family history and APOE ɛ4 on brain integrity, in addition to assessing possible additive effects of these two risk factors.

Application of Brodmann's area templates for ROI selection in white matter tractography studies

Brodmanns areas are part of the common vernacular used by neuroscientists to indicate specific location of brain activity in functional brain imaging studies. Here, we have employed a template based on the Brodmanns areas as a means of compartmentalizing underlying white matter pathways. White matter tractography was performed on the diffusion tensor data of sixteen subjects using a streamline tracking technique with Runge-Kutta integration. After co-registration, the Brodmann template was utilized for ROI selection. Tracts were segmented based on their termination in a particular area of the template. Binary masks were generated based on the tractography segmentation for a given Brodmanns area in each individual subject. Following registration to a normalized coordinate space, the binary masks were averaged, generating a map that estimates the probability of tractography connectivity for particular white matter pathways to a specific Brodmanns area. The probability maps were color-coded and overlaid on anatomical images to provide perspective. In this study, particular attention was given to the areas of the frontal cortex. A composite map of these areas was generated by assigning each voxel to the Brodmanns area with the highest probability of connectivity, based on the average results. The average maps generated with this method reveal consistent patterns of connectivity across subjects. The use of a normalized template for ROI selection automates the process of segmenting tractography data, making it particularly useful for multi-subject studies. In the future, this method could be used to help elucidate relationships between function and anatomical structure.

Spontaneous brain activity in combat related PTSD

Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder, especially in combat veterans. Existing functional neuroimaging studies have provided important insights into the neural mechanisms of PTSD using various experimental paradigms involving trauma recollection or other forms of emotion provocation. However it is not clear whether the abnormal brain activity is specific to the mental processes related to the experimental tasks or reflects general patterns across different brain states. Thus, studying intrinsic spontaneous brain activity without the influence of external tasks may provide valuable alternative perspectives to further understand the neural characteristics of PTSD. The present study evaluated the magnitudes of spontaneous brain activity of male US veterans with or without PTSD, with the two groups matched on age, gender, and ethnicity. Amplitudes of low frequency fluctuation (ALFF), a data driven analysis method, were calculated on each voxel of the resting state fMRI data to measure the magnitudes of spontaneous brain activity. Results revealed that PTSD subjects showed increased spontaneous activity in the amygdala, ventral anterior cingulate cortex, insula, and orbital frontal cortex, as well as decreased spontaneous activity in the precuneus, dorsal lateral prefrontal cortex and thalamus. Within the PTSD group, larger magnitudes of spontaneous activity in the thalamus, precuneus and dorsal lateral prefrontal cortex were associated with lower re-experiencing symptoms. Comparing our results with previous functional neuroimaging findings, increased activity of the amygdala and anterior insula and decreased activity of the thalamus are consistent patterns across emotion provocation states and the resting state.