The ability to inhibit ongoing responses that suddenly become inappropriate is essential for safe and effective interaction with an ever-changing and often unpredictable world. This ability is quantified by the stop-signal reaction time (SSRT), the completion time of an inhibitory process triggered by a signal to stop responding. Because SSRT cannot be directly observed, it must be inferred based on a model in which inhibitory (''stop'') and response (''go'') processes race with each other to control behavior. Inhibitory control is usually studied in the context of choice responses, but there has been increasing recent interest in what is often a key component of skilled behaviour, stopping a response that is timed to coincide with an anticipated event. We show that SSRT measurement via the commonly used independent race model fails for anticipated responses because the event signaling the need to stop changes the perception of the passage of time, due to the long known ''filled-interval illusion''. We propose a computational cognitive model of anticipated response inhibition that takes account of the distortion of time perception caused by the filled-interval illusion. We show that this model produces valid estimates of not only SSRT, but also another key process that determines inhibitory ability, lapses in attention. Our new model and accompanying Bayesian estimation procedures provide a solid basis for the burgeoning study of timed-action control.

Unified structural equation modeling (uSEM) implemented in the Group Iterative Multiple Model Estimation (GIMME) framework has recently been widely used for characterizing within-person network dynamics of behavioral and functional neuroimaging variables. Previous studies have established that GIMME accurately recovers the presence of relations between variables. However, recovery of relation directionality is less consistent, which is concerning given the importance of directionality estimates for many research questions. There is evidence that strong autoregressive relations may aid directionality recovery and indirect evidence that a novel version of GIMME allowing for multiple solutions could improve recovery when such relations are weak, but it remains unclear how these strategies perform under a range of study conditions. Using comprehensive simulations that varied the strength of autoregressive relations among other factors, this study evaluated the directionality recovery of two GIMME search strategies: 1) estimating autoregressive relations by default in the null model (GIMME-AR), and 2) generating multiple solution paths (GIMME-MS). Both strategies recovered directionality best – and were roughly equivalent in performance – when autoregressive relations were strong (e.g., β = .60). When they were weak (β <= .10), GIMME-MS displayed an advantage, although overall directionality recovery was modest. Analyses of empirical data in which autoregressive relations were characteristically strong (resting state fMRI) versus weak (daily diary) mirrored simulation results and confirmed that these strategies typically disagree on directionality when autoregressive relations are weak. Findings have important implications for psychological and neuroimaging applications of uSEM/GIMME and suggest specific contexts which allow researchers to place confidence in directionality results.

Deficits in response to reward and loss are implicated in antisocial personality disorder (ASPD) and psychopathy. This study examined sex differences in associations of neural response to reward and loss with triarchic model traits and ASPD symptoms. Functional neuroimaging data was collected during a monetary incentive delay task from 158 participants. We predicted that males high in ASPD would show greater neural response to reward anticipation and less neural response to loss. Analyses examining the triarchic model were exploratory. A significant sex by Boldness interaction was associated with left nucleus accumbens response during loss anticipation. There were also significant sex by ASPD associations with left nucleus accumbens and left amygdala activation during the loss feedback condition and left nucleus accumbens during loss anticipation. These results demonstrate the importance of considering the effects of sex and triarchic model traits when examining reward and loss processing in the context of antisocial behavior.

Adolescent risk-taking, including sensation seeking (SS), is often attributed to developmental changes in connectivity among brain regions implicated in cognitive control and reward processing. Despite considerable scientific and popular interest in this neurodevelopmental framework, there are few empirical investigations of adolescent network connectivity–let alone examinations of its links to SS behavior. The studies that have been done focus on mean-based approaches and leave unanswered questions about individual differences in neurodevelopment and behavior. The goal of this paper is to take a person-specific approach to the study of adolescent functional connectivity during reward processing, and to examine links between connectivity and self-reported SS behavior in 104 adolescents (MAge=19.3; SDAge=1.3). Using group iterative multiple model estimation (GIMME), person-specific connectivity during two neuroimaging runs of a monetary incentive delay task was estimated among 12 a priori brain regions of interest representing reward, cognitive, and salience networks. Two data-driven subgroups were detected, a finding that was consistent between both neuroimaging runs, but associations with SS were only found in the first run, potentially reflecting neural habituation in the second run. Specifically, the subgroup that had unique connections between reward-related regions had greater SS and showed a distinctive relation between connectivity strength in the reward network and SS. These findings provide novel evidence for heterogeneity in adolescent brain-behavior relations by showing that subsets of adolescents have unique associations between neural reward processing and SS. Findings have broader implications for future work on reward processing, as they demonstrate that brain-behavior relations may attenuate across runs.