Reward prediction errors are quantitative signed terms that express the difference between the value of an obtained outcome and the expected value that was placed on it prior to its receipt. Positive reward prediction errors constitute reward, negative reward prediction errors constitute punishment. Reward prediction errors have been shown to be powerful drivers of reinforcement learning in formal models and there is thus a strong reason to believe they are used in the brain. Isolating such neural signals stands to help elucidate how reinforcement learning is implemented in the brain, and may ultimately shed light on individual differences, psychopathologies of reward such as addiction and depression, and the apparently non-normative behaviour under risk described by behavioural economics. In the present thesis, I used the event related potential technique to isolate and study electrophysiological components whose behaviour resembled reward prediction errors. I demonstrated that a candidate component, “feedback related negativity”, occurring 250 to 350 ms after receipt of reward or punishment, showed such behaviour. A meta-analysis of the existing literature on this component, using a novel technique of “great grand averaging”, supported this view. The component showed marked asymmetries however, being more responsive to reward than punishment and more responsive to appetitive rather than aversive outcomes. I also used novel data-driven techniques to examine activity outside the temporal interval associated with the feedback related negativity. This revealed a later component responding solely to punishments incurred in a Pavlovian learning task. It also revealed numerous salience-encoding components which were sensitive to a prediction error’s size but not its sign.

Cílem této diplomové práce je najít a popsat souvislost mezi fixací očí v emočně zabarveném stimulu, kterým je obrázek či video, a EEG signálu. K tomuto studiu je třeba vyvinout softwarové nástroje v prostředí Matlab k úpravě a zpracování dat získaných z eye trackeru a propojení s EEG signály pomocí nově vytvořených markerů. Na základě získaných znalostí o fixacích, jsou v prostředí BrainVision Analyzeru EEG data zpracovány a následně jsou segmentovány a průměrovány jako evokované potenciály pro jednotlivé stimuly (ERP a EfRP). Tato práce je vypracována ve spolupráci s Gipsa-lab v rámci výzkumného projektu.

Moderate-to-severe traumatic brain injury (M/S TBI) is a growing public health concern with significant impact on the cognitive functioning of survivors. Cognitive control and deficits in awareness have been linked to poor recovery and rehabilitation outcomes. One way to research cognitive control is through awareness of errors using electroencephalogram and event-related potentials (ERPs). Both the error-related negativity and the post-error positivity components of the ERP are linked to error awareness and cognitive control processes. Attentional capacity and levels of apathy influence error awareness in those with M/S TBI. There are strong links between awareness, attention, and apathy. However, limited research has examined the role of attention, awareness, and apathy using electrophysiological indices of error awareness to further understand cognitive control in a M/S TBI sample. The current study sought to elucidate the role of apathy in error awareness in those with M/S TBI. Participants included 75 neurologically-healthy controls (divided randomly into two control groups) and 24 individuals with M/S TBI. All participants completed self-report measures of mood, apathy, and executive functioning, as well as a brief neuropsychological battery to measure attention and cognitive ability. To measure awareness, participants completed the error awareness task (EAT), a modified Stroop go/no-go task. Participants signaled awareness of errors committed on the previous trial. The M/S TBI group decreased accuracy while improving or maintaining error awareness compared to controls over time. There were no significant between-group differences for ERN and Pe amplitudes. Levels of apathy in the M/S TBI group were included in three multiple regression analyses predicting proportion of unaware errors, ERN amplitude, and Pe amplitude. Apathy was predictive of error awareness, although not in the predicted direction. Major analyses were replicated using two distinct control groups to determine potential sample effects. Results showed consistent results comparing both control groups to a M/S TBI group. Findings show variable levels of awareness and accuracy over time for those with M/S TBI when compared to controls. Conclusions include varying levels of attention and awareness from the M/S TBI group over time, evidenced by improving awareness of errors when they are happening, but an inability to regulate performance sufficiently to improve accuracy. Levels of apathy are playing a role in error awareness, however, not in predicted directions. The study provides support for the role of attentional impairments in error awareness and encourages future studies to look for varying levels of performance within a given task when using populations linked to elevated levels of apathy and attentional deficits.

