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Highly Accurate Inverse Consistent Registration: A Robust Approach
, 2010
"... The registration of images is a task that is at the core of many applications in computer vision. In computational neuroimaging where the automated segmentation of brain structures is frequently used to quantify change, a highly accurate registration is necessary for motion correction of images take ..."
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Cited by 29 (6 self)
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The registration of images is a task that is at the core of many applications in computer vision. In computational neuroimaging where the automated segmentation of brain structures is frequently used to quantify change, a highly accurate registration is necessary for motion correction of images taken in the same session, or across time in longitudinal studies where changes in the images can be expected. This paper, inspired by Nestares and Heeger (2000), presents a method based on robust statistics to register images in the presence of differences, such as jaw movement, differential MR distortions and true anatomical change. The approach we present guarantees inverse consistency (symmetry), can deal with different intensity scales and automatically estimates a sensitivity parameter to detect outlier regions in the images. The resulting registrations are highly accurate due to their ability to ignore outlier regions and show superior robustness with respect to noise, to intensity scaling and outliers when compared to state-of-the-art registration tools such as FLIRT (in FSL) or the coregistration tool in SPM.
Cognitive and neural contributors to emotion regulation in aging.Social
- Cognitive, and Affective Neuroscience
, 2011
"... Older adults, compared to younger adults, focus on emotional well-being. While the lifespan trajectory of emotional processing and its regulation has been characterized behaviorally, few studies have investigated the underlying neural mechanisms. Here, older adults (range: 59-73 years) and younger ..."
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Cited by 15 (1 self)
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Older adults, compared to younger adults, focus on emotional well-being. While the lifespan trajectory of emotional processing and its regulation has been characterized behaviorally, few studies have investigated the underlying neural mechanisms. Here, older adults (range: 59-73 years) and younger adults (range: 19-33 years) participated in a cognitive reappraisal task during functional magnetic resonance imaging (fMRI) scanning. On each trial, participants viewed positive, negative or neutral pictures and either naturally experienced the image ('Experience' condition) or attempted to detach themselves from the image ('Reappraise' condition). Across both age groups, cognitive reappraisal activated prefrontal regions similar to those reported in prior studies of emotion regulation, while emotional experience activated the bilateral amygdala. Psychophysiological interaction analyses revealed that the left inferior frontal gyrus (IFG) and amygdala demonstrated greater inverse connectivity during the 'Reappraise' condition relative to the 'Experience' condition. The only regions exhibiting significant age differences were the left IFG and the left superior temporal gyrus, for which greater regulation-related activation was observed in younger adults. Controlling for age, increased performance on measures of cognition predicted greater regulation-related decreases in amygdala activation. Thus, while older and younger adults use similar brain structures for emotion regulation and experience, the functional efficacy of those structures depends on underlying cognitive ability.
A WEIGHTED COMMUNICABILITY MEASURE APPLIED TO COMPLEX BRAIN NETWORKS
, 2008
"... Abstract. Recent advances in experimental neuroscience allow non-invasive studies of the white matter tracts in the human central nervous system, thus making available cutting-edge brain anatomical data describing these global connectivity patterns. Via magnetic resonance imaging, this non-invasive ..."
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Cited by 14 (4 self)
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Abstract. Recent advances in experimental neuroscience allow non-invasive studies of the white matter tracts in the human central nervous system, thus making available cutting-edge brain anatomical data describing these global connectivity patterns. Via magnetic resonance imaging, this non-invasive technique is able to infer a snap-shot of the cortical network within the living human brain. Here, we report on the initial success of a new weighted network communicability measure in distinguishing local and global differences between diseased patients and controls. This approach builds on recent advances in network science, where an underlying connectivity structure is used as a means to measure the ease with which information can flow between nodes. One advantage of our method is that it deals directly with the real-valued connectivity data, thereby avoiding the need to discretise the corresponding adjacency matrix, that is, to round weights up to 1 or down to 0, depending upon some threshold value. Experimental results indicate that the new approach is able to extract biologically relevant features that are not immediately apparent from the raw connectivity data. 1.
