Le travail présenté dans cette thèse fait partie d’un programme de recherche qui vise à comprendre comment le cerveau traite et représente les structures symboliques dans des domaines comme le langage ou les mathématiques. L’existence de structures composées de sous-éléments, tel que les morphèmes, les mots ou les phrases est très fortement suggérée par les analyses linguistiques et les données expérimentales de la psycholinguistique. En revanche, l’implémentation neuronale des opérations et des représentations qui permettent la nature combinatoire du langage reste encore essentiellement inconnue. Certaines opérations de composition élémentaires permettant une représentation interne stable des objets dans le cortex sensoriel, tel que la reconnaissance hiérarchique des formes, sont aujourd’hui mieux comprises [5]. En revanche, les modèles concernant les opérations de liaisons(binding) nécessaires à la construction de structures symboliques complexes et possiblement hiérarchiques, pour lesquelles des manipulations précises des composants doit être possible, sont encore peu testés de façon expérimentale et incapables de prédire les signaux en neuroimagerie. Combler le fossé entre les données de neuroimagerie expérimentale et les modèles proposés pour résoudre le problème de binding est une étape cruciale pour mieux comprendre les processus de traitements et de représentation des structures symboliques. Au regard de ce problème, l’objectif de ce travail était d’identifier et de tester expérimentalement les théories basées sur des réseaux neuronaux, capables de traiter des structures symboliques pour lesquelles nous avons pu établir des prédictions testables, contre des mesures existantes de neuroimagerie fMRI et ECoG dérivées de tâches de traitement du langage. Nous avons identifié deux approches de modélisation pertinentes. La première approche s’inscrit dans le contexte des architectures symboliques vectorielles (VSA), qui propose une modélisation mathématique précise des opérations nécessaires pour représenter les structures dans des réseaux neuronaux artificiels. C’est le formalisme de Paul Smolensky[10], utilisant des produit tensoriel (TPR) qui englobe la plupart des architectures VSA précédemment proposées comme, par exemple, les modèles d’Activation synchrones[9], les représentations réduites holographique[8], et les mémoires auto-associatives récursives[1]. La seconde approche que nous avons identifiée est celle du "Neural Blackboard Architecture" (NBA), développée par Marc De Kamps et Van der Velde[11]. Elle se démarque des autres en proposant une implémentation des mécanismes associatifs à travers des circuits formés par des assemblages de réseaux neuronaux. L’architecture du Blackboard repose sur des changements de connectivité transitoires des circuits d’assemblages neuronaux, de sorte que le potentiel de l’activité neurale permise par les mécanismes de mémoire de travail après un processus de liaison, représente implicitement les structures symboliques. Dans la première partie de cette thèse, nous détaillons la théorie derrière chacun de ces modèles et les comparons, du point de vue du problème de binding. Les deux modèles sont capables de répondre à la plupart des défis théoriques posés par la modélisation neuronale des structures symboliques, notamment ceux présentées par Jackendo[3]. Néanmoins, ces deux classes de modèles sont très différentes. Le TPR de Smolenky s’appuie principalement sur des considérations spatiales statiques d’unités neurales artificielles, avec des représentations explicites complètement distribuées et spatialement stables mises en œuvre par des vecteurs. La NBA en revanche, considère les dynamiques temporelles de décharge de neurones artificiels, avec des représentations spatialement instables implémentées par des assemblages neuronaux. (...) / The aim of this thesis is to understand how the brain computes and represents symbolic structures, such like those encountered in language or mathematics. The existence of parts in structures like morphemes, words and phrases has been established through decades of linguistic analysis and psycholinguistic experiments. Nonetheless the neural implementation of the operations that support the extreme combinatorial nature of language remains unsettled. Some basic composition operations that allow the stable internal representation of sensory objects in the sensory cortex, like hierarchical pattern recognition, receptive fields, pooling and normalization, have started to be understood[5]. But models of the binding operations required for construction of complex, possibly hierarchical, symbolic structures on which precise manipulation of its components is a requisite, lack empirical testing and are still unable to predict neuroimaging signals. In this sense, bridging the gap between experimental neuroimaging evidence and the available modelling solutions to the binding problem is a crucial step for the advancement of our understanding of the brain computation and representation of symbolic structures. From the recognition of this problem, the goal of this PhD became the identification and experimental test of the theories, based on neural networks, capable of dealing with symbolic structures, for which we could establish testable predictions against existing fMRI and ECoG neuroimaging measurements derived from language processing tasks. We identified two powerful but very different modelling approaches to the problem. The first is in the context of the tradition of Vectorial Symbolic Architectures (VSA) that bring precise mathematical modelling to the operations required to represent structures in the neural units of artificial neural networks and manipulate them. This is Smolensky’s formalism with tensor product representations (TPR)[10], which he demonstrates can encompass most of the previous work in VSA, like Synchronous Firing[9], Holographic Reduced Representations[8] and Recursive Auto-Associative Memories[1]. The second, is the Neural Blackboard Architecture (NBA) developed by Marc De Kamps and Van der Velde[11], that