Objective. The phase of the electroencephalographic (EEG) signal predicts performance in motor, somatosensory, and cognitive functions. Studies suggest that brain phase resets align neural oscillations with external stimuli, or couple oscillations across frequency bands and brain regions. Transcranial Magnetic Stimulation (TMS) can cause phase resets noninvasively in the cortex, thus providing the potential to control phase-sensitive cognitive functions. However, the relationship between TMS parameters and phase resetting is not fully understood. This is especially true of TMS intensity, which may be crucial to enabling precise control over the amount of phase resetting that is induced. Additionally, TMS phase resetting may interact with the instantaneous phase of the brain. Understanding these relationships is crucial to the development of more powerful and controllable stimulation protocols.Approach.To test these relationships, we conducted a TMS-EEG study. We applied single-pulse TMS at varying degrees of stimulation intensity to the motor area in an open loop. Offline, we used an autoregressive algorithm to estimate the phase of the intrinsicµ-Alpha rhythm of the motor cortex at the moment each TMS pulse was delivered.Main results. We identified post-stimulation epochs whereµ-Alpha phase resetting and N100 amplitude depend parametrically on TMS intensity and are significantversusperipheral auditory sham stimulation. We observedµ-Alpha phase inversion after stimulations near peaks but not troughs in the endogenousµ-Alpha rhythm.Significance. These data suggest that low-intensity TMS primarily resets existing oscillations, while at higher intensities TMS may activate previously silent neurons, but only when endogenous oscillations are near the peak phase. These data can guide future studies that seek to induce phase resetting, and point to a way to manipulate the phase resetting effect of TMS by varying only the timing of the pulse with respect to ongoing brain activity.

Recent studies suggest that attention is rhythmic. Whether that rhythmicity can be explained by the phase of ongoing neural oscillations, however, is still debated. We contemplate that a step toward untangling the relationship between attention and phase stems from employing simple behavioral tasks that isolate attention from other cognitive functions (perception/decision-making) and by localized monitoring of neural activity with high spatiotemporal resolution over the brain regions associated with the attentional network. In this study, we investigated whether the phase of electroencephalography (EEG) oscillations predicts alerting attention. We isolated the alerting mechanism of attention using the Psychomotor Vigilance Task, which does not involve a perceptual component, and collected high resolution EEG using novel high-density dry EEG arrays at the frontal region of the scalp. We identified that alerting attention alone is sufficient to induce a phase-dependent modulation of behavior at EEG frequencies of 3, 6, and 8 Hz throughout the frontal region, and we quantified the phase that predicts the high and low attention states in our cohort. Our findings disambiguate the relationship between EEG phase and alerting attention.

Social phobia (SP) is associated with changes in functional connectivity strength and topology. However, reported changes have been heterogeneous due to small sample sizes, inconsistent methodologies, and comorbidities, such as attention-deficit/hyperactivity disorder (ADHD), which has a high comorbidity rate with SP. Furthermore, there are few studies looking at SP in an adolescent population, a critical period for the development of the social brain. This project focuses on functional connectivity strength and topological differences in social phobia patients with and without ADHD comorbidity. We examined resting-state functional MRI images from 158 subjects, including 36 SP participants without ADHD comorbidity, 60 SP participants with ADHD comorbidity, and 62 healthy controls, with an overall average age of 14.16. We used a data-driven approach to examine impaired functional connectivity in a whole-brain analysis and higher-order topological differences in functional brain networks. We identified changes in the cerebellum and default mode network in social phobia patients as a whole, with the presence of ADHD comorbidity affecting various subsystems of the default mode network. Social phobia functional connectivity networks resembled random graphs, and local connectivity patterns in the superior occipital gyrus were different due to ADHD comorbidity. These alterations may indicate impairments in self-related processing, imagery, mentalizing, and predictive processes. We then used these changes in a linear support vector machine to distinguish between each pair of groups and achieved prediction accuracy significantly above chance rates. Our study extends prior research by showing that functional connectivity changes exist at adolescence, which are affected by ADHD comorbidity. As such, these results offer a new perspective in examining neurobiological changes in SP patients.

Our results indicated that we could predict EEG phase accurately across cognitive conditions and datasets, with higher accuracy for high instantaneous band-power and SNR. Accordingly, real-time EEG phase experiments, closed-loop technologies, and BCIs should minimize external unwanted noise while targeting periods of high power, as opposed to manipulating experimental and cognitive conditions.

