Electrocortical components of anticipation and consumption in a monetary incentive delay task

In order to improve our understanding of the components that reflect functionally important processes during reward anticipation and consumption, we used principle components analyses (PCA) to separate and quantify averaged ERP data obtained from each stage of a modified monetary incentive delay (MID) task. Although a small number of recent ERP studies have reported that reward and loss cues potentiate ERPs during anticipation, action preparation, and consummatory stages of reward processing, these findings are inconsistent due to temporal and spatial overlap between the relevant electrophysiological components. Our results show three components following cue presentation are sensitive to incentive cues (N1, P3a, P3b). In contrast to previous research, reward‐related enhancement occurred only in the P3b, with earlier components more sensitive to break‐even and loss cues. During feedback anticipation, we observed a lateralized centroparietal negativity that was sensitive to response hand but not cue type. We also show that use of PCA on ERPs reflecting reward consumption successfully separates the reward positivity from the independently modulated feedback‐P3. Last, we observe for the first time a new reward consumption component: a late negativity distributed over the left frontal pole. This component appears to be sensitive to response hand, especially in the context of monetary gain. These results illustrate that the time course and sensitivities of electrophysiological activity that follows incentive cues do not follow a simple heuristic in which reward incentive cues produce enhanced activity at all stages and substages

Electrophysiological underpinnings of reward processing: Are we exploiting the full potential of EEG?

Understanding how the brain processes reward is an important and complex endeavor, which has involved the use of a range of complementary neuroimaging tools, including electroencephalography (EEG). EEG has been praised for its high temporal resolution but, because the signal recorded at the scalp is a mixture of brain activities, it is often considered to have poor spatial resolution. Besides, EEG data analysis has most often relied on event-related potentials (ERPs) which cancel out non-phase locked oscillatory activity, thus limiting the functional discriminative power of EEG attainable through spectral analyses. Because these three dimensions -temporal, spatial and spectral- have been unequally leveraged in reward studies, we argue that the full potential of EEG has not been exploited. To back up our claim, we first performed a systematic survey of EEG studies assessing reward processing. Specifically, we report on the nature of the cognitive processes investigated (i.e., reward anticipation or reward outcome processing) and the methods used to collect and process the EEG data (i.e., event-related potential, time-frequency or source analyses). A total of 359 studies involving healthy subjects and the delivery of monetary rewards were surveyed. We show that reward anticipation has been overlooked (88% of studies investigated reward outcome processing, while only 24% investigated reward anticipation), and that time-frequency and source analyses (respectively reported by 19% and 12% of the studies) have not been widely adopted by the field yet, with ERPs still being the dominant methodology (92% of the studies). We argue that this focus on feedback-related ERPs provides a biased perspective on reward processing, by ignoring reward anticipation processes as well as a large part of the information contained in the EEG signal. Finally, we illustrate with selected examples how addressing these issues could benefit the field, relying on approaches combining time-frequency analyses, blind source separation and source localization

Electrophysiology of Social Reward Processing in Schizophrenia

Poor social outcomes have been long observed in schizophrenia. Most studies have identified social cognition as an important contributor to social functioning. Recent research suggests that some people with schizophrenia do not appropriately respond to social rewards, including facial expression of positive affect. The aim of the current study was (1) to use electroencephalogram (EEG) and the event related potential (ERP) technique to examine how people with schizophrenia (SZ) and healthy control (HC) participants anticipate and respond to social (smiles) and nonsocial (money) types of feedback; (2) to examine how deficits in social reward processing are associated with motivation and pleasure deficits and social functioning; and (3) to examine differential contributions of social cognition and social reward processing in understanding functioning. Social and monetary incentive delay tasks were used to characterize reward processing. The stimulus preceding negativity (SPN) was evaluated as an index of reward anticipation, and the reward positivity (RewP) was evaluated as an index of reward sensitivity. Results indicated that HC participants (n = 22) showed significantly more anticipation of reward feedback than neutral feedback, as indexed by the SPN. SZ participants (n = 25) showed similar anticipation regardless of whether there was a potential to win a reward. SZ participants were more sensitive to social rewards than HC participants, as indexed by a larger RewP. We were unable to measure the RewP on the money task; however, exploratory analyses on a P2 component suggested there were no group differences in nonsocial reward sensitivity. Within the SZ group, reduced social reward anticipation was related to greater motivation and pleasure deficits but not social functioning. Social cognition was not significantly related to social functioning or social reward processing in the SZ sample. This is the first study to measure the electrophysiological correlates of social and nonsocial reward processing in schizophrenia. Findings provide preliminary evidence of a generalized anticipatory deficit in schizophrenia that is related to impairments in motivation and pleasure. Reward sensitivity to social rewards appears to be intact. Future experimental design considerations are discussed

