Positive emotional perceptions and healthy emotional intelligence (EI) are important for social functioning. In this study, we investigated whether loving kindness meditation (LKM) combined with anodal transcranial direct current stimulation (tDCS) would facilitate improvements in EI and changes in affective experience of visual stimuli. LKM has been shown to increase positive emotional experiences and we hypothesized that tDCS could enhance these effects. Eighty-seven undergraduates were randomly assigned to 30 minutes of LKM or a relaxation control recording with anodal tDCS applied to the left dorsolateral prefrontal cortex (left dlPFC) or right temporoparietal junction (right TPJ) at 0.1 or 2.0 milliamps. The primary outcomes were self-reported affect ratings of images from the International Affective Picture System and EI as measured by the Mayer, Salovey and Caruso Emotional Intelligence Test. Results indicated no effects of training on EI, and no main effects of LKM, electrode placement, or tDCS current strength on affect ratings. There was a significant interaction of electrode placement by meditation condition (p = 0.001), such that those assigned to LKM and right TPJ tDCS, regardless of current strength, rated neutral and positive images more positively after training. Results suggest that LKM may enhance positive affective experience.

In light of the Army’s intent to leverage advances in Artificial Intelligence (AI) for augmenting dismounted Soldier Lethality through the development of in-scope and Heads-Up Display (HUD)-based Automatic Target Recognition (ATR) systems, the Combat Capabilities Development Command U. S. Army Research Laboratory’s Human Research and Engineering Directorate (CCDC-ARL/HRED) has identified several critical gaps that must be addressed in order to effectively team the Soldier with ATR for the desired augmented Lethality. One of these areas pertains to the way in which ATR is displayed and requires a thorough understanding and leveraging of relevant cognitive processes that will enable use of this technology. Additionally, insufficient consideration of perceptual, attentional, and cognitive capabilities increases the risk of burdening the Soldier with excessive, unnecessary, or distracting representations of information, which may impede Lethality rather than augment it. HRED’s planned and ongoing research is intended to develop novel mechanisms through which Soldiers teamed with ATR will perform more adaptively and effectively than either the Soldier or the intelligent system could accomplish individually. Based on HRED’s significant expertise in the cognitive sciences, coupled with familiarity with the military-relevant domain spaces, the following initial recommendations for ATR information display requirements are made:1.ATR highlighting should leverage a non-binary display schema to continuously encode threat information (e.g., target class/identity, uncertainty, and prioritization).2.ATR highlighting should be integrated with the target itself instead of functioning as a discrete feature of the display (i.e., highlight the target rather than highlighting a region with the target inside).3.Information about threat certainty or classification confidence (which can also include priority) should be embedded into ATR highlighting.4.Yellow highlights may offer advantages for display5.Changing information (e.g., target certainty) should be accomplished through formation or modification of highlight gradients rather than sudden changes in the display.6.Human performance evaluations of ATR should consider the incorporation of changing threat states and contexts into scenarios for more relevant findings.7.Human performance evaluations of ATR should consider the incorporation of uncued (non-highlighted) targets and miscued targets (false identifications; e.g. ATR identifies non-threat as threat) for more relevant findings.

Brain-computer interfaces (BCIs) have the potential to significantly change the ways in which humans interact with technology, the environment, and even each other. Unfortunately, BCI technologies are seldom robust enough for use in real-world applications, in part due to the large amount of data that must be collected, processed, and classified in order to develop models of task-related neural activity that account for two of the most important and least-understood drivers of BCI illiteracy: individual differences in neural signals and intra-individual differences across interdependent, time-varying neural states. This paper describes the feasibility of using a game with a purpose (GWAP) as a viable instrument for collecting data from BCI-relevant research tasks. By leveraging game-related reward processes to maintain participant interest and engagement, this approach will enable large amounts of BCI data to be acquired, both across many individuals and longitudinally from specific individuals as neural states vary naturally over time. Pilot and technical testing results are presented here to demonstrate that the BCI-relevant tasks embedded within the research game elicit neural signals similar to those that would be expected from more traditional BCI tasks. These preliminary data provide support and validation of the use of GWAPs as promising tools to enable long-term collection of BCI-relevant data in an engaging environment.

