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D Cordes

Publications and source records attributed to D Cordes.

At least 19 recordsLinked to original sources
PubMed2002

Test-retest precision of functional magnetic resonance imaging processed with independent component analysis.

This study was designed to compare the test-retest precision of functional magnetic resonance imaging (fMRI) data processed with independent component analysis (ICA) and the same data analyzed with a conventional model-dependent method (Student's- t mapping). Volunteers underwent two or three iterations of visual and auditory stimuli, while data were collected for fMRI scans. The scan data were separately processed with ICA and with Student's- t mapping (STM). As a measure of test-retest precision, concurrence ratios were calculated for each subject and each task as the number of voxels that were activated by two iterations of a task divided by the average number of voxels activated in each repetition. In 28 test-retest comparisons, the average concurrence ratio was 0.69+/-0.10 for ICA and 0.65+/-0.13 for the conventional method, a statistically insignificant difference. In fMR image data of block stimulus paradigms, ICA had similar test-retest precision to a conventional model-dependent method.

Acoustic Stimulation↗
PubMed2001

Effect of focal and nonfocal cerebral lesions on functional connectivity studied with MR imaging.

BACKGROUND AND PURPOSE: Functional connectivity MR (fcMR) imaging is used to map regions of brain with synchronous, regional, slow fluctuations in cerebral blood flow. We tested the hypothesis that focal cerebral lesions do not eradicate expected functional connectivity. METHODS: Functional MR (fMR) and fcMR maps were acquired for 12 patients with focal cerebral tumors, cysts, arteriovenous malformations, or in one case, agenesis of the corpus callosum. Task activation secondary to text listening, finger tapping, and word generation was mapped by use of fMR imaging. Functional connectivity was measured by selecting "seed" voxels in brain regions showing activation (based on the fMR data) and cross correlating with every other voxel (based on data acquired while the subject performed no task). Concurrence of the fMR and fcMR maps was measured by comparing the location and number of voxels selected by both methods. RESULTS: Technically adequate fMR and fcMR maps were obtained for all patients. In patients with focal lesions, the fMR and fcMR maps correlated closely. The fcMR map generated for the patient with agenesis of the corpus callosum failed to reveal functional connectivity between blood flow in the left and right sensorimotor cortices and in the frontal lobe language regions. Nonetheless, synchrony between blood flow in the auditory cortices was preserved. On average, there was 40% concurrence between all fMR and fcMR maps. CONCLUSION: Patterns of functional connectivity remain intact in patients with focal cerebral lesions. Disruption of major neuronal networks, such as agenesis of the corpus callosum, may diminish the normal functional connectivity patterns. Therefore, functional connectivity in such patients cannot be fully demonstrated with fcMR imaging.

Agenesis of Corpus Callosum↗
PubMed2001

Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.

BACKGROUND AND PURPOSE: In subjects performing no specific cognitive task ("resting state"), time courses of voxels within functionally connected regions of the brain have high cross-correlation coefficients ("functional connectivity"). The purpose of this study was to measure the contributions of low frequencies and physiological noise to cross-correlation maps. METHODS: In four healthy volunteers, task-activation functional MR imaging and resting-state data were acquired. We obtained four contiguous slice locations in the "resting state" with a high sampling rate. Regions of interest consisting of four contiguous voxels were selected. The correlation coefficient for the averaged time course and every other voxel in the four slices was calculated and separated into its component frequency contributions. We calculated the relative amounts of the spectrum that were in the low-frequency (0 to 0.1 Hz), the respiratory-frequency (0.1 to 0.5 Hz), and cardiac-frequency range (0.6 to 1.2 Hz). RESULTS: For each volunteer, resting-state maps that resembled task-activation maps were obtained. For the auditory and visual cortices, the correlation coefficient depended almost exclusively on low frequencies (<0.1 Hz). For all cortical regions studied, low-frequency fluctuations contributed more than 90% of the correlation coefficient. Physiological (respiratory and cardiac) noise sources contributed less than 10% to any functional connectivity MR imaging map. In blood vessels and cerebrospinal fluid, physiological noise contributed more to the correlation coefficient. CONCLUSION: Functional connectivity in the auditory, visual, and sensorimotor cortices is characterized predominantly by frequencies slower than those in the cardiac and respiratory cycles. In functionally connected regions, these low frequencies are characterized by a high degree of temporal coherence.

