These data support the notion that WM training improves near-transfer task performance and may enhance the effects of EFT DD in a subset of alcohol-dependent individuals trapped within the narrowest temporal window. Rate-dependent changes highlight that we should attend to baseline performance to better identify individuals who would most benefit from an intervention.

Research on the rate at which people discount the value of future rewards has become increasingly prevalent as discount rate has been shown to be associated with many unhealthy patterns of behavior such as drug abuse, gambling, and overeating. fMRI research points to a fronto-parietal-limbic pathway that is active during decisions between smaller amounts of money now and larger amounts available after a delay. Researchers in this area have used different variants of delay discounting tasks and reported various contrasts between choice trials of different types from these tasks. For instance, researchers have compared 1) choices of delayed monetary amounts to choices of the immediate monetary amounts, 2) ‘hard’ choices made near one’s point of indifference to ‘easy’ choices that require little thought, and 3) trials where an immediate choice is available versus trials where one is unavailable, regardless of actual eventual choice. These differences in procedure and analysis make comparison of results across studies difficult. In the present experiment, we designed a delay discounting task with the intended capability of being able to construct contrasts of all three comparisons listed above while optimizing scanning time to reduce costs and avoid participant fatigue. This was accomplished with an algorithm that customized the choice trials presented to each participant with the goal of equalizing choice trials of each type. We compared this task, which we refer to here as the individualized discounting task (IDT), to two other delay discounting tasks previously reported in the literature (McClure et al., 2004; Amlung et al., 2014) in 18 participants. Results show that the IDT can examine each of the three contrasts mentioned above, while yielding a similar degree of activation as the reference tasks. This suggests that this new task could be used in delay discounting fMRI studies to allow researchers to more easily compare their results to a majority of previous research while minimizing scanning duration.

The collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eye’s orbit using a 1.5-min calibration scan. Here, we provide confirmatory validation of the PEER method’s ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individuals (median angular deviation < 2°). Then, we examine variations in the predictive validity of PEER models across individuals in a subset of data (n = 448) from the Child Mind Institute Healthy Brain Network Biobank, identifying head motion as a primary determinant. Finally, we accurately classify which of the two movies is being watched based on the predicted eye gaze patterns (area under the curve = 0.90 ± 0.02) and map the neural correlates of eye movements derived from PEER. PEER is a freely available and easy-to-use tool for determining eye fixations during naturalistic viewing.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.