Biomedical subjects

G D Pearlson

Publications and source records attributed to G D Pearlson.

At least 19 recordsLinked to original sources

PubMed2006

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.

Acoustic Stimulation↗

PubMed2005

Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data.

Event-related potential (ERP) studies of the brain's response to infrequent, target (oddball) stimuli elicit a sequence of physiological events, the most prominent and well studied being a complex, the P300 (or P3) peaking approximately 300 ms post-stimulus for simple stimuli and slightly later for more complex stimuli. Localization of the neural generators of the human oddball response remains challenging due to the lack of a single imaging technique with good spatial and temporal resolution. Here, we use independent component analyses to fuse ERP and fMRI modalities in order to examine the dynamics of the auditory oddball response with high spatiotemporal resolution across the entire brain. Initial activations in auditory and motor planning regions are followed by auditory association cortex and motor execution regions. The P3 response is associated with brainstem, temporal lobe, and medial frontal activity and finally a late temporal lobe "evaluative" response. We show that fusing imaging modalities with different advantages can provide new information about the brain.

Adult↗

PubMed2005

Using virtual reality to study alcohol intoxication effects on the neural correlates of simulated driving.

The use of virtual reality in the form of simulated tasks can provide a realistic environment in which to study complex naturalistic behaviors. Many of the behavioral effects of alcohol intoxication are well known, but there is relatively little imaging evidence examining how alcohol exposure might transiently modulate brain function, especially in the context of task performance. In this review, we provide a brief synopsis of previous work using functional magnetic resonance imaging (fMRI) to study the neural correlates of alcohol intoxication. We describe in detail two studies from our published work, the first involving a visual perception paradigm, and the second involving virtual reality through a naturalistic behavior; simulated driving. Participants received single-blind individualized doses of beverage alcohol designed to produce blood alcohol content (BAC) of 0.04 and 0.08 or placebo. Subjects were fMRI scanned after training to asymptote performance. In both studies we found specific circuits that were differentially modulated by alcohol, we revealed both global and local effects of alcohol, and we examined relationships between behavior, brain function, and alcohol blood levels.

Adolescent↗

PubMed2004

fMRI analysis with the general linear model: removal of latency-induced amplitude bias by incorporation of hemodynamic derivative terms.

Functional magnetic resonance imaging (fMRI) data are often analyzed using the general linear model employing a hypothesized neural model convolved with a hemodynamic response function. Mismatches between this hemodynamic model and the data can be induced by spatially varying delays or slice-timing differences. It is common practice to desensitize the analysis to such delays by incorporation of the hemodynamic model plus its temporal derivative. The rationale often used is that additional variance will be captured and regressed out from the data. Though this is true, it ignores the potential for amplitude bias induced by small model mismatches due to, for example, variable hemodynamic delays and is not helpful for "random effects" analyses which typically do not account for the first level variance at all. Amplitude bias is due to the use of only the nonderivative portion of the model in the final test for significant amplitudes. We propose instead testing an amplitude value that is a function of both the nonderivative and the derivative terms of the model. Using simulations, we show that the proposed amplitude test does not suffer from delay-induced bias and that a model incorporating temporal derivatives is a more natural test for amplitude differences. The proposed test is applied in a random-effects analysis of 100 subjects. It reveals increased amplitudes in areas consistent with the task, with the largest increases in regions with greater hemodynamic delays.

Acoustic Stimulation↗

PubMed2003

Dynamic programming generation of boundaries of local coordinatized submanifolds in the neocortex: application to the planum temporale.

Dynamic programming is used to define boundaries of cortical submanifolds with focus on the planum temporale (PT) of the superior temporal gyrus (STG), which has been implicated in a variety of neuropsychiatric disorders. To this end, automated methods are used to generate the PT manifold from 10 high-resolution MRI subvolumes ROI masks encompassing the STG. A procedure to define the subvolume ROI masks from original MRI brain scans is developed. Bayesian segmentation is then used to segment the subvolumes into cerebrospinal fluid, gray matter (GM), and white matter (WM). 3D isocontouring using the intensity value at which there is equal probability of GM and WM is used to reconstruct the triangulated graph representing the STG cortical surface, enabling principal curvature at each point on the graph to be computed. Dynamic programming is used to delineate the PT manifold by tracking principal curves from the retro-insular end of the Heschl's gyrus (HG) to the STG, along the posterior STG up to the start of the ramus and back to the retro-insular end of the HG. A coordinate system is then defined on the PT manifold. The origin is defined by the retro-insular end of the HG and the y-axis passes through the point on the posterior STG where the ramus begins. Automated labeling of GM in the STG is robust with L(1) distances between Bayesian and manual segmentation in the range 0.001-0.12 (n = 20). PT reconstruction is also robust with 90% of the vertices of the reconstructed PT within about 1 voxel (n = 20) from semiautomated contours. Finally, the reliability index (based on interrater intraclass correlation) for the surface area derived from repeated reconstructions is 0.96 for the left PT and 0.94 for the right PT, thus demonstrating the robustness of dynamic programming in defining a coordinate system on the PT. It provides a method with potential significance in the study of neuropsychiatric disorders.

