An item response theory analysis of the matrix reasoning item bank (MaRs-IB).

Matrix reasoning tasks are among the most widely used measures of cognitive ability in the behavioral sciences, but the lack of matrix reasoning tests in the public domain complicates their use. Here, we present an extensive investigation and psychometric validation of the matrix reasoning item bank (MaRs-IB), an open-access set of matrix reasoning items. In a first study, we calibrate the psychometric functioning of the items in the MaRs-IB in a large sample of adult participants (N = 1501). Using additive multilevel item structure models, we establish that the MaRs-IB has many desirable psychometric properties: its items span a wide range of difficulty, possess medium-to-large levels of discrimination, and exhibit robust associations between item complexity and difficulty. However, we also find that item clones are not always psychometrically equivalent and cannot be assumed to be exchangeable. In a second study, we demonstrate how experimenters can use the estimated item parameters to design new matrix reasoning tests using optimal item assembly. Specifically, we design and validate two new sets of test forms in an independent sample of adults (N = 600). We find these new tests possess good reliability and convergent validity with an established measure of matrix reasoning. We hope that the materials and results made available here will encourage experimenters to use the MaRs-IB in their research.

Inattentive responding can induce spurious associations between task behaviour and symptom measures.

Although online samples have many advantages for psychiatric research, some potential pitfalls of this approach are not widely understood. Here we detail circumstances in which spurious correlations may arise between task behaviour and symptom scores. The problem arises because many psychiatric symptom surveys have asymmetric score distributions in the general population, meaning that careless responders on these surveys will show apparently elevated symptom levels. If these participants are similarly careless in their task performance, this may result in a spurious association between symptom scores and task behaviour. We demonstrate this pattern of results in two samples of participants recruited online (total N = 779) who performed one of two common cognitive tasks. False-positive rates for these spurious correlations increase with sample size, contrary to common assumptions. Excluding participants flagged for careless responding on surveys abolished the spurious correlations, but exclusion based on task performance alone was less effective.

Improving the Reliability of Cognitive Task Measures: A Narrative Review.

Cognitive tasks are capable of providing researchers with crucial insights into the relationship between cognitive processing and psychiatric phenomena. However, many recent studies have found that task measures exhibit poor reliability, which hampers their usefulness for individual differences research. Here, we provide a narrative review of approaches to improve the reliability of cognitive task measures. Specifically, we introduce a taxonomy of experiment design and analysis strategies for improving task reliability. Where appropriate, we highlight studies that are exemplary for improving the reliability of specific task measures. We hope that this article can serve as a helpful guide for experimenters who wish to design a new task, or improve an existing one, to achieve sufficient reliability for use in individual differences research.

A neural substrate of sex-dependent modulation of motivation.

While there is emerging evidence of sex differences in decision-making behavior, the neural substrates that underlie such differences remain largely unknown. Here we demonstrate that in mice performing a value-based decision-making task, while choices are similar between the sexes, motivation to engage in the task is modulated by action value more strongly in females than in males. Inhibition of activity in anterior cingulate cortex (ACC) neurons that project to the dorsomedial striatum (DMS) preferentially disrupts this relationship between value and motivation in females, without affecting choice in either sex. In line with these effects, in females compared to males, ACC-DMS neurons have stronger representations of negative outcomes and more neurons are active when the value of the chosen option is low. By contrast, the representation of each choice is similar between the sexes. Thus, we identify a neural substrate that contributes to sex-specific modulation of motivation by value.

Anxiety, avoidance, and sequential evaluation.

Anxiety disorders are characterized by a range of aberrations in the processing of and response to threat, but there is little clarity what core pathogenesis might underlie these symptoms. Here we propose that a particular set of unrealistically pessimistic assumptions can distort an agent's behavior and underlie a host of seemingly disparate anxiety symptoms. We formalize this hypothesis in a decision theoretic analysis of maladaptive avoidance and a reinforcement learning model, which shows how a localized bias in beliefs can formally explain a range of phenomena related to anxiety. The core observation, implicit in standard decision theoretic accounts of sequential evaluation, is that the potential for avoidance should be protective: if danger can be avoided later, it poses less threat now. We show how a violation of this assumption - via a pessimistic, false belief that later avoidance will be unsuccessful - leads to a characteristic, excessive propagation of fear and avoidance to situations far antecedent of threat. This single deviation can explain a range of features of anxious behavior, including exaggerated threat appraisals, fear generalization, and persistent avoidance. Simulations of the model reproduce laboratory demonstrations of abnormal decision making in anxiety, including in situations of approach-avoid conflict and planning to avoid losses. The model also ties together a number of other seemingly disjoint phenomena in anxious disorders. For instance, learning under the pessimistic bias captures a hypothesis about the role of anxiety in the later development of depression. The bias itself offers a new formalization of classic insights from the psychiatric literature about the central role of maladaptive beliefs about control and self-efficacy in anxiety. This perspective also extends previous computational accounts of beliefs about control in mood disorders, which neglected the sequential aspects of choice.