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8–12 Hz) and beta oscillations (13–30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance), and are encoded in gamma oscillations (>30 Hz) and associated with suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning

Indirect Compatibilism

In this thesis, I will defend a new kind of compatibilist account of free action, indirect conscious control compatibilism (or indirect compatibilism for short), and argue that some of our actions are free according to it. My argument has three components, and involves the development of a brand new tool for experimental philosophy, and the use of cognitive neuroscience. The first component of the argument shows that compatibilism (of some kind) is a conceptual truth. Contrary to the current orthodoxy in the free will literature, which is that our concept of free will is an incompatibilist concept - a concept according to which we have free will only if determinism is false - I will show that our concept of free will is in fact a compatibilist concept - a concept according to which we can have free will even if determinism is true - and I do so using a new experimental philosophy methodology inspired by two-dimensional semantics. Of course, even if our concept of free will is a compatibilist concept, this does not mean that there are any free actions in the world: the current empirical evidence from the brain sciences appears to show that there might be no, or very few, free actions in the world, even on many compatibilist understandings of what it would take for there to be free will. The second component of the argument addresses this concern by extending our understanding of compatibilism. Agents act freely either when their actions are caused by compatibilistically acceptable psychological processes, or are indirectly caused by those same processes. Hence the name of my account: indirect compatibilism. The final component of the argument defends my new account against some interesting objections and provides evidence from cognitive neuroscience that some of our actions count as free by the lights of indirect compatibilism

A biophysical model of striatal microcircuits suggests gamma and beta oscillations interleaved at delta/theta frequencies mediate periodicity in motor control

Striatal oscillatory activity is associated with movement, reward, and decision-making, and observed in several interacting frequency bands. Local field potential recordings in rodent striatum show dopamine- and reward-dependent transitions between two states: a "spontaneous" state involving β (∼15-30 Hz) and low γ (∼40-60 Hz), and a state involving θ (∼4-8 Hz) and high γ (∼60-100 Hz) in response to dopaminergic agonism and reward. The mechanisms underlying these rhythmic dynamics, their interactions, and their functional consequences are not well understood. In this paper, we propose a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms, as well as their modulation by dopamine. Building on previous modeling and experimental work suggesting that striatal projection neurons (SPNs) are capable of generating β oscillations, we show that networks of striatal fast-spiking interneurons (FSIs) are capable of generating δ/θ (ie, 2 to 6 Hz) and γ rhythms. Under simulated low dopaminergic tone our model FSI network produces low γ band oscillations, while under high dopaminergic tone the FSI network produces high γ band activity nested within a δ/θ oscillation. SPN networks produce β rhythms in both conditions, but under high dopaminergic tone, this β oscillation is interrupted by δ/θ-periodic bursts of γ-frequency FSI inhibition. Thus, in the high dopamine state, packets of FSI γ and SPN β alternate at a δ/θ timescale. In addition to a mechanistic explanation for previously observed rhythmic interactions and transitions, our model suggests a hypothesis as to how the relationship between dopamine and rhythmicity impacts motor function. We hypothesize that high dopamine-induced periodic FSI γ-rhythmic inhibition enables switching between β-rhythmic SPN cell assemblies representing the currently active motor program, and thus that dopamine facilitates movement in part by allowing for rapid, periodic shifts in motor program execution.R01 MH114877 - NIMH NIH HHSPublished versio

L’étude de la contribution des mécanismes dépendants de la répétition aux processus de consolidation des mémoires motrices dans le cortex moteur primaire et de la manifestation électrophysiologique du traitement des récompenses monétaires au-dessus des aires cérébrales motrices