Algorithms↗

PubMed2003

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.

Adult↗

PubMed2002

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.

Brain↗

PubMed2001

Cerebral blood flow in obsessive-compulsive patients with major depression: effect of treatment with sertraline or desipramine on treatment responders and non-responders.

We examined the effects of sertraline and of desipramine on patients with OCD and comorbid major depressive episodes at study entry. Sixteen patients, 9 receiving sertraline and 7 desipramine, received HMPAO SPECT scans while free of medication and after 12 weeks of treatment. Patients on sertraline showed significantly reduced regional cerebral blood flow (rCBF) in the right prefrontal and temporal regions. Patients on desipramine showed more diffuse rCBF reductions in frontal and temporal regions, more so in the left side. In a second analysis, patients who had a symptom reduction on the Yale-Brown Obsessive Compulsive Scale (YBOCS), irrespective of the type of medication, were retrospectively classified as 'responders' to treatment. Eleven patients were 'responders' and 5 'non-responders'. Before being medicated, responders differed from non-responders through higher rCBF in prefrontal regions, mostly on the left, and higher rCBF in the cingulate and basal ganglia bilaterally. After 12 weeks of treatment, responders showed a diffuse reduction of rCBF in prefrontal regions while non-responders showed only a few scattered low-frequency responses. Thus, higher prefrontal and subcortical activity was associated with better response to drug treatment. In addition, clinical change, but not the administration of medication as such, was associated with a decrease of prefrontal rCBF.

Adult↗

PubMed2001

Regional cortical white matter reductions in velocardiofacial syndrome: a volumetric MRI analysis.

BACKGROUND: Velocardiofacial syndrome, caused by a microdeletion on chromosome 22q.11, is associated with craniofacial anomalies, cardiac defects, learning disabilities, and psychiatric disorders. To understand how the 22q.11 deletion affects brain development, this study examined gray and white matter volumes in major lobar brain regions of children with velocardiofacial syndrome relative to control subjects. METHODS: Subjects were ten children with velocardiofacial syndrome and ten age- and gender-matched unaffected children. Coronal images were acquired with a 3-D spoiled gradient echo series and partitioned into 124, 1.5-mm contiguous slices. A stereotaxic grid was used to subdivide brain tissue into cerebral lobes, which were segmented into gray, white, and CSF compartments using an algorithm based on intensity values and tissue boundaries. Nonparametric statistics were used to compare lobar volumes of gray and white matter. RESULTS: Analyses indicated that children with velocardiofacial syndrome had significantly smaller volumes in nonfrontal, but not frontal, lobar brain regions. Volume reductions affected nonfrontal white matter to a greater extent than nonfrontal gray matter. CONCLUSIONS: The presence of white matter reductions may be related to disturbances in myelination or axonal integrity in velocardiofacial syndrome. Further work is required to delineate the nature and extent of white matter anomalies, and to link them to variation in the neurocognitive and neuropsychiatric phenotype of velocardiofacial syndrome.

Adolescent↗

PubMed2001

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.

Algorithms↗

PubMed2001

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.

Algorithms↗

PubMed2001

Diffusion tensor imaging and axonal tracking in the human brainstem.

Diffusion tensor MRI was used to demonstrate in vivo anatomical mapping of brainstem axonal connections. It was possible to identify the corticospinal tract (CST), medial lemniscus, and the superior, medial, and inferior cerebellar peduncles. In addition, the cerebral peduncle could be subparcellated into component tracts, namely, the frontopontine tract, the CST, and the temporo-/parieto-/occipitopontine tract. Anatomical landmarks and tracking thresholds were established for each fiber and, using these standards, reproducibility of automated tracking as assessed by intra- and interrater reliability was found to be high (kappa > 0.82). Reconstructed fibers corresponded well to existing anatomical knowledge, validating the tracking. Information on the location of individual tracts was coregistered with quantitative MRI maps to automatically measure MRI parameters on a tract-by-tract basis. The results reveal that each tract has a unique spatial signature in terms of water relaxation and diffusion anisotropy.

Adult↗

PubMed2001

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.

Attention↗

PubMed2001

Neuroimaging studies in Rett syndrome.

Neuroimaging is a key instrument for determining structural and in vivo functional status of the brain, non-invasively. Multiple approaches can now determine aspects of anatomic and neurochemical changes in brain, and have been utilized effectively in Rett Syndrome patients to understand the biological basis of this neurodevelopmental disorder. Studies performed at our institute include volumetric analyses of MRI, magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), cerebral blood flow measurements with MRI, and positron emission tomography scans (PET). These studies have provided considerable insight into mechanisms underlying the clinical features of this disease. Volumetric analyses suggest that decreased brain volume in RS results from global reductions in both gray and white matter of the brain. A selective vulnerability of the frontal lobes is evidenced by the preferential reduction of blood flow, increased choline and reduced n-acetyl aspartate (NAA) by MRS, and increased glucose uptake in these same regions as shown by ((18)F)-fluorodeoxyglucose (FDG) PET scans. We hypothesize that the increased glucose uptake relates to increased glutamate cycling in synapses. The resulting neuroexcitotoxic injury to the developing brain contributes to the seizures, behavioral disturbance and respiratory irregularities commonly seen in phases 1 and 2 of this disorder.

