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.

Unraveling the influence of trial-based motivational changes on performance monitoring stages in a flanker task.

Performance monitoring (PM) is a vital component of adaptive behavior and known to be influenced by motivation. We examined effects of potential gain (PG) and loss avoidance (LA) on neural correlates of PM at different processing stages, using a task with trial-based changes in these motivational contexts. Findings suggest more attention is allocated to the PG context, with higher amplitudes for respective correlates of stimulus and feedback processing. The PG context favored rapid responses, while the LA context emphasized accurate responses. Lower response thresholds in the PG context after correct responses derived from a drift-diffusion model also indicate a more approach-oriented response style in the PG context. This cognitive shift is mirrored in neural correlates: negative feedback in the PG context elicited a higher feedback-related negativity (FRN) and higher theta power, whereas positive feedback in the LA context elicited higher P3a and P3b amplitudes, as well as higher theta power. There was no effect of motivational context on response-locked brain activity. Given the similar frequency of negative feedback in both contexts, the elevated FRN and theta power in PG trials cannot be attributed to variations in reward prediction error. The observed variations in the FRN indicate that the effect of outcome valence is modulated by motivational salience.

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.

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.

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.

Performance monitoring in obsessive-compulsive disorder: Insights from internal capsule/nucleus accumbens deep brain stimulation.

BACKGROUND: Symptoms of obsessive-compulsive disorder (OCD) are partly related to impaired cognitive control processes and theta modulations constitute an important electrophysiological marker for cognitive control processes such as signaling negative performance feedback in a fronto-striatal network. Deep brain stimulation (DBS) targeting the anterior limb of the internal capsule (ALIC)/nucleus accumbens (NAc) shows clinical efficacy in OCD, while the exact influence on the performance monitoring system remains largely unknown. METHODS: Seventeen patients with treatment-refractory OCD performed a probabilistic reinforcement learning task. Analyses were focused on 4-8 Hz (theta) power, intertrial phase coherence (ITPC) and debiased weighted Phase-Lag Index (dwPLI) in response to negative performance feedback. Combined EEG and local field potential (LFP) recordings were obtained shortly after DBS electrode implantation to investigate fronto-striatal network modulations. To assess the impact of clinically effective DBS on negative performance feedback modulations, EEG recordings were obtained pre-surgery and at follow-up with DBS on and off. RESULTS: Medial frontal cortex ITPC, striatal ITPC and striato-frontal dwPLI were increased following negative performance feedback. Decreased right-lateralized dwPLI was associated with pre-surgery symptom severity. ITPC was globally decreased during DBS-off. CONCLUSION: We observed a theta phase coherence mediated fronto-striatal performance monitoring network. Within this network, decreased connectivity was related to increased OCD symptomatology, consistent with the idea of impaired cognitive control in OCD. While ALIC/NAc DBS decreased theta network activity globally, this effect was unrelated to clinical efficacy and performance monitoring.

Decreased transfer of value to action in Tourette syndrome.

OBJECTIVE: Tourette syndrome is a neurodevelopmental disorder putatively associated with a hyperdopaminergic state. Therefore, it seems plausible that excessive dopamine transmission in Tourette syndrome alters the ability to learn based on rewards and punishments. We tested whether Tourette syndrome patients exhibited altered reinforcement learning and corresponding feedback-related EEG deflections. METHODS: We used a reinforcement learning task providing factual and counterfactual feedback in a sample of 15 Tourette syndrome patients and matched healthy controls whilst recording EEG. The paradigm presented various reward probabilities to enforce adaptive adjustments. We employed a computational model to derive estimates of the prediction error, which we used for single-trial regression analysis of the EEG data. RESULTS: We found that Tourette syndrome patients showed increased choice stochasticity compared to controls. The feedback-related negativity represented an axiomatic prediction error for factual feedback and did not differ between groups. We observed attenuated P3a modulation specifically for factual feedback in Tourette syndrome patients, representing impaired coding of attention allocation. CONCLUSION: Our findings indicate that cortical prediction error coding is unaffected by Tourette syndrome. Nonetheless, the transfer of learned values into choice formation is degraded, in line with a hyperdopaminergic state.

The feedback-related negativity indexes prediction error in active but not observational learning.

