Cortical ß Power Reflects a Neural Implementation of Decision Boundary Collapse in Speeded Decisions.

A prominent account of decision-making assumes that information is accumulated until a fixed response threshold is crossed. However, many decisions require weighting of information appropriately against time. Collapsing response thresholds are a mathematically optimal solution to this decision problem. However, our understanding of the neurocomputational mechanisms underlying dynamic response thresholds remains significantly incomplete. To investigate this issue, we used a multistage drift-diffusion model (DDM) and also analyzed EEG ß power lateralization (BPL). The latter served as a neural proxy for decision signals. We analyzed a large dataset (n = 863; 434 females and 429 males) from a speeded flanker task and data from an independent confirmation sample (n = 119; 70 females and 49 males). We showed that a DDM with collapsing decision thresholds, a process wherein the decision boundary reduces over time, captured participants' time-dependent decision policy more accurately than a model with fixed thresholds. Previous research suggests that BPL over motor cortices reflects features of a decision signal and that its peak, coinciding with the motor response, may serve as a neural proxy for the decision threshold. We show that BPL around the response decreased with increasing RTs. Together, our findings offer compelling evidence for the existence of collapsing decision thresholds in decision-making processes.

Transdiagnostic inflexible learning dynamics explain deficits in depression and schizophrenia.

Deficits in reward learning are core symptoms across many mental disorders. Recent work suggests that such learning impairments arise by a diminished ability to use reward history to guide behaviour, but the neuro-computational mechanisms through which these impairments emerge remain unclear. Moreover, limited work has taken a transdiagnostic approach to investigate whether the psychological and neural mechanisms that give rise to learning deficits are shared across forms of psychopathology. To provide insight into this issue, we explored probabilistic reward learning in patients diagnosed with major depressive disorder (n = 33) or schizophrenia (n = 24) and 33 matched healthy controls by combining computational modelling and single-trial EEG regression. In our task, participants had to integrate the reward history of a stimulus to decide whether it is worthwhile to gamble on it. Adaptive learning in this task is achieved through dynamic learning rates that are maximal on the first encounters with a given stimulus and decay with increasing stimulus repetitions. Hence, over the course of learning, choice preferences would ideally stabilize and be less susceptible to misleading information. We show evidence of reduced learning dynamics, whereby both patient groups demonstrated hypersensitive learning (i.e. less decaying learning rates), rendering their choices more susceptible to misleading feedback. Moreover, there was a schizophrenia-specific approach bias and a depression-specific heightened sensitivity to disconfirmational feedback (factual losses and counterfactual wins). The inflexible learning in both patient groups was accompanied by altered neural processing, including no tracking of expected values in either patient group. Taken together, our results thus provide evidence that reduced trial-by-trial learning dynamics reflect a convergent deficit across depression and schizophrenia. Moreover, we identified disorder distinct learning deficits.

Cholinergic modulation of motor sequence learning.

The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double-blind placebo-controlled crossover design, we tested 30 healthy young participants and showed that biperiden impairs the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4-25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha and beta bands over ipsilateral motor and bilateral parietal-occipital areas. The reduced early theta power during a repeated compared with random sequence, likely reflecting disengagement of top-down attention to sensory processes, was disrupted by biperiden. Alpha synchronization during repeated sequences reflects sensory gating and lower visuospatial attention requirements compared with visuomotor responses to random sequences. After biperiden, alpha synchronization was greater, potentially reflecting excessive visuospatial attention reduction, affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing repeated sequences and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning.

Beyond peaks and troughs: Multiplexed performance monitoring signals in the EEG.

With the discovery of event-related potentials elicited by errors more than 30 years ago, a new avenue of research on performance monitoring, cognitive control, and decision making emerged. Since then, the field has developed and expanded fulminantly. After a brief overview on the EEG correlates of performance monitoring, this article reviews recent advancements based on single-trial analyses using independent component analysis, multiple regression, and multivariate pattern classification. Given the close interconnection between performance monitoring and reinforcement learning, computational modeling and model-based EEG analyses have made a particularly strong impact. The reviewed findings demonstrate that error- and feedback-related EEG dynamics represent variables reflecting how performance-monitoring signals are weighted and transformed into an adaptation signal that guides future decisions and actions. The model-based single-trial analysis approach goes far beyond conventional peak-and-trough analyses of event-related potentials and enables testing mechanistic theories of performance monitoring, cognitive control, and decision making.

