Post-error action control is neurobehaviorally modulated under conditions of constant speeded response

Post-error slowing in anxiety and obsessive-compulsive disorders

Altered brain response to errors in anxiety and obsessive-compulsive disorders (OCD) suggests cognitive control abnormalities across both types of illness, but behavioral metrics of cognitive control function have yet to be compared in patients selected from these different diagnostic categories. Thus, we examined post-error slowing (PES), a behavioral adjustment that typically occurs after a mistake, in children and adolescents with and without a primary anxiety disorder (N = 103 anxiety and N = 28 healthy controls) and adolescents and adults with and without OCD (N = 118 OCD and N = 60 healthy controls) using a go/no-go task. Primary analyses tested for differences in PES between diagnostic groups (anxiety, OCD, healthy), controlling for age, overall reaction time, and overall accuracy. Results indicated that patients with anxiety disorders exhibited more post-error slowing than both patients with OCD and healthy volunteers. In contrast, participants with OCD did not differ from healthy volunteers in post-error slowing. In subgroup analyses restricted to adolescent participants (ages 13-17 years), more post-error slowing was observed in the anxiety disorders group compared with either the OCD or healthy groups. These data suggest that excessive post-error slowing, an index of behavioral adjustment following errors, may uniquely characterize patients with anxiety disorders relative to healthy individuals and those with OCD.

Pre-specified Anxiety Predicts Future Decision-Making Performances Under Different Temporally Constrained Conditions

In real-life circumstances, people occasionally require making forced decisions when encountering unpredictable events and situations that yield socially and privately unfavorable consequences. In order to prevent future negative consequences, it is beneficial to successfully predict future decision-making behaviors based on various types of information, including behavioral traits and/or psychological states. For this prospective purpose, the present study used the Iowa Gambling Task, which simulates multiple aspects of real-life decision-making processes, such as choice preference, selection and evaluation of output feedback, and investigated how anxiety profiles predict decision-making performances under conditions with different temporal pressures on task execution. To conduct a temporally causal analysis, we assessed the trait and state anxiety profiles of 33 young participants prior to the task and analyzed their subsequent decision-making performances. We separated two disadvantageous card decks with high rewards and losses into high- and middle-risk decks, and calculated local performance indexes for decision-making immediately after salient penalty events for the high-risk deck in addition to traditional global performance indexes concerning overall trial outcomes such as final winnings and net scores. For global decision-making, higher trait anxiety predicted more risky choices solely in the self-paced condition without temporal pressure. For local decision-making, state anxiety predicted risk-taking performances differently in the self- and forced-paced conditions. In the self-paced condition, higher state anxiety predicted higher risk-avoidance. In the forced-paced condition, higher state anxiety predicted more frequent choices of the middle-risk deck. These findings suggest not only that pre-specified anxiety profiles can effectively predict future decision-making behaviors under different temporal pressures, but also newly indicate that behavioral mechanisms for moderate risk-taking under an emergent condition should be focused on to effectively prevent future unfavorable consequences when actually encountering negative events.

Foraging Value, Risk Avoidance, and Multiple Control Signals: How the Anterior Cingulate Cortex Controls Value-based Decision-making

Recent work on the role of the ACC in cognition has focused on choice difficulty, action value, risk avoidance, conflict resolution, and the value of exerting control among other factors. A main underlying question is what are the output signals of ACC, and relatedly, what is their effect on downstream cognitive processes? Here we propose a model of how ACC influences cognitive processing in other brain regions that choose actions. The model builds on the earlier Predicted Response Outcome model and suggests that ACC learns to represent specifically the states in which the potential costs or risks of an action are high, on both short and long timescales. It then uses those cost signals as a basis to bias decisions to minimize losses while maximizing gains. The model simulates both proactive and reactive control signals and accounts for a variety of empirical findings regarding value-based decision-making.

Neural substrates underlying reconcentration for the preparation of an appropriate cognitive state to prevent future mistakes: a functional magnetic resonance imaging study

The ability to reconcentrate on the present situation by recognizing one’s own recent errors is a cognitive mechanism that is crucial for safe and appropriate behavior in a particular situation. However, an individual may not be able to adequately perform a subsequent task even if he/she recognize his/her own error; thus, it is hypothesized that the neural mechanisms underlying the reconcentration process are different from the neural substrates supporting error recognition. The present study performed a functional magnetic resonance imaging (fMRI) analysis to explore the neural substrates associated with reconcentration related to achieving an appropriate cognitive state, and to dissociate these brain regions from the neural substrates involved in recognizing one’s own mistake. This study included 44 healthy volunteers who completed an experimental procedure that was based on the Eriksen flanker task and included feedback regarding the results of the current trial. The hemodynamic response induced by each instance of feedback was modeled using a combination of the successes and failures of the current and subsequent trials in order to identify the neural substrates underlying the ability to reconcentrate for the next situation and to dissociate them from those involved in recognizing current errors. The fMRI findings revealed significant and specific activation in the dorsal aspect of the medial prefrontal cortex (MFC) when participants successfully reconcentrated on the task after recognizing their own error based on feedback. Additionally, this specific activation was clearly dissociated from the activation foci that occurred during error recognition. These findings indicate that the dorsal aspect of the MFC may be a distinct functional region that specifically supports the reconcentration process and that is associated with the prevention of successive errors when a human subject recognizes his/her own mistake. Furthermore, it is likely that this reconcentration mechanism acts as a trigger to perform successful post-error behavioral adjustments.

Impulsivity is Associated with Early Sensory Inhibition in Neurophysiological Processing of Affective Sounds

Impulsivity is widely related to socially problematic behaviors and psychiatric illness. Previous studies have investigated the relationship between response inhibition and impulsivity. However, no study has intensively examined how impulsivity correlates with automatic sensory processing before the drive for response inhibition to sensory inputs. Sensory gating (SG) is an automatic inhibitory function that attenuates the neural response to redundant sensory information and protects higher cognitive functions from the burst of information processing. Although SG functions abnormally in several clinical populations, there is very little evidence supporting SG changes in conjunction with impulsivity traits in non-clinical populations. The present study recruited healthy adults (n = 23) to conduct a neurophysiological experiment using a paired-click paradigm and self-report scales assessing impulsive behavioral traits. Auditory stimuli included not only a pure tone but also white noise to explore the differences in auditory-evoked potential (AEP) responses between the two stimuli. White noise is more affective than pure tones; therefore, we predicted that the SG of AEPs (P50, N100, and P200) for white noise would correlate more with self-reported impulsivity than with those for pure tones. Our main findings showed that SG of the P50 and P200 amplitudes significantly correlated with self-reported reward responsiveness and fun-seeking, respectively, only for white noise stimuli, demonstrating that higher-scoring impulsivity subcomponents were related to greater SG. Frequency-domain analyses also revealed that greater desynchronization of the beta band for the second white noise stimulus was associated with higher motor impulsivity scores, suggesting that an impulsivity-related change of SG was associated with attentional modulation. These findings indicate that the measurement of SG of white noise may be an efficient tool to evaluate impulsivity in non-clinical populations, and should also be applied to clinical populations.