Reinforcement learning (RL) theory states that learning is driven by prediction errors (PEs)-the discrepancy between the predicted and actual outcome of an action. When participants learn from their own actions, PEs correlate with the feedback-related negativity (FRN), but it is not clear if the FRN reflects a PE in observational learning. We use a model-based regression analysis of single-trial event-related potentials to determine if the FRN in observational learning is PE driven. Twenty participants (16 female) learned the stimulus-outcome contingencies for a probabilistic three-armed bandit task. They played in pairs, with the acting and observing player switching every one to three trials. An RL-learning algorithm was fit to participants' choices in the task to extract individual PE estimates for every trial of the experiment. In the acting condition, model-estimated PEs covaried positively with neural signal at electrode FCz, 200-350 ms after outcome presentation, which is a typical time frame for the FRN. There was no PE effect in the observation condition in the same time frame. From 300 ms the outcome correlated negatively with the frontal P300 component at FCz and parietal P300 at Pz. At Pz the effect was greater in the acting than the observing condition. The frontal and parietal P300 components have been linked to attentional reorienting and stimulus value updating, respectively. These findings indicate that observed outcomes undergo processing that is distinguishable from directly experienced outcomes in the time windows of the FRN and P3b but that attention dedicated to the two outcomes types is comparable.

Cortical beta power reflects decision dynamics and uncovers multiple facets of post-error adaptation.

Adapting to errors quickly is essential for survival. Reaction slowing after errors is commonly observed but whether this slowing is adaptive or maladaptive is unclear. Here, we analyse a large dataset from a flanker task using two complementary approaches: a multistage drift-diffusion model, and the lateralisation of EEG beta power as a time-resolved index of choice formation. Fitted model parameters and their independently measured neuronal proxies in beta power convergently show a complex interplay of multiple mechanisms initiated after mistakes. Suppression of distracting evidence, response threshold increase, and reduction of evidence accumulation cause slow and accurate post-error responses. This data provides evidence for both adaptive control and maladaptive orienting after errors yielding an adaptive net effect - a decreased likelihood to repeat mistakes. Generally, lateralised beta power provides a non-invasive readout of action selection for the study of speeded cognitive control processes.

Planning Your Way: How Humans Strategically Evaluate Prospective Decisions.

We are capable of planning ahead by incorporating dynamic factors influencing future choices. In this issue of Neuron, Kolling et al. (2018) present fMRI results of a novel task that demonstrates how humans evaluate alternative environments by prospectively incorporating their characteristics over time and account for their own decision tendencies.

Short-term reward experience biases inference despite dissociable neural correlates.

Optimal decision-making employs short-term rewards and abstract long-term information based on which of these is deemed relevant. Employing short- vs. long-term information is associated with different learning mechanisms, yet neural evidence showing that these two are dissociable is lacking. Here we demonstrate that long-term, inference-based beliefs are biased by short-term reward experiences and that dissociable brain regions facilitate both types of learning. Long-term inferences are associated with dorsal striatal and frontopolar cortex activity, while short-term rewards engage the ventral striatum. Stronger concurrent representation of reward signals by mediodorsal striatum and frontopolar cortex correlates with less biased, more optimal individual long-term inference. Moreover, dynamic modulation of activity in a cortical cognitive control network and the medial striatum is associated with trial-by-trial control of biases in belief updating. This suggests that counteracting the processing of optimally to-be-ignored short-term rewards and cortical suppression of associated reward-signals, determines long-term learning success and failure.

An Update on the Role of Serotonin and its Interplay with Dopamine for Reward.

The specific role of serotonin and its interplay with dopamine (DA) in adaptive, reward guided behavior as well as drug dependance, still remains elusive. Recently, novel methods allowed cell type specific anatomical, functional and interventional analyses of serotonergic and dopaminergic circuits, promising significant advancement in understanding their functional roles. Furthermore, it is increasingly recognized that co-release of neurotransmitters is functionally relevant, understanding of which is required in order to interpret results of pharmacological studies and their relationship to neural recordings. Here, we review recent animal studies employing such techniques with the aim to connect their results to effects observed in human pharmacological studies and subjective effects of drugs. It appears that the additive effect of serotonin and DA conveys significant reward related information and is subjectively highly euphorizing. Neither DA nor serotonin alone have such an effect. This coincides with optogenetically targeted recordings in mice, where the dopaminergic system codes reward prediction errors (PE), and the serotonergic system mainly unsigned PE. Overall, this pattern of results indicates that joint activity between both systems carries essential reward information and invites parallel investigation of both neurotransmitter systems.