Motor cortical signals reflecting decision making and action preparation.

Decision making often requires accumulating evidence in favour of a particular option. When choices are expressed with a motor response, these actions are preceded by reductions in the power of oscillations in the alpha and beta range in motor cortices. For unimanual movements, these reductions are greater over the hemisphere contralateral to the response side. Such lateralizations are hypothesized to be an online index of the neural state of decisions as they develop over time of processing. In contrast, the lateralized readiness potential (LRP) is considered to selectively activate a response and appears shortly before the motor output. We investigated to what extent these neural signals reflect integration of decision evidence or more motor-related action preparation. Using two different experiments, we found that lateralization of alpha and beta power (APL and BPL, respectively) rapidly emerged after stimulus presentation, even when making an overt response was not yet possible. In contrast, we show that even after prolonged stimulus presentation, no LRP was present. Instead, the LRP emerged only after an imperative cue, prompting participants to indicate their choice. Furthermore, we could show that variations in sensory evidence strength modulate APL and BPL onset times, suggesting that integration of evidence is represented in these motor cortical signals. We conclude that APL and BPL reflect higher cognitive processes rather than pure action preparation, whereas LRP is more closely tied to motor performance. APL and BPL potentially encode decision information in motor areas serving the later preparation of overt decision output.

Feedback-related EEG dynamics separately reflect decision parameters, biases, and future choices.

Optimal decision making in complex environments requires dynamic learning from unexpected events. To speed up learning, we should heavily weight information that indicates state-action-outcome contingency changes and ignore uninformative fluctuations in the environment. Often, however, unrelated information is hard to ignore and can potentially bias our learning. Here we used computational modelling and EEG to investigate learning behaviour in a modified probabilistic choice task that introduced two task-irrelevant factors that were uninformative for optimal task performance, but nevertheless could potentially bias learning: pay-out magnitudes were varied randomly and, occasionally, feedback presentation was enhanced by visual surprise. We found that participants' overall good learning performance was biased by distinct effects of these non-normative factors. On the neural level, these parameters are represented in a dynamic and spatiotemporally dissociable sequence of EEG activity. Later in feedback processing the different streams converged on a central to centroparietal positivity reflecting a signal that is interpreted by downstream learning processes that adjust future behaviour.

Conflict- and error-related theta activities are coupled to BOLD signals in different brain regions.

Both conflict and error processing have been linked to the midfrontal theta power (4-8 Hz) increase as indicated by EEG studies and greater hemodynamic activity in the anterior midcingulate cortex (aMCC) as indicated by fMRI studies. Conveniently, the source of the midfrontal theta power was estimated in or nearby aMCC. However, previous studies using concurrent EEG and fMRI recordings in resting-state or other cognitive tasks observed only a negative relationship between theta power and BOLD signal in the brain regions typically showing task-related deactivations. In this study, we used a simultaneous EEG-fMRI technique to investigate a trial-by-trial coupling between theta power and hemodynamic activity during the performance of two conflict tasks. Independent component analysis (ICA) was applied to denoise the EEG signal and select individual midfrontal EEG components, whereas group ICA was applied to fMRI data to obtain a functional parcellation of the frontal cortex. Using a linear mixed-effect model, theta power was coupled with the peak of hemodynamic responses from various frontal, cingulate, and insular cortical sites to unravel the potential brain sources that contribute to conflict- and error-related theta variability. Although several brain regions exhibited conflict-related increases in hemodynamic activity, the conflict pre-response theta showed only a negative correlation to BOLD signal in the midline area 9 (MA9), a region exhibiting conflict-sensitive deactivation. Conversely, and more expectedly, error-related theta showed a positive relationship to activity in the aMCC. Our results provide novel evidence suggesting that the amplitude of pre-response theta reflects the process of active inhibition that suppresses the MA9 activity. This process is affected independently by the stimulus congruency, reaction times variance, and is susceptible to the time-on-task effect. Finally, it predicts the commitment of an omission error. Together, our findings highlight that conflict- and error-related theta oscillations represent fundamentally different processes.

Disentangling performance-monitoring signals encoded in feedback-related EEG dynamics.

