Measurement and Reliability of Response Inhibition

Response inhibition plays a critical role in adaptive functioning and can be assessed with the Stop-signal task, which requires participants to suppress prepotent motor responses. Evidence suggests that this ability to inhibit a prepotent motor response (reflected as Stop-signal reaction time (SSRT)) is a quantitative and heritable measure of interindividual variation in brain function. Although attention has been given to the optimal method of SSRT estimation, and initial evidence exists in support of its reliability, there is still variability in how Stop-signal task data are treated across samples. In order to examine this issue, we pooled data across three separate studies and examined the influence of multiple SSRT calculation methods and outlier calling on reliability (using Intra-class correlation). Our results suggest that an approach which uses the average of all available sessions, all trials of each session, and excludes outliers based on predetermined lenient criteria yields reliable SSRT estimates, while not excluding too many participants. Our findings further support the reliability of SSRT, which is commonly used as an index of inhibitory control, and provide support for its continued use as a neurocognitive phenotype

Decoding Developmental Differences and Individual Variability in Response Inhibition Through Predictive Analyses Across Individuals

Response inhibition is thought to improve throughout childhood and into adulthood. Despite the relationship between age and the ability to stop ongoing behavior, questions remain regarding whether these age-related changes reflect improvements in response inhibition or in other factors that contribute to response performance variability. Functional neuroimaging data shows age-related changes in neural activity during response inhibition. While traditional methods of exploring neuroimaging data are limited to determining correlational relationships, newer methods can determine predictability and can begin to answer these questions. Therefore, the goal of the current study was to determine which aspects of neural function predict individual differences in age, inhibitory function, response speed, and response time variability. We administered a stop-signal task requiring rapid inhibition of ongoing motor responses to healthy participants aged 9–30. We conducted a standard analysis using GLM and a predictive analysis using high-dimensional regression methods. During successful response inhibition we found regions typically involved in motor control, such as the ACC and striatum, that were correlated with either age, response inhibition (as indexed by stop-signal reaction time; SSRT), response speed, or response time variability. However, when examining which variables neural data could predict, we found that age and SSRT, but not speed or variability of response execution, were predicted by neural activity during successful response inhibition. This predictive relationship provides novel evidence that developmental differences and individual differences in response inhibition are related specifically to inhibitory processes. More generally, this study demonstrates a new approach to identifying the neurocognitive bases of individual differences

The impact of sound field systems on learning and attention in elementary school classrooms

Purpose: An evaluation of the installation and use of sound field systems (SFS) was carried out to investigate their impact on teaching and learning in elementary school classrooms. Methods: The evaluation included acoustic surveys of classrooms, questionnaire surveys of students and teachers and experimental testing of students with and without the use of SFS. Students ’ perceptions of classroom environments and objective data evaluating change in performance on cognitive and academic assessments with amplification over a six month period are reported. Results: Teachers were positive about the use of SFS in improving children’s listening and attention to verbal instructions. Over time students in amplified classrooms did not differ from those in nonamplified classrooms in their reports of listening conditions, nor did their performance differ in measures of numeracy, reading or spelling. Use of SFS in the classrooms resulted in significantly larger gains in performance in the number of correct items on the nonverbal measure of speed of processing and the measure of listening comprehension. Analysis controlling for classroom acoustics indicated that students ’ listening comprehension score

Decreasing Ventromedial Prefrontal Cortex Activity During Sequential Risk-Taking: An fMRI Investigation of the Balloon Analog Risk Task

Functional imaging studies examining the neural correlates of risk have mainly relied on paradigms involving exposure to simple chance gambles and an economic definition of risk as variance in the probability distribution over possible outcomes. However, there is little evidence that choices made during gambling tasks predict naturalistic risk-taking behaviors such as drug use, extreme sports, or even equity investing. To better understand the neural basis of naturalistic risk-taking, we scanned participants using fMRI while they completed the Balloon Analog Risk Task, an experimental measure that includes an active decision/choice component and that has been found to correlate with a number of naturalistic risk-taking behaviors. In the task, as in many naturalistic settings, escalating risk-taking occurs under uncertainty and might be experienced either as the accumulation of greater potential rewards, or as exposure to increasing possible losses (and decreasing expected value). We found that areas previously linked to risk and risk-taking (bilateral anterior insula, anterior cingulate cortex, and right dorsolateral prefrontal cortex) were activated as participants continued to inflate balloons. Interestingly, we found that ventromedial prefrontal cortex (vmPFC) activity decreased as participants further expanded balloons. In light of previous findings implicating the vmPFC in value calculation, this result suggests that escalating risk-taking in the task might be perceived as exposure to increasing possible losses (and decreasing expected value) rather than the increasing potential total reward relative to the starting point of the trial. A better understanding of how neural activity changes with risk-taking behavior in the task offers insight into the potential neural mechanisms driving naturalistic risk-taking

Sharing brain mapping statistical results with the neuroimaging data model

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html

Predicting risky choices from brain activity patterns

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights

Deficits in visual working-memory capacity and general cognition in African Americans with psychosis

On average, patients with psychosis perform worse than controls on visual change-detection tasks, implying that psychosis is associated with reduced capacity of visual working memory (WM). In the present study, 79 patients diagnosed with various psychotic disorders and 166 controls, all African Americans, completed a change-detection task and several other neurocognitive measures. The aims of the study were to (1) determine whether we could observe a between-group difference in performance on the change-detection task in this sample; (2) establish whether such a difference could be specifically attributed to reduced WM capacity (k); and (3) estimate k in the context of the general cognitive deficit in psychosis. Consistent with previous studies, patients performed worse than controls on the change-detection task, on average. Bayesian hierarchical cognitive modeling of the data suggested that this between-group difference was driven by reduced k in patients, rather than differences in other psychologically meaningful model parameters (guessing behavior and lapse rate). Using the same modeling framework, we estimated the effect of psychosis on k while controlling for general intellectual ability (g, obtained from the other neurocognitive measures). The results suggested that reduced k in patients was stronger than predicted by the between-group difference in g. Moreover, a mediation analysis suggested that the relationship between psychosis and g (i.e., the general cognitive deficit) was mediated by k. The results were consistent with the idea that reduced k is a specific deficit in psychosis, which contributes to the general cognitive deficit