Comparing the error-related negativity across groups: The impact of error- and trial-number differences.

The error-related negativity (ERN or Ne) is increasingly being investigated as a marker discriminating interindividual factors and moves toward a surrogate marker for disorders or interventions. Although reproducibility and validity of neuroscientific and psychological research has been criticized, clear data on how different quantification methods of the ERN and their relation to available trial numbers affect within- and across-participant studies is sparse. Within a large sample of 863 healthy human participants, we demonstrate that, across participants, the number of errors correlates with the amplitude of the ERN independently of the number of errors included in ERN quantification per participant, constituting a possible confound when such variance is unaccounted for. Additionally, we find that ERN amplitudes reach high consistency within participants at lower trial numbers, yet when comparisons between groups of participants are desired, increasing error-trial numbers lead to higher statistical power. We derive concrete suggestions for specific types of analyses, which may help researchers to more effectively design studies and analyze error-related EEG data with the most appropriate measurement technique for the question at hand and trial number available.

Gender Influences on Brain Responses to Errors and Post-Error Adjustments.

Sexual dimorphisms have been observed in many species, including humans, and extend to the prevalence and presentation of important mental disorders associated with performance monitoring malfunctions. However, precisely which underlying differences between genders contribute to the alterations observed in psychiatric diseases is unknown. Here, we compare behavioural and neural correlates of cognitive control functions in 438 female and 436 male participants performing a flanker task while EEG was recorded. We found that males showed stronger performance-monitoring-related EEG amplitude modulations which were employed to predict subjects' genders with ~72% accuracy. Females showed more post-error slowing, but both samples did not differ in regard to response-conflict processing and coupling between the error-related negativity (ERN) and consecutive behavioural slowing. Furthermore, we found that the ERN predicted consecutive behavioural slowing within subjects, whereas its overall amplitude did not correlate with post-error slowing across participants. These findings elucidate specific gender differences in essential neurocognitive functions with implications for clinical studies. They highlight that within- and between-subject associations for brain potentials cannot be interpreted in the same way. Specifically, despite higher general amplitudes in males, it appears that the dynamics of coupling between ERN and post-error slowing between men and women is comparable.

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.

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.

Dual serotonergic signals: a key to understanding paradoxical effects?

Neuroscientists have been puzzled by the fact that acute administration of a selective serotonin reuptake inhibitor (SSRI) produces results that are, at times, compatible with either decreases or increases in serotonergic neurotransmission. Furthermore, the underlying cause of the delayed onset of antidepressant effects of SSRI treatment has remained obscure. It has recently been reported that serotonergic raphe neurons co-release glutamate and that serotonergic and glutamatergic components constitute a dual signal with behaviorally distinct effects. We discuss the consequences of these novel findings and propose a framework for understanding the controversial effects of acute SSRI administration. Furthermore, we suggest that the delayed remedial onset of SSRI treatment could be explained by an initial reduction of the glutamatergic component of the dual serotonergic signal.

When is the time for a change? Decomposing dynamic learning rates.

Humans flexibly weight incoming evidence when updating beliefs and adjusting behavior. In the current issue of Neuron, McGuire et al. (2014) show how distinct neuronal correlates of main factors underlying this weighting converge on a common mechanism driving belief updates.

Neural mechanisms and temporal dynamics of performance monitoring.

Successful goal-directed behavior critically depends on performance monitoring, a set of cognitive and affective functions determining whether adaptive control is needed and, if so, which type and magnitude is required. Knowledge of the brain structures involved in such a process has grown enormously, although the time course of performance-monitoring (PM) activity remains poorly understood. Here, we review evidence from EEG recordings in humans and show that monitored events elicit a rather uniform sequence of cortical activity reflecting the detection, accumulation, and weighting of evidence for the necessity to adapt and (re)act. We link the EEG findings with invasive and pharmacological findings and evaluate the neurobiological plausibility of current theories of PM.