144 research outputs found

    Impaired regulation of emotion: Neural correlates of reappraisal and distraction in bipolar disorder and unaffected relatives

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    Deficient emotion regulation has been proposed as a crucial pathological mechanism in bipolar disorder (BD). We therefore investigated emotion regulation impairments in BD, the related neural underpinnings and their etiological relevance for the disorder. Twenty-two euthymic patients with bipolar-I disorder and 17 unaffected first-degree relatives of BD-I patients, as well as two groups of healthy gender-, age- and education-matched controls (N=22/17, respectively) were included. Participants underwent functional magnetic resonance imaging while applying two different emotion regulation techniques, reappraisal and distraction, when presented with emotional images. BD patients and relatives showed impaired downregulation of amygdala activity during reappraisal, but not during distraction, when compared with controls. This deficit was correlated with the habitual use of reappraisal. The negative connectivity of amygdala and orbitofrontal cortex (OFC) observed during reappraisal in controls was reversed in BD patients and relatives. There were no significant differences between BD patients and relatives. As being observed in BD patients and unaffected relatives, deficits in emotion regulation through reappraisal may represent heritable neurobiological abnormalities underlying BD. The neural mechanisms include impaired control of amygdala reactivity to emotional stimuli and dysfunctional connectivity of the amygdala to regulatory control regions in the OFC. These are, thus, important aspects of the neurobiological basis of increased vulnerability for BD

    Bipolar disorder: A neural network perspective on a disorder of emotion and motivation

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    Bipolar disorder (BD) is a severe, chronic disease with a heritability of 60–80%. BD is frequently misdiagnosed due to phenomenological overlap with other psychopathologies, an important issue that calls for the identification of biological and psychological vulnerability and disease markers. Altered structural and functional connectivity, mainly between limbic and prefrontal brain areas, have been proposed to underlie emotional and motivational dysregulation in BD and might represent relevant vulnerability and disease markers. In the present laboratory review we discuss functional and structural neuroimaging findings on emotional and motivational dysregulation from our research group in BD patients and healthy individuals at risk to develop BD. As a main result of our studies, we observed altered orbitofrontal and limbic activity and reduced connectivity between dorsal prefrontal and limbic brain regions, as well as reduced integrity of fiber tracts connecting prefrontal and subcortical brain structures in BD patients and high-risk individuals. Our results provide novel insights into pathophysiological mechanisms of bipolar disorder. The current laboratory review provides a specific view of our group on altered brain connectivity and underlying psychological processes in bipolar disorder based on our own work, integrating relevant findings from others. Thereby we attempt to advance neuropsychobiological models of BD

    Affective Bias without Hemispheric Competition: Evidence for Independent Processing Resources in Each Cortical Hemisphere

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    We assessed the extent of neural competition for attentional processing resources in early visual cortex between foveally presented task stimuli and peripheral emotional distracter images. Task-relevant and distracting stimuli were shown in rapid serial visual presentation (RSVP) streams to elicit the steady-state visual evoked potential, which serves as an electrophysiological marker of attentional resource allocation in early visual cortex. A taskrelated RSVP stream of symbolic letters was presented centrally at 15 Hz while distracting RSVP streams were displayed at 4 or 6 Hz in the left and right visual hemifields. These image streams always had neutral content in one visual field and would unpredictably switch from neutral to unpleasant content in the opposite visual field. We found that the steady-state visual evoked potential amplitude was consistently modulated as a function of change in emotional valence in peripheral RSVPs, indicating sensory gain in response to distracting affective content. Importantly, the facilitated processing for emotional content shown in one visual hemifield was not paralleled by any perceptual costs in response to the task-related processing in the center or the neutral image stream in the other visual hemifield. Together, our data provide further evidence for sustained sensory facilitation in favor of emotional distracters. Furthermore, these results are in line with previous reports of a “different hemifield advantage” with lowlevel visual stimuli and are suggestive of independent processing resources in each cortical hemisphere that operate beyond lowlevel visual cues, that is, with complex images that impact early stages of visual processing via reentrant feedback loops from higher order processing areas

    The impact of the CACNA1C gene polymorphism on frontolimbic function in bipolar disorder

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    Genome-wide association studies in bipolar disorder (BD)1 have implicated a single-nucleotide polymorphism (rs1006737, G right arrow A) in the CACNA1C gene, which encodes for the alpha 1c (CAV1.2) subunit of the voltage-gated, L-type calcium channel. Neuroimaging studies of healthy individuals report that this risk allele modulates brain function within limbic (amygdala, anterior cingulate gyrus) and hippocampal regions during tasks of reward processing2, 3 and episodic memory. Moreover, animal studies suggest that the CaV1.2 L-type calcium channels influence emotional behaviour through enhanced neurotransmission via the lateral amygdala pathway. On the basis of this evidence, we tested the hypotheses that the CACNA1C rs1006737 risk allele will modulate neural responses within predefined prefrontal and subcortical regions of interest during emotional face processing and that this effect would be amplified in BD patients

    Size Matters: The Number of Prostitutes and the Global HIV/AIDS Pandemic

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    Background. HIV/AIDS prevalence rates across countries of the world vary more than 500-fold from.06 % in Hungary to 33.4% in Swaziland. One of the most cited research papers in the field, utilizing cross country regression analysis to analyze other correlates with this HIV prevalence data, is flawed in that it weights each country’s results by the country’s population. Methodology/Principal Findings. Based on cross-country linear and multiple regressions using newly gathered data from UNAIDS, the number of female commercial sex workers as a percentage of the female adult population is robustly positively correlated with countrywide HIV/AIDS prevalence levels. Confirming earlier studies, female illiteracy levels, gender illiteracy differences and income inequality within countries are also significantly positively correlated with HIV/AIDS levels. Muslims as a percentage of the population, itself highly correlated with country circumcision rates and previously found to be negatively correlated with HIV/AIDS prevalence, is insignificant when the percentage of commercial sex workers in a population is included in the analysis. Conclusions/Significance. This paper provides strong evidence that when conducted properly, cross country regression data does not support the theory that male circumcision is the key to slowing the AIDS epidemic. Rather, it is the number of infected prostitutes in a country that is highly significant and robust in explaining HIV prevalence levels across countries. An explanation is offered for why Africa has been hit the hardest by the AIDS pandemic and why there appears to be very little correlation between HIV/AIDS infection rates and country wealth

    Glycosylation Focuses Sequence Variation in the Influenza A Virus H1 Hemagglutinin Globular Domain

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    Antigenic drift in the influenza A virus hemagglutinin (HA) is responsible for seasonal reformulation of influenza vaccines. Here, we address an important and largely overlooked issue in antigenic drift: how does the number and location of glycosylation sites affect HA evolution in man? We analyzed the glycosylation status of all full-length H1 subtype HA sequences available in the NCBI influenza database. We devised the “flow index” (FI), a simple algorithm that calculates the tendency for viruses to gain or lose consensus glycosylation sites. The FI predicts the predominance of glycosylation states among existing strains. Our analyses show that while the number of glycosylation sites in the HA globular domain does not influence the overall magnitude of variation in defined antigenic regions, variation focuses on those regions unshielded by glycosylation. This supports the conclusion that glycosylation generally shields HA from antibody-mediated neutralization, and implies that fitness costs in accommodating oligosaccharides limit virus escape via HA hyperglycosylation

    Comparison of evolutionary algorithms in gene regulatory network model inference

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    Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very di±cult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insu±cient. Results: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and o®er a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. Conclusions: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identi¯ed and a platform for development of appropriate model formalisms is established
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