Biomedical subjects

John D Carew

Publications and source records attributed to John D Carew.

8 recordsLinked to original sources

PubMed2005

Independent component analysis applied to self-paced functional MR imaging paradigms.

Self-paced functional MR imaging (fMRI) paradigms, in which the task timing is determined by the subject's performance, can offer several advantages over commonly applied paradigms with predetermined stimulus timing. Independent component analysis (ICA) does not require specification of a timed response function, and could be an advantageous method of deriving results from fMRI data sets with varying response timings and durations. In this study normal volunteers (N = 10) each performed two self-paced fMRI motor and arithmetic paradigms. Individual data sets were analyzed with the Infomax spatial ICA algorithm. Conventional regression analysis was performed for comparison purposes. Spatial ICA effectively produced task-related components from each of the self-paced data sets, even in a few cases where regression analysis yielded non-specific functional maps. For the motor paradigm, these components consistently mapped to primary motor areas. ICA of the arithmetic paradigm yielded multiple task-related components that variably mapped to regions of parietal and frontal lobes. Regression analysis generally yielded similar spatial maps. The multiple task-related ICA components that were sometimes produced from each self-paced data set can be challenging to identify and evaluate for significance. These preliminary results indicate that ICA is useful as an exploratory and complementary method to conventional regression analysis for fMRI of self-paced paradigms.

Adult↗

PubMed2004

Hemispheric asymmetry in supplementary motor area connectivity during unilateral finger movements.

Studies of unilateral finger movement in right-handed subjects have shown asymmetrical patterns of activation in primary motor cortex. Some studies have measured a similar asymmetry in the supplementary motor area (SMA), but others have not. To shed more light on the symmetry of function in the SMA, we used path analysis of functional MRI data to investigate effective connectivity during a unilateral finger movement task. We observed a slight asymmetry in task activation: left SMA was equally active during movement of either hand, while right SMA was more active for left-hand movement, suggesting a dominant role of left SMA. In addition, we tested for a corresponding asymmetry in the influence of SMA on sensorimotor cortex (SMC) using a path model based on the well-established principle that SMA is involved in motor control and SMC in execution. We observed that the influence of left SMA on left SMC increased during right-hand movement, and the influence of left SMA on right SMC increased during left-hand movement. However, there was no significant hand-dependent change in the influences of the right SMA. This asymmetry in connectivity implies that left SMA does play a dominant role in unilateral movements of either hand in right handers. The experiment also provides a basis for further studies of motor system connectivity in healthy or patient populations.

Adult↗

PubMed2003

Optimal spline smoothing of fMRI time series by generalized cross-validation.

Linear parametric regression models of fMRI time series have correlated residuals. One approach to address this problem is to condition the autocorrelation structure by temporal smoothing. Smoothing splines with the degree of smoothing selected by generalized cross-validation (GCV-spline) provide a method to find an optimal smoother for an fMRI time series. The purpose of this study was to determine if GCV-spline of fMRI time series yields unbiased variance estimates of linear regression model parameters. GCV-spline was evaluated with a real fMRI data set and bias of the variance estimator was computed for simulated time series with autocorrelation structures derived from fMRI data. This study only considered fMRI experimental designs of boxcar type. The results from the real data suggest that GCV-spline determines appropriate amounts of smoothing. The simulations show that the variance estimates are, on average, unbiased. The unbiased variance estimates come at some cost to signal detection efficiency. This study demonstrates that GCV-spline is an appropriate method for smoothing fMRI time series.

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PubMed2002

Characterizing instantaneous phase relationships in whole-brain fMRI activation data.

Typically, fMRI data is processed in the time domain with linear methods such as regression and correlation analysis. We propose that the theory of phase synchronization may be used to more completely understand the dynamics of interacting systems, and can be applied to fMRI data as a novel method of detecting activation. Generalized synchronization is a phenomenon that occurs when there is a nonlinear functional relationship present between two or more coupled, oscillatory systems, whereas phase synchronization is defined as the locking of the phases while the amplitudes may vary. In this study, we developed an application of phase synchronization analysis that is appropriate for fMRI data, in which the phase locking condition is investigated between a voxel time series and the reference function of the task performed. A synchronization index is calculated to quantify the level of phase locking, and a nonparametric permutation test is used to determine the statistical significance of the results. We performed the phase synchronization analysis on the data from five volunteers for an event-related finger-tapping task. Functional maps were created that provide information on the interrelations between the instantaneous phases of the reference function and the voxel time series in a whole-brain fMRI activation data set. We conclude that this method of analysis is useful for revealing additional information on the complex nature of the fMRI time series.