Adult↗
PubMed2000

Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets.

A new approach in studying interregional functional connectivity using functional magnetic resonance imaging (fMRI) is presented. Functional connectivity may be detected by means of cross correlating time course data from functionally related brain regions. These data exhibit high temporal coherence of low frequency fluctuations due to synchronized blood flow changes. In the past, this fMRI technique for studying functional connectivity has been applied to subjects that performed no prescribed task ("resting" state). This paper presents the results of applying the same method to task-related activation datasets. Functional connectivity analysis is first performed in areas not involved with the task. Then a method is devised to remove the effects of activation from the data using independent component analysis (ICA) and functional connectivity analysis is repeated. Functional connectivity, which is demonstrated in the "resting brain," is not affected by tasks which activate unrelated brain regions. In addition, ICA effectively removes activation from the data and may allow us to study functional connectivity even in the activated regions.

Adult↗
PubMed2000

Compensation of susceptibility-induced signal loss in echo-planar imaging for functional applications.

Functional magnetic resonance imaging favors the use of multi-slice gradient-recalled echo-planar imaging due to its short image acquisition times, whole brain coverage and sensitivity to BOLD contrast. However, despite its advantages, gradient-recalled echo-planar imaging also is sensitive to static magnetic field gradients arising primarily from air-tissue interfaces. This can lead to image artifacts such as voxel shifts and complete signal loss. A method to recover signal loss by adjusting the refocusing gradient amplitude in the slice-select direction, preferably axially, is proposed. This method is implemented as an automated computer algorithm that partitions echo-planar images into regions of recoverable signal intensities using a histogram analysis and determines each region's proper refocusing gradient amplitude. As an example, different refocusing gradient amplitudes are interleaved in a fMRI acquisition to maximize the signal to noise ratio and obtain functional activation in normal and dropout regions. The effectiveness of this method is demonstrated by recovering signal voids in the orbitofrontal cortex, parahippocampal/amygdala region, and inferior visual association cortex near the cerebellum.

Algorithms↗
PubMed2000

Functional MR imaging activation after finger tapping has a shorter duration in the basal ganglia than in the sensorimotor cortex.

BACKGROUND AND PURPOSE: Repetitive motor tasks that produce sustained neuronal activity in the sensorimotor cortex produce transient neuronal activity in subcortical regions. We tested the hypothesis that a reference function modeling a transient hemodynamic response would more reliably detect activation in the basal ganglia than would a conventional reference function, which models a sustained hemodynamic response. METHODS: Functional MR imaging data were acquired in eight subjects performing an alternating-hand finger-tapping task. Postprocessing was performed by cross-correlation to two types of reference functions: one that models a sustained hemodynamic response to finger tapping and one that models an initial transient hemodynamic response. Activation in the sensorimotor cortex, supplementary motor area, cerebellum, thalamus, and corpus striatum was tabulated for each reference function. RESULTS: With the conventional boxcar reference function, activation was detected in the sensorimotor cortex, supplementary motor area, and cerebellum, but intermittently in the corpus striatum in all subjects. With the reference function for a transient response, activation in the corpus striatum was not detected in all subjects. CONCLUSION: In the corpus striatum, activation is detected more frequently with a reference function that models a transient response. Activated cortical and subcortical regions can be mapped with an alternating-hand finger-tapping paradigm and a combination of reference functions.

Adult↗
PubMed2000

Functional connectivity in the thalamus and hippocampus studied with functional MR imaging.

