Showing papers by "Richard J. Davidson published in 2004"

Placebo-induced changes in FMRI in the anticipation and experience of pain.

Abstract: The experience of pain arises from both physiological and psychological factors, including one's beliefs and expectations Thus, placebo treatments that have no intrinsic pharmacological effects may produce analgesia by altering expectations However, controversy exists regarding whether placebos alter sensory pain transmission, pain affect, or simply produce compliance with the suggestions of investigators In two functional magnetic resonance imaging (fMRI) experiments, we found that placebo analgesia was related to decreased brain activity in pain-sensitive brain regions, including the thalamus, insula, and anterior cingulate cortex, and was associated with increased activity during anticipation of pain in the prefrontal cortex, providing evidence that placebos alter the experience of pain

Long-term meditators self-induce high-amplitude gamma synchrony during mental practice

Abstract: ‡Practitioners understand ‘‘meditation,’’ or mental training, to be a process of familiarization with one’s own mental life leading to long-lasting changes in cognition and emotion. Little is known about this process and its impact on the brain. Here we find that long-term Buddhist practitioners self-induce sustained electroencephalographic high-amplitude gamma-band oscillations and phase-synchrony during meditation. These electroencephalogram patterns differ from those of controls, in particular over lateral frontoparietal electrodes. In addition, the ratio of gamma-band activity (25– 42 Hz) to slow oscillatory activity (4 –13 Hz) is initially higher in the resting baseline before meditation for the practitioners than the controls over medial frontoparietal electrodes. This difference increases sharply during meditation over most of the scalp electrodes and remains higher than the initial baseline in the postmeditation baseline. These data suggest that mental training involves temporal integrative mechanisms and may induce shortterm and long-term neural changes. electroencephalogram synchrony gamma activity meditation

Making a Life Worth Living Neural Correlates of Well-Being

Abstract: Despite the vast literature that has implicated asymmetric activation of the prefrontal cortex in approach-withdrawal motivation and emotion, no published reports have directly explored the neural correlates of well-being. Eighty-four right-handed adults (ages 57-60) completed self-report measures of eudaimonic well-being, hedonic well-being, and positive affect prior to resting electroencephalography. As hypothesized, greater left than right superior frontal activation was associated with higher levels of both forms of well-being. Hemisphere-specific analyses documented the importance of goal-directed approach tendencies beyond those captured by approach-related positive affect for eudaimonic but not for hedonic well-being. Appropriately engaging sources of appetitive motivation, characteristic of higher left than right baseline levels of prefrontal activation, may encourage the experience of well-being.

Well-being and affective style: neural substrates and biobehavioural correlates.

Abstract: One of the most salient features of emotion is the pronounced variability among individuals in their reactions to emotional incentives and in their dispositional mood. Collectively, these individual differences have been described as affective style. Recent research has begun to dissect the constituents of affective style. The search for these components is guided by the neural systems that instantiate emotion and emotion regulation. In this article, this body of research and theory is applied specifically to positive affect and well-being. The central substrates and peripheral biological correlates of well-being are described. A resilient affective style is associated with high levels of left prefrontal activation, effective modulation of activation in the amygdala and fast recovery in response to negative and stressful events. In peripheral biology, these central patterns are associated with lower levels of basal cortisol and with higher levels of antibody titres to influenza vaccine. The article concludes with a consideration of whether these patterns of central and peripheral biology can be modified by training and shifted toward a more salubrious direction.

The Role of the Central Nucleus of the Amygdala in Mediating Fear and Anxiety in the Primate.

Abstract: Numerous studies demonstrate that the rhesus monkey is an excellent species with which to investigate mechanisms underlying human emotion and psychopathology. To examine the role of the central nucleus of the amygdala (CeA) in mediating the behavioral and physiological responses associated with fear and anxiety, we used rhesus monkeys to assess the effects of excitotoxic lesions of the CeA. Behavioral and physiological responses of nine monkeys with bilateral CeA destruction (ranging from 46 to 98%) were compared with five animals with asymmetric lesions (42-86.5% destruction on the most affected side) and with 16 unoperated controls. Results suggest that similar to rodent species, the primate CeA plays a role in mediating fear- and anxiety-related behavioral and endocrine responses. Compared with controls and the asymmetric-lesion group, bilaterally lesioned monkeys displayed significantly less fear-related behavior when exposed to a snake and less freezing behavior when confronted by a human intruder. In addition, bilaterally lesioned monkeys had decreased levels of CSF corticotrophin-releasing factor (CRF), and both lesioned groups had decreased plasma ACTH concentrations. In contrast to these findings, patterns of asymmetric frontal brain electrical activity, as assessed by regional scalp EEG, did not significantly differ between control and lesioned monkeys. These findings suggest that in primates, the CeA is involved in mediating fear- and anxiety-related behavioral and pituitary-adrenal responses as well as in modulating brain CRF activity.