The feedback-related negativity (FRN) is a well-established electrophysiological correlate of feedback-processing. However, there is still an ongoing debate whether the FRN is driven by negative or positive reward prediction errors (RPE), valence of feedback, or mere surprise. Our study disentangles independent contributions of valence, surprise, and RPE on the feedback-related neuronal signal including the FRN and P3 components using the statistical power of a sample of N = 992 healthy individuals. The participants performed a modified time-estimation task, while EEG from 64 scalp electrodes was recorded. Our results show that valence coding is present during the FRN with larger amplitudes for negative feedback. The FRN is further modulated by surprise in a valence-dependent way being more positive-going for surprising positive outcomes. The P3 was strongly driven by both global and local surprise, with larger amplitudes for unexpected feedback and local deviants. Behavioral adaptations after feedback and FRN just show small associations. Results support the theory of the FRN as a representation of a signed RPE. Additionally, our data indicates that surprising positive feedback enhances the EEG response in the time window of the P3. These results corroborate previous findings linking the P3 to the evaluation of PEs in decision making and learning tasks.

Deep Brain Stimulation Reduces Conflict-Related Theta and Error-Related Negativity in Patients With Obsessive-Compulsive Disorder.

OBJECTIVES: Obsessive-compulsive disorder (OCD) is a psychiatric disorder with alterations of cortico-striato-thalamo-cortical loops and impaired performance monitoring. Electrophysiological markers such as conflict-related medial frontal theta (MFT) and error-related negativity (ERN) may be altered by clinically effective deep brain stimulation (DBS) of the anterior limb of the internal capsule and nucleus accumbens (ALIC/NAc). We hypothesized that ALIC/NAc DBS modulates electrophysiological performance monitoring markers. MATERIALS AND METHODS: Fifteen patients (six male) with otherwise treatment-refractory OCD receiving ALIC/NAc DBS performed a flanker task with EEG recordings at three sessions: presurgery and at follow-up with DBS on and off. We examined MFT, ERN, and task performance. Furthermore, we investigated interrelations with clinical efficacy and then explored the influence of the location of individual stimulation volumes on EEG modulations. RESULTS: MFT and ERN were significantly attenuated by DBS with differences most pronounced between presurgery and DBS-on states. Also, we observed reaction time slowing for erroneous responses during DBS-off. Larger presurgery ERN amplitudes were associated with decreased clinical efficacy. Exploratory anatomical analyses suggested that stimulation volumes encompassing the NAc were associated with MFT modulation, whereas ALIC stimulation was associated with modulation of the ERN and clinical efficacy. CONCLUSION: ALIC/NAc DBS diminished MFT and ERN, demonstrating modulation of the medial frontal performance monitoring system in OCD. Furthermore, our findings encourage further studies to explore the ERN as a potential predictor for clinical efficacy.

Unbiased post-error slowing in interference tasks: A confound and a simple solution.

We typically slow down after committing an error, an effect termed post-error slowing (PES). Traditionally, PES has been calculated by subtracting post-correct from post-error RTs. Dutilh et al. (Journal of Mathematical Psychology, 56(3), 208-216, 2012), however, showed PES values calculated in this way are potentially biased. Therefore, they proposed to compute robust PES scores by subtracting pre-error RTs from post-error RTs. Based on data from a large-scale study using the flanker task, we show that both traditional and robust PES estimates can be biased. The source of the bias are differential imbalances in the percentage of congruent vs. incongruent post-correct, pre-error, and post-error trials. Specifically, we found that post-correct, pre-error, and post-error trials were more likely to be congruent than incongruent, with the size of the imbalance depending on the trial type as well as the length of the response-stimulus interval (RSI). In our study, for trials preceded by a 700-ms RSI, the percentages of congruent trials were 62% for post-correct trials, 66% for pre-error trials, and 56% for post-error trials. Relative to unbiased estimates, these imbalances inflated traditional PES estimates by 37% (9 ms) and robust PES estimates by 42% (16 ms) when individual-participant means were calculated. When individual-participant medians were calculated, the biases were even more pronounced (40% and 50% inflation, respectively). To obtain unbiased PES scores for interference tasks, we propose to compute unweighted individual-participant means by initially calculating mean RTs for congruent and incongruent trials separately, before averaging congruent and incongruent mean RTs to calculate means for post-correct, pre-error and post-error trials.

