Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Diffusion tensor imaging (DTI) studies have shown significant cross-sectional differences among normal controls (NC) mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients in several fiber tracts in the brain, but longitudinal assessment is needed. METHODS: We studied 75 participants (25 NC, 25 amnestic MCI, and 25 mild AD) at baseline and 3 months later, with both imaging and clinical evaluations. Fractional anisotropy (FA) was analyzed in regions of interest (ROIs) in: (1) fornix, (2) cingulum bundle, (3) splenium, and (4) cerebral peduncles. Clinical data included assessments of clinical severity and cognitive function. Cross-sectional and longitudinal differences in FA, within each ROI, were analyzed with generalized estimating equations (GEE). RESULTS: Cross-sectionally, AD patients had lower FA than NC (p<0.05) at baseline and 3 months in the fornix and anterior portion of the cingulum bundle. Compared to MCI, AD cases had lower FA (p<0.05) in these regions and the splenium at 0 and 3 months. Both the fornix and anterior cingulum correlated across all clinical cognitive scores; lower FA in these ROIs corresponded to worse performance. Over the course of 3 months, when the subjects were clinically stable, the ROIs were also largely stable. CONCLUSIONS: Using DTI, findings indicate FA is decreased in specific fiber tracts among groups of subjects that vary along the spectrum from normal to AD, and that this measure is stable over short periods of time. The fornix is a predominant outflow tract of the hippocampus and may be an important indicator of AD progression.

Functional MRI of sentence comprehension in children with dyslexia: beyond word recognition.

Sentence comprehension (SC) studies in typical and impaired readers suggest that reading for meaning involves more extensive brain activation than reading isolated words. Thus far, no reading disability/dyslexia (RD) studies have directly controlled for the word recognition (WR) components of SC tasks, which is central for understanding comprehension processes beyond WR. This experiment compared SC to WR in 29, 9-14 year olds (15 typical and 14 impaired readers). The SC-WR contrast for each group showed activation in left inferior frontal and extrastriate regions, but the RD group showed significantly more activation than Controls in areas associated with linguistic processing (left middle/superior temporal gyri), and attention and response selection (bilateral insula, right cingulate gyrus, right superior frontal gyrus, and right parietal lobe). Further analyses revealed this overactivation was driven by the RD group's response to incongruous sentences. Correlations with out-of-scanner measures showed that better word- and text-level reading fluency was associated with greater left occipitotemporal activation, whereas worse performance on WR, fluency, and comprehension (reading and oral) were associated with greater right hemisphere activation in a variety of areas, including supramarginal and superior temporal gyri. Results provide initial foundations for understanding the neurobiological correlates of higher-level processes associated with reading comprehension.

Sex differences in cerebral laterality of language and visuospatial processing.

Sex differences on language and visuospatial tasks are of great interest, with differences in hemispheric laterality hypothesized to exist between males and females. Some functional imaging studies examining sex differences have shown that males are more left lateralized on language tasks and females are more right lateralized on visuospatial tasks; however, findings are inconsistent. Here we used functional magnetic resonance imaging to study thirty participants, matched on task performance, during phonological and visuospatial tasks. For each task, region-of-interest analyses were used to test differences in cerebral laterality. Results indicate that lateralization differences exist, with males more left lateralized during the phonological task and showing greater bilateral activity during the visuospatial task, whereas females showed greater bilateral activity during the phonological task and were more right lateralized during the visuospatial task. Our data provide clear evidence for differences in laterality between males and females when processing language versus visuospatial information.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task.

Differential components of sentence comprehension: beyond single word reading and memory.

A number of studies have used functional neuroimaging to examine the neural mechanisms of sentence comprehension; however, few fMRI studies have examined activation patterns associated with sentence comprehension after accounting for activation attributable to single-word-level tasks important for sentence comprehension. To investigate the patterns of activation associated with sentence comprehension after controlling for single word reading and maintaining single words in memory, 20 unimpaired adult readers completed a block design paradigm which included sentence comprehension, single word reading, and short-term memory (for words) tasks. Results indicated that, regardless of the aspect of sentence comprehension being controlled for, activation was observed in bilateral temporal lobes (left > right) as well as bilateral occipital lobes and middle frontal gyri. Additional findings showed that bilateral superior parietal lobe activation was greatest for short-term memory for words, while left anterior inferior frontal gyri activation (centered around Brodmann's area 47) was greatest for single word reading. Results suggest that temporal cortex (left > right) is a core region important for sentence comprehension beyond the short-term memory and semantic requirements inherent in processing sentences.

