Feroze B. Mohamed

Functional localization of a “time keeper” function separate from attentional resources and task strategy

The functional neuroanatomy of time estimation has not been well-documented. This research investigated the fMRI measured brain response to an explicit, prospective time interval production (TIP) task. The study tested for the presence of brain activity reflecting a primary time keeper function, distinct from the brain systems involved either in conscious strategies to monitor time or attentional resource and other cognitive processes to accomplish the task. In the TIP task participants were given a time interval and asked to indicate when it elapsed. Two control tasks (counting forwards, backwards) were administered, in addition to a dual task format of the TIP task. Whole brain images were collected at 1.5 Tesla. Analyses (n = 6) yielded a statistical parametric map (SPM ¿z¿) reflecting time keeping and not strategy (counting, number manipulation) or attention resource utilization. Additional SPM ¿z¿s involving activation associated with the accuracy and magnitude the of time estimation response are presented. Results revealed lateral cerebellar and inferior temporal lobe activation were associated with primary time keeping. Behavioral data provided evidence that the procedures for the explicit time judgements did not occur automatically and utilized controlled processes. Activation sites associated with accuracy, magnitude, and the dual task provided indications of the other structures involved in time estimation that implemented task components related to controlled processing. The data are consistent with prior proposals that the cerebellum is a repository of codes for time processing, but also implicate temporal lobe structures for this type of time estimation task.

Increased differentiation of intracranial white matter lesions by multispectral 3D-tissue segmentation: preliminary results.

MRI is a very sensitive imaging modality, however with relatively low specificity. The aim of this work was to determine the potential of image post-processing using 3D-tissue segmentation technique for identification and quantitative characterization of intracranial lesions primarily in the white matter. Forty subjects participated in this study: 28 patients with brain multiple sclerosis (MS), 6 patients with subcortical ischemic vascular dementia (SIVD), and 6 patients with lacunar white matter infarcts (LI). In routine MR imaging these pathologies may be almost indistinguishable. The 3D-tissue segmentation technique used in this study was based on three input MR images (T(1), T(2)-weighted, and proton density). A modified k-Nearest-Neighbor (k-NN) algorithm optimized for maximum computation speed and high quality segmentation was utilized. In MS lesions, two very distinct subsets were classified using this procedure. Based on the results of segmentation one subset probably represent gliosis, and the other edema and demyelination. In SIVD, the segmented images demonstrated homogeneity, which differentiates SIVD from the heterogeneity observed in MS. This homogeneity was in agreement with the general histological findings. The LI changes pathophysiologically from subacute to chronic. The segmented images closely correlated with these changes, showing a central area of necrosis with cyst formation surrounded by an area that appears like reactive gliosis. In the chronic state, the cyst intensity was similar to that of CSF, while in the subacute stage, the peripheral rim was more prominent. Regional brain lesion load were also obtained on one MS patient to demonstrate the potential use of this technique for lesion load measurements. The majority of lesions were identified in the parietal and occipital lobes. The follow-up study showed qualitatively and quantitatively that the calculated MS load increase was associated with brain atrophy represented by an increase in CSF volume as well as decrease in normal brain tissue volumes. Importantly, these results were consistent with the patients clinical evolution of the disease after a six-month period. In conclusion, these results show there is a potential application for a 3D tissue segmentation technique to characterize white matter lesions with similar intensities on T(2)-weighted MR images. The proposed methodology warrants further clinical investigation and evaluation in a large patient population.

Bold fMRI of the visual cortex: Quantitative responses measured with a graded stimulus at 1.5 Tesla

To measure and quantitatively characterize an activity generated by the neurons of the visual cortex (VC) in response to graded luminous intensity contrast stimuli using a 1.5 Tesla scanner.

Utililization of experimental animal model for correlative multispectral MRI and pathological analysis of brain tumors.

Magnetic resonance imaging is the method of choice for non-invasive detection and evaluation of tumors of the central nervous system. However, discrimination of tumor boundaries from normal tissue, and the evaluation of heterogeneous lesions have proven to be limitations in traditional magnetic resonance imaging. The use of post-image acquisition processing techniques, such as multispectral tissue segmentation analysis, may provide more accurate clinical information. In this report, we have employed an experimental animal model for brain tumors induced by glial cells transformed by the human neurotropic JC virus to examine the utility of multispectral tissue segmentation for tumor cell identification. Six individual tissue types were discriminated by segmentation analysis, including heterogeneous tumor tissue, a clear demarcation of the boundary between tumor and non-tumor tissue, deep and cortical gray matter, and cerebrospinal fluid. Furthermore, the segmentation analysis was confirmed by histopathological evaluation. The use of multispectral tissue segmentation analysis may optimize the non-invasive determination and volumetric analysis of CNS neoplasms, thus providing improved clinical evaluation of tumor growth and evaluation of the effectiveness of therapeutic treatments.

Differential brain responses when applying criterion attribute versus family resemblance rule learning

Subsystems of category learning have been identified on the basis of general domains of content (e.g., tools, faces). The present study examined categories from the standpoint of internal structure and determined brain topography associated with expressing two fundamentally different category rule structures (criterion attribute, CA, and family resemblance, FR). CA category learning involves processing stimuli by isolated features and classifying by properties held by all members. FR learning involves processing stimuli by integral wholes and classifying on overall similarity among members without sharing identical features. fMRI BOLD response to CA and FR categorization was measured with pseudowords as stimuli. Category knowledge for both tasks was mastered prior to brain imaging. Areas of activation emerged unique to the structure of each category and followed from the nature of the rule abstraction procedure. CA categorization was implemented by strong target monitoring and expectation (medial parietal), rule maintenance in working memory, feature selection processes (inferior frontal), and a sensitivity to high frequency components of the stimulus such as isolated features (anterior temporal). FR categorization, consistent with its multi-featural nature, involved word-level processing (left extrastriate) that evoked articulatory rehearsal (medial cerebellar). The data suggest category structure is an important determinant of brain response during categorization. For instance, anterior temporal structures may help attune visual processing systems to high frequency components to support the learning of criterial, highly predictive rules.