Objective. To evaluate the signal quality of dry MXene-based electrode arrays (also termed 'MXtrodes') for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard. Approach. We placed 4 x 4 MXtrode arrays and gelled Ag/AgCl electrodes on different scalp locations. The scalp was cleaned with alcohol and rewetted with saline before application. We recorded from both electrode types simultaneously while participants performed a vigilance task. Main results. The root mean squared amplitude of MXtrodes was slightly higher than that of Ag/AgCl electrodes (.24-1.94 uV). Most MXtrode pairs had slightly lower broadband spectral coherence (.05 to .1 dB) and Delta- and Theta-band timeseries correlation (.05 to .1 units) compared to the Ag/AgCl pair (p < .001). However, the magnitude of correlation and coherence was high across both electrode types. Beta-band timeseries correlation and spectral coherence were higher between neighboring MXtrodes in the array (.81 to .84 units) than between any other pair (.70 to .75 units). This result suggests the close spacing of the nearest MXtrodes (3 mm) more densely sampled high spatial-frequency topographies. Event-related potentials were more similar between MXtrodes (rho >= .95) than equally spaced Ag/AgCl electrodes (rho >= .77, p < .001). Dry MXtrode impedance ((x) over bar = 5.15 K Omega cm(2)) was higher and more variable than gelled Ag/AgCl electrodes ((x) over bar = 1.21 K Omega cm(2), p < .001). EEG was also recorded on the scalp across diverse hair types. Significance. Dry MXene-based electrodes record EEG at a quality comparable to conventional gelled Ag/AgCl while requiring minimal scalp preparation and no gel. MXtrodes can record independent signals at a spatial density four times higher than conventional electrodes, including through hair, thus opening novel opportunities for research and clinical applications that could benefit from dry and higher-density configurations.

To examine complex relationships among variables, researchers in human resource management, industrial-organizational psychology, organizational behavior, and related fields have increasingly used meta-analytic procedures to aggregate effect sizes across primary studies to form meta-analytic correlation matrices, which are then subjected to further analyses using linear models (e.g., multiple linear regression). Because missing effect sizes (i.e., correlation coefficients) and different sample sizes across primary studies can occur when constructing meta-analytic correlation matrices, the present study examined the effects of missingness under realistic conditions and various methods for estimating sample size (e.g., minimum sample size, arithmetic mean, harmonic mean, and geometric mean) on the estimated squared multiple correlation coefficient (R2) and the power of the significance test on the overall R2 in linear regression. Simulation results suggest that missing data had a more detrimental effect as the number of primary studies decreased and the number of predictor variables increased. It appears that using second-order sample sizes of at least 10 (i.e., independent effect sizes) can improve both statistical power and estimation of the overall R2 considerably. Results also suggest that although the minimum sample size should not be used to estimate sample size, the other sample size estimates appear to perform similarly.

Given a convex disk K (a convex compact planar set with nonempty interior), let δ L ( K ) and θ L ( K ) denote the lattice packing density and the lattice covering density of K , respectively. We prove that for every centrally-symmetric convex disk K we have that 1≤δ_L(K)θ_L(K)≤1.17225… The left inequality is tight and it improves a 10-year old result.

The Context-Sensitivity of Rationality and Knowledge Brian Kim My dissertation argues that the beliefs, desires, and preferences that count as rational may change from one deliberative context to another. The argument rests on the premise that rational deliberation requires one to identify all the possibilities that are relevant to a decision problem. How does a decision maker accomplish this task? What impact does this demarcation have on the beliefs and desires that she uses to deliberate? The answers I propose suggest changes to the way we view rational agents and what they know. Appealing to empirical research and normative concerns, I argue that an agent’s deliberative beliefs, desires, and preferences are “constructed” on a case to case basis and are distinct from the agent’s stable set of background attitudes. For deliberative judgments depend upon the ways one speciVes what is relevant for a decision problem and this may change from one context to the next. Upon articulating a suitable context-sensitive view of rational decision making, I develop accounts of warranted assertion, rational full belief and knowledge that are similarly context-sensitive. These views criticize simple constitutive norms of assertion, like the knowledge norm, and propose a way to connect degrees of belief and full belief. In addition, the proUered account of knowledge explains how knowledge precludes epistemic luck, as required by Gettier cases, by appealing to the way the standards of knowledge vary from one deliberative context to the next.

Investigations of differential item functioning (DIF) have been conducted mostly on ability tests and have found little evidence of easily interpretable differences across various demographic subgroups. In this study, we examined the degree to which DIF in biographical data items referencing academically relevant background, experiences, and interests was related to differences in judgments about access to these experiences by members of different gender and race subgroups. DIF in the location parameter was significantly related (r = -.51, p .01) to gender differences in perceived accessibility to experience. No significant relationships with accessibility were observed for DIF in the slope parameter across gender groups or for the slope and location parameters associated with DIF across Black and White groups. Practical implications for use of biodata and theoretical implications for DIF research are discussed.