Semi-blind ICA of fMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis.

Independent component analysis (ICA) is a data-driven approach utilizing high-order statistical moments to find maximally independent sources that has found fruitful application in functional magnetic resonance imaging (fMRI). Being a blind source separation technique, ICA does not require any explicit constraints upon the fMRI time courses. However, for some fMRI data analysis applications, such as for the analysis of an event-related paradigm, it would be useful to flexibly incorporate paradigm information into the ICA analysis. In this paper, we present an approach for constrained or semi-blind ICA (sbICA) analysis of event-related fMRI data by imposing regularization on certain estimated time courses using the paradigm information. We demonstrate the performance of our approach using both simulations and fMRI data from a three-stimulus auditory oddball paradigm. Simulation results suggest that (1) a regression approach slightly outperforms ICA when prior information is accurate and ICA outperforms the general linear model (GLM)-based approach when prior information is not completely accurate, (2) prior information improves the robustness of ICA in the presence of noise, and (3) ICA analysis using prior information with temporal constraints can outperform a regression approach when the prior information is not completely accurate. Using fMRI data, we compare a regression-based conjunction analysis of target and novel stimuli, both of which elicit an orienting response, to an sbICA approach utilizing both the target and novel stimuli to constrain the ICA time courses. Results show similar positive associations for both GLM and sbICA, but sbICA detects additional negative associates consistent with regions implicated in a default mode of brain activity. This suggests that task-related default mode decreases have a more "complex" signal that benefits from a flexible modeling approach. Compared with a traditional GLM approach, the sbICA approach provides a flexible way to analyze fMRI data that reduces the assumptions placed upon the hemodynamic response of the brain. The advantages and limitations of our technique are discussed in detail in the manuscript to provide guidelines to the reader for developing useful applications. The use of prior time course information in a spatial ICA analysis, which combines elements of both a regression approach and a blind ICA approach, may prove to be a useful tool for fMRI analysis.

Latency (in)sensitive ICA. Group independent component analysis of fMRI data in the temporal frequency domain.

Independent component analysis (ICA), a data-driven approach utilizing high-order statistical moments to find maximally independent sources, has found fruitful application in functional magnetic resonance imaging (fMRI). A limitation of the standard fMRI ICA model is that a given component's time course is required to have the same delay at every voxel. As spatially varying delays (SVDs) may be found in fMRI data, using an ICA model with a fixed temporal delay for each source will have two implications. Larger SVDs can result in the splitting of regions with different delays into different components. Second, smaller SVDs can result in a biased ICA amplitude estimate due to only a slight delay difference. We propose a straightforward approach for incorporating this prior temporal information and removing the limitation of a fixed source delay by performing ICA on the amplitude spectrum of the original fMRI data (thus removing latency information). A latency map is then estimated for each component using the resulting component images and the raw data. We show that voxels with similar time courses, but different delays, are grouped into the same component. Additionally, when using traditional ICA, the amplitudes of motor areas are diminished due to systematic delay differences between visual and motor areas. The amplitudes are more accurately estimated when using a latency-insensitive ICA approach. The resulting time courses, the component maps, and the latency maps may prove useful as an addition to the collection of methods for fMRI data analysis.

Independent component analysis of fMRI data in the complex domain.

In BOLD fMRI a series of MR images is acquired and examined for task-related amplitude changes. These functional changes are small, so it is important to maximize detection efficiency. Virtually all fMRI processing strategies utilize magnitude information and ignore the phase, resulting in an unnecessary loss of efficiency. As the optimum way to model the phase information is not clear, a flexible modeling technique is useful. To analyze complex data sets, independent component analysis (ICA), a data-driven approach, is proposed. In ICA, the data are modeled as spatially independent components multiplied by their respective time-courses. There are thus three possible approaches: 1) the time-courses can be complex-valued, 2) the images can be complex-valued, or 3) both the time-courses and the images can be complex-valued. These analytic approaches are applied to data from a visual stimulation paradigm, and results from three complex analysis models are presented and compared with magnitude-only results. Using the criterion of the number of contiguous activated voxels at a given threshold, an average of 12-23% more voxels are detected by complex-valued ICA estimation at a threshold of /Z/ > 2.5. Additionally, preliminary results from the complex models reveal a phase modulation similar to the magnitude time-course in some voxels, and oppositely modulated in other voxels.

fMRI activation in a visual-perception task: network of areas detected using the general linear model and independent components analysis.