Functional but not structural subgenual prefrontal cortex abnormalities in melancholia

Abstract: 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.

Perceived Controllability Modulates the Neural Response to Pain

Abstract: The response to painful stimulation depends not only on peripheral nociceptive input but also on the cognitive and affective context in which pain occurs. One contextual variable that affects the neural and behavioral response to nociceptive stimulation is the degree to which pain is perceived to be controllable. Previous studies indicate that perceived controllability affects pain tolerance, learning and motivation, and the ability to cope with intractable pain, suggesting that it has profound effects on neural pain processing. To date, however, no neuroimaging studies have assessed these effects. We manipulated the subjects' belief that they had control over a nociceptive stimulus, while the stimulus itself was held constant. Using functional magnetic resonance imaging, we found that pain that was perceived to be controllable resulted in attenuated activation in the three neural areas most consistently linked with pain processing: the anterior cingulate, insular, and secondary somatosensory cortices. This suggests that activation at these sites is modulated by cognitive variables, such as perceived controllability, and that pain imaging studies may therefore overestimate the degree to which these responses are stimulus driven and generalizable across cognitive contexts.

Functional coupling of simultaneous electrical and metabolic activity in the human brain

Abstract: The relationships between brain electrical and metabolic activity are being uncovered currently in animal models using invasive methods; however, in the human brain this relationship remains not well understood. In particular, the relationship between noninvasive measurements of electrical activity and metabolism remains largely undefined. To understand better these relations, cerebral activity was measured simultaneously with electroencephalography (EEG) and positron emission tomography using [(18)f]-fluoro-2-deoxy-D-glucose (PET-FDG) in 12 normal human subjects during rest. Intracerebral distributions of current density were estimated, yielding tomographic maps for seven standard EEG frequency bands. The PET and EEG data were registered to the same space and voxel dimensions, and correlational maps were created on a voxel-by-voxel basis across all subjects. For each band, significant positive and negative correlations were found that are generally consistent with extant understanding of EEG band power function. With increasing EEG frequency, there was an increase in the number of positively correlated voxels, whereas the lower alpha band (8.5-10.0 Hz) was associated with the highest number of negative correlations. This work presents a method for comparing EEG signals with other more traditionally tomographic functional imaging data on a 3-D basis. This method will be useful in the future when it is applied to functional imaging methods with faster time resolution, such as short half-life PET blood flow tracers and functional magnetic resonance imaging.

Context-specific freezing and associated physiological reactivity as a dysregulated fear response.

Abstract: The putative association between fear-related behaviors and peripheral sympathetic and neuroendocrine reactivity has not been replicated consistently. This inconsistency was addressed in a reexamination of the characterization of children with extreme fearful reactions by focusing on the match between distress behaviors and the eliciting context. Eighty 24-month-old children were observed in 4 mildly threatening contexts, and the relations among different measures of fear-related behaviors, reactive and basal cortisol levels, and baseline cardiac measures of heart rate, respiratory sinus arrhythmia, and preejection period (PEP) were examined. The hypothesis that only behaviors under the less threatening context would be associated with higher cortisol and sympathetic cardiac activity was confirmed; only task-specific freezing behavior predicted higher reactive and basal cortisol levels and resting PEP measured 1 week later. Implications for the conceptualization of dysregulated fear behaviors in the classification of extremely fearful children are discussed.

Disambiguating the Components of Emotion Regulation.

Abstract: Affective neuroscience and cognitive science approaches are useful for understanding the components of emotion regulation; several examples from current research are provided. Individual differences in emotion regulation and a focus on the context of emotion experience and expression provide additional tools to study emotion regulation, and its development, from a biobehavioral perspective.

Unequally masked: Indexing differences in the perceptual salience of unseen facial expressions

Abstract: Two experiments investigated the degree to which different facial expressions, when backwardly masked by neutral faces, are blocked from different levels of perceptual access as indexed by explicit (self-reported) awareness, forced-identification performance, and stimulus sensitivity in a signal detection paradigm. Results indicate that a 16.67ms target-mask stimulus onset asynchrony (SOA) is insufficient to reliably block either the simple detection or the forced-identification of backwardly masked expressions. This finding holds even for participants who deny possessing any explicit awareness of the masked images whatsoever. Furthermore, unseen happy faces are less effectively masked by neutral expressions than are unseen angry or neutral faces, an observation that might also extend to other affective expressions (e.g., fear). These results expand upon previous findings (Esteves & Ohman, 1993) and provide new information about the multitude of factors that may be operating in research that involves backwardly masked facial expressions.