Neurophysiology of performance monitoring and adaptive behavior.

Successful goal-directed behavior requires not only correct action selection, planning, and execution but also the ability to flexibly adapt behavior when performance problems occur or the environment changes. A prerequisite for determining the necessity, type, and magnitude of adjustments is to continuously monitor the course and outcome of one's actions. Feedback-control loops correcting deviations from intended states constitute a basic functional principle of adaptation at all levels of the nervous system. Here, we review the neurophysiology of evaluating action course and outcome with respect to their valence, i.e., reward and punishment, and initiating short- and long-term adaptations, learning, and decisions. Based on studies in humans and other mammals, we outline the physiological principles of performance monitoring and subsequent cognitive, motivational, autonomic, and behavioral adaptation and link them to the underlying neuroanatomy, neurochemistry, psychological theories, and computational models. We provide an overview of invasive and noninvasive systemic measures, such as electrophysiological, neuroimaging, and lesion data. We describe how a wide network of brain areas encompassing frontal cortices, basal ganglia, thalamus, and monoaminergic brain stem nuclei detects and evaluates deviations of actual from predicted states indicating changed action costs or outcomes. This information is used to learn and update stimulus and action values, guide action selection, and recruit adaptive mechanisms that compensate errors and optimize goal achievement.

Neural and behavioral traces of error awareness.

Monitoring for errors and behavioral adjustments after errors are essential for daily life. A question that has not been addressed systematically yet, is whether consciously perceived errors lead to different behavioral adjustments compared to unperceived errors. Our goal was to develop a task that would enable us to study different commonly observed neural correlates of error processing and post-error adjustments in their relation to error awareness and accuracy confidence in a single experiment. We assessed performance in a new number judgement error awareness task in 70 participants. We used multiple, robust, single-trial EEG regressions to investigate the link between neural correlates of error processing (e.g., error-related negativity (ERN) and error positivity (Pe)) and error awareness. We found that only aware errors had a slowing effect on reaction times in consecutive trials, but this slowing was not accompanied by post-error increases in accuracy. On a neural level, error awareness and confidence had a modulating effect on both the ERN and Pe, whereby the Pe was most predictive of participants' error awareness. Additionally, we found partial support for a mediating role of error awareness on the coupling between the ERN and behavioral adjustments in the following trial. Our results corroborate previous findings that show both an ERN/Pe and a post-error behavioral adaptation modulation by error awareness. This suggests that conscious error perception can support meta-control processes balancing the recruitment of proactive and reactive control. Furthermore, this study strengthens the role of the Pe as a robust neural index of error awareness.

A brief demonstration of frontostriatal connectivity in OCD patients with intracranial electrodes.

Closed-loop neuromodulation is presumed to be the logical evolution for improving the effectiveness of deep brain stimulation (DBS) treatment protocols (Widge et al., 2018). Identifying symptom-relevant biomarkers that provide meaningful feedback to stimulator devices is an important initial step in this direction. This report demonstrates a technique for assaying neural circuitry hypothesized to contribute to OCD and DBS treatment outcomes. We computed phase-lag connectivity between LFPs and EEGs in thirteen treatment-refractory OCD patients. Simultaneous recordings from scalp EEG and externalized DBS electrodes in the ventral capsule/ventral striatum (VC/VS) were collected at rest during the perioperative treatment stage. Connectivity strength between midfrontal EEG sensors and VC/VS electrodes correlated with baseline OCD symptoms and 12-month posttreatment OCD symptoms. Results are qualified by a relatively small sample size, and limitations regarding the conclusiveness of VS and mPFC as neural generators given some concerns about volume conduction. Nonetheless, findings are consistent with treatment-relevant tractography findings and theories that link frontostriatal hyperconnectivity to the etiopathogenesis of OCD. Findings support the continued investigation of connectivity-based assays for aiding in determination of optimal stimulation location, and are an initial step towards the identification of biomarkers that can guide closed-loop neuromodulation systems.

The human habenula is responsive to changes in luminance and circadian rhythm.