There is extensive laboratory research studying the effects of acute sleep deprivation on biological and cognitive functions, yet much less is known about naturalistic patterns of sleep loss and the potential impact on daily or weekly functioning of an individual. Longitudinal studies are needed to advance our understanding of relationships between naturalistic sleep and fluctuations in human health and performance, but it is first necessary to understand the efficacy of current tools for long-term sleep monitoring. The present study used wrist actigraphy and sleep log diaries to obtain daily measurements of sleep from 30 healthy adults for up to 16 consecutive weeks. We used non-parametric Bland-Altman analysis and correlation coefficients to calculate agreement between subjectively and objectively measured variables including sleep onset time, sleep offset time, sleep onset latency, number of awakenings, the amount of wake time after sleep onset, and total sleep time. We also examined compliance data on the submission of daily sleep logs according to the experimental protocol. Overall, we found strong agreement for sleep onset and sleep offset times, but relatively poor agreement for variables related to wakefulness including sleep onset latency, awakenings, and wake after sleep onset. Compliance tended to decrease significantly over time according to a linear function, but there were substantial individual differences in overall compliance rates. There were also individual differences in agreement that could be explained, in part, by differences in compliance. Individuals who were consistently more compliant over time also tended to show the best agreement and lower scores on behavioral avoidance scale (BIS). Our results provide evidence for convergent validity in measuring sleep onset and sleep offset with wrist actigraphy and sleep logs, and we conclude by proposing an analysis method to mitigate the impact of non-compliance and measurement errors when the two methods provide discrepant estimates.

Mindfulness-based training (MBT) and transcranial electrical stimulation (TES) methods such as direct current stimulation (tDCS) have demonstrated promise for the augmentation of cognitive abilities. The current study investigated the potential compatibility of concurrent "electrical" MBT and tDCS (or eMBT) by testing its combined effects on behavioral and neurophysiological indices of working memory (WM) and attentional resource allocation. Thirty-four healthy participants were randomly assigned to either a MBT task with tDCS group (eMBT) or an active control training task with sham tDCS (Control) group. Training lasted 4-weeks, with up to twenty MBT sessions and with up to eight of those sessions that were eMBT sessions. Electroencephalography was acquired during varying WM load conditions using the n-back task (1-, 2-, 3-back), along with performance on complex WM span tasks (operation and symmetry span) and fluid intelligence measures (Ravens and Shipley) before and after training. Improved performance was observed only on the 3-back and spatial span tasks for eMBT but not the Control group. During 3-back performance in the eMBT group, an increase in P3 amplitude and theta power at electrode site Pz was also observed, along with a simultaneous decrease in frontal midline P3 amplitude and theta power compared to the Control group. These results are consistent with the neural efficiency hypothesis, where higher cognitive capacity was associated with more distributed brain activity (i.e., increase in parietal and decrease in frontal amplitudes). Future longitudinal studies are called upon to further examine the direct contributions of tDCS on MBT by assessing the differential effects of electrode montage, polarity, current strength and a direct contrast between the eMBT and MBT conditions on performance and neuroimaging outcome data. While preliminary, the current results provided evidence for the potential compatibility of using eMBT to modulate WM capacity through the allocation of attention and its neurophysiological correlates.

There is extensive laboratory research on acute sleep deprivation and biological/cognitive functions, yet much less is known about naturalistic patterns of sleep loss and the impact on daily or weekly performance of an individual. Longitudinal studies provide an avenue to understand direct relationships between naturalistic sleep and fluctuations in human health and performance. The present study used wrist actigraphy and sleep log diaries to obtain daily measurements of sleep-related variables from 30 healthy adults for up to 16 consecutive weeks. We used non-parametric Bland-Altman analysis and correlation coefficients to calculate agreement between variables including sleep onset time, sleep offset time, sleep onset latency, number of awakenings, wake after sleep onset, and total sleep time. To better understand individual variability, we examined compliance data on the submission of daily sleep logs as well as performance data across several diverse cognitive tasks. Overall, we found strong agreement for sleep onset and sleep offset times, but relatively poor agreement for variables related to night wakefulness. Compliance tended to decrease significantly over time according to a linear function, but there were also substantial individual differences in compliance that could help explain variability in agreement. Individuals who were consistently more compliant over time also tended to show the best agreement between objective measures and self-report. Individual variability in sleep onset time often revealed the strongest relationship with differences in task performance. These results demonstrate convergent validity in measuring sleep onset and sleep offset times with actigraphy/sleep logs across several months in a natural environment, but also recommend caution interpreting variables related to night wakefulness and self-report data from individuals showing relatively poor compliance. This research was supported by the U.S. Army Research Laboratory.

Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses.

The goal of this study was to investigate patterns of axonal injury in the first week after mild traumatic brain injury (mTBI). We performed a prospective cohort study of 20 patients presenting to the emergency department with mTBI, using 3.0T diffusion tensor MRI immediately after injury and again at 1 week post-injury. Corresponding data were acquired from 16 controls over a similar time interval. Fractional anisotropy (FA) and other diffusion measures were calculated from 11 a priori selected axon tracts at each time-point, and the change across time in each region was quantified for each subject. Clinical outcomes were determined by standardized neurocognitive assessment. We found that mTBI subjects were significantly more likely to have changes in FA in those 11 regions of interest across the one week time period, compared to control subjects whose FA measurements were stable across time. Longitudinal imaging was more sensitive to these subtle changes in white matter integrity than cross-sectional assessments at either of two time points, alone. Analyzing the sources of variance in our control population, we show that this increased sensitivity is likely due to the smaller within-subject variability obtained by longitudinal analysis with each subject as their own control. This is in contrast to the larger between-subject variability obtained by cross-sectional analysis of each individual subject to normalized data from a control group. We also demonstrated that inclusion of all a priori ROIs in an analytic model as opposed to measuring individual ROIs improves detection of white matter changes by overcoming issues of injury heterogeneity. Finally, we employed genetic programming (a bio-inspired computational method for model estimation) to demonstrate that longitudinal changes in FA have utility in predicting the symptomatology of patients with mTBI. We conclude concussive brain injury caused acute, measurable changes in the FA of white matter tracts consistent with evolving axonal injury and/or edema, which may contribute to post-concussive symptoms.

In the last few decades, noninvasive neuroimaging has revealed macroscale brain dynamics that underlie perception, cognition, and action. Advances in noninvasive neuroimaging target two capabilities: 1) increased spatial and temporal resolution of measured neural activity; and 2) innovative methodologies to extract brain-behavior relationships from evolving neuroimaging technology. We target the second. Our novel methodology integrated three neuroimaging methodologies and elucidated expertise-dependent differences in functional (fused EEG-fMRI) and structural (dMRI) brain networks for a perception-action coupling task. A set of baseball players and controls performed a Go/No-Go task designed to mimic the situation of hitting a baseball. In the functional analysis, our novel fusion methodology identifies 50-ms windows with predictive EEG neural correlates of expertise and fuses these temporal windows with fMRI activity in a whole-brain 2-mm voxel analysis, revealing time-localized correlations of expertise at a spatial scale of millimeters. The spatiotemporal cascade of brain activity reflecting expertise differences begins as early as 200 ms after the pitch starts and lasts up to 700 ms afterwards. Network differences are spatially localized to include motor and visual processing areas, providing evidence for differences in perception-action coupling between the groups. Furthermore, an analysis of structural connectivity reveals that the players have significantly more connections between cerebellar and left frontal/motor regions, and many of the functional activation differences between the groups are located within structurally defined network modules that differentiate expertise. In short, our novel method illustrates how multimodal neuroimaging can provide specific macroscale insights into the functional and structural correlates of expertise development.