importantly differentiates itself by proposing an implementation of binding by process in circuits formed by neural assemblies of spiking neural networks. Instead of solving binding by assuming precise and particular algebraic operations on vectors, the NBA proposes the establishment of transient connectivity changes in a circuit structure of neural assemblies, such that the potential _ow of neural activity allowed by working memory mechanisms after a binding process takes place, implicitly represents symbolic structures. The first part of the thesis develops in more detail the theory behind each of these models and their relationship from the common perspective of solving the binding problem. Both models are capable of addressing most of the theoretical challenges posed currently for the neural modelling of symbolic structures, including those presented by Jackendo_[3]. Nonetheless they are very different, Smolenky’s TPR relies mostly on spatial static considerations of artificial neural units with explicit completely distributed and spatially stable representations implemented through vectors, while the NBA relies on temporal dynamic considerations of biologically based spiking neural units with implicit semi-local and spatially unstable representations implemented through neural assemblies. For the second part of the thesis, we identified the superposition principle, which consists on the addition of the neural activations of each of the sub-parts of a symbolic structure, as one of the most crucial assumptions of Smolensky’s TPR. (...)

One of the major goals of cognitive neuroscience is to better understand the psychological and neural bases of human executive-attention. Executive or supervisory attention refers to a collection of higher-order cognitive functions whose primary contribution to behavior is to support controlled information processing and action. The capacity to control attention is essential for our adaptive interaction with the environment because it allows flexibility in our responses to ever changing situational contexts and demands. Executive-attention processes therefore play a unique role in shaping the human experience. Use of three-dimensional functional neuroimaging has fast become the empirical standard for investigating how executive-attention is implemented in the human brain. Most recently, emphasis has been placed on the use of these techniques to parse discrete components of a putative neural network relating to action-monitoring and cognitive control processes of the medial and lateral prefrontal cortex. This work has relied heavily on the use of popular experimental paradigms such as the Stroop task and their unique capacity to challenge such processes in humans. These tasks have also been especially useful for conceptualizing the nature of higher-cognitive dysfunction in complex brain disorders such as schizophrenia. The focus of this thesis concerns a novel application of the Stroop paradigm and functional imaging approach to examine executive-attention performance in healthy subjects and patients with schizophrenia and obsessive-compulsive disorder. On one hand, this work aimed to address current ideas on the nature of executive-control mechanisms and how they may be compromised in these two common psychiatric disorders. On the other hand, this work aimed to examine important conceptual and methodological issues associated with functional imaging approaches to the study of higher-cognition and cognitive psychopathology in humans. In line with connectionist models of executive-attention phenomena, the first study in this thesis investigated the effects of task practice on a larger-scale neurocognitive network associated with performance of the Stroop task in healthy subjects. This study involved the use of a novel methodological approach to model physiological covariances or ?functional connectivity? in PET data, which generated previously unseen and interesting insights into the neural basis of Stroop phenomena, whilst complimenting existing ideas on the role of the anterior cingulate and lateral prefrontal cortex in mediating executive-control functions. These findings were then extended to a comparative study of patients with schizophrenia and obsessive-compulsive disorder. This study largely corroborated previous reports of prefrontal executive dysfunction in schizophrenia, although patients also showed evidence for a compensatory strengthening of connectivity in a fronto-parietal network that accompanied task practice. This finding has important implications for existing models of higher-cognitive dysfunction and abnormal brain integration in schizophrenia. For patients with OCD compared to healthy subjects, performance of the Stroop task evoked a pattern of abnormal connectivity among predominantly corticostriatal regions, including a previously reported hyperfunction of the dorsal anterior cingulate cortex. While this latter result has been linked to a specific disturbance of action-monitoring in patients with OCD, the current study suggests that this may map onto a more extensive corticostriatal network abnormality in line with current theoretical models of this illness. One caveat raised in the first study of patients with schizophrenia concerned the effects of illnesschronicity and medication on functional imaging studies of higher-cognition and prefrontal function in schizophrenia. To address this, a second clinical study was undertaken in patients with a first-episode of schizophrenia (diagnosis confirmed at follow-up) who were examined before and after commencing antipsychotic treatment. Overall, the findings from this study support the idea of trait-like disturbances of prefrontal executive function in schizophrenia; however, they also suggested that aspects of this disturbance may be specific to the critical, early stage of illness - implicating progressive changes with illness chronicity and/or treatment intervention. These findings are discussed in relation to the developmental context of cognitive psychopathology in schizophrenia.