BACKGROUND AND PURPOSE: With functional connectivity functional MR imaging, co-variance in signal intensity has been shown in functionally related regions of brain in participants instructed to perform no cognitive task. These changes are thought to represent synchronous fluctuations in blood flow, which imply neuronal connections between the regions. The purpose of this study was to map functional connectivity in subcortical nuclei with functional connectivity functional MR imaging. METHODS: Imaging data were acquired with an echo-planar sequence from six volunteers who performed no specific cognitive task. For functional connectivity functional MR imaging, a "seed" voxel or group of voxels was selected from the resting data set in the thalamus or in the hippocampus. Control voxels in gray matter presumed not to be eloquent cortex were also chosen. The correlation coefficient of the seed voxels and the control voxels with every other voxel in the resting data set was calculated. The voxels with correlation coefficients greater than or equal to 0.5 were mapped onto anatomic images for the functional connectivity functional MR images. The anatomic location of these voxels was determined by conventional parcellation methods. RESULTS: For each participant, functional connectivity functional MR imaging maps based on four seed voxels in the thalamus or hippocampus showed clusters of voxels in the ipsilateral and contralateral thalamus or hippocampus. For control voxels, few voxels in the hippocampus or thalamus showed significant correlation. Significantly more pixels in the ipsilateral hippocampus correlated with the seed voxel than in the contralateral hippocampus. The differences between numbers of functionally connected voxels in ipsilateral thalamus and those in contralateral thalamus were not significant. CONCLUSIONS: The thalamus and hippocampus show functional connectivity, presumably representing synchronous changes in blood flow.

Adult↗
PubMed2000

Whole-brain functional MR imaging activation from a finger-tapping task examined with independent component analysis.

BACKGROUND AND PURPOSE: Independent component analysis (ICA), unlike other methods for processing functional MR (fMR) imaging data, requires no a priori assumptions about the hemodynamic response to the task. The purpose of this study was to analyze the temporal characteristics and the spatial mapping of the independent components identified by ICA when the subject performs a finger-tapping task. METHODS: Ten healthy subjects performed variations of the finger-tapping task conventionally used to map the sensorimotor cortex. The scan data were processed with ICA, and the temporal configuration of the components and their spatial localizations were studied. The locations with activation were tabulated and compared with locations known to be involved in the organization of motor functions in the brain. RESULTS: Components were identified that correlated to varying degrees with the conventional boxcar reference function. One or more of these components mapped to the sensorimotor cortex, supplementary motor area (SMA), putamen, and thalamus. By means of ICA components, sensorimotor cortex, supplementary motor area, and superior cerebellar activation were identified bilaterally in 100% of the subjects; thalamus activation was contralateral to the active hand in 80%; and putamen activation was contralateral to the active hand in 60%. CONCLUSION: ICA processing of multislice fMR imaging data acquired during finger tapping identifies the sensorimotor cortex, SMA, cerebellar, putamen, and thalamic activation. ICA appears to be a method that provides information on both the temporal and spatial characteristics of activation. Multiple task-related components can be identified by ICA, and specific activation maps can be derived from each separate component.

Brain↗
PubMed2000

Mapping functionally related regions of brain with functional connectivity MR imaging.

BACKGROUND AND PURPOSE: In subjects who are performing no prescribed cognitive task, functional connectivity mapped with MR imaging (fcMRI) shows regions with synchronous fluctuations of cerebral blood flow. When specific tasks are performed, functional MR imaging (fMRI) can map locations in which regional cerebral blood flow increases synchronously with the performance of the task. We tested the hypothesis that fcMRI maps, based on the synchrony of low-frequency blood flow fluctuations, identify brain regions that show activation on fMRI maps of sensorimotor, visual, language, and auditory tasks. METHODS: In four volunteers, task-activation fMRI and functional connectivity (resting-state) fcMRI data were acquired. A small region of interest (in an area that showed maximal task activation) was chosen, and the correlation coefficient of the corresponding resting-state signal with the signal of all other voxels in the resting data set was calculated. The correlation coefficient was decomposed into frequency components and its distribution determined for each fcMRI map. The fcMRI maps were compared with the fMRI maps. RESULTS: For each task, fcMRI maps based on one to four seed voxel(s) produced clusters of voxels in regions of eloquent cortex. For each fMRI map a closely corresponding fcMRI map was obtained. The frequencies that predominated in the cross-correlation coefficients for the functionally related regions were below 0.1 Hz. CONCLUSION: Functionally related brain regions can be identified by means of their synchronous slow fluctuations in signal intensity. Such blood flow synchrony can be detected in sensorimotor areas, expressive and receptive language regions, and the visual cortex by fcMRI. Regions identified by the slow synchronous fluctuations are similar to those activated by motor, language, or visual tasks.

