The Design Organization Test: Further Demonstration of Reliability and Validity as a Brief Measure of Visuospatial Ability

Neuropsychological assessments are frequently time-consuming and fatiguing for patients. Brief screening evaluations may reduce test duration and allow more efficient use of time by permitting greater attention toward neuropsychological domains showing probable deficits. The Design Organization Test (DOT) was initially developed as a 2-min paper-and-pencil alternative for the Block Design (BD) subtest of the Wechsler scales. Although initially validated for clinical neurologic patients, we sought to further establish the reliability and validity of this test in a healthy, more diverse population. Two alternate versions of the DOT and the Wechsler Abbreviated Scale of Intelligence (WASI) were administered to 61 healthy adult participants. The DOT showed high alternate forms reliability (r = .90–.92), and the two versions yielded equivalent levels of performance. The DOT was highly correlated with BD (r = .76–.79) and was significantly correlated with all subscales of the WASI. The DOT proved useful when used in lieu of BD in the calculation of WASI IQ scores. Findings support the reliability and validity of the DOT as a measure of visuospatial ability and suggest its potential worth as an efficient estimate of intellectual functioning in situations where lengthier tests may be inappropriate or unfeasible

Parameters as Trait Indicators: Exploring a Complementary Neurocomputational Approach to Conceptualizing and Measuring Trait Differences in Emotional Intelligence

Current assessments of trait emotional intelligence (EI) rely on self-report inventories. While this approach has seen considerable success, a complementary approach allowing objective assessment of EI-relevant traits would provide some potential advantages. Among others, one potential advantage is that it would aid in emerging efforts to assess the brain basis of trait EI, where self-reported competency levels do not always match real-world behavior. In this paper, we review recent experimental paradigms in computational cognitive neuroscience (CCN), which allow behavioral estimates of individual differences in range of parameter values within computational models of neurocognitive processes. Based on this review, we illustrate how several of these parameters appear to correspond well to EI-relevant traits (i.e., differences in mood stability, stress vulnerability, self-control, and flexibility, among others). In contrast, although estimated objectively, these parameters do not correspond well to the optimal performance abilities assessed within competing "ability models" of EI. We suggest that adapting this approach from CCN-by treating parameter value estimates as objective trait EI measures-could (1) provide novel research directions, (2) aid in characterizing the neural basis of trait EI, and (3) offer a promising complementary assessment method.Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Physical Exercise Habits Correlate with Gray Matter Volume of the Hippocampus in Healthy Adult Humans

Physical activity facilitates neurogenesis of dentate cells in the rodent hippocampus, a brain region critical for memory formation and spatial representation. Recent findings in humans also suggest that aerobic exercise can lead to increased hippocampal volume and enhanced cognitive functioning in children and elderly adults. However, the association between physical activity and hippocampal volume during the period from early adulthood through middle age has not been effectively explored. Here, we correlated the number of minutes of self-reported exercise per week with gray matter volume of the hippocampus using voxel-based morphometry (VBM) in 61 healthy adults ranging from 18 to 45 years of age. After controlling for age, gender, and total brain volume, total minutes of weekly exercise correlated significantly with volume of the right hippocampus. Findings highlight the relationship between regular physical exercise and brain structure during early to middle adulthood

A randomized, double-blind, placebo-controlled trial of blue wavelength light exposure on sleep and recovery of brain structure, function, and cognition following mild traumatic brain injury.

Sleep and circadian rhythms are among the most powerful but least understood contributors to cognitive performance and brain health. Here we capitalize on the circadian resetting effect of blue-wavelength light to phase shift the sleep patterns of adult patients (aged 18-48 years) recovering from mild traumatic brain injury (mTBI), with the aim of facilitating recovery of brain structure, connectivity, and cognitive performance. During a randomized, double-blind, placebo-controlled trial of 32 adults with a recent mTBI, we compared 6-weeks of daily 30-min pulses of blue light (peak lambda = 469 nm) each morning versus amber placebo light (peak lambda= 578 nm) on neurocognitive and neuroimaging outcomes, including gray matter volume (GMV), resting-state functional connectivity, directed connectivity using Granger causality, and white matter integrity using diffusion tensor imaging (DTI). Relative to placebo, morning blue light led to phase-advanced sleep timing, reduced daytime sleepiness, and improved executive functioning, and was associated with increased volume of the posterior thalamus (i.e., pulvinar), greater thalamo-cortical functional connectivity, and increased axonal integrity of these pathways. These findings provide insight into the contributions of the circadian and sleep systems in brain repair and lay the groundwork for interventions targeting the retinohypothalamic system to facilitate injury recovery.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Role of Prefrontal Cortical Surface Area and Volume in Preclinical Suicidal Ideation in a Non-Clinical Sample