The privileged status of emotion in the brain.

Abstract: The recent report in PNAS by Ishai et al . (1) is part of a growing corpus of literature that establishes the privileged status of emotional stimuli for the brain. Stimuli that convey emotion command attention and enjoy enhanced processing in a distributed network of brain regions that represents different features of the stimulus and options for responding to such stimuli (2). There are two findings in the Ishai et al . article that are consistent with this framework: ( i ) subjects respond more quickly and more accurately to fear relative to neutral targets; and ( ii ) in all face-responsive regions of interest in the brain (see Fig. 1), fear faces were associated with relatively greater activation than neutral faces were during several phases of the experiment, including during initial encoding of the stimuli, in response to the first match of the target to the memoranda, and in response to the distracter stimuli. These findings are consistent with the notion that stimuli of affective import command extensive resources and are strongly and broadly represented in the brain. The third major observation reported by Ishai et al . is their featured finding, and it is somewhat counterintuitive. They find that in all face regions of interest repetition of fearful targets was associated with stronger suppression effects than repetition of neutral targets was. In other words, activation levels were found to decrease more with repetition of attended fear faces than attended neutral faces. Furthermore, neither fear nor neutral distracters were associated with repetition suppression. In this Commentary, we first discuss some empirical and methodological features of the experiment that is reported and then highlight some important implications of these data and raise questions for future research. Fig. 1. The distributed representation of visual emotional stimuli in the human brain. ( A ) The network of face-responsive regions examined …

Weighted Spherical Harmonic Representation and Its Application to Cortical Analysis

Abstract: We present a novel weighted spherical harmonic (SPHARM) representation of cortical surfaces and its application to a cortical thickness analysis in autism. The weighted-SPHARM is a hierarchical smoothing technique given as the solution to a parabolic partial differential equation. The weighted-SPHARM generalizes the classical-SPHARM with an additional parameter that modulates the high frequency content of data. We introduce a new algorithm called the iterative residual fitting (IRF) and address the problem of determining the optimal degree of the weighted-SPHARM. As an illustration, our unified framework has been applied in detecting the regions of abnormal behavior-structure correlation in a group of autistic subjects.

Subpixel Curvature Estimation of the Corpus Callosum via Splines and its Application to Autism

Abstract: Number: 796 Subpixel curvature estimation of the corpus callosum via splines and its application to autism Thomas J. Hoffmann1 , Moo K. Chung,1,2,3 , Kim M. Dalton,3 , Andrew L. Alexander,3,4,5 , Grace Wahba,1,2 , Richard J. Davidson,3,4,6 1Department of Statistics, 2Department of Biotatistics and Medical Informatics, 3Keck Laboratory for Functional Brain Imaging and Behavior, 4Department of Psychiatry, 5Department of Medical Physics, 6Department of Psychology, University of Wisconsin-Madison Abstract Autism is a neurodevelopmental disorder with abnormal corpus callosum (CC) size [1]. Most previous studies used the area of predefined Witelson partition [5] as a morphometric measure but other shape metrics have not been considered. We present a novel computational technique for curvature estimation via piecewise quintic splines and use it in both CC nonlinear dynamic time warping algorithm [4] and detecting the regions of curvature difference.Autism is a neurodevelopmental disorder with abnormal corpus callosum (CC) size [1]. Most previous studies used the area of predefined Witelson partition [5] as a morphometric measure but other shape metrics have not been considered. We present a novel computational technique for curvature estimation via piecewise quintic splines and use it in both CC nonlinear dynamic time warping algorithm [4] and detecting the regions of curvature difference. Methods A group of 2D mid sagittal cross section images of the corpus callosum was taken from males of similar age, 15 autistic, and 12 normal controls. The level set method as described by Sethian[2], was used to extract the outline of the corpus callosum automatically. Thus the pixelated CC contour was reconstructed into a rough closed curve in Euclidean space (Figure 1. red). Smoothing of this zigzag contour was necessary to account for the partial volume effect (Figure 1. blue). Two different methods were used to smooth and estimate the curvature function. The first method uses Taubin's smoothing [3], a Gaussian filtering without shrinkage, followed by the least-squares estimation. The second method uses a series of quintic splines to estimate the first and second derivatives to compute the curvature. Afterwards a curve from the control group was chosen as a template and all other curves are registered to the template. First an affine registration was used to normalize the global CC size differences. Second the fast nonlinear dynamic-time warping algorithm was used [4]. The algorithm penalized against large deformation and curvature difference, thereby matching the extrema of curvature while maintaining a smooth and stable deformation. After registering the curves, a local estimation of curvature could be compared across subjects, using Welch's t-test at each point to correct for the somewhat unequal variance in a few areas (Figure 3). Results Both methods provided effective estimates of curvature for the entire CC contours. The smoothing splines performed better in terms of ease of fit and more stable results. The results of the comparison of curvatures between the autistic and control subjects are as shown in Figure 2 where the sample mean curvature functions are plotted (blue: autistic, red: control). Figure 4 is the P-value map where the blue areas indicate more significant curvature difference. Most significant curvature difference is detected at the posterior midbody (R1). Acknowledgements The original level set and dynamic time warping code were obtained from Fan Ding and Yuefeng Lu and have been modified extensively. This work was funded by WARF, NIMH U54 MH0663981A1, NSF Grant DMS0072292 and by a NARSAD Distinguished Investigator Award to RJD. References [1] Harden, A.Y. et al. Corpus Callosum Size in Autism. Neurology, 55:1033-1036, 2000. [2] Malladi, R. and Sethian, J.A. An o(n log(n)) Algorithm for Shape Modeling. Applied Mathematics 18:9389-9392, 1996. [3] Taubin, G. A Signal Processing Approach to Fair Surface Design. Computer Graphics, 29:351358, 1995. [4] Wang, K. and Wang, Y. Alignment of Curves by Dynamic Time Warping. Annals of Statistics, 25:1251-1276, 1997. [5] Witelson, S.F. Hand and sex differences in the isthmus and genu of the human corpus callosum. Brain 112:799-835. 1989. Figure 1. Leveset segmentation and smoothing Figure 2. Mean curvatures for autism and control Figure 3. t-map of curvature difference between autism and control Figure 4. p-map of curvature difference

