abstract: Adapting to one novel condition of a motor task has been shown to generalize to other naïve conditions (i.e., motor generalization). In contrast, learning one task affects the proficiency of another task that is altogether different (i.e. motor transfer). Much more is known about motor generalization than about motor transfer, despite of decades of behavioral evidence. Moreover, motor generalization is studied as a probe to understanding how movements in any novel situations are affected by previous experiences. Thus, one could assume that mechanisms underlying transfer from trained to untrained tasks may be same as the ones known to be underlying motor generalization. However, the direct relationship between transfer and generalization has not yet been shown, thereby limiting the assumption that transfer and generalization rely on the same mechanisms. The purpose of this study was to test whether there is a relationship between motor generalization and motor transfer. To date, ten healthy young adult subjects were scored on their motor generalization ability and motor transfer ability on various upper extremity tasks. Although our current sample size is too small to clearly identify whether there is a relationship between generalization and transfer, Pearson product-moment correlation results and a priori power analysis suggest that a significant relationship will be observed with an increased sample size by 30%. If so, this would suggest that the mechanisms of transfer may be similar to those of motor generalization. / Dissertation/Thesis / Masters Thesis Biomedical Engineering 2018

In this thesis we pitted two views of action selection. On the one hand, a traditional view suggesting that action selection emerges from a sequential process whereby perception, cognition and action proceed serially and are subtended by distinct brain areas. On the other hand, an ecological view (formalized in the affordance competition hypothesis) advocating that action selection stems from the parallel implementation of potential action plans. In parallel, the competition between these action plans would be biased by relevant task factors. We first addressed the issue of the temporal dynamics of action selection processes in Chapter 2. We built a reaching task design that crucially gave equal opportunities for serial and parallel processing of cognitive and motor processes to occur. In our study, we first cued participants with probabilities associated to upcoming potential reaches. After several hundreds of milliseconds, participants were given a deterministic go signal indicating which target to reach for. They had to reach for the signaled target as fast as possible. Importantly, our design tries to cope with the biases involved in previous reaching tasks, allowing for a much more informative way to tackle the issue of serial versus parallel processing in action selection. We show that effects of action probability are not only present in the initiation time (i.e. the time it takes to initiate the movement), but crucially also in the movement time (i.e. the time interval between movement initiation and target reaching). Furthermore, an analysis of the movement trajectories showed that reach probability influenced the trajectories according to the predicted pattern. Thus, these results back up a system where cognitive and motor processes continuously interact with one another to come up with a decision. After clarifying the temporal dynamics, we concentrate our efforts on exposing the neural architecture of processes subtending action selection in Chapter 3. In a two-choice button press task, participants were first cued with predictive information regarding upcoming button presses. Crucially, we experimentally manipulated the amount of information in favor of specific button presses whilst adopting a design as similar as possible to those used in monkey neurophysiology (e.g. Cisek & Kalaska, 2005). Using fMRI, our results showed that as information in favor a button press increases, so does activity in the contralateral primary motor cortex, while activity in the ipsilateral primary motor cortex decreases. Moreover, we observed that primary motor regions are more tightly coupled with fronto-parietal areas in a condition involving a decision compared with a situation not implicating a decision between two button presses. Our results are compatible with an account predicting that decision-making emerges from motor areas, and therefore suggest that the architecture presented in the affordance competition hypothesis is not only valid in monkeys but also humans. In Chapter 4, we combine the findings acquired in the studies of chapter 2 and 3 with recent neurophysiological insights to develop a neuro-computational model capable of grasping the continuous interaction between cognitive and motor processes, responsible for the behavioral pattern in reach selection tasks. Our