The habenula is a pivotal structure in the neural network that implements various forms of cognitive and motivational functions and behaviors. Moreover, it has been suggested to be part of the brain's circadian system, not at least because habenular neurons are responsive to retinal illumination and exhibit circadian modulations of their firing patterns in animal research. However, no study has directly investigated the human habenula in this regard. We developed a paradigm in which alternating phases of high and low luminance are used to study human habenular functioning. In two experiments with independent samples, fMRI data of 24 healthy participants were acquired at a field strength of 7T, and of 21 healthy participants at 3T. Region of interest analyses revealed that the human habenula is responsive to light as well, resulting in a decrease in activation when a change in luminance occurs. Although this pattern is not predicted by animal research, we were able to replicate this finding in a second independent data set. Furthermore, we demonstrate that the strength of decrease in activation is modulated in a circadian fashion, being more strongly deactivated in morning than in afternoon sessions. Taken together, these findings provide strong evidence that changes in illumination elicit changes in habenular activation and that these changes appear to be more pronounced in the morning than in the afternoon.

Serotonin reuptake inhibitors and serotonin transporter genotype modulate performance monitoring functions but not their electrophysiological correlates.

Serotonin (5-HT) has been hypothesized to be implicated in performance monitoring by promoting behavioral inhibition in the face of aversive events. However, it is unclear whether this is restricted to external (punishment) or includes internal (response errors) events. The aim of the current study was to test whether higher 5-HT levels instigate inhibition specifically in the face of errors, measured as post-error slowing (PES), and whether this is represented in electrophysiological correlates of error processing, namely error-related negativity (ERN) and positivity. Therefore, from a large sample of human subjects (n = 878), two extreme groups were formed regarding hypothesized high and low 5-HT transporter (5-HTT) expression based on 5-HTTLPR and two additional single nucleotide polymorphisms (rs25531, rs25532). Seventeen higher (LL) and 15 lower (SS) expressing Caucasian subjects were administered the selective serotonin reuptake inhibitor (SSRI) citalopram (10 mg) intravenously in a double-blind crossover design. We found pharmacogenetic evidence for a role of 5-HT in mediating PES: SSRI administration increased PES in both genetic groups, and SS subjects displayed higher PES. These effects were absent on post-conflict slowing. However, ERN and error positivity were unaffected by pharmacogenetic factors, but ERN was decoupled from behavioral adaptation by SSRI administration in the LL group. Thus, pharmacogenetic evidence suggests that increased 5-HT levels lead to behavioral inhibition in the context of internal aversive events, but electrophysiological correlates of performance monitoring appear unrelated to the 5-HT system. Therefore, our findings are consistent with theories suggesting that 5-HT mediates the link between aversive processing and inhibition.

An Obesity-Predisposing Variant of the FTO Gene Regulates D2R-Dependent Reward Learning.

Variations in the fat mass and obesity-associated (FTO) gene are linked to obesity. However, the underlying neurobiological mechanisms by which these genetic variants influence obesity, behavior, and brain are unknown. Given that Fto regulates D2/3R signaling in mice, we tested in humans whether variants in FTO would interact with a variant in the ANKK1 gene, which alters D2R signaling and is also associated with obesity. In a behavioral and fMRI study, we demonstrate that gene variants of FTO affect dopamine (D2)-dependent midbrain brain responses to reward learning and behavioral responses associated with learning from negative outcome in humans. Furthermore, dynamic causal modeling confirmed that FTO variants modulate the connectivity in a basic reward circuit of meso-striato-prefrontal regions, suggesting a mechanism by which genetic predisposition alters reward processing not only in obesity, but also in other disorders with altered D2R-dependent impulse control, such as addiction. Significance statement: Variations in the fat mass and obesity-associated (FTO) gene are associated with obesity. Here we demonstrate that variants of FTO affect dopamine-dependent midbrain brain responses and learning from negative outcomes in humans during a reward learning task. Furthermore, FTO variants modulate the connectivity in a basic reward circuit of meso-striato-prefrontal regions, suggesting a mechanism by which genetic vulnerability in reward processing can increase predisposition to obesity.

Differential modulation of reinforcement learning by D2 dopamine and NMDA glutamate receptor antagonism.