Suicidal ideation (SUI) can occur in the absence of concomitant psychiatric diagnoses, and even normal levels can be problematic among individuals experiencing excess stress or lack of social support. The objective of this study was to investigate the neuroanatomical basis of SUI in non-clinical human populations who are within the normal limits of SUI, after accounting for elevated stress and perceived lack of social support. Neuroanatomical data were collected from 55 healthy individuals (mean age 30.9 +/- 8.1 years, 27 females) whose depression severity levels were below the Diagnostic and Statistical Manual of Mental Disorders criteria. Measures of SUI, aggression, stress, non-support, and treatment rejection were collected from the treatment-consideration scales (TCS) of the Personality Assessment Inventory (PAI). Correlations between standardized SUI scores and three brain morphometry measures, including vertex wise cortical thickness (CT), cortical surface area (CSA), and cortical volume (CV), were estimated for each participant, controlling for age, sex, intracranial volume, and the remaining TCS measures. We observed a significant negative association between scores on SUI and both CSA and CV (cluster-forming threshold of p < 0.005, clusterwise threshold of p < 0.05, FOR corrected for multiple comparisons) within the left rostral middle frontal gyrus. Our findings suggest that greater CSA and CV within the dorsolateral prefrontal cortex are associated with reduced SUI in a non-clinical population with mild levels of stress and perceived lack of social support. Because the dorsolateral prefrontal cortex has been broadly linked to cognitive reappraisal, self-critical thoughts, and emotional regulation, greater CSA and CV within these regions may lead to better mental health by protecting healthy individuals from engaging in SUI during periods of stress and perceived insufficient social support. As our data consisted of only healthy individuals with non-clinical levels of SUI, further investigation will be necessary to explore the neural basis of SUI in populations who may be at greater risk of future suicidal behavior.U.S. Army Medical Research and Materiel Command [W81XWH-09-1-0730]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The right-hemisphere and valence hypotheses: could they both be right (and sometimes left)?

The two halves of the brain are believed to play different roles in emotional processing, but the specific contribution of each hemisphere continues to be debated. The right-hemisphere hypothesis suggests that the right cerebrum is dominant for processing all emotions regardless of affective valence, whereas the valence specific hypothesis posits that the left hemisphere is specialized for processing positive affect while the right hemisphere is specialized for negative affect. Here, healthy participants viewed two split visual-field facial affect perception tasks during functional magnetic resonance imaging, one presenting chimeric happy faces (i.e. half happy/half neutral) and the other presenting identical sad chimera (i.e. half sad/half neutral), each masked immediately by a neutral face. Results suggest that the posterior right hemisphere is generically activated during non-conscious emotional face perception regardless of affective valence, although greater activation is produced by negative facial cues. The posterior left hemisphere was generally less activated by emotional faces, but also appeared to recruit bilateral anterior brain regions in a valence-specific manner. Findings suggest simultaneous operation of aspects of both hypotheses, suggesting that these two rival theories may not actually be in opposition, but may instead reflect different facets of a complex distributed emotion processing system

Ability-Based Emotional Intelligence Is Associated With Greater Cardiac Vagal Control and Reactivity