The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis.

Approach-avoidance conflict arises when the drives to pursue reward and avoid harm are incompatible. Previous neuroimaging studies of approach-avoidance conflict have shown large variability in reported neuroanatomical correlates. These prior studies have generally neglected to account for potential sources of variability, such as individual differences in choice preferences and modeling of hemodynamic response during conflict. In the present study, we controlled for these limitations using a hierarchical Bayesian model (HBM). This enabled us to measure participant-specific per-trial estimates of conflict during an approach-avoidance task. We also employed a variable epoch method to identify brain structures specifically sensitive to conflict. In a sample of 28 human participants, we found that only a limited set of brain structures [inferior frontal gyrus (IFG), right dorsolateral prefrontal cortex (dlPFC), and right pre-supplementary motor area (pre-SMA)] are specifically correlated with approach-avoidance conflict. These findings suggest that controlling for previous sources of variability increases the specificity of the neuroanatomical correlates of approach-avoidance conflict.

Relative insensitivity to time-out punishments induced by win-paired cues in a rat gambling task.

RATIONALE: Pairing rewarding outcomes with audiovisual cues in simulated gambling games increases risky choice in both humans and rats. However, the cognitive mechanism through which this sensory enhancement biases decision-making is unknown. OBJECTIVES: To assess the computational mechanisms that promote risky choice during gambling, we applied a series of reinforcement learning models to a large dataset of choices acquired from rats as they each performed one of two variants of a rat gambling task (rGT), in which rewards on "win" trials were delivered either with or without salient audiovisual cues. METHODS: We used a sampling technique based on Markov chain Monte Carlo to obtain posterior estimates of model parameters for a series of RL models of increasing complexity, in order to assess the relative contribution of learning about positive and negative outcomes to the latent valuation of each choice option on the cued and uncued rGT. RESULTS: Rats which develop a preference for the risky options on the rGT substantially down-weight the equivalent cost of the time-out punishments during these tasks. For each model tested, the reduction in learning from the negative time-outs correlated with the degree of risk preference in individual rats. We found no apparent relationship between risk preference and the parameters that govern learning from the positive rewards. CONCLUSIONS: The emergence of risk-preferring choice on the rGT derives from a relative insensitivity to the cost of the time-out punishments, as opposed to a relative hypersensitivity to rewards. This hyposensitivity to punishment is more likely to be induced in individual rats by the addition of salient audiovisual cues to rewards delivered on win trials.

Treating refractory mental illness with closed-loop brain stimulation: Progress towards a patient-specific transdiagnostic approach.

Mental disorders are a leading cause of disability, morbidity, and mortality among civilian and military populations. Most available treatments have limited efficacy, particularly in disorders where symptoms vary over relatively short time scales. Targeted modulation of neural circuits, particularly through open-loop deep brain stimulation (DBS), showed initial promise but has failed in blinded clinical trials. We propose a new approach, based on targeting neural circuits linked to functional domains that cut across diagnoses. Through that framework, which includes measurement of patients using six psychophysical tasks, we seek to develop a closed-loop DBS system that corrects dysfunctional activity in brain circuits underlying those domains. We present convergent preliminary evidence from functional neuroimaging, invasive human electrophysiology, and human brain stimulation experiments suggesting that this approach is feasible. Using the Emotional Conflict Resolution (ECR) task as an example, we show that emotion-related networks can be identified and modulated in individual patients. Invasive and non-invasive methodologies both identify a network between prefrontal cortex, cingulate cortex, insula, and amygdala. Further, stimulation in cingulate and amygdala changes patients' performance in ways that are linked to the task's emotional content. We present preliminary statistical models that predict this change and allow us to track it at a single-trial level. As these diagnostic and modeling strategies are refined and embodied in an implantable device, they offer the prospect of a new approach to psychiatric treatment and its accompanying neuroscience.

Predictors of Hypomania During Ventral Capsule/Ventral Striatum Deep Brain Stimulation.

Deep brain stimulation (DBS) of the ventral capsule/ventral striatum (VC/VS) is a novel therapy for neuropsychiatric disorders. Hypomania is a known complication of VC/VS DBS, but who is at risk is less understood. Factors such as family history, combined with details of DBS programming, might quantify that risk. The authors performed an iterative modeling procedure on a VC/VS DBS patient registry to identify key predictors. Hypomania was less common for men and for patients stimulated on the ventral right contact. It was more common with right monopolar stimulation. These findings may help to establish decision rules to reduce complications of VC/VS DBS.