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With successful antiretroviral therapy in the US, HIV-positive adults now routinely survive into old age. However, increased life expectancy with HIV introduces the added complication of age-related cognitive decline. Aging with HIV has been associated with poorer cognitive outcomes compared to HIV-negative adults. While up to 50% of older HIV-positive adults will develop some degree of cognitive impairment over their lifetime, cognitive symptoms are often not consistently monitored, until those symptoms are significant enough to impair daily life. In this study we found that subjective memory complaint (SMC) ratings correlated with measurable memory performance impairments in HIV-positive adults, but not HIV-negative adults. As the HIV-positive population ages, structured subjective cognitive assessment may be beneficial to identify the early signs of cognitive impairment, and subsequently allow for earlier interventions to maintain cognitive performance as these adults continue to survive into old age.
Impulsivity, and in particular the negative urgency aspect of this trait, is associated with poor inhibitory control when experiencing negative emotion. Individual differences in aspects of impulsivity have been correlated with striatal dopamine D2/D3 receptor availability and function. This multi-modal pilot study used both positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) to evaluate dopaminergic and neural activity, respectively, using modified versions of the monetary incentive delay task. Twelve healthy female subjects underwent both scans and completed the NEO Personality Inventory Revised to assess Impulsiveness (IMP). We examined the relationship between nucleus accumbens (NAcc) dopaminergic incentive/reward release, measured as a change in D2/D3 binding potential between neutral and incentive/reward conditions with [(11)C]raclopride PET, and blood oxygen level-dependent (BOLD) activation elicited during the anticipation of rewards, measured with fMRI. Left NAcc incentive/reward dopaminergic release correlated with anticipatory reward activation within the medial prefrontal cortex (mPFC), left angular gyrus, mammillary bodies, and left superior frontal cortex. Activation in the mPFC negatively correlated with IMP and mediated the relationship between IMP and incentive/reward dopaminergic release in left NAcc. The mPFC, with a regulatory role in learning and valuation, may influence dopamine incentive/reward release.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
In typical perceptual learning experiments, one stimulus type (e.g., a bisection stimulus offset either to the left or right) is presented per trial. In roving, two different stimulus types (e.g., a 30' and a 20' wide bisection stimulus) are randomly interleaved from trial to trial. Roving can impair both perceptual learning and task sensitivity. Here, we investigate the relationship between the two. Using a bisection task, we found no effect of roving before training. We next trained subjects and they improved. A roving condition applied after training impaired sensitivity.
Copyright © 2013 Elsevier Ltd. All rights reserved.
Response inhibition in stop signal tasks has been explained as the outcome of a race between GO and STOP processes (e.g., Logan, 1981). Response choice in two-alternative perceptual categorization tasks has been explained as the outcome of an accumulation of evidence for the alternative responses. To begin unifying these two powerful investigation frameworks, we obtained data from humans and macaque monkeys performing a stop signal task with responses guided by perceptual categorization and variable degrees of difficulty, ranging from low to high accuracy. Comparable results across species reinforced the validity of this animal model. Response times and errors increased with categorization difficulty. The probability of failing to inhibit responses on stop signal trials increased with stop signal delay, and the response times for failed stop signal trials were shorter than those for trials with no stop signal. Thus, the Logan race model could be applied to estimate the duration of the stopping process. We found that the duration of the STOP process did not vary across a wide range of discrimination accuracies. This is consistent with the functional, and possibly mechanistic, independence of choice and inhibition mechanisms.
Population-based studies indicate that between 5 and 9 percent of US children exhibit significant deficits in mathematical reasoning, yet little is understood about the brain morphological features related to mathematical performances. In this work, deformation-based morphometry (DBM) analyses have been performed on magnetic resonance images of the brains of 79 third graders to investigate whether there is a correlation between brain morphological features and mathematical proficiency. Group comparison was also performed between Math Difficulties (MD-worst math performers) and Normal Controls (NC), where each subgroup consists of 20 age and gender matched subjects. DBM analysis is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a common space. To evaluate the effect of registration algorithms on DBM results, five nonrigid registration algorithms have been used: (1) the Adaptive Bases Algorithm (ABA); (2) the Image Registration Toolkit (IRTK); (3) the FSL Nonlinear Image Registration Tool; (4) the Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. The deformation field magnitude (DFM) was used to measure the displacement at each voxel, and the Jacobian determinant (JAC) was used to quantify local volumetric changes. Results show there are no statistically significant volumetric differences between the NC and the MD groups using JAC. However, DBM analysis using DFM found statistically significant anatomical variations between the two groups around the left occipital-temporal cortex, left orbital-frontal cortex, and right insular cortex. Regions of agreement between at least two algorithms based on voxel-wise analysis were used to define Regions of Interest (ROIs) to perform an ROI-based correlation analysis on all 79 volumes. Correlations between average DFM values and standard mathematical scores over these regions were found to be significant. We also found that the choice of registration algorithm has an impact on DBM-based results, so we recommend using more than one algorithm when conducting DBM studies. To the best of our knowledge, this is the first study that uses DBM to investigate brain anatomical features related to mathematical performance in a relatively large population of children.