The firing pattern of midbrain dopamine (DA) neurons is well known to reflect reward prediction errors (PEs), the difference between obtained and expected rewards. The PE is thought to be a crucial signal for instrumental learning, and interference with DA transmission impairs learning. Phasic increases of DA neuron firing during positive PEs are driven by activation of NMDA receptors, whereas phasic suppression of firing during negative PEs is likely mediated by inputs from the lateral habenula. We aimed to determine the contribution of DA D2-class and NMDA receptors to appetitively and aversively motivated reinforcement learning. Healthy human volunteers were scanned with functional magnetic resonance imaging while they performed an instrumental learning task under the influence of either the DA D2 receptor antagonist amisulpride (400 mg), the NMDA receptor antagonist memantine (20 mg), or placebo. Participants quickly learned to select ("approach") rewarding and to reject ("avoid") punishing options. Amisulpride impaired both approach and avoidance learning, while memantine mildly attenuated approach learning but had no effect on avoidance learning. These behavioral effects of the antagonists were paralleled by their modulation of striatal PEs. Amisulpride reduced both appetitive and aversive PEs, while memantine diminished appetitive, but not aversive PEs. These data suggest that striatal D2-class receptors contribute to both approach and avoidance learning by detecting both the phasic DA increases and decreases during appetitive and aversive PEs. NMDA receptors on the contrary appear to be required only for approach learning because phasic DA increases during positive PEs are NMDA dependent, whereas phasic decreases during negative PEs are not.

Interactive effects of citalopram and serotonin transporter genotype on neural correlates of response inhibition and attentional orienting.

The brain's serotonergic (5-HT) system has been implicated in controlling impulsive behavior and attentional orienting and linked to impulse control and anxiety related disorders. However, interactions between genotypical variation and responses to serotonergic drugs impede both treatment efficacy and neuroscientific research. We examine behavioral and electrophysiological responses to acute intravenous administration of a selective serotonin reuptake inhibitor (SSRI) while controlling for major genetic differences regarding 5-HT transporter (5-HTT) genotypes. Out of a genotyped sample of healthy Caucasian subjects (n=878) two extreme-groups regarding 5-HTT genotypes were selected (n=32). A homozygous high-expressing group based on tri-allelic 5-HTTLPR and rs25532 (LAC/LAC=LL) was compared to homozygous S allele carriers (SS). Both groups were administered a low dose of citalopram (10mg) intravenously in a double blind crossover fashion and performed a novelty NoGo paradigm while high density EEG was recorded. Interactions between drug and genotype were seen on both behavioral and neurophysiological levels. Reaction slowing following inhibitory events was decreased by the administration of citalopram in the LL but not SS group. This was accompanied by decreases in the amplitude of the inhibitory N2 EEG component and the P3b in the LL group, which was not seen in the SS group. SS subjects showed an increase in P3a amplitudes following SSRI administration to any type of deviant stimulus possibly reflecting increased attentional capture. The acute SSRI response on inhibitory processes and attentional orienting interacts with genotypes regulating 5-HTT gene expression. SS subjects may show increased attentional side effects reflected in increases in P3a amplitudes which could contribute to treatment discontinuation. Inhibitory processes and their neural correlates are affected only in LL subjects. These findings may indicate an underlying mechanism that could relate genotypical differences to altered side effect profiles and drug responses and are compatible with a non-monotonic relationship between 5-HT levels and optimal functioning.

Success versus failure in cognitive control: Meta-analytic evidence from neuroimaging studies on error processing.

Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.

Methamphetamine-induced adaptation of learning rate dynamics depend on baseline performance.

The ability to calibrate learning according to new information is a fundamental component of an organism's ability to adapt to changing conditions. Yet, the exact neural mechanisms guiding dynamic learning rate adjustments remain unclear. Catecholamines appear to play a critical role in adjusting the degree to which we use new information over time, but individuals vary widely in the manner in which they adjust to changes. Here, we studied the effects of a low dose of methamphetamine (MA), and individual differences in these effects, on probabilistic reversal learning dynamics in a within-subject, double-blind, randomized design. Participants first completed a reversal learning task during a drug-free baseline session to provide a measure of baseline performance. Then they completed the task during two sessions, one with MA (20 mg oral) and one with placebo (PL). First, we showed that, relative to PL, MA modulates the ability to dynamically adjust learning from prediction errors. Second, this effect was more pronounced in participants who performed poorly at baseline. These results present novel evidence for the involvement of catecholaminergic transmission on learning flexibility and highlights that baseline performance modulates the effect of the drug.