The Motor-Free Visual Perception Test, revised (MVPT-R), provides a measure of visual perceptual processing. It involves different cognitive elements including visual discrimination, spatial relationships, and mental rotation. We adapted the MVPT-R to an event-related functional MRI (fMRI) environment to investigate the brain regions involved in the interrelation of these cognitive elements. Two complementary analysis methods were employed to characterize the fMRI data: (a) a general linear model SPM approach based upon a model of the time course and a hemodynamic response estimate and (b) independent component analysis (ICA), which does not constrain the specific shape of the time course per se, although we did require it to be at least transiently task-related. Additionally, we implemented ICA in a novel way to create a group average that was compared with the SPM group results. Both methods yielded similar, but not identical, results and detected a network of robustly activated visual, inferior parietal, and frontal eye-field areas as well as thalamus and cerebellum. SPM appeared to be the more sensitive method and has a well-developed theoretical approach to thresholding. The ICA method segregated functional elements into separate maps and identified additional regions with extended activation in response to presented events. The results demonstrate the utility of complementary analyses for fMRI data and suggest that the cerebellum may play a significant role in visual perceptual processing. Additionally, results illustrate functional connectivity between frontal eye fields and prefrontal and parietal regions.

A method for making group inferences from functional MRI data using independent component analysis.

Independent component analysis (ICA) is a promising analysis method that is being increasingly applied to fMRI data. A principal advantage of this approach is its applicability to cognitive paradigms for which detailed models of brain activity are not available. Independent component analysis has been successfully utilized to analyze single-subject fMRI data sets, and an extension of this work would be to provide for group inferences. However, unlike univariate methods (e.g., regression analysis, Kolmogorov-Smirnov statistics), ICA does not naturally generalize to a method suitable for drawing inferences about groups of subjects. We introduce a novel approach for drawing group inferences using ICA of fMRI data, and present its application to a simple visual paradigm that alternately stimulates the left or right visual field. Our group ICA analysis revealed task-related components in left and right visual cortex, a transiently task-related component in bilateral occipital/parietal cortex, and a non-task-related component in bilateral visual association cortex. We address issues involved in the use of ICA as an fMRI analysis method such as: (1) How many components should be calculated? (2) How are these components to be combined across subjects? (3) How should the final results be thresholded and/or presented? We show that the methodology we present provides answers to these questions and lay out a process for making group inferences from fMRI data using independent component analysis.

Measurement of tissue oxygen extraction ratios from venous blood T(2): increased precision and validation of principle.

It has recently been shown that parenchymal oxygen extraction ratios (OERs) can be quantified using the absolute T(2) of venous blood draining from this tissue (Oja et al., J Cereb Blood Flow Metab 1999;19:1289-1295). Here, a modified Carr-Purcell-Meiboom-Gill (CPMG) multiecho experiment was used to increase the efficiency and precision of this approach and to test the applicability of the two-compartment exchange model for spin-echo BOLD effects in pure venous blood. Relaxation measurements on bovine blood as a function of CPMG interecho spacing, oxygen saturation, and hematocrit provided the baseline relaxation and susceptibility shift parameters necessary to directly relate OER to T(2) of venous blood in vivo. Using an interecho spacing of 25 ms, the results on visual activation studies in eight volunteers showed T(2)(CPMG) values increasing from 128 +/- 9 ms to 174 +/- 18 ms upon activation, corresponding to local OER values of 0.38 +/- 0.04 and 0.18 +/- 0.05 during baseline activity and visual stimulation, respectively. These OER values are in good agreement with literature data on venous oxygenation and numbers determined previously using a single-echo approach, while the measured T(2)s are about 20-40 ms longer.

Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

Independent component analysis (ICA) is a technique that attempts to separate data into maximally independent groups. Achieving maximal independence in space or time yields two varieties of ICA meaningful for functional MRI (fMRI) applications: spatial ICA (SICA) and temporal ICA (TICA). SICA has so far dominated the application of ICA to fMRI. The objective of these experiments was to study ICA with two predictable components present and evaluate the importance of the underlying independence assumption in the application of ICA. Four novel visual activation paradigms were designed, each consisting of two spatiotemporal components that were either spatially dependent, temporally dependent, both spatially and temporally dependent, or spatially and temporally uncorrelated, respectively. Simulated data were generated and fMRI data from six subjects were acquired using these paradigms. Data from each paradigm were analyzed with regression analysis in order to determine if the signal was occurring as expected. Spatial and temporal ICA were then applied to these data, with the general result that ICA found components only where expected, e.g., S(T)ICA "failed" (i.e., yielded independent components unrelated to the "self-evident" components) for paradigms that were spatially (temporally) dependent, and "worked" otherwise. Regression analysis proved a useful "check" for these data, however strong hypotheses will not always be available, and a strength of ICA is that it can characterize data without making specific modeling assumptions. We report a careful examination of some of the assumptions behind ICA methodologies, provide examples of when applying ICA would provide difficult-to-interpret results, and offer suggestions for applying ICA to fMRI data especially when more than one task-related component is present in the data.

Dissociation of the neural systems for working memory maintenance of verbal and nonspatial visual information.

Working memory for names and faces was investigated to ascertain whether verbal and nonspatial visual information is maintained in working memory by separate neural systems. The subjects performed a delayed match-to-sample task for famous or unfamous faces and names and a sensorimotor control task. Several occipital, temporal, parietal, and prefrontal areas were activated during all memory delays, in comparison with the control delays. Greater delay activity for unfamous faces than for names was obtained in the right fusiform gyrus, right inferior frontal gyrus (IFG), right IFG/precentral gyrus, and right medial superior frontal gyrus, whereas greater delay activity for unfamous names than for faces was observed in the precuneus, left insula/postcentral gyrus, and left IFG/precentral gyrus. There was no significant difference in the prefrontal activity in the comparison between famous faces and names. Greater delay activity for famous names than for faces was obtained in visual association and parietal areas. The results indicate that there is a functional dissociation based on information type within the neural system that is responsible for working memory maintenance of verbal and nonspatial visual information.

Diffusion and high resolution MRI of traumatic brain injury in rats: time course and correlation with histology.

Although widely employed in studies of cerebral ischemia, the use of diffusion-weighted imaging (DWI) for traumatic brain injury (TBI) has been both limited and primarily confined to the first few hours after injury. Therefore, the present study examined the temporal evolution of magnetic resonance imaging (MRI) signal changes from hours to weeks after moderate fluid-percussion TBI in rats. We used isotropic diffusion along three directions and high resolution (HR) spin-echo pulse sequences to visualize DWI and HR MRI changes, respectively. Late changes were compared to histopathological and neurological outcome. A significant decrease (P<0.05) in the apparent diffusion coefficients (ADC) below preinjury levels was found in the left cortex and left hippocampus (ipsilateral to injury) at 1-2 h post-TBI. At 2 weeks post-TBI, ADCs were significantly elevated (P<0.05) above preinjury levels in both cortex and hippocampus. Regions of hypo- and hyperintensity detected in HR MRI scans also showed evidence of tissue damage by histological evaluation. Neurological assessment indicated that such changes were observed at a level of injury which produced moderate impairment 2 weeks after the insult. These results indicate that alterations in DWI and HR MRI signals occur both early (hours) and late (weeks) after lateral fluid-percussion injury. Furthermore, the study showed that DWI was sensitive to MR signal change at 1-2 h post TBI (in select ROIs), whereas HR scans showed MR signal change primarily at later time points (3-4 h and later). Moreover, regions which demonstrate late changes are associated with histological damage and neurological impairment. The study demonstrates the utility of MRI to detect early changes, in some cases, that are predictive of long-lasting damage verified histologically.

Anatomical and functional imaging of the auditory cortex in awake mustached bats using magnetic resonance technology.