L'étude par neuro-imagerie de l'activité de plusieurs cerveaux en interaction (hyperscanning) permet d'étendre notre compréhension des neurosciences sociales. Nous proposons un cadre pour l'hyperscanning utilisant les interfaces cerveau-ordinateur multi-utilisateur qui inclut différents paradigmes sociaux tels que la coopération ou la compétition. Les travaux de cette thèse comportent trois contributions interdépendantes. Notre première contribution est le développement d'une plateforme expérimentale sous la forme d'un jeu vidéo multijoueur, nommé Brain Invaders 2, contrôlé par la classification de potentiels évoqués visuels enregistrés par électroencéphalographie (EEG). Cette plateforme est validée par deux protocoles expérimentaux comprenant dix-neuf et vingt-deux paires de sujets et utilise différentes approches de classification adaptative par géométrie riemannienne. Ces approches sont théoriquement et expérimentalement comparées et nous montrons la supériorité de la fusion des classifieurs indépendants sur la classification d'un hypercerveau durant la seconde contribution. L'analyse de coïncidence des signaux entre les individus est une approche classique pour l'hyperscanning, elle est pourtant difficile quand les signaux EEG concernés sont transitoires avec une grande variabilité (intra- et inter-sujet) spatio-temporelle et avec un faible rapport signal-à-bruit. En troisième contribution, nous proposons un nouveau modèle composite de séparation aveugle de sources physiologiquement plausibles permettant de compenser cette variabilité. Une solution par diagonalisation conjointe approchée est proposée avec une implémentation d'un algorithme de type Jacobi. A partir des données de Brain Invaders 2, nous montrons que cette solution permet d'extraire simultanément des sources d'artéfacts, des sources d'EEG évoquées et des sources d'EEG continues avec plus de robustesse et de précision que les modèles existants. / The study of several brains interacting (hyperscanning) with neuroimagery allows to extend our understanding of social neurosciences. We propose a framework for hyperscanning using multi-user Brain-Computer Interfaces (BCI) that includes several social paradigms such as cooperation or competition. This dissertation includes three interdependent contribution. The first contribution is the development of an experimental platform consisting of a multi-player video game, namely Brain Invaders 2, controlled by classification of visual event related potentials (ERP) recorded by electroencephalography (EEG). The plateform is validated through two experimental protocols including nineteen and twenty two pairs of subjects while using different adaptive classification approaches using Riemannian geometry. Those approaches are theoretically and experimentally compared during the second contribution ; we demonstrates the superiority in term of accuracy of merging independent classifications over the classification of the hyperbrain during the second contribution. Analysis of inter-brain synchronizations is a common approach for hyperscanning, however it is challenging for transient EEG waves with an great spatio-temporal variability (intra- and inter-subject) and with low signal-to-noise ratio such as ERP. Therefore, as third contribution, we propose a new blind source separation model, namely composite model, to extract simultaneously evoked EEG sources and ongoing EEG sources that allows to compensate this variability. A solution using approximate joint diagonalization is given and implemented with a fast Jacobi-like algorithm. We demonstrate on Brain Invaders 2 data that our solution extracts simultaneously evoked and ongoing EEG sources and performs better in term of accuracy and robustness compared to the existing models.

In this dissertation the effects of variations in stimulus properties and CTOA, in auditory attention tasks were explored using recently developed approaches to EEG analysis including LIMO. The last experiment was structured using information theory, designing an effective experiment. Four studies were carried out using a number parity decision task, that employed different combinations of cueing Tone (T), Novel (N) and the Goal (G) stimuli. In the first EEG study, contrary to previous findings (Polich 2002, 2007) in control participants, no correlation between the time of a novel condition to the next novel condition and P300 amplitude was found. Therefore single trial across-subject averaging of participants’ data revealed significant correlations (r > .3) of stimulus properties (such as probability, frequency, amplitude and duration) on P300, and even r > .5 was found when N was an environmental sound in schizophrenic patients. In the second EEG study, simultaneously with fMRI recordings, the participants that showed significant behavioural distraction evoked brain activations and differences in both hemispheres (similar to Corbetta, 2002, 2008) while the participants, as a whole, produced significant activations mainly in left cortical and subcortical regions. A context analysis was run in distracted participants contrasting the trials immediately prior to the G trials, resulting in different prefrontal activations, which was consistent with studies of prefrontal control of visual attention (Koechlin 2003, 2007). In the third EEG study, the distractor noise type was manipulated (white vs environmental sounds) as well as presence or absence of scanner background noise in a blocked design. Results showed consistent P300, MMN and RON due to environmental noise. In addition, using time constants found in MEG results (Lu, Williamson & Kaufman, 1992) and adding the CTOA to the analysis, an information theory framework was calculated. After the simulation of the information of the experiment, a saddle indentation in the curve of the information measure based on the states of the incoming signal at around 300 ms CTOA was found. This saddle indentation was evident in more than 60 novel trials. In the fourth study, the CTOA and stimulus properties were manipulated in a parametric experiment. Based on the three studies, reducing complexity if the task (first study), using more than 60 stimuli in the novel conditions (third study). The CTOA randomly varying between 250 ms or 500 ms. Thirty-eight ANCOVA with 2 categorical and 1 continuous regressors were conducted and determined which time and channels elicited reliably signatures (p <.05) in the whole participants at short CTOA. Results revealed differences for the waveforms of current condition by depending on which condition appeared previously as well in terms of frequency and duration in scalp frontal electrodes (such as the second study). These results were interpreted as a consequence of switching between modes of attention and alerting states which resulted in the activation of frontal areas. Moreover, contextual analyses showed that systematic manipulation of stimulus properties allowed the visualization of the relationships between CTOA, executive function and orienting of attention.