model functions on the principles of cascade forward models whereby activation at one stage of processing systematically spills to the next one, thereby substantially blurring the boundaries between perceptive, cognitive and motor processes. Contrary to most computational models confining action selection processes prior to action execution, our model allows for these processes to leak into action execution. Moreover, the threshold for action execution is not fixed, but rather dynamic and crucially depends on the activity pattern of the model’s primary motor neurons. We propose that the modification of the threshold is governed by the subthalamic nucleus, receiving direct input signals from the primary motor cortex and in turn imposing a dynamical brake on action execution. By including this dynamical threshold, our model has the advantage that it can release movement execution either rapidly or slowly depending on the context. Our model accounts not only for initiation times, but also movement times in reaching task studies. Furthermore, it can grasp the qualitative pattern of movement trajectories. This study suggests that to explain unfolding actions a classical fixed threshold is not sufficient, but rather an execution threshold level that is continuously being updated depending on the context is required. / Doctorat en Sciences psychologiques et de l'éducation / info:eu-repo/semantics/nonPublished

La simulation du geste humain est une thématique de recherche importante et trouve notamment une application dans l'analyse ergonomique pour l'aide à la conception de postes de travail. Le sujet de cette thèse concerne la génération automatique de tâches d'atteinte dans le plan horizontal pour un humanoïde. Ces dernières, à partir d'un objectif exprimé dans l'espace de la tâche, requièrent une coordination de l'ensemble des liaisons. L'une des principales difficultés rencontrées lors de la simulation de gestes réalistes est liée à la redondance naturelle de l'humain. Notre démarche est focalisée principalement sur deux aspects : - le mouvement de la main dans l'espace opérationnel (trajectoire spatiale et profil temporel), - la coordination des différentes sous-chaînes cinématiques. Afin de caractériser le mouvement humain, nous avons mené une campagne de capture de mouvements pour des gestes d'atteinte contraignant la position et l'orientation de la main dans le plan horizontal. Ces acquisitions nous ont permis de connaître l'évolution spatiale et temporelle de la main dans l'espace de la tâche, en translation et en rotation. Ces données acquises couplées à une méthode de rejeu ont également permis d'analyser les relations intrinsèques qui lient l'espace de la tâche à l'espace articulaire du mannequin. Le schéma de génération automatique de mouvements réalistes est basé sur une pile de tâche avec une approche cinématique. L'hypothèse retenue pour simuler le geste est de suivre le chemin le plus court dans l'espace de la tâche tout en bornant le coût dans l'espace articulaire. Un ensemble de paramètres permet de régler le schéma. Il en résulte une cartographie de réglages qui permet de simuler une classe de mouvements réalistes. Enfin, ce schéma de génération automatique de mouvements réalistes est validé par une comparaison quantitative et qualitative entre la simulation et le geste humain. / The simulation of human movement is an active theme of research, particularly in ergonomic analysis to aid in the design of workstations. The aim of this thesis concerns the automatic generation of reaching tasks in the horizontal plane for a virtual humanoid. An objective expressed in the task space, requires coordination of all joints of the mannequin. The main difficulties encountered in the simulation of realistic movements is related to the natural redundancy of the human. Our approach is focused mainly on two aspects: - Motion of the hand's operator in the task space (spatial and temporal aspect), - Coordination of all kinematic chains. To characterize human movement, we conducted a set of motion capture with position and orientation constraints of the hand in the horizontal plane. These acquisitions allowed to know the spatial and temporal evolution of the hand in the task space, for translation and rotation aspects. These acquired data were coupled with a playback method to analyze the intrinsic relations that link the task space to joint space of the model. The automatic generation scheme of realistic motion is based on a stack of task with a kinematic approach. The assumption used to simulate the action is to follow the shortest path in the task space while limiting the cost in the joint space. The scheme is characterized by a set of parameters. A global map of parameter adjustment enables the simulation of a class of realistic movements. Finally, this scheme is validated quantitatively and qualitatively with comparison between the simulation and the human gesture.