The auditory cortex of mustached bats, Pteronotus parnellii, has been studied extensively using neuroanatomical tract-tracing and electrophysiological techniques to elucidate the functional organization and neural mechanisms important for auditory processing. While these techniques have identified several cortical maps involved in processing auditory information, there has been no direct observation of the dynamics of simultaneous activation of several discrete areas. We applied magnetic resonance (MR) imaging techniques for visualizing brain structures in awake bats using a 7-Tesla magnet system; we also investigated functional MR imaging by measuring changes in stimulus-correlated blood oxygenation levels to detect cortical areas exhibiting evoked neural activity. High resolution (100 microm) anatomical images were successfully acquired without any motion artifacts. It was possible to reconstruct the whole brain image and analyze brain surface structures with three dimensional (3D) MR imaging data. These data provide detailed morphometric measurements that will allow localization of stimulus specific neural activity patterns using modified functional magnetic-resonance-imaging (fMRI) protocols. Motion artifacts is the primary disadvantage of using awake bats; our study shows that fMRI of a bat's brain is feasible and may prove to be an important advancement for a further understanding of auditory processing in this species.Themes: Sensory systems, Neural basis of behavior.

Effect of magnetization transfer on the measurement of cerebral blood flow using steady-state arterial spin tagging approaches: a theoretical investigation.

A simple four-compartment model for magnetization transfer was used to obtain theoretical expressions for the relationship between regional cerebral blood flow and delta M, the change in longitudinal magnetization of brain water spins when arterial water spins are perturbed. The theoretical relationship can be written in two forms, depending on the approach used to normalize delta M. Using the first approach, the calculation of cerebral blood flow requires a knowledge of R1(omega 1, delta omega), the longitudinal relaxation rate observed in the presence of continuous off-resonance RF irradiation. Using the second approach, the calculation of cerebral blood flow requires a knowledge of R1(omega 1, delta omega), where R1(omega 1, delta omega) is given by the product of R1(omega 1, delta omega) and the fractional steady-state longitudinal water magnetization in the presence of off-resonance RF irradiation. If the off-resonance RF irradiation used for arterial tagging does not produce appreciable magnetization transfer effects, R1(omega 1, delta omega) can be approximated by the longitudinal relaxation rate measured in the absence of off-resonance RF irradiation, R1obs. Theoretical expressions obtained by using the four-component model for magnetization transfer are compared with equivalent expressions obtained by using two-compartment models.

Whole-brain functional mapping with isotropic MR imaging.

PURPOSE: To assess the reliability and sensitivity of gradient-echo, isotropic multisection echo-planar magnetic resonance (MR) imaging for within-subject whole-brain mapping. MATERIALS AND METHODS: Eight right-handed healthy volunteers underwent gradient-echo, echo-planar MR imaging while they performed a motor task on three occasions over 2-3 months. Ninety-six whole-brain volumes were acquired in 8 minutes 48 seconds. A rigorous statistical threshold for determining activation was set at P < .05 and was Bonferroni corrected for approximately 15,000 cortical voxels. RESULTS: In all subjects, reproducible activation was demonstrated in multiple cortical areas and in the cerebellum specific to the motor system. Of the activated voxels, 75%-78% were confined to the motor areas during all sessions. No statistically significant difference was found in the proportion of activated voxels in any motor region (relative to the total number of activated voxels in the whole brain) across the three sessions. The centers of mass of the activated areas were within 2.5 resolution elements of the image across the three sessions. CONCLUSION: Isotropic multisection echo-planar MR imaging, has the potential for noninvasive, reliable within-subject mapping of whole-brain functional anatomy.

Perfusion imaging of the human brain at 1.5 T using a single-shot EPI spin tagging approach.

Single-shot echo planar imaging (EPI) techniques have been applied, in conjunction with arterial spin tagging approaches, to obtain images of cerebral blood flow in a single axial slice in the human brain. Serial studies demonstrate that cerebral blood flow images acquired in 8 min are reproducible, with a statistical precision of approximately +/-10 cc/100 g/min. The average value of cerebral blood flow in the slice is 51 +/- 11 cc/100 g/min for six normal subjects. The cerebral blood flow images contain two types of artifact, probably due to arterial and venous blood volume contributions, which must be overcome before the arterial spin tagging approach can be used for routine clinical studies.