57 research outputs found

    Evaluation of emotion processing in HIV-infected patients and correlation with cognitive performance

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    Background: Facial emotion recognition depends on cortical and subcortical networks. HIV infection of the central nervous system can damage these networks, leading to impaired facial emotion recognition. Methods: We performed a cross-sectional single cohort study consecutively enrolling HIV + subjects during routine outpatient visits. Age, gender and education-matched HIV-negative healthy individuals were also selected. Subjects were submitted to a Facial Emotion Recognition Test, which assesses the ability to recognize six basic emotions (disgust, anger, fear, happiness, surprise, sadness). The score for each emotion and a global score (obtained by summing scores for each emotion) were analyzed. General cognitive status of patients was also assessed. Results: A total of 49 HIV + and 20 HIV−subjects were enrolled. On the Facial Emotion Recognition Test, ANOVA revealed a significantly lower performance of HIV + subjects than healthy controls in recognizing fear. Moreover, fear facial emotion recognition was directly correlated with Immediate Recall of Rey Words. The lower the patients’ neurocognitive performance the less accurate they were in recognizing happiness. AIDS-defining events were negatively related to the correct recognition of happiness. Conclusions: Fear recognition deficit in HIV + patients might be related to the impaired function of neural networks in the frontostriatal system. AIDS events, including non-neurological ones, may have a negative effect on this system. Inclusion of an emotion recognition test in the neuropsychological test battery could help clinicians during the long term management of HIV-infected patients, to better understand the cognitive mechanisms involved in the reduction of emotion recognition ability and the impact of this impairment on daily lif

    High Natality Rates of Endangered Steller Sea Lions in Kenai Fjords, Alaska and Perceptions of Population Status in the Gulf of Alaska

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    Steller sea lions experienced a dramatic population collapse of more than 80% in the late 1970s through the 1990s across their western range in Alaska. One of several competing hypotheses about the cause holds that reduced female reproductive rates (natality) substantively contributed to the decline and continue to limit recovery in the Gulf of Alaska despite the fact that there have been very few attempts to directly measure natality in this species. We conducted a longitudinal study of natality among individual Steller sea lions (n = 151) at a rookery and nearby haulouts in Kenai Fjords, Gulf of Alaska during 2003–2009. Multi-state models were built and tested in Program MARK to estimate survival, resighting, and state transition probabilities dependent on whether or not a female gave birth in the previous year. The models that most closely fit the data suggested that females which gave birth had a higher probability of surviving and giving birth in the following year compared to females that did not give birth, indicating some females are more fit than others. Natality, estimated at 69%, was similar to natality for Steller sea lions in the Gulf of Alaska prior to their decline (67%) and much greater than the published estimate for the 2000s (43%) which was hypothesized from an inferential population dynamic model. Reasons for the disparity are discussed, and could be resolved by additional longitudinal estimates of natality at this and other rookeries over changing ocean climate regimes. Such estimates would provide an appropriate assessment of a key parameter of population dynamics in this endangered species which has heretofore been lacking. Without support for depressed natality as the explanation for a lack of recovery of Steller sea lions in the Gulf of Alaska, alternative hypotheses must be more seriously considered

    Network analysis of prospective brain development in youth with benign epilepsy with centrotemporal spikes and its relationship to cognition

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    ObjectiveBenign epilepsy with centrotemporal spikes (BECTS) is the most common childhood idiopathic localization-related epilepsy syndrome. BECTS presents normal routine magnetic resonance imaging (MRI); however, quantitative analytic techniques have captured subtle cortical and subcortical magnetic resonance anomalies. Network science, including graph theory (GT) analyses, facilitates understanding of brain covariance patterns, potentially informing in important ways how this common self-limiting epilepsy syndrome may impact normal patterns of brain and cognitive development.MethodsGT analyses examined the developmental covariance among cortical and subcortical regions in children with new/recent onset BECTS (n = 19) and typically developing healthy controls (n = 22) who underwent high-resolution MRI and cognitive assessment at baseline and 2 years later. Global (transitivity, global efficiency, and modularity index [Q]) and regional measures (local efficiency and hubs) were investigated to characterize network development in each group. Associations between baseline-based GT measures and cognition at both time points addressed the implications of GT analyses for cognition and prospective cognitive development. Furthermore, an individual contribution measure was investigated, reflecting how important for cognition it is for BECTS to resemble the correlation matrices of controls.ResultsGroups exhibited similar Q and overall network configuration, with BECTS presenting significantly higher transitivity and both global and local efficiency. Furthermore, both groups presented a similar number of hubs, with BECTS showing a higher number in temporal lobe regions compared to controls. The investigated measures were negatively associated with 2-year cognitive outcomes in BECTS.SignificanceChildren with BECTS present a higher-than-normal global developmental configuration compared to controls, along with divergence from normality in terms of regional configuration. Baseline GT measures demonstrate potential as a cognitive biomarker to predict cognitive outcome in BECTS 2 years after diagnosis. Similarities and differences in developmental network configurations and their implications for cognition and behavior across common epilepsy syndromes are of theoretical interest and clinical relevance
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