Investigation of alternating and continuous experimental task designs during single finger opposition fMRI: a comparative study.

The purpose of this study was to empirically investigate and compare the effects of alternating and continuous experimental task designs on blood oxygenation level dependent (BOLD) signal contrast. Six healthy volunteers underwent single-finger opposition functional magnetic resonance imaging (fMRI) using T2*-weighted echo planar imaging technique on a 1.5 T MR scanner. Two different acquisition patterns were tested: alternating (ABABAB) and continuous (AAABBB), rest: A, activation: B. The BOLD signal contrast within a primary motor cortex region of interest (ROI) was evaluated using normalized t-values (z-scores) and mean region of interest (ROI) intensity for the two patterns. Analysis of variance (ANOVA) on ROI mean z-score and signal intensities demonstrate that the alternating pattern of administering rest and activation epochs produced a more robust statistical difference than a continuous pattern. The results showed that different patterns of acquisition yield differences in the BOLD signal at field strength of 1.5 T, and that an alternating task design can be considered more optimal than a continuous task design.

A simple method to improve image nonuniformity of brain MR images at the edges of a head coil.

One of the major sources of image nonuniformity in the high field MR scanners is the radiofrequency (RF) coil inhomogeneity. It degrades conspicuity of lesion(s) in the MR images of the brain and surrounding tissues and reduces accuracy of image postprocessing particularly at the edges of the coil. In this investigation, we have devised and tested a simple method to correct for nonuniformity of MR images of the brain at the edges of the RF head coil. Initially, a cylindrical oil phantom, which fit exactly in the head coil, was scanned on a 1.5 T imager. Then, a correction algorithm identified a reference pixel value in the phantom at the most homogeneous region of the RF coil. Next, every pixel inside the phantom was normalized relative to this reference value. The resulting set of coefficients or correction matrices was obtained for different types of MR contrast agent. Finally, brain MR images of normal subjects and multiple sclerosis patients were acquired and processed by the corresponding correction matrices obtained with different pulse sequences. Application of correction matrices to brain MR images showed a gain in pixel intensity particularly in the slices at the edge of the coil.

Image-Based Modeling of Arteriovenous Hemodialysis Access Graft Flow

Thrombosis in an arteriovenous hemodialysis access graft is a major cause of graft failure. Changes in flow features due to increasing resistance at the venous anastomosis may promote the development of thrombosis. A three-dimensional computational fluid dynamics model was developed to analyze flow at the arterial anastomosis of a PTFE brachial-brachial arteriovenous access graft. The geometry was obtained from contrast-enhanced magnetic resonance images. A surface mesh was extracted using Amira software, and the final volume mesh was generated by Tgrid (Fluent, Inc). The simulation was carried out for steady flow conditions using Fluent CFD software with low-Reynolds number k-ω turbulence model. Small areas of recirculation can be seen in the area of the bifurcation, and results show a pressure difference between the proximal artery and the graft that is consistent with reported values.Copyright

Investigation of alternating and continuous functional MRI experimental designs at 1.5 T

Studies the effect of two different functional MRI (fMRI) experimental design parameters on blood oxygenation level dependent (BOLD) signal contrast. The design parameters examined were: (1) the pattern of administering the control and activation conditions; and (2) the quantity of the control signals collected. Six normal volunteers underwent single finger opposition fMRI using T2*-weighted echo planar imaging technique. The BOLD signal contrast was evaluated using analysis of variance on normalized t-values and mean region-of-interest (ROI) intensity. The results demonstrate: (1) the alternating pattern of administering rest and activation epochs produced a more robust statistical difference in BOLD signal than a continuous pattern, and (2) a reduction in the amount of rest signal collected did not result in a statistically significant reduction in the BOLD signal. The results indicate that manipulating such factors of signal collection does alter BOLD signal properties.

A new fMRI postprocessing HASTE map technique to increase accuracy of the cortical BOLD activation in the visual cortex

In functional MRI (fMRT), blood oxygenation level dependent (BOLD) imaging studies of the brain activated voxels often appear in sulci. True positive activation appears due to the presence of paramagnetic deoxyhemoglobin blood because of cortical neural activity. False positive activation may occur within noncortical cerebrospinal fluid (CSF) spaces due to activation in vessels and CFS how within sulci adjacent to the area performing a task. Also, true positive task-nonrelevant BOLD activation appearing in sulci away from the neuroanatomical regions associated with a specific task was assumed as false activation. Such false activations may lead to misinterpretations of fMRI maps. The currently used echo-planar imaging (EPI) techniques lack high spatial resolution to differentiate such false positive activation from true positive activation. The specific aim of the work was to develop an fMRI image postprocessing technique to identify the sulci in the EPI images using half-Fourier turbo-spin echo (HASTE) sequence. High resolution HASTE images are insensitive to susceptibility effect and have high contrast differences between areas filled with fluids and brain parenchyma. Therefore these HASTE images can be effectively used to clearly separate CSF in the sulci from other cortical brain structures where the true BOLD activation is present.