Adolescent↗

PubMed2001

Determinants of Benton Facial Recognition Test performance in normal adults.

Clinical investigations have found that lesions of the right cerebral hemisphere can disrupt face perception. Much less is known about the determinants of facial discrimination in healthy adults, although age-related differences in many cognitive abilities have been shown to correlate with simple processing speed and variation in regional brain volumes. In this study, 174 healthy adults between the ages of 20 and 92 were asked to match pictures of unfamiliar faces. After their performance was regressed on age, sex, education, and perceptual comparison speed, adding terms for frontal lobe volume, nonfrontal volume, and ventricle-to-brain ratio (VBR) derived from magnetic resonance imaging improved the model and accounted for 35% of the variance in facial discrimination. VBR and processing speed alone accounted for nearly 34% of the variance. These findings suggest that both normal atrophic brain changes and decreases in processing speed contribute to individual differences in facial discrimination.

Adult↗

PubMed2001

The familial aggregation of psychotic symptoms in bipolar disorder pedigrees.

OBJECTIVE: Symptomatic overlap between affective disorders and schizophrenia has long been noted. More recently, family and linkage studies have provided some evidence for overlapping genetic susceptibility between bipolar disorder and schizophrenia. If shared genes are responsible for the psychotic manifestations of both disorders, these genes may result in clustering of psychotic symptoms in some bipolar disorder pedigrees. The authors tested this hypothesis in families ascertained for a genetic study of bipolar disorder. METHOD: Rates of psychotic symptoms-defined as hallucinations or delusions-during affective episodes were compared in families of 47 psychotic and 18 nonpsychotic probands with bipolar I disorder. The analysis included 202 first-degree relatives with major affective disorder. RESULTS: Significantly more families of psychotic probands than families of nonpsychotic probands (64% versus 28%) contained at least one relative who had affective disorder with psychotic symptoms. Significantly more affectively ill relatives of psychotic probands than of nonpsychotic probands (34% versus 11%) had psychotic symptoms. An analysis of clustering of psychotic subjects across all families revealed significant familial aggregation. Clustering of psychosis was also apparent when only bipolar I disorder was considered the affected phenotype. CONCLUSIONS: Psychotic bipolar disorder may delineate a subtype of value for genetic and biological investigations. Families with this subtype should be used to search for linkage in chromosomal regions 10p12-13, 13q32, 18p11.2, and 22q11-13, where susceptibility genes common to bipolar disorder and schizophrenia may reside. Putative schizophrenia-associated biological markers, such as abnormal evoked response, oculomotor, and neuroimaging measures, could similarly be explored in such families.

Adult↗

PubMed2000

Measurement of the planum temporale (PT) on magnetic resonance imaging scans: temporal PT alone and with parietal extension.

The planum temporale (PT) has been of interest because of (1) its consistent left greater than right asymmetry among right-handed and most left-handed normal individuals; and (2) its relation to language, another variable shown to be highly left-lateralized in normal subjects. Individuals with neurodevelopmental disorders have been reported to show abnormal PT asymmetry (either reversed or absent asymmetry). Several studies have been conducted measuring the PT on MRI scans, although the results do not always concur. We review some of these studies and discuss methodological differences between them. Additionally, we propose a method that has proved to be highly reliable for the measurement of both temporal PT and its parietal extension (PT+).

Adult↗

PubMed2000

Rate of caudate atrophy in presymptomatic and symptomatic stages of Huntington's disease.

Previous research by our group demonstrated a longitudinal change in caudate volume for symptomatic subjects with Huntington's disease (HD), and suggested that volume of the caudate may be a useful outcome measure for therapeutic studies in symptomatic patients. The current study was designed to determine whether longitudinal change in caudate atrophy could be documented in presymptomatic carriers of the HD gene mutation, and to compare rate of change in these subjects with rate of change in mildly and moderately affected symptomatic patients. We measured caudate volumes on serial magnetic resonance image scans from 30 patients at three stages of HD: 10 presymptomatic; 10 with mild symptoms, as indicated by scores on the Quantified Neurological Exam (QNE) < or =35; and 10 with moderate symptoms (QNE >45). The mean interscan interval was 36 months. When analyzed separately, both symptomatic groups and the presymptomatic group demonstrated a significant change in caudate volume over time. Amount of change over time did not differ significantly among the three groups. We conclude that change in caudate volume may be a useful outcome measure for assessing treatment effectiveness in both presymptomatic and symptomatic subjects.

Adult↗