Common and dissociable prefrontal loci associated with component mechanisms of analogical reasoning
, 2010
"... The ability to draw analogies requires 2 key cognitive processes, relational integration and resolution of interference. The present study aimed to identify the neural correlates of both component processes of analogical reasoning within a single, nonverbal analogy task using event-related function ..."
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Cited by 13 (0 self)
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The ability to draw analogies requires 2 key cognitive processes, relational integration and resolution of interference. The present study aimed to identify the neural correlates of both component processes of analogical reasoning within a single, nonverbal analogy task using event-related functional magnetic resonance imaging. Participants verified whether a visual analogy was true by considering either 1 or 3 relational dimensions. On half of the trials, there was an additional need to resolve interference in order to make a correct judgment. Increase in the number of dimensions to integrate was associated with increased activation in the lateral prefrontal cortex as well as lateral frontal pole in both hemispheres. When there was a need to resolve interference during reasoning, activation increased in the lateral prefrontal cortex but not in the frontal pole. We identified regions in the middle and inferior frontal gyri which were exclusively sensitive to demands on each component process, in addition to a partial overlap between these neural correlates of each component process. These results indicate that analogical reasoning is mediated by the coordination of multiple regions of the prefrontal cortex, of which some are sensitive to demands on only one of these 2 component processes, whereas others are sensitive to both.
Multilevel Segmentation and Integrated Bayesian Model Classification with an Application to Brain Tumor Segmentation
- MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION
, 2006
"... We present a new method for automatic segmentation of heterogeneous image data, which is very common in medical image analysis. The main contribution of the paper is a mathematical formulation for incorporating soft model assignments into the calculation of affinities, which are traditionally model ..."
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Cited by 12 (4 self)
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We present a new method for automatic segmentation of heterogeneous image data, which is very common in medical image analysis. The main contribution of the paper is a mathematical formulation for incorporating soft model assignments into the calculation of affinities, which are traditionally model free. We integrate the resulting modelaware affinities into the multilevel segmentation by weighted aggregation algorithm. We apply the technique to the task of detecting and segmenting brain tumor and edema in multimodal MR volumes. Our results indicate the benefit of incorporating model-aware affinities into the segmentation process for the difficult case of brain tumor.
Model-free group analysis shows altered BOLD FMRI networks in dementia. Human brain mapping
, 2009
"... Abstract: FMRI research in Alzheimer's disease (AD) and mild cognitive impairment (MCI) typically is aimed at determining regional changes in brain function, most commonly by creating a model of the expected BOLD-response and estimating its magnitude using a general linear model (GLM) analysis ..."
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Cited by 12 (0 self)
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Abstract: FMRI research in Alzheimer's disease (AD) and mild cognitive impairment (MCI) typically is aimed at determining regional changes in brain function, most commonly by creating a model of the expected BOLD-response and estimating its magnitude using a general linear model (GLM) analysis. This crucially depends on the suitability of the temporal assumptions of the model and on assumptions about normality of group distributions. Exploratory data analysis techniques such as independent component analysis (ICA) do not depend on these assumptions and are able to detect unknown, yet structured spatiotemporal processes in neuroimaging data. Tensorial probabilistic ICA (T-PICA) is a model free technique that can be used for analyzing multiple subjects and groups, extracting signals of interest (components) in the spatial, temporal, and also subject domain of FMRI data. We applied T-PICA and model-based GLM to study FMRI signal during face encoding in 18 AD, 28 MCI patients, and 41 healthy elderly controls. T-PICA showed activation in regions associated with motor, visual, and cognitive processing, and deactivation in the default mode network. Six networks showed a significantly decreased response in patients. For two networks the T-PICA technique was significantly more sensitive to detect group differences than the standard model-based technique. We conclude that T-PICA is a promising tool to identify and detect differences in (de)activated brain networks in elderly controls and dementia patients. The technique is more sensitive than the commonly applied model-based method. Consistent with other research, we show that networks of activation and deactivation show decreased reactivity in dementia.
