A computational study of whole-brain connectivity in resting state and task fMRI

Background: We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results: In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions: In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition

Scale Changes Provide an Alternative Cue For the Discrimination of Heading, But Not Object Motion

Background: Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). Material/Methods 16 right handed healthy observers (ages 18–28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. Results: Statistical analyses of performance on the test-experiments in comparison to the control experiments suggests that while scale changes may be involved in the detection of heading, they are not correctly integrated with translational motion and, thus, do not provide a correct discrimination of 3D object trajectories. Conclusions: These results have the important implication for the type of visual guided navigation that can be done by an observer blind to optic flow. Scale change is an important alternative cue for self-motion

When does Subliminal Affective Image Priming Influence the Ability of Schizophrenic Patients to Perceive Face Emotions?

Background: Deficits in face emotion perception are among the most pervasive aspects of schizophrenia impairments which strongly affects interpersonal communication and social skills. Material/Methods Schizophrenic patients (PSZ) and healthy control subjects (HCS) performed 2 psychophysical tasks. One, the SAFFIMAP test, was designed to determine the impact of subliminally presented affective or neutral images on the accuracy of face-expression (angry or neutral) perception. In the second test, FEP, subjects saw pictures of face-expression and were asked to rate them as angry, happy, or neutral. The following clinical scales were used to determine the acute symptoms in PSZ: Positive and Negative Syndrome (PANSS), Young Mania Rating (YMRS), Hamilton Depression (HAM-D), and Hamilton Anxiety (HAM-A). Results: On the SAFFIMAP test, different from the HCS group, the PSZ group tended to categorize the neutral expression of test faces as angry and their response to the test-face expression was not influenced by the affective content of the primes. In PSZ, the PANSS-positive score was significantly correlated with correct perception of angry faces for aggressive or pleasant primes. YMRS scores were strongly correlated with PSZ’s tendency to recognize angry face expressions when the prime was a pleasant or a neutral image. The HAM-D score was positively correlated with categorizing the test-faces as neutral, regardless of the affective content of the prime or of the test-face expression (angry or neutral). Conclusions: Despite its exploratory nature, this study provides the first evidence that conscious perception and categorization of facial emotions (neutral or angry) in PSZ is directly affected by their positive or negative symptoms of the disease as defined by their individual scores on the clinical diagnostic scales

Select and Cluster: A Method for Finding Functional Networks of Clustered Voxels in fMRI

Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challenge stimulating the development of effective data-driven or model based techniques. Here, we present a novel data-driven method for the extraction of significantly connected functional ROIs directly from the preprocessed fMRI data without relying on a priori knowledge of the expected activations. This method finds spatially compact groups of voxels which show a homogeneous pattern of significant connectivity with other regions in the brain. The method, called Select and Cluster (S&C), consists of two steps: first, a dimensionality reduction step based on a blind multiresolution pairwise correlation by which the subset of all cortical voxels with significant mutual correlation is selected and the second step in which the selected voxels are grouped into spatially compact and functionally homogeneous ROIs by means of a Support Vector Clustering (SVC) algorithm. The S&C method is described in detail. Its performance assessed on simulated and experimental fMRI data is compared to other methods commonly used in functional connectivity analyses, such as Independent Component Analysis (ICA) or clustering. S&C method simplifies the extraction of functional networks in fMRI by identifying automatically spatially compact groups of voxels (ROIs) involved in whole brain scale activation networks

Significance of characterization of non-culprit lesions: An underscored clinical problem

Sudden death or acute coronary syndromes are frequently the first manifestation of plaque rupture at non-culprit lesions. Thus, identification of high-risk non-culprit plaques may have significant impact on the prognosis of patients with coronary artery disease. At present a widely accepted diagnostic method to prospectively identify such ‘high-risk’ plaques is not available. Improved identification of high-risk plaques by novel imaging coronary modalities currently available is a goal of great importance since it will result in major decreases in coronary artery disease morbidity and mortality. Potential new treatments with systemic, regional, and local approaches have been proposed. In this review article we focus on common and different morphologic characteristics between culprit and non-culprit lesions, the natural history of non-culprit lesions, and potential methods to identify the high-risk lesions for future adverse cardiovascular events. (C) 2007 Elsevier Ireland Ltd. All rights reserved

Inflammation in lone atrial fibrillation: New insights by coronary sinus thermography

Background: In the clinical setting there are conflicting results regarding the role of inflammatory activation in atrial fibrillation (AF). Coronary sinus (CS) thermography assesses myocardial heat production and is correlated with inflammatory states. We investigated in patients with AF whether 1) there is increased CS blood temperature and 2) the correlation of heat production with systemic inflammation. Methods: We included patients with AF and subjects with sinus rhythm. C-reactive protein (CRP) levels were measured in all patients. CS and right atrium (RA) blood temperature measurements were performed by a dedicated 7F thermography catheter. Delta T was calculated by subtracting RA from CS blood temperature. Results: We included 47 patients with AF and 23 subjects with sinus rhythm. We stratified patients with AF into two groups: normotensive (AFN) and hypertensive (AFH). Delta T was lower in the RA compared with the CS in AFH (37.27 +/- 0.52 degrees C vs 37.47 +/- 0.54 degrees C, p<0.01), in AFN (37.13 +/- 0.53 degrees C vs 37.34 +/- 0.54 degrees C, p<0.01), and in controls (37.41 +/- 0.69 degrees C vs 37.55 +/- 0.68 degrees C, p<0.01). Delta T was greater in AFH, and AFN compared to controls (0.20 +/- 0.07 degrees C, 0.20 +/- 0.08 degrees C, vs 0.14 +/- 0.06 degrees C, p<0.01). Delta T was similar between AFH and AFN (p = 0.95). CRP was higher in AFH and AFN compared to controls (1.72 +/- 0.85 mg/Dl, 1.69 +/- 0.94 mg/dL, 0.98 +/- 0.71 mg/dL, p<0.01). CRP was similar between AFH and AFN (p = 0.87). A correlation between CRP with Delta T was observed in AFH and AFN (R = 0.58, p<0.01, R = 0.44, p = 0.02). Conclusions: Patients with AF have increased myocardial heat production, which is correlated to the systemic inflammation. CS blood temperature measurement may provide significant information for the pathogenesis of AF. (C) 2008 Elsevier Ireland Ltd. All rights reserved