Une variété de modèles sur le processus de prise de décision dans divers contextes présume que les sujets accumulent les évidences sensorielles, échantillonnent et intègrent constamment les signaux pour et contre des hypothèses alternatives. L'intégration continue jusqu'à ce que les évidences en faveur de l'une des hypothèses dépassent un seuil de critère de décision (niveau de preuve exigé pour prendre une décision). De nouveaux modèles suggèrent que ce processus de décision est plutôt dynamique; les différents paramètres peuvent varier entre les essais et même pendant l’essai plutôt que d’être un processus statique avec des paramètres qui ne changent qu’entre les blocs d’essais. Ce projet de doctorat a pour but de démontrer que les décisions concernant les mouvements d’atteinte impliquent un mécanisme d’accumulation temporelle des informations sensorielles menant à un seuil de décision. Pour ce faire, nous avons élaboré un paradigme de prise de décision basée sur un stimulus ambigu afin de voir si les neurones du cortex moteur primaire (M1), prémoteur dorsal (PMd) et préfrontal (DLPFc) démontrent des corrélats neuronaux de ce processus d’accumulation temporelle. Nous avons tout d’abord testé différentes versions de la tâche avec l’aide de sujets humains afin de développer une tâche où l’on observe le comportement idéal des sujets pour nous permettre de vérifier l’hypothèse de travail. Les données comportementales chez l’humain et les singes des temps de réaction et du pourcentage d'erreurs montrent une augmentation systématique avec l'augmentation de l'ambigüité du stimulus. Ces résultats sont cohérents avec les prédictions des modèles de diffusion, tel que confirmé par une modélisation computationnelle des données. Nous avons, par la suite, enregistré des cellules dans M1, PMd et DLPFc de 2 singes pendant qu'ils s'exécutaient à la tâche. Les neurones de M1 ne semblent pas être influencés par l'ambiguïté des stimuli mais déchargent plutôt en corrélation avec le mouvement exécuté. Les neurones du PMd codent la direction du mouvement choisi par les singes, assez rapidement après la présentation du stimulus. De plus, l’activation de plusieurs cellules du PMd est plus lente lorsque l'ambiguïté du stimulus augmente et prend plus de temps à signaler la direction de mouvement. L’activité des neurones du PMd reflète le choix de l’animal, peu importe si c’est une bonne réponse ou une erreur. Ceci supporte un rôle du PMd dans la prise de décision concernant les mouvements d’atteinte. Finalement, nous avons débuté des enregistrements dans le cortex préfrontal et les résultats présentés sont préliminaires. Les neurones du DLPFc semblent beaucoup plus influencés par les combinaisons des facteurs de couleur et de position spatiale que les neurones du PMd. Notre conclusion est que le cortex PMd est impliqué dans l'évaluation des évidences pour ou contre la position spatiale de différentes cibles potentielles mais assez indépendamment de la couleur de celles-ci. Le cortex DLPFc serait plutôt responsable du traitement des informations pour la combinaison de la couleur et de la position des cibles spatiales et du stimulus ambigu nécessaire pour faire le lien entre le stimulus ambigu et la cible correspondante. / A variety of models of the decision-making process in many different contexts suggest that subjects sample, accumulate and integrate sensory evidence for and against different alternative choices, until one of those signals exceeds a decision criterion threshold. Early models assumed that this process is static and does not change during a trial or even between trials, but only between blocks of trials when task demands such as speed versus accuracy change. However, newer models suggest that the decision-making process is dynamic and factors that influence the evidence accumulation process might change both between trials in a block and even during a trial. This thesis project aims to demonstrate that decisions about reaching movements emerge from a mechanism of integration of sensory evidence to a decision criterion threshold. We developed a paradigm for decision-making about reach direction based on ambiguous sensory input to search for neural correlates of the decision-making process in primary motor cortex (M1), premotor cortex (PMd) and dorsolateral prefrontal cortex (DLPFc). We first tested several versions of the task with human subjects before developing a task (“Choose and Go”) that showed ideal behavior from the subjects to test our hypothesis. The task required subjects to choose between two color-coded targets in different spatial locations by deciding the predominant color of a central “decision cue” that contained different amounts of colored squares of the two target colors. The strength of the evidence was manipulated by varying the relative numbers of squares of the two colors. The response times and error rates both increased in parallel as the strength of the sensory evidence in the decision cue (its color bias) became increasingly weaker. Computational modelling showed that the choice behaviour of the subjects could be captured by different variants of the drift-diffusion model for accumulation of sensory evidence to a decision threshold. We then recorded cells from M1, PMd and DLPFc in 2 macaques while they performed the task. Behavioral data showed that response times and error rates increased with the amount of ambiguity of the decision cues. M1 cells discharged in correlation with movement onset and were not influenced by the ambiguity of the decision cues. In contrast, the discharge of PMd cells increased more slowly with increased ambiguity of the decision cues and took increasingly more time to signal the movement direction chosen by the monkeys. The changes in activity reflected the monkeys’ reach choices. These data support a role for PMd in the choice of reach direction. DLPFc data are preliminary but reveal a stronger effect of the color-location conjunction rule in the neuronal discharge than in PMd. Our conclusion is that PMd is involved in the evaluation of evidence for and against different alternatives and about target spatial location independent of the color of the targets. DLPFC neurons play a greater role in processing information about the color and location of the spatial targets and decision cue to resolve the color-location conjunction rule required to decide on the reach target direction.