Several distinct models of emotional intelligence (EI) have been developed over the past two decades. The ability model conceptualizes EI as a narrow set of interconnected, objectively measured, cognitive-emotional abilities, including the ability to perceive, manage, facilitate, and understand the emotions of the self and others. By contrast, trait or mixed models focus on subjective ratings of emotional/social competencies. Theoretically, EI is associated with neurobiological processes involved in emotional regulation and reactivity. The neurovisceral integration (NVI) model proposes a positive relationship between cardiac vagal control (CVC) and cognitive-emotional abilities similar to those encompassed by EI. The current study examined the association between CVC and EI. Because ability EI is directly tied to actual performance on emotional tasks, we hypothesized that individuals with higher ability-based EI scores would show greater levels of CVC at rest, and in response to a stressful task. Because mixedmodels of EI are not linked directly to observable emotional behavior, we predicted no association with CVC. Consistent with expectations, individuals with higher levels of ability EI, but not mixed EI, had higher levels of CVC. We also found that individuals with greater levels of CVC who demonstrated reactivity to a stress induction had significantly higher EI compared to individuals that did not respond to the stress induction. Our findings support the theoretically expected overlap between constructs within the NVI model and ability EI model, however, the observed effect size was small, and the associations between EI and CVC should not be taken to indicate a causal connection. Results suggest that variance in the ability to understand emotional processes in oneself and to reason about one's visceral experience may facilitate better CVC. Future work manipulating either CVC or EI may prove informative in teasing apart the causal role driving their observed relationship.Joint Warfighter Medical Research Program [W81XWH-16-1-0062]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Functional MRI and the Wada test provide complementary information for predicting post-operative seizure control

AbstractPrediction of post-surgical seizure relief and potential cognitive deficits secondary to anterior temporal lobectomy (ATL) are important to pre-surgical planning. Although the intracarotid amobarbital test (IAT) is predictive of post-ATL seizure outcome, development of non-invasive and more precise means for determining post-ATL seizure relief are needed. We previously reported on a technique utilizing functional MRI (fMRI) to evaluate the relative functional adequacy of mesial temporal lobe structures in preparation for ATL . In the present study, we report follow-up outcome data on eight temporal lobe epilepsy (TLE) patients 1-year post-ATL who were evaluated pre-surgically using IAT and fMRI. Functional memory lateralization using fMRI predicted post-ATL seizure outcome as effectively as the IAT. In general, asymmetry of functional mTL activation favouring the non-epileptic hemisphere was associated with seizure-free status at 1-year follow-up. Moreover, when combined, fMRI and IAT provided complementary data that resulted in improved prediction of post-operative seizure control compared with either procedure alone

Parameters as Trait Indicators: Exploring a Complementary Neurocomputational Approach to Conceptualizing and Measuring Trait Differences in Emotional Intelligence

Current assessments of trait emotional intelligence (EI) rely on self-report inventories. While this approach has seen considerable success, a complementary approach allowing objective assessment of EI-relevant traits would provide some potential advantages. Among others, one potential advantage is that it would aid in emerging efforts to assess the brain basis of trait EI, where self-reported competency levels do not always match real-world behavior. In this paper, we review recent experimental paradigms in computational cognitive neuroscience (CCN), which allow behavioral estimates of individual differences in range of parameter values within computational models of neurocognitive processes. Based on this review, we illustrate how several of these parameters appear to correspond well to EI-relevant traits (i.e., differences in mood stability, stress vulnerability, self-control, and flexibility, among others). In contrast, although estimated objectively, these parameters do not correspond well to the optimal performance abilities assessed within competing “ability models” of EI. We suggest that adapting this approach from CCN—by treating parameter value estimates as objective trait EI measures—could (1) provide novel research directions, (2) aid in characterizing the neural basis of trait EI, and (3) offer a promising complementary assessment method

Denoising scanner effects from multimodal MRI data using linked independent component analysis

Pooling magnetic resonance imaging (MRI) data across research studies, or utilizing shared data from imaging repositories, presents exceptional opportunities to advance and enhance reproducibility of neuroscience research. However, scanner confounds hinder pooling data collected on different scanners or across software and hardware upgrades on the same scanner, even when all acquisition protocols are harmonized. These confounds reduce power and can lead to spurious findings. Unfortunately, methods to address this problem are scant. In this study, we propose a novel denoising approach that implements a data-driven linked independent component analysis (LICA) to identify scanner-related effects for removal from multimodal MRI to denoise scanner effects. We utilized multi-study data to test our proposed method that were collected on a single 3T scanner, pre- and post-software and major hardware upgrades and using different acquisition parameters. Our proposed denoising method shows a greater reduction of scanner-related variance compared with standard GLM confound regression or ICA-based single-modality denoising. Although we did not test it here, for combining data across different scanners, LICA should prove even better at identifying scanner effects as between-scanner variability is generally much larger than within-scanner variability. Our method has great promise for denoising scanner effects in multi-study and in large-scale multi-site studies that may be confounded by scanner differences.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]