The purpose of this research was to explore the effects of small monetary or economic gains and/or losses on choice behavior through the use of a computerized game and to determine gain/loss ratio differences using both behavioral and electrophysiological measures. Participants (N=53) played the game in several 36 minute sessions. These sessions operated with concurrent variable-interval schedules for both rewards and penalties. Previously, asymmetrical effects of gains and losses have been identified through cognitive studies, primarily due to the work of nobel laureates Daniel Kahneman and Amos Tversky (1979). They found that the effect of a loss is twice (i.e., 2:1) that of a gain. Similar results have been observed in the behavioral laboratory as exemplified by the research of Rasmussen and Newland (2008), who found a 3:1 ratio for the effect of losses versus gains. The asymmetry of gains and losses was estimated behaviorally and through event-related brain potentials (ERPs) and the cognitive (Kahneman and Tversky) and behavioral (Rasmussen and Newland) discrepancy elucidated. In the game, the player moves an animated submarine around sea rocks to collect yellow coins and other treasures on the sea floor. Upon collecting a coin, one of three things can happen: The player triggers a penalty (loss), the player triggers a payoff (gain), or there is no change. The behavioral measures consisted in counting the number of clicks, reinforces, and punishers and then determining ratio differences between punished (loss) and no punished condition (gain) conditions. The obtained gain/loss ratio corresponded to an asymmetry of 2:1. Similarly ratio differences were found between male and female, virtual money and cash, risk averse versus risk seeking, and generosity versus profit behavior. Also, no ratio difference was found when players receive information about other player's performances in the game (players with information versus players without information). In electroencephalographic (EEG) studies, visual evoked potentials (VEPs) and ERPs components (e.g., P300) were examined. I found increased ERP amplitudes for the losses in relation to the gains that corresponded to the calculated behavioral asymmetry of 2:1. A correlational strategy was adopted that sought to identify neural correlates of choice consistent with cognitive and behavioral approaches. In addition, electro cortical ratio differences were observed between different sets of electrodes that corresponded to the front, middle, and back sections of the brain; differences between sessions, risk averse and risk seeking behavior and sessions with concurrent visual and auditory stimuli and only visual were also estimated.

Attention Deficit Hyperactivity Disorder (ADHD) is a disorder affecting cognitive control. These functions are important to achieve goals when different actions need to be executed in close succession. This type of multi-component behavior, which often further requires the processing of information from different modalities, is important for everyday activities. Yet, possible changes in neurophysiological mechanisms have not been investigated in adolescent ADHD. We examined N = 31 adolescent ADHD patients and N = 35 healthy controls (HC) in two Stop-Change experiments using either uni-modal or bi-modal stimuli to trigger stop and change processes. These stimuli were either presented together (SCD0) or in close succession of 300 milliseconds (SCD300). Using event-related potentials (ERP), EEG data decomposition and source localization we analyzed neural processes and functional neuroanatomical correlates of multicomponent behavior. Compared to HCs, ADHD patients had longer reaction times and higher error rates when Stop and Change stimuli were presented in close succession (SCD300), but not when presented together (SCD0). This effect was evident in the uni-modal and bi-modal experiment and is reflected by neurophysiological processes reflecting response selection mechanisms in the inferior parietal cortex (BA40). These processes were only detectable after accounting for intra-individual variability in neurophysiological data; i.e. there were no effects in standard ERPs. Multi-component behavior is not always deficient in ADHD. Rather, modulations in multi-component behavior depend on a critical temporal integration window during response selection which is associated with functioning of the inferior parietal cortex. This window is smaller than in HCs and independent of the complexity of sensory input.

Attention Deficit Hyperactivity Disorder (ADHD) is a disorder affecting cognitive control. These functions are important to achieve goals when different actions need to be executed in close succession. This type of multi-component behavior, which often further requires the processing of information from different modalities, is important for everyday activities. Yet, possible changes in neurophysiological mechanisms have not been investigated in adolescent ADHD. We examined N = 31 adolescent ADHD patients and N = 35 healthy controls (HC) in two Stop-Change experiments using either uni-modal or bi-modal stimuli to trigger stop and change processes. These stimuli were either presented together (SCD0) or in close succession of 300 milliseconds (SCD300). Using event-related potentials (ERP), EEG data decomposition and source localization we analyzed neural processes and functional neuroanatomical correlates of multicomponent behavior. Compared to HCs, ADHD patients had longer reaction times and higher error rates when Stop and Change stimuli were presented in close succession (SCD300), but not when presented together (SCD0). This effect was evident in the uni-modal and bi-modal experiment and is reflected by neurophysiological processes reflecting response selection mechanisms in the inferior parietal cortex (BA40). These processes were only detectable after accounting for intra-individual variability in neurophysiological data; i.e. there were no effects in standard ERPs. Multi-component behavior is not always deficient in ADHD. Rather, modulations in multi-component behavior depend on a critical temporal integration window during response selection which is associated with functioning of the inferior parietal cortex. This window is smaller than in HCs and independent of the complexity of sensory input.