Adult↗

PubMed2002

Independent component analysis applied to diffusion tensor MRI.

The accuracy of the outcome in a diffusion tensor imaging (DTI) experiment depends on the acquisition scheme as well as the postprocessing methods used. In the present study, the DTI results acquired after applying different combinations of diffusion-weighted (DW) gradient orientations were initially compared. Then, spatially independent component analysis (ICA) was applied to the T(2) and DW images. In all cases a single component was detected that was similar to the map of the trace of the diffusion tensor, but contained a reduced amount of noise. Furthermore, when no correction for eddy current artifacts was used in the image acquisition scheme, the effects of eddy currents were separated by ICA into independent components. After these components were removed, conventional estimation of the diffusion tensor was performed on the modified data. No artifact was contained in the final rotationally invariant scalar quantities that describe the intrinsic diffusion properties. Additionally, independent components that mapped major white matter fiber tracts in the human brain were identified. Finally, the noise included in the original T(2) and DW images was also separated by ICA into independent components. These components were subsequently removed and a reduction of noise in the final DTI results was achieved.

Adult↗

PubMed2002

Hierarchical clustering to measure connectivity in fMRI resting-state data.

Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band.

Adult↗

PubMed2002

Diffusion tensor MRI in temporal lobe epilepsy.

The purpose of this study was to investigate the diffusion characteristics of white matter in patients with focal temporal lobe epilepsy (TLE). Diffusion tensor imaging (DTI) was applied to patients and normal controls. Rotationally invariant mean diffusivity and diffusion anisotropy maps were calculated for all subjects. Comparisons between the two groups were performed for several white matter structures. Mean diffusivity and diffusion anisotropy of each selected structure were tested for correlations with age at onset and duration of epilepsy. Significantly lower diffusion anisotropy, and higher diffusivity in directions perpendicular to the axons, was detected in several white matter structures of the patients when compared to the controls. These structures were not located in the temporal lobes. No significant difference in mean diffusivity was detected between the selected structures from the two groups. Diffusion anisotropy was significantly correlated with age at onset of epilepsy in the posterior corpus callosum. Duration of epilepsy was not significantly correlated with the diffusion indices from any of the selected structures. The results of this study suggest that diffusion anisotropy may reveal abnormalities in patients with focal TLE. In addition, these abnormal changes are not necessarily restricted to the temporal lobes but might extend in other brain regions as well. Furthermore, the age at onset of epilepsy may be an important factor in determining the extent of the effect of epilepsy on white matter.

Adult↗

PubMed2002

Diffusion tensor MR imaging in diffuse axonal injury.

BACKGROUND AND PURPOSE: Disruption of the cytoskeletal network and axonal membranes characterizes diffuse axonal injury (DAI) in the first few hours after traumatic brain injury. Histologic abnormalities seen in DAI hypothetically decrease the diffusion along axons and increase the diffusion in directions perpendicular to them. DAI therefore is hypothetically associated in the short term with decreased diffusion anisotropy. We tested this hypothesis by measuring the diffusion characteristics of traumatized brain tissue with use of diffusion tensor MR imaging. METHODS: Five patients with mild traumatic brain injuries and 10 control subjects were studied with CT, conventional MR imaging, and diffusion tensor imaging. All patients were examined within 24 hours of injury. In each participant, diffusion tensor indices from homologous normal-appearing white matter regions of both hemispheres were compared. These indices were also compared between homologous regions of each patient and the control group. In two patients, diffusion tensor images from the immediate post-trauma period were compared with those at 1 month follow-up. RESULTS: Patients displayed significant reduction of diffusion anisotropy in several regions compared with the homologous ones in the contralateral hemisphere. Such differences were not observed in the control subjects. Significant reduction of diffusion anisotropy was also detected when diffusion tensor results from the patients were compared with those of the controls. This reduction was often less evident 1 month after injury. CONCLUSION: White matter regions with reduced anisotropy are detected in the first 24 hours after traumatic brain injury. Therefore, diffusion tensor imaging may be a powerful technique for in vivo detection of DAI.

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