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David A Rottenberg

Publications and source records attributed to David A Rottenberg.

12 recordsLinked to original sources
PubMed2006

Automatic segmentation of left and right cerebral hemispheres from MRI brain volumes using the graph cuts algorithm.

An automated algorithm has been developed to segment stripped (non-brain tissue excluded) T1-weighted MRI brain volumes into left and right cerebral hemispheres and cerebellum+brainstem. The algorithm, which uses the Graph Cuts technique, performs a fully automated segmentation in approximately 30 s following pre-processing. It is robust and accurate and has been tested on datasets from two scanners using different field strengths and pulse sequences. We describe the Graph Cuts algorithm and compare the results of Graph Cuts segmentations against "gold standard" manual segmentations and segmentations produced by three popular software packages used by neuroimagers: BrainVisa, CLASP, and SurfRelax.

Adult↗
PubMed2006

Mapping cerebral blood flow during speech production in hereditary ataxia.

Dysarthria is a significant feature of the dominantly inherited spinocerebellar ataxias (SCA), but little is known about the patterns of brain activity associated with this disorder of motor speech control. Positron emission tomography (PET) was used to study regional cerebral blood flow during speech and rest in a group of 24 subjects with hereditary ataxia with mild-to-moderate dysarthria. These data were compared to the results obtained from a group of 13 age-matched, normal speakers. In the ataxic subjects, speech rates during scanning were significantly slowed compared to normal speakers. Significant reductions in mean regional blood flow were found in the cerebellum but not in supratentorial regions in the ataxic subjects. Multiple linear regression was used to model speech rate from regional blood flow. Four regions were identified as having significant relationships with speech rate in the model: the left inferior frontal and transverse temporal regions, and the right inferior cerebellar region and caudate nucleus. The relationship between flow and rate was positive in the inferior frontal and cerebellar regions and negative in the caudate and the transverse temporal region. The ataxic model represents an elaboration of the relationship previously reported for normal speakers, likely reflecting both the effects of, and compensation for, cerebellar degeneration in motor speech control. Although the mean regional blood flow values presented a pattern of functional organization for motor speech control at odds with lesion data, the performance-based model was in agreement with clinical experience. Incorporating performance data in functional image analysis may be more revealing of system characteristics than simply examining mean blood flow values.

Adult↗
PubMed2005

Impact of acquisition protocols and processing streams on tissue segmentation of T1 weighted MR images.

The segmentation of T1-weighted images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) is a fundamental processing step in neuroimaging, the results of which affect many other structural imaging analyses. Variability in the segmentation process can decrease the power of a study to detect anatomical differences, and minimizing such variability can lead to more robust results. This paper outlines a straightforward strategy that can be used (1) to select more optimal data acquisition and processing protocols and (2) to quantify the impact of such optimization. Using this approach with multiple scans of a single subject, we found that the choice of a segmentation algorithm had the largest impact on variability, while the choice of a pulse sequence had the second largest impact. The data indicate that the classification of GM is the most variable, and that the optimal protocol may differ across tissue types. Therefore, the intended use of segmentation data should play a role in optimization. Examples are provided to demonstrate that the minimization of variability is not sufficient for optimization; the overall accuracy of the approach must also be considered. Simple volumetric computations are included to illustrate the potential gain of optimization; these results show that volume estimates from optimal pathways were on average three times less variable than estimates from suboptimal pathways. Therefore, the simple strategy illustrated here can be applied to many studies to optimize tissue segmentation, which should lead to a net increase in the power of structural neuroimaging studies.

Adult↗
PubMed2004

The effect of set on the resting state in functional imaging: a role for the striatum?

The effects of experimental set on brain activity during the resting state were identified in four positron emission tomography (PET) studies that employed different tasks, identical resting states, and the same subjects. A group of 11, right-handed, normal volunteers participated in four PET studies that shared the same block design in which four resting scans were alternated with four performance scans. The tasks were finger opposition, syllable repetition, sustained phonation, and repetitive lip closure. Each study used only one task and different studies were done on different days. Repeated measures analysis of variance revealed that resting regional cerebral blood flow was significantly affected by the task being studied. This influence varied with task and region. A series of analyses examining left/right regional pairs revealed significant effects of state (rest versus performance) and task and their interaction on most brain regions. The caudate was the only region in which state was not significant either as a main effect or in an interaction with task. Additional analyses revealed that resting and performance blood flow values from a single study were more highly correlated than were resting values across studies. Set may be associated with brain changes that fall into a class of recently described pre- and post-performance effects and may reflect the striatum's role in learning.

Adult↗
PubMed2004

A meta-algorithm for brain extraction in MRI.

