A statistical meta-analysis combines the results of several studies that address a set of related research hypotheses, thus increasing the power and reliability of the inference. Meta-analytic methods are over 50 years old and play an important role in science; pooling evidence from many trials to provide answers that any one trial would have insufficient samples to address. On the other hand, the number of neuroimaging studies is growing dramatically, with many of these publications containing conflicting results, or being based on only a small number of subjects. Hence there has been increasing interest in using meta-analysis methods to find consistent results for a specific functional task, or for predicting the results of a study that has not been performed directly. Current state of neuroimaging meta-analysis is limited to coordinate-based meta-analysis (CBMA), i.e., using only the coordinates of activation peaks that are reported by a group of studies, in order to "localize" the brain regions that respond to a certain type of stimulus. This class of meta-analysis suffers from a series of problems and hence cannot result in as accurate results as desired. In this research, we describe the problems that existing CBMA methods are suffering from and introduce a hierarchical mixed-effects image-based metaanalysis (IBMA) solution that incorporates the sufficient statistics (i.e., voxel-wise effect size and its associated uncertainty) from each study. In order to improve the statistical-inference stage of our proposed IBMA method, we introduce a nonparametric technique that is capable of adjusting such an inference for spatial nonstationarity. Given that in common practice, neuroimaging studies rarely provide the full image data, in an attempt to improve the existing CBMA techniques we introduce a fully automatic model-based approach that employs Gaussian-process regression (GPR) for estimating the meta-analytic statistic image from its corresponding sparse and noisy observations (i.e., the collected foci). To conclude, we introduce a new way to approach neuroimaging meta-analysis that enables the analysis to result in information such as “functional connectivity” and networks of the brain regions’ interactions, rather than just localizing the functions.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

A wide literature of predominantly behavioural experiments that use Stimulus Response Compatibility (SRC) have suggested that visual action information such as object affordance yields rapid and concurrent activation of visual and motor brain areas, but has rarely provided direct evidence for this proposition. This thesis examines some of the key claims from the affordance literature by applying electrophysiological measures to well established SRC procedures to determine the verities of the behavioural claims of rapid and automatic visuomotor activation evoked by viewing affording objects. The temporal sensitivity offered by the Lateralised Readiness Potential and by visual evoked potentials P1 and N1 made ideal candidates to assess the behavioural claims of rapid visuomotor activation by seen objects by examining the timecourse of neural activation elicited by viewing affording objects under various conditions. The experimental work in this thesis broadly confirms the claims of the behavioural literature however it also found a series of novel results that are not predicted by the behavioural literature due to limitations in reaction time measures. For example, while different classes of affordance have been shown to exert the same behavioural facilitation, electrophysiological measures reveal very different patterns of cortical activation for grip-type and lateralised affordances. These novel findings question the applicability of the label ‘visuomotor’ to grip-type affordance processing and suggest considerable revision to models of affordance. This thesis also offers a series of novel and surprising insights into the ability to dissociate afforded motor activity from behavioural output, into the relationship between affordance and early visual evoked potentials, and into affordance in the absence of the intention to act. Overall, this thesis provides detailed suggestions for considerable changes to current models of the neural activity underpinning object affordance.