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OBJECTIVE: The anterior cingulate cortex has been implicated in depression. Results are best interpreted by considering anatomic and cytoarchitectonic subdivisions. Evidence suggests depression is characterized by hypoactivity in the dorsal anterior cingulate, whereas hyperactivity in the rostral anterior cingulate is associated with good response to treatment. The authors tested the hypothesis that activity in the rostral anterior cingulate during the depressed state has prognostic value for the degree of eventual response to treatment. Whereas prior studies used hemodynamic imaging, this investigation used EEG. METHOD: The authors recorded 28-channel EEG data for 18 unmedicated patients with major depression and 18 matched comparison subjects. Clinical outcome was assessed after nortriptyline treatment. Of the 18 depressed patients, 16 were considered responders 4-6 months after initial assessment. A median split was used to classify response, and the pretreatment EEG data of patients showing better (N=9) and worse (N=9) responses were analyzed with low-resolution electromagnetic tomography, a new method to compute three-dimensional cortical current density for given EEG frequency bands according to a Talairach brain atlas. RESULTS: The patients with better responses showed hyperactivity (higher theta activity) in the rostral anterior cingulate (Brodmann's area 24/32). Follow-up analyses demonstrated the specificity of this finding, which was not confounded by age or pretreatment depression severity. CONCLUSIONS: These results, based on electrophysiological imaging, not only support hemodynamic findings implicating activation of the anterior cingulate as a predictor of response in depression, but they also suggest that differential activity in the rostral anterior cingulate is associated with gradations of response.
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Research on the neural substrates of emotion has found evidence for cortical asymmetries for aspects of emotion. A recent article by Nicholls et al. has used a new imaging method to interrogate facial movement in 3D to assess possible asymmetrical action during expressions of happiness and sadness. Greater left-sided movement, particularly during expressions of sadness was observed. These findings have implications for understanding hemispheric differences in emotion and lend support to the notion that aspects of emotion processing might be differentially localized in the two hemispheres.
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Major depression is a heterogeneous condition, and the search for neural correlates specific to clinically defined subtypes has been inconclusive. Theoretical considerations implicate frontostriatal, particularly subgenual prefrontal cortex (PFC), dysfunction in the pathophysiology of melancholia--a subtype of depression characterized by anhedonia--but no empirical evidence has been found yet for such a link. To test the hypothesis that melancholic, but not nonmelancholic depression, is associated with the subgenual PFC impairment, concurrent measurement of brain electrical (electroencephalogram, EEG) and metabolic (positron emission tomography, PET) activity were obtained in 38 unmedicated subjects with DSM-IV major depressive disorder (20 melancholic, 18 nonmelancholic subjects), and 18 comparison subjects. EEG data were analyzed with a tomographic source localization method that computed the cortical three-dimensional distribution of current density for standard frequency bands, allowing voxelwise correlations between the EEG and PET data. Voxel-based morphometry analyses of structural magnetic resonance imaging (MRI) data were performed to assess potential structural abnormalities in melancholia. Melancholia was associated with reduced activity in the subgenual PFC (Brodmann area 25), manifested by increased inhibitory delta activity (1.5-6.0 Hz) and decreased glucose metabolism, which themselves were inversely correlated. Following antidepressant treatment, depressed subjects with the largest reductions in depression severity showed the lowest post-treatment subgenual PFC delta activity. Analyses of structural MRI revealed no group differences in the subgenual PFC, but in melancholic subjects, a negative correlation between gray matter density and age emerged. Based on preclinical evidence, we suggest that subgenual PFC dysfunction in melancholia may be associated with blunted hedonic response and exaggerated stress responsiveness.
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Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper presents a unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The weighted spherical harmonic representation is used to parameterize, smooth out, and normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using the SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects.
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We present a new subcortical structure shape modeling framework using heat kernel smoothing constructed with the Laplace-Beltrami eigenfunctions. The cotan discretization is used to numerically obtain the eigenfunctions of the Laplace-Beltrami operator along the surface of subcortical structures of the brain. The eigenfunctions are then used to construct the heat kernel and used in smoothing out measurements noise along the surface. The proposed framework is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shape. We detected a significant age effect on hippocampus in accordance with the previous studies. In addition, we also detected a significant gender effect on amygdala. Since we did not find any such differences in the traditional volumetric methods, our results demonstrate the benefit of the current framework over traditional volumetric methods.
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This experiment was designed to test whether reading disabled boys differ from matched controls on behavioral measures of interhemispheric transfer time (IHTT). Specifically, we proposed that language-disordered reading disabled children who had deficits in naming would show either faster or slower IHTTs compared with controls. From an initial group of 118 right-handed males, we selected a group of 25 disabled and 25 normal readers, matched on age. All subjects had to obtain a full scale IQ of 90 or above, a PIQ score of 85 or above, and a scaled score of 7 or above on the Block Design Subtest of the WISC-R. After meeting additional criteria for group assignment, manual reaction time (RT) measures of IHTT were obtained in response to simple visual and tactile stimuli during two laboratory testing sessions. Half the trials were conducted with the hands in an uncrossed orientation and half with the hands crossed in order to examine the effects of spatial compatibility on estimates of IHTT. The results revealed no overall group differences in IHTT for any of the conditions. However, correlations between IHTT measures and indices of cognitive performance indicated that faster IHTTs were significantly correlated with poorer performance on measures of reading and language function in the dyslexic group. These data are discussed within the context of a model of interhemispheric transfer deficits in disabled readers.
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Social cognition, including complex social judgments and attitudes, is shaped by individual learning experiences, where affect often plays a critical role. Aversive classical conditioning-a form of associative learning involving a relationship between a neutral event (conditioned stimulus, CS) and an aversive event (unconditioned stimulus, US)-represents a well-controlled paradigm to study how the acquisition of socially relevant knowledge influences behavior and the brain. Unraveling the temporal unfolding of brain mechanisms involved appears critical for an initial understanding about how social cognition operates. Here, 128-channel ERPs were recorded in 50 subjects during the acquisition phase of a differential aversive classical conditioning paradigm. The CS+ (two fearful faces) were paired 50% of the time with an aversive noise (CS upward arrow + /Paired), whereas in the remaining 50% they were not (CS upward arrow + /Unpaired); the CS- (two different fearful faces) were never paired with the noise. Scalp ERP analyses revealed differences between CS upward arrow + /Unpaired and CS- as early as approximately 120 ms post-stimulus. Tomographic source localization analyses revealed early activation modulated by the CS+ in the ventral visual pathway (e.g. fusiform gyrus, approximately 120 ms), right middle frontal gyrus (approximately 176 ms), and precuneus (approximately 240 ms). At approximately 120 ms, the CS- elicited increased activation in the left insula and left middle frontal gyrus. These findings not only confirm a critical role of prefrontal, insular, and precuneus regions in aversive conditioning, but they also suggest that biologically and socially salient information modulates activation at early stages of the information processing flow, and thus furnish initial insight about how affect and social judgments operate.
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We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.
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We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination of basis functions. The basic properties of the representation are investigated in connection with a self-adjoint partial differential equation and the traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, a new iterative residual fitting (IRF) algorithm is developed. Its computational and numerical implementation issues are discussed in detail. The computer codes are also available at http://www.stat.wisc.edu/-mchung/softwares/weighted.SPHARM/weighted-SPHARM.html. As an illustration, the WFS is applied i n quantifying the amount ofgray matter in a group of high functioning autistic subjects. Within the WFS framework, cortical thickness and gray matter density are computed and compared.
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