Adult↗
PubMed1998

Basic concepts of functional arteriovenous MR imaging malformations.

This article reviews the technical features of functional MR imaging. Examples are presented demonstrating how MR imaging may be used to identify primary cortical regions adjacent to AVMs. Preliminary results suggest that cortical functions may undergo translocation when the AVM involves eloquent cortex. This finding underscores the importance of cortical mapping prior to surgical excision.

Brain Mapping↗
PubMed1998

Basic concepts of functional magnetic resonance imaging and arteriovenous malformations

Cortical mapping is an important adjunct to the workup of patients with arteriovenous malformation (AVMs) near eloquent cortical regions. Task activation imaging can be performed that clearly identifies primary cortical regions. Although current methods require considerable postprocessing, advances in hardware and software will likely make functional MR imaging a routing examination before surgical resection of AVMs in the near future.

Journal Article↗
PubMed1988

Susceptibility of Microsporum and Trichophyton species to suicide inhibitors of polyamine biosynthesis.

DFMO (difluoromethylornithine) and DFMA (difluoromethylarginine), irreversible suicide inhibitors of ornithine and arginine decarboxylase activities (ODC and ADC) respectively, inhibit the growth of six species of Microsporum and six species of Trichophyton. Trichophyton species in general, are more sensitive than Microsporum species. DFMA inhibits growth as effectively as DFMO but at a 10-fold lower concentration. Inhibition is specific, as a number of substrates and end products of ODC and ADC activities antagonize DFMA and DFMO (i.e. ornithine greater than putrescine = spermidine greater than agmatine). The methylester analogue of ornithine, MFMOme (monofluormethyldehydroornithine methylester) is at least a 25-fold more effective inhibitor than DFMO; the inhibition is specific as it is reversed by ornithine.

Antifungal Agents↗
PubMedDate not supplied

Spontaneous pericardial hematoma in an infant.

The finding of a pericardial hematoma is rare in the pediatric population. Its occurrence in an otherwise healthy 3-month-old infant is unprecedented in the literature. The hematoma was initially identified by echocardiography. Computerized tomography and magnetic resonance imaging did not contribute to the identification of the mass. An exploratory thoracotomy was necessary to rule out a neoplastic process. The final diagnosis of hemorrhagic pericarditis was made.

Acute Disease↗
PubMedDate not supplied

BOLD-fMRI of PTZ-induced seizures in rats.

PURPOSE: To develop a non-invasive method for exploring seizure initiation and propagation in the brain of intact experimental animals. METHODS: We have developed and applied a model-independent statistical method--Hierarchical Cluster Analysis (HCA)--for analyzing BOLD-fMRI data following administration of pentylenetetrazol (PTZ) to intact rats. HCA clusters voxels into groups that share similar time courses and magnitudes of signal change, without any assumptions about when and/or where the seizure begins. RESULTS: Epileptiform spiking activity was monitored by EEG (outside the magnet) following intravenous PTZ (IV-PTZ; n=4) or intraperitoneal PTZ administration (IP-PTZ; n=5). Onset of cortical spiking first occurred at 29+/-16 s (IV-PTZ) and 147+/-29 s (IP-PTZ) following drug delivery. HCA of fMRI data following IV-PTZ (n=4) demonstrated a single dominant cluster, involving the majority of the brain and first activating at 27+/-23s. In contrast, IP-PTZ produced multiple, relatively small, clusters with heterogeneous time courses that varied markedly across animals (n=5); activation of the first cluster (involving cortex) occurred at 130+/-59 s. With both routes of PTZ administration, the timing of the fMRI signal increase correlated with onset of EEG spiking. CONCLUSIONS: These experiments demonstrate that fMRI activity associated with seizure activity can be analyzed with a model-independent statistical method. HCA indicated that seizure initiation in the IV- and IP-PTZ models involves multiple regions of sensitivity that vary with route of drug administration and that show significant variability across animal subjects. Even given this heterogeneity, fMRI shows clear differences that are not apparent with typical EEG monitoring procedures, in the activation patterns between IV and IP-PTZ models. These results suggest that fMRI can be used to assess different models and patterns of seizure activation.

Animals↗