Joint Modeling of Anatomical and Functional Connectivity for Population Studies
"... Abstract—We propose a novel probabilistic framework to merge information from diffusion weighted imaging tractography and resting-state functional magnetic resonance imaging correlations to identify connectivity patterns in the brain. In particular, we model the interaction between latent anatomical ..."
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Cited by 11 (2 self)
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Abstract—We propose a novel probabilistic framework to merge information from diffusion weighted imaging tractography and resting-state functional magnetic resonance imaging correlations to identify connectivity patterns in the brain. In particular, we model the interaction between latent anatomical and functional connectivity and present an intuitive extension to population studies. We employ the EM algorithm to estimate the model parameters by maximizing the data likelihood. The method simultaneously infers the templates of latent connectivity for each population and the differences in connectivity between the groups. We demonstrate our method on a schizophrenia study. Our model identifies significant increases in functional connectivity between the parietal/posterior cingulate region and the frontal lobe and reduced functional connectivity between the parietal/posterior cingulate region and the temporal lobe in schizophrenia. We further establish that our model learns predictive differences between the control and clinical populations, and that combining the two modalities yields better results than considering each one in isolation. Index Terms—Biomedical imaging, brain modeling, magnetic resonance imaging (MRI), population analysis. I.
Depression, rumination and the default network
"... Major depressive disorder (MDD) has been characterized by excessive default-network activation and connectivity with the subgenual cingulate. These hyper-connectivities are often interpreted as reflecting rumination, where MDDs perseverate on negative, self-referential thoughts. However, the relatio ..."
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Cited by 10 (0 self)
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Major depressive disorder (MDD) has been characterized by excessive default-network activation and connectivity with the subgenual cingulate. These hyper-connectivities are often interpreted as reflecting rumination, where MDDs perseverate on negative, self-referential thoughts. However, the relationship between connectivity and rumination has not been established. Furthermore, previous research has not examined how connectivity with the subgenual cingulate differs when individuals are engaged in a task or not. The purpose of the present study was to examine connectivity of the default network specifically in the subgenual cingulate both on- and off-task, and to examine the relationship between connectivity and rumination. Analyses using a seed-based connectivity approach revealed that MDDs show more neural functional connectivity between the posterior-cingulate cortex and the subgenual-cingulate cortex than healthy individuals during rest periods, but not during task engagement. Importantly, these rest-period connectivities correlated with behavioral measures of rumination and brooding, but not reflection.
The neuroanatomy of grapheme-color synesthesia.
- Eur. J. Neurosci.
, 2009
"... Abstract Grapheme-color synesthetes perceive particular colors when seeing a letter, word or number (grapheme). Functional neuroimaging studies have provided some evidence in favor of a neural basis for this type of synesthesia. Most of these studies have reported extra activations in the fusiform ..."
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Cited by 9 (0 self)
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Abstract Grapheme-color synesthetes perceive particular colors when seeing a letter, word or number (grapheme). Functional neuroimaging studies have provided some evidence in favor of a neural basis for this type of synesthesia. Most of these studies have reported extra activations in the fusiform gyrus, which is known to be involved in color, letter and word processing. The present study examined different neuroanatomical features (i.e. cortical thickness, cortical volume and cortical surface area) in a sample of 48 subjects (24 grapheme-color synesthetes and 24 control subjects), and revealed increased cortical thickness, volume and surface area in the right and left fusiform gyrus and in adjacent regions, such as the lingual gyrus and the calcarine cortex, in grapheme-color synesthetes. In addition, we set out to analyze structural connectivity based on fractional anisotropy (FA) measurements in a subsample of 28 subjects (14 synesthetes and 14 control subjects). In contrast to the findings of a recent neuroanatomical study using modern diffusion tensor imaging measurement techniques, we did not detect any statistically significant difference in FA between synesthetes and non-synesthetes in the fusiform gyri. Our study thus supports the hypothesis of local anatomical differences in cortical characteristics in the vicinity of the V4 complex. The observed altered brain anatomy in grapheme-color synesthetes might be the anatomical basis for this particular form of synesthesia but it is also possible that the detected effects are a consequence (rather than the primary cause) of the life-long experience of grapheme-color synesthesia.