In their comment, M. L. Rohling et al. (2011) accused us of offering a "misleading" review of response bias. In fact, the additional findings they provided on this topic are relevant only to bias assessment in I of the domains we discussed, neuropsychological assessment. Furthermore, we contend that, even in that 1 domain, the additional findings they described do not merit revision of our conclusion that the data are insufficient for evaluating the status of bias indicators. We remain hopeful that our review will spur researchers to publish additional tests of the validity of bias indicators in real-world settings and reduce the reliance on analogue studies as an evidence base for their use.

After 100 years of discussion, response bias remains a controversial topic in psychological measurement. The use of bias indicators in applied assessment is predicated on the assumptions that (a) response bias suppresses or moderates the criterion-related validity of substantive psychological indicators and (b) bias indicators are capable of detecting the presence of response bias. To test these assumptions, we reviewed literature comprising investigations in which bias indicators were evaluated as suppressors or moderators of the validity of other indicators. This review yielded only 41 studies across the contexts of personality assessment, workplace variables, emotional disorders, eligibility for disability, and forensic populations. In the first two contexts, there were enough studies to conclude that support for the use of bias indicators was weak. Evidence suggesting that random or careless responding may represent a biasing influence was noted, but this conclusion was based on a small set of studies. Several possible causes for failure to support the overall hypothesis were suggested, including poor validity of bias indicators, the extreme base rate of bias, and the adequacy of the criteria. In the other settings, the yield was too small to afford viable conclusions. Although the absence of a consensus could be used to justify continued use of bias indicators in such settings, false positives have their costs, including wasted effort and adverse impact. Despite many years of research, a sufficient justification for the use of bias indicators in applied settings remains elusive.

In organizational research, situational judgment tests (SJTs) consistently demonstrate incremental validity, yet our theoretical understanding of SJTs is limited. Our knowledge could be advanced by decomposing the variance of SJT items into trait variance and situation variance; we do that by applying statistical methods used to analyze multitrait–multimethod matrices. A college-student sample (N = 2,747) was administered an SJT of goal orientation traits (i.e., mastery, performance-approach, and performance-avoid). Structural equation modeling was used to estimate the proportions of item variance to attributable to situational differences (across students) and to trait-based differences in students (across situations). Situation factors accounted for over three times the amount of variance as did individual difference factors. We conclude with general implications for the design of SJTs in organizational research.

As we engage the new millennium, accelerating technological, cultural, political, and financial turbulence buffets organizations-often unpredictably so. Responding to an uncertain and unpredictable future is not so much an issue of advanced strategy and planning but rather one of organizational innovation, agility, and adaptability (Terreberry, 1968). Organizations that can adapt quickly will survive and may even exploit hidden opportunities in the unexpected. Those that are slow to adapt face decline and dissolution. These environmental trends have been evident for some three decades. Many organizations have responded by creating leaner and more agile structures, by shifting to team-based work organizations (Lawler, Mohrman, & Ledford, 1995), and by building the capabilities of their members.

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To determine whether profiles of predictor variables provide incremental prediction of college student outcomes, the authors 1st applied an empirical clustering method to profiles based on the scores of 2,771 entering college students on a battery of biographical data and situational judgment measures, along with SAT and American College Test scores and high school grade point average, which resulted in 5 student groups. Performance of the students in these clusters was meaningfully different on a set of external variables, including college grade point average, self-rated performance, class absenteeism, organizational citizenship behavior, intent to quit their university, and satisfaction with college. The 14 variables in the profile were all significantly correlated with 1 or more of the outcome measures; however, nonlinear prediction of these outcomes on the basis of cluster membership did not add incrementally to a linear-regression-based combination of these 14 variables as predictors.

Biodata measures and situational judgment inventories (SJIs) have been shown to be use- ful supplements to traditional selection tests in a variety of employment and educational settings. However, scores on both measures may be systematically biased when applicants are motivated and know how to perform well on the tests. This study examines the inde- pendent and joint effects of motivation, coaching, and warning not to fake on scores on biodata and SJI measures. Generally, coaching and motivation improved scores on these measures, and warning statements did not decrease scores. Item characteristics including objectivity, controllability, verifiability, and relevance were all shown to be related to bio- data scores, as was the requirement to provide written elaboration on multiple-choice item responses. Based on our findings, we offer practical advice regarding the use of biodata and SJIs.