Accurate identification of brain tissue and cerebrospinal fluid (CSF) in a whole-head MRI is a critical first step in many neuroimaging studies. Automating this procedure can eliminate intra- and interrater variance and greatly increase throughput for a labor-intensive step. Many available procedures perform differently across anatomy and under different acquisition protocols. We developed the Brain Extraction Meta-Algorithm (BEMA) to address these concerns. It executes many extraction algorithms and a registration procedure in parallel to combine the results in an intelligent fashion and obtain improved results over any of the individual algorithms. Using an atlas space, BEMA performs a voxelwise analysis of training data to determine the optimal Boolean combination of extraction algorithms to produce the most accurate result for a given voxel. This allows the provided extractors to be used differentially across anatomy, increasing both the accuracy and robustness of the procedure. We tested BEMA using modified forms of BrainSuite's Brain Surface Extractor (BSE), FSL's Brain Extraction Tool (BET), AFNI's 3dIntracranial, and FreeSurfer's MRI Watershed as well as FSL's FLIRT for the registration procedure. Training was performed on T1-weighted scans of 136 subjects from five separate data sets with different acquisition parameters on separate scanners. Testing was performed on 135 separate subjects from the same data sets. BEMA outperformed the individual algorithms, as well as interrater results from a subset of the scans, when compared for the mean Dice coefficient, a rating of the similarity of output masks to the manually defined gold standards.

Adult↗
PubMed2003

Predicting performance from functional imaging data: methods matter.

In the standard approach to functional imaging studies, brain-behavior relationships are studied by contrasting data obtained during different behavioral states. It is generally assumed that relative change yields meaningful data about relevant brain processes, and that the magnitude of the change reflects the extent of a region's involvement in the behavior being studied. The present study takes a different approach by asking the question, Can functional imaging data predict performance? Regional cerebral blood flow was measured using positron emission tomography in a group of 13 right-handed, normal volunteers during speech production and quiet baseline. A number of methodological assumptions were addressed by examining the relationships between different imaging measures derived from the same raw data and performance on the speech task. The results demonstrate that several common assumptions are not necessarily true. First, although measures based on "activated" scans alone had predictive value with respect to speech rate, measures based on contrasts between "baseline" and "activated" states did not. This was true regardless of whether the contrast was based on subtraction or covariance analyses. Second, while many regions demonstrated large signal increases during speech, speech rate could be predicted by a linear combination of data from two regions, neither of which had the highest "activation" peak, and one of which had a negative relationship with performance. The results demonstrate that contrasting experimental conditions do not necessarily isolate or enhance brain activity related to performance, and that the current assumptions about activation in functional imaging need to be reconsidered.

Adult↗
PubMed2002

Cluster analysis of activity-time series in motor learning.

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing.

Adult↗
PubMed2002

Production and dosimetry of [14O]water for PET activation studies.

[14O]water was produced by the 14N(p,n)14O reaction in quantities greater than 80mCi (EOB). The carbon-11 impurity in the final product was approximately 0.003 +/- 0.002% of 14O activity at EOB. A factor of 0.5 +/- 0.02 was obtained to correct the dose calibrator for the additional 2.313 MeV gamma-ray. The effective dose equivalent was calculated for 14O and 15O using MIRDOSE, and the 14O dose was found to be approximately 70% of that for 15O. For scanner performance based on noise equivalent count measurements, the peak activity concentration for 14O was 30% lower than that for 15O. At their peak activity concentrations the noise equivalent count rate for 14O was found to be about 13% less than that for 15O.

Blood Circulation↗
PubMed1986

Compulsive thalamic self-stimulation: a case with metabolic, electrophysiologic and behavioral correlates.

A 48-year-old woman with a stimulating electrode implanted in the right thalamic nucleus ventralis posterolateralis developed compulsive self-stimulation associated with erotic sensations and changes in autonomic and neurologic function. Stimulation effects were evaluated by neuropsychologic testing, endocrine studies, positron emission tomographic measurements of regional cerebral metabolic rate for glucose, EEG and evoked potentials. During stimulation, vital signs and pupillary diameter increased and a left hemiparesis and left hemisensory loss developed. Verbal functions deteriorated and visuospatial processing improved. Plasma growth hormone concentrations decreased, and adrenocorticotrophic hormone and cortisol levels rose. With stimulation, glucose metabolism increased in both thalami and both hemispheres, reversing baseline right-sided hypometabolism and right-left asymmetries. EEG and both somatosensory and brain-stem auditory evoked potentials remained unchanged during stimulation, while visual evoked potentials revealed evidence of anterior visual pathway dysfunction in the left eye. This case establishes the potential for addiction to deep brain stimulation and demonstrates that widespread behavioral and physiological changes, with concomitant alteration in the regional cerebral metabolic rate for glucose, may accompany unilateral thalamic stimulation.

Brain↗