Post‐task resting state dynamics can be viewed as a task‐driven state where behavioral performance is improved through endogenous, non‐explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post‐task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division‐1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No‐Go task before a resting state scan, and we compared post‐task resting state connectivity using a seed‐based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post‐task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA–L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD‐alpha oscillation correlations between groups suggests variability in modulatory attention in the post‐task state, and (3) group differences between BOLD‐beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post‐task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454–4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Chronic pain is a complex physiological and psychological phenomenon. Implicit learning mechanisms contribute to the development of chronic pain and to persistent changes in the central nervous system. We hypothesized that these central abnormalities can be remedied with Cognitive Behavioral Therapy (CBT). Specifically, since regions of the anterior Default Mode Network (DMN) are centrally involved in emotional regulation via connections with limbic regions, such as the amygdala, remediation of maladaptive behavioral and cognitive patterns as a result of CBT for chronic pain would manifest itself as a change in the intrinsic functional connectivity (iFC) between these prefrontal and limbic regions. Resting-state functional neuroimaging was performed in patients with chronic pain before and after 11-week CBT (n = 19), as well as a matched (ages 19–59, both sexes) active control group of patients who received educational materials (n = 19). Participants were randomized prior to the intervention. To investigate the differential impact of treatment on intrinsic functional connectivity (iFC), we compared pre–post differences in iFC between groups. In addition, we performed exploratory whole brain analyses of changes in fractional amplitude of low frequency fluctuations (fALFF). The course of CBT led to significant improvements in clinical measures of pain and self-efficacy for coping with chronic pain. Significant group differences in pre–post changes in both iFC and fALFF were correlated with clinical outcomes. Compared to control patients, iFC between the anterior DMN and the amygdala/periaqueductal gray decreased following CBT, whereas iFC between the basal ganglia network and the right secondary somatosensory cortex increased following CBT. CBT patients also had increased post-therapy fALFF in the bilateral posterior cingulate and the cerebellum. By delineating neuroplasticity associated with CBT-related improvements, these results add to mounting evidence that CBT is a valuable treatment option for chronic pain.

UNLABELLED:There is emerging evidence that chronic musculoskeletal pain is associated with anatomic and functional abnormalities in gray matter. However, little research has investigated the relationship between chronic musculoskeletal pain and white matter. In this study, we used whole-brain tract-based spatial statistics and region-of-interest analyses of diffusion tensor imaging data to demonstrate that patients with chronic musculoskeletal pain exhibit several abnormal metrics of white matter integrity compared with healthy controls. Chronic musculoskeletal pain was associated with lower fractional anisotropy in the splenium of the corpus callosum and the left cingulum adjacent to the hippocampus. Patients also had higher radial diffusivity in the splenium, right anterior and posterior limbs of the internal capsule, external capsule, superior longitudinal fasciculus, and cerebral peduncle. Patterns of axial diffusivity (AD) varied: patients exhibited lower AD in the left cingulum adjacent to the hippocampus and higher AD in the anterior limbs of the internal capsule and in the right cerebral peduncle. Several correlations between diffusion metrics and clinical variables were also significant at a P < .01 level: fractional anisotropy in the left uncinate fasciculus correlated positively with total pain experience and typical levels of pain severity. AD in the left anterior limb of the internal capsule and left uncinate fasciculus was correlated with total pain experience and typical pain level. Positive correlations were also found between AD in the right uncinate and both total pain experience and pain catastrophizing. These results demonstrate that white matter abnormalities play a role in chronic musculoskeletal pain as a cause, a predisposing factor, a consequence, or a compensatory adaptation. PERSPECTIVE:Patients with chronic musculoskeletal pain exhibit altered metrics of diffusion in the brain's white matter compared with healthy volunteers, and some of these differences are directly related to symptom severity.

Chronic pain is a medical condition that severely decreases the quality of life for those who struggle to cope with it. Interactive voice response (IVR) technology has the ability to track symptoms and disease progression, to investigate the relationships between symptom patterns and clinical outcomes, to assess the efficacy of ongoing treatments, and to directly serve as an adjunct to therapeutic treatment for chronic pain. While many approaches exist toward the management of chronic pain, all have their pitfalls and none work universally. Cognitive behavioral therapy (CBT) is one approach that has been shown to be fairly effective, and therapeutic interactive voice response technology provides a convenient and easy-to-use means of extending the therapeutic gains of CBT long after patients have discontinued clinical visitations. This review summarizes the advantages and disadvantages of IVR technology, provides evidence for the efficacy of the method in monitoring and managing chronic pain, and addresses potential future directions that the technology may take as a therapeutic intervention in its own right.