2D Voxel-based Morphometry Shows Less White Matter Concentration in Autism

Abstract: Autism is a neurodevelopmental disorder with the abnormal reduction in anterior, midbody and posterior part of the corpus callosum (CC) [2]. We applied 2D version of the voxel-based morphometry (VBM) in quantifying the dynamic pattern of the CC and show less white matter concentration in the high functioning autistic (HFA) group at the genu and spleninum removing the effect of age using the general linear model (GLM). Further it is shown that the less white matter concentration is due to hypoplasia rather than atrophy.

Partial correlation mapping of cognitive measure and cortical thickness in autism

Abstract: s: We correlated face recognition task scores to cortical thickness measurements in a group of autistic subjects. Many previous autism anatomical studies neglect to account for age effect and the subsequent statistical parametric maps tend to report spurious results. We demonstrate that the partial correlation mapping proposed here can remove the effect of age and global cortical area difference effectively while localizing the regions of high correlation. Methods: 14 high functioning autistic (HFA) and 12 normal control (NC) subjects used in the study were screened to be right-handed males (Chung, et al., 2004). Face recognition task was performed for the both groups. Age distributions for HFA and NC are 15.93±4.71 and 17.08±2.78 respectively. The face recognition task scores for HFA and NC are 27.14±15.34 and 39.42±0.79 respectively. The outer cortical surface areas are and for HFA and NC respectively. MRIs were collected and both the outer and inner cortical surfaces were extracted for each subject via deformable surface algorithm (MacDonald et al., 2000). Surface normalization is performed by minimizing an objective function that measures the global fit of two surfaces while maximizing the smoothness of the deformation in such a way that the pattern of gyral ridges are matched smoothly (Robbins, 2003). Afterward cortical thickness was computed for each subject (Chung et al., 2005). Heat kernel smoothing was applied to the cortical thickness measures to increase the signal-to-noise ratio with relatively large FWHM of 30mm (Chung et al., 2005). The simple correlation between thickness and score were computed for both groups. To partial out the effect of age and global surface area difference in the correlation, the concept of partial correlation was used (Grunwald et al., 2001). 5 (2.84 0.17) 10 mm ± ⋅ 2 2 5 (2.73 0.06) 10 mm ± ⋅ Results: Comparing the partial correlation to the simple correlation, there is statistically significant increase in the correlation in many areas indicating that the age and the area terms should be accounted for proper correlation analysis. The partial correlation mapping can remove the effect of the age and global area difference in the simple correlation measure as illustrated in the figure. Conclusions: The partial correlation mapping is an effective way of visualizing and localizing the cortical regions of high correlation removing the effect of covariates. Figure 1. Correlation map of face recognition task and cortical thickness. The partial correlation mapping can remove the effect of the age and global area difference in the simple correlation measure.