Abstract : The present thesis seeks to provide insights into the contribution of the two major learning mechanisms driving motor memory consolidation in the primary motor cortex (M1): repetition-dependent and reward-based learning mechanisms. However, because evidence remains scarce on this last learning mechanism, the study of the neural manifestation of reward processing in motor areas was investigated. More specifically, the first scientific contribution presented in this thesis sought to address the contribution of repetition-dependent mechanisms to motor memory consolidation in M1. As such, the first project used single-pulse transcranial magnetic stimulation (TMS) to interfere with M1 activity as participants executed newly learned motor behaviors during a performance asymptote. Results revealed that motor memory formation in M1 was initiated when behaviors were repeating, suggesting that repetition-dependent mechanisms contributed to retention in M1. The second scientific contribution sought to use scalp electroencephalography (EEG) recordings to investigate the electrophysiological manifestations of reward processing over cortical motor areas. Overall, results revealed that increases in beta-band power (20-30 Hz) over contralateral motor electrodes are modulated by reward processing. Although these results did not allow specifically addressing the contribution of reward-based learning mechanisms to consolidation in M1, they nonetheless provide the plausible neural substrates involved in this learning mechanism. The discussion first sought to integrate these two projects and second to provide an overview of the future perspectives that the two projects have led to. Overall, the proposed research projects mainly revolve around the demonstration of the associations– even maybe causality – between motor memory consolidation in M1, reward processing, beta-band power and dopaminergic activity. Throughout the discussion, working hypotheses as well as the methodological means to test them – ranging from non-invasive brain stimulation to electroencephalography recordings and even to the study of interindividual variations in the expression of dopamine-related genes – are outlined.Le présent mémoire cherche à fournir un aperçu des mécanismes neurophysiologiques qui sous-tendent les deux mécanismes principaux d’apprentissage impliqués dans la consolidation des mémoires motrices dans le cortex moteur primaire (M1). Bien que le modèle cellulaire le plus accepté pour la formation des mémoires motrices soit la potentialisation à long-terme (long-term potentiation, en anglais), la littérature suggère que les mécanismes d’apprentissage qui initient le stockage synaptique des mémoires motrices dépendent de la plasticité Hebienne (i.e., répétitions dans les mouvements) et des récompenses vécues pendant l’acquisition d’une nouvelle habileté motrice. La première contribution scientifique du présent mémoire aborde la contribution des mécanismes Hebbiens d’apprentissage à la consolidation des mémoires motrices dans le M1. Dans ce premier projet, la stimulation magnétique transcrânienne (SMT) a été utilisée pour interférer avec l’activité neuronale du M1 lorsque les participants acquéraient et exécutaient de nouveaux comportements moteurs pendant l’atteinte d’un plateau de performance (i.e., répétitions dans les mouvements). Les résultats démontrent que la formation des mémoires motrices dans le M1 est initiée lorsque les comportements moteurs sont de plus en plus répétés, ce qui suggère que le stockage synaptique des mémoires motrices dans M1 est dépendant de la répétition des comportements pendant l’acquisition. Le deuxième projet scientifique a cherché à mettre en lumière la contribution des régions motrices au traitement des récompenses dans un contexte moteur en utilisant l’enregistrement d’activités électroencéphalographiques. Entre autres, suite à l’octroi d’une récompense, les résultats démontrent une augmentation de la puissance spectrale dans la bande de fréquences bêta (20-30 Hz) des électrodes motrices contralatérales à la main utilisée pendant la tâche motrice. Dans l’ensemble, bien que ce deuxième projet ne puisse statuer sur la contribution spécifique du M1 dans la consolidation des mémoires motrices sur la base des récompenses vécues pendant l’acquisition, les résultats qui en émergent pourraient être un reflet des substrats neuronaux impliqués dans ce mécanisme d’apprentissage. Dans un premier temps, la discussion intègre ces deux contributions et, dans un deuxième temps, donne un aperçu des perspectives futures de recherche qui émanent de ces deux contributions scientifiques. Globalement, les hypothèses de recherche suggérées se concentrent principalement autour de la démonstration d’une association ou d’un lien causal entre la formation des mémoires motrices dans le M1, le traitement de récompenses, les réponses spectrales en bêta ainsi que l’activité dopaminergique. Au travers de la discussion, les hypothèses spécifiques ainsi que les moyens méthodologiques pour les tester – qui vont des techniques de stimulation cérébrale non invasives à l’enregistrement d’activité électroencéphalographique et même jusqu’à l’étude des variations génétiques interindividuelles dans l’expression des gènes régulant l’activité dopaminergique – sont décrits