BACKGROUND - We evaluated focused training in lung hilar dissection with a reanimated porcine lung model in the boot camp setting.
METHODS - A total of 64 first-year cardiothoracic surgical residents participated in four consecutive hours devoted to training in open hilar dissection as part of the Thoracic Surgical Directors Association boot camps. Each resident participated in two open hilar dissections. Component tasks were assessed on a 5-point rating scale for the first and second dissections.
RESULTS - Immediate assessment performed after completion of the session showed improvements in all graded components. The mean total score on a 50-point scale improved significantly between the first and second repetition (36.03 ± 7.03 to 41.16 ± 6.95; p = 0.001).
CONCLUSIONS - Focused massed (single-session) practice in the boot camp setting improved the ability of residents to perform hilar dissection on simulators using reanimated porcine lung models. Given these early successes in massed simulation-based surgical education, there is good reason to expect that deliberate and distributed practice on similar simulators would improve resident education in cardiothoracic surgery.
Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Although it is generally recognized that the concurrent performance of two tasks incurs costs, the sources of these dual-task costs remain controversial. The serial bottleneck model suggests that serial postponement of task performance in dual-task conditions results from a central stage of response selection that can only process one task at a time. Cognitive-control models, by contrast, propose that multiple response selections can proceed in parallel, but that serial processing of task performance is predominantly adopted because its processing efficiency is higher than that of parallel processing. In the present study, we empirically tested this proposition by examining whether parallel processing would occur when it was more efficient and financially rewarded. The results indicated that even when parallel processing was more efficient and was incentivized by financial reward, participants still failed to process tasks in parallel. We conclude that central information processing is limited by a serial bottleneck.
We present novel graph-based visualizations of self-organizing maps for unsupervised functional magnetic resonance imaging (fMRI) analysis. A self-organizing map is an artificial neural network model that transforms high-dimensional data into a low-dimensional (often a 2-D) map using unsupervised learning. However, a postprocessing scheme is necessary to correctly interpret similarity between neighboring node prototypes (feature vectors) on the output map and delineate clusters and features of interest in the data. In this paper, we used graph-based visualizations to capture fMRI data features based upon 1) the distribution of data across the receptive fields of the prototypes (density-based connectivity); and 2) temporal similarities (correlations) between the prototypes (correlation-based connectivity). We applied this approach to identify task-related brain areas in an fMRI reaction time experiment involving a visuo-manual response task, and we correlated the time-to-peak of the fMRI responses in these areas with reaction time. Visualization of self-organizing maps outperformed independent component analysis and voxelwise univariate linear regression analysis in identifying and classifying relevant brain regions. We conclude that the graph-based visualizations of self-organizing maps help in advanced visualization of cluster boundaries in fMRI data enabling the separation of regions with small differences in the timings of their brain responses.
Event-related potentials (ERPs) have provided crucial data concerning the time course of psychological processes, but the neural mechanisms producing ERP components remain poorly understood. This study continues a program of research in which we investigated the neural basis of attention-related ERP components by simultaneously recording intracranially and extracranially from macaque monkeys. Here, we compare the timing of attentional selection by the macaque homologue of the human N2pc component (m-N2pc) with the timing of selection in the frontal eye field (FEF), an attentional-control structure believed to influence posterior visual areas thought to generate the N2pc. We recorded FEF single-unit spiking and local field potentials (LFPs) simultaneously with the m-N2pc in monkeys performing an efficient pop-out search task. We assessed how the timing of attentional selection depends on task demands by direct comparison with a previous study of inefficient search in the same monkeys (e.g., finding a T among Ls). Target selection by FEF spikes, LFPs, and the m-N2pc was earlier during efficient pop-out search rather than during inefficient search. The timing and magnitude of selection in all three signals varied with set size during inefficient but not efficient search. During pop-out search, attentional selection was evident in FEF spiking and LFP before the m-N2pc, following the same sequence observed during inefficient search. These observations are consistent with the hypothesis that feedback from FEF modulates neural activity in posterior regions that appear to generate the m-N2pc even when competition for attention among items in a visual scene is minimal.
Discharge rate modulation of frontal eye field (FEF) neurons has been identified with a representation of visual search salience (physical conspicuity and behavioral relevance) and saccade preparation. We tested whether salience or saccade preparation are evident in the trial-to-trial variability of discharge rate. We quantified response variability via the Fano factor in FEF neurons recorded in monkeys performing efficient and inefficient visual search tasks. Response variability declined following stimulus presentation in most neurons, but despite clear discharge rate modulation, variability did not change with target salience. Instead, we found that response variability was modulated by stimulus luminance and the number of items in the visual field independently of attentional demands. Response variability declined to a minimum before saccade initiation, and presaccadic response variability was directionally tuned. In addition, response variability was correlated with the response time of memory-guided saccades. These results indicate that the trial-by-trial response variability of FEF neurons reflects saccade preparation and the strength of sensory input, but not visual search salience or attentional allocation.