This is a work in the epistemology of functional neuroimaging (fNI) and it applies the error-statistical (ES) philosophy to inferential problems in fNI to formulate and address these problems. This gives us a clear, accurate, and more complete understanding of what we can learn from fNI and how we can learn it. I review the works in the epistemology of fNI which I group into two categories; the first category consists of discussions of the theoretical significance of fNI findings and the second category discusses methodological difficulties of fNI. Both types of works have shortcomings; the first category has been too theory-centered in its approach and the second category has implicitly or explicitly adopted the assumption that methodological difficulties of fNI cannot be satisfactorily addressed. In this dissertation, I address these shortcomings and show how and what kind of experimental knowledge fNI can reliably produce which would be theoretically significant. I take fMRI as a representative fNI procedure and discuss the history of its development. Two independent trajectories of research in physics and physiology eventually converge to give rise to fMRI. Thus, fMRI findings are laden in the theories of physics and physiology and I propose how this creates a kind of useful theory-ladenness which allows for the representation of and intervention in the constructs of cognitive neuroscience. Duhemian challenges and problems of underdetermination are often raised to argue that fNI is of little, if any, epistemic value for psychology. I show how the ES notions of severe tests and error probabilities can be applied in epistemological analyses of fMRI. The result is that hemodynamic hypotheses can be severely tested in fMRI experiments and I demonstrate how these hypotheses are theoretically significant and fuel the growth of experimental knowledge in cognitive neuroscience. Throughout this dissertation, I put the emphasis on the experimental knowledge we obtain from fNI and argue that this is the fruitful approach that enables us to see how fNI can contribute to psychology. In doing so, I offer an error-statistical epistemology of fNI, which hopefully will be a significant contribution to the philosophy of psychology. / Ph. D.

Nous étudions dans cette thèse l'influence d'un système d'authentification utilisant des codes graphiques 2D modifiés lors de l'impression par un procédé physique non-clônable. Un tel procédé part du principe qu'à très haute résolution le système d'impression acquisition peut être modélisé comme un processus stochastique, de part le caractère aléatoire de la disposition des fibres de papiers, de mélange des particules d'encre, de l'adressabilité de l'imprimante ou encore du bruit d'acquisition. Nous considérons un scénario où l'adversaire pourra estimer le code original et essaiera de le reproduire en utilisant son propre système d'impression. La première solution que nous proposons pour arriver à l'authentification est d'utiliser un test d'hypothèse à partir des modèles à priori connus et sans mémoire des canaux d'impression-acquisition de l'imprimeur légitime et du contrefacteur. Dans ce contexte nous proposons une approximation fiable des probabilités d'erreur via l'utilisation de bornes exponentiels et du principe des grandes déviations. Dans un second temps, nous analysons un scénario plus réaliste qui prends en compte une estimation a priori du canal du contrefacteur et nous mesurons l'impact de cette étape sur les performances du système d'authentification. Nous montrons qu'il est possible de calculer la distribution des probabilité de non-détection et d'en extraire par exemple ses performances moyennes. La dernière partie de cette thèse propose d'optimiser, au travers d'un jeu minimax, le canal de l'imprimeur. / We study in this thesis the impact of an authentication system based on 2D graphical codes that are corrupted by a physically unclonable noise such as the one emitted by a printing process. The core of such a system is that a printing process at very high resolution can be seen as a stochastic process and hence produces noise, this is due to the nature of different elements such as the randomness of paper fibers, the physical properties of the ink drop, the dot addressability of the printer, etc. We consider a scenario where the opponent may estimate the original graphical code and tries to reproduce the forged one using his printing process in order to fool the receiver. Our first solution to perform authentication is to use hypothesis testing on the observed memoryless sequences of a printed graphical code considering the assumption that we are able to perfectly model the printing process. The proposed approach arises from error exponent using exponential bounds as a direct application of the large deviation principle. Moreover, when looking for a more practical scenario, we take into account the estimation of the printing process used to generate the graphical code of the opponent, and we see how it impacts the performance of the authentication system. We show that it is both possible to compute the distribution of the probability of non-detection and to compute the average performance of the authentication system when the opponent channel has to be estimated. The last part of this thesis addresses the optimization problem of the printing channel.