Huntington disease (HD) is a progressive neurodegenerative disorder caused by expression of polyglutamine-expanded mutant huntingtin protein (mhtt). Most evidence indicates that soluble mhtt species, rather than insoluble aggregates, are the important mediators of HD pathogenesis. However, the differential roles of soluble monomeric and oligomeric mhtt species in HD and the mechanisms of oligomer formation are not yet understood. We have shown previously that copper interacts with and oxidizes the polyglutamine-containing N171 fragment of huntingtin. In this study we report that oxidation-dependent oligomers of huntingtin form spontaneously in cell and mouse HD models. Levels of these species are modulated by copper, hydrogen peroxide, and glutathione. Mutagenesis of all cysteine residues within N171 blocks the formation of these oligomers. In cells, levels of oligomerization-blocked mutant N171 were decreased compared with native N171. We further show that a subset of the oligomerization-blocked form of glutamine-expanded N171 huntingtin is rapidly depleted from the soluble pool compared with "native " mutant N171. Taken together, our data indicate that huntingtin is subject to specific oxidations that are involved in the formation of stable oligomers and that also delay removal from the soluble pool. These findings show that inhibiting formation of oxidation-dependent huntingtin oligomers, or promoting their dissolution, may have protective effects in HD by decreasing the burden of soluble mutant huntingtin.

Huntington's disease (HD) is a progressive neurodegenerative disease caused by a glutamine expansion within huntingtin protein. The exact pathological mechanisms determining disease onset and progression remain unclear. However, aggregates of insoluble mutant huntingtin (mhtt), a hallmark of HD, are readily detected within neurons in HD brain. Although aggregated polyglutamines may not be inherently toxic, they constitute a biomarker for mutant huntingtin useful for developing therapeutics. We previously reported that the small molecule, C2-8, inhibits polyglutamine aggregation in cell culture and brain slices and rescues degeneration of photoreceptors in a Drosophila model of HD. In this study, we assessed the therapeutic potential of C2-8 in the R6/2 mouse model of HD, which has been used to provide proof-of-concept data in considering whether to advance therapies to human HD. We show that, at nontoxic doses, C2-8 penetrates the blood–brain barrier and is present in brain at a high concentration. C2-8-treated mice showed improved motor performance and reduced neuronal atrophy and had smaller huntingtin aggregates. There have been no prior drug-like, non-toxic, brain-penetrable aggregation inhibitors to arise from cell-based high-throughput screens for reducing huntingtin aggregation that is efficacious in preclinical in vivo models. C2-8 provides an essential tool to help elucidate mechanisms of neurodegeneration in HD and a therapeutic lead for further optimization and development.

Huntington's disease (HD) is caused by a dominant polyglutamine expansion within the N-terminus of huntingtin protein and results in oxidative stress, energetic insufficiency and striatal degeneration. Copper and iron are increased in the striata of HD patients, but the role of these metals in HD pathogenesis is unknown. We found, using inductively-coupled-plasma mass spectroscopy, that elevations of copper and iron found in human HD brain are reiterated in the brains of affected HD transgenic mice. Increased brain copper correlated with decreased levels of the copper export protein, amyloid precursor protein. We hypothesized that increased amounts of copper bound to low affinity sites could contribute to pro-oxidant activities and neurodegeneration. We focused on two proteins:huntingtin, because of its centrality to HD, and lactate dehydrogenase (LDH), because of its documented sensitivity to copper, necessity for normoxic brain energy metabolism and evidence for altered lactate metabolism in HD brain. The first 171 amino acids of wild-type huntingtin, and its glutamine expanded mutant form, interacted with copper, but not iron. N171 reduced Cu2+ in vitro in a 1:1 copper:protein stoichiometry indicating that this fragment is very redox active. Further, copper promoted and metal chelation inhibited aggregation of cell-free huntingtin. We found decreased LDH activity, but not protein, and increased lactate levels in HD transgenic mouse brain. The LDH inhibitor oxamate resulted in neurodegeneration when delivered intra-striatially to healthy mice, indicating that LDH inhibition is relevant to neurodegeneration in HD. Our findings support a role of pro-oxidant copper-protein interactions in HD progression and offer a novel target for pharmacotherapeutics.