<p>Although consciousness has been studied since ancient time, how the brain implements consciousness is still considered a great mystery by most. This thesis investigates the neural correlates of consciousness by measuring brain activity with functional magnetic resonance imaging (fMRI) while specific contents of consciousness are defined and maintained in various experimental settings. Study 1 showed that the brain works differently when creating a new conscious percept compared to when maintaining the same percept over time. Specifically, sensory and fronto-parietal regions were activated for both conditions but with different activation patterns within these regions. This distinction between creating and maintaining a conscious percept was further supported by Study 2, which in addition showed that there are both differences and similarities in how the brain works when defining a visual compared to an auditory percept. In particular, frontal cortex was commonly activated while posterior cortical activity was modality specific. Study 3 showed that task difficulty influenced the degree of frontal and parietal cortex involvement, such that fronto-parietal activity decreased as a function of ease of identification. This is interpreted as evidence of the non-necessity of these regions for conscious perception in situations where the stimuli are distinct and apparent. Based on these results a model is proposed where sensory regions interact with controlling regions to enable conscious perception. The amount and type of required interaction depend on stimuli and task characteristics, to the extent that higher-order cortical involvement may not be required at all for easily recognizable stimuli.</p>

Patients suffering from different forms of neurodegenerative diseases, such as: Creutzfeldt Jacob Disease (CJD), Alzheimer disease (AD), mild cognitive impairment (MCI), frontotemporal dementia and Parkinson’s disease (PD) were examined with Positron Emission Tomography (PET) and the combination of different radiotracers: 15O-water, N-[11C-methyl]-L-deuterodeprenyl (DED), [18F] 2-fluorodeoxyglucose: (FDG), N-methyl-[11C]2-(4-methylaminophenyl)-6-hydroxybenzothiazole (PIB) and L-[11C]-3,4-dihydroxiphenyl-alanine (DOPA). The radiotracers and the combinations of different radiotracers were selected with the intention to detect, in the brain, patterns of neuronal dysfunction, astrocytosis, axon degeneration or protein aggregation (amyloid), in the brain which are pathognomonic for specific diseases and may contribute to improve clinical differential diagnoses. Examinations in healthy volunteers were performed to allow comparisons with patients. In addition, animal studies were conducted to complement the information. In some cases, the PET findings could be compared with the results of autopsies. In contrast to the micropathology, in which only a limited part of a tissue (obtained post-mortem or by biopsy) is inspected, one PET acquisition provides an image of the whole system (e.g.: the brain and the cerebellum). This form of imaging pathology is “in vivo”, where the examination is innocuous for the patient. This thesis is an attempt to stimulate the development of new tracers, new tracer combinations and methods that directly or indirectly describe the anatomo-physiopathological changes produced in the brain in neurodegenerative diseases. A better description of different diseases can be obtained, confirming or questioning the clinical diagnoses and widening our understanding of the mechanisms underlying neurodegeneration. Different pathologies can produce similar symptoms and thus causing confusion regarding clinical diagnosis. The used PET combinations improved the accuracy of the diagnoses. The incipient knowledge emerging from a new neuroimaging pathology in combination with other disciplines may open the way to new classifications of dementias and neurodegenerative diseases based on an “in vivo” pathology.

Although consciousness has been studied since ancient time, how the brain implements consciousness is still considered a great mystery by most. This thesis investigates the neural correlates of consciousness by measuring brain activity with functional magnetic resonance imaging (fMRI) while specific contents of consciousness are defined and maintained in various experimental settings. Study 1 showed that the brain works differently when creating a new conscious percept compared to when maintaining the same percept over time. Specifically, sensory and fronto-parietal regions were activated for both conditions but with different activation patterns within these regions. This distinction between creating and maintaining a conscious percept was further supported by Study 2, which in addition showed that there are both differences and similarities in how the brain works when defining a visual compared to an auditory percept. In particular, frontal cortex was commonly activated while posterior cortical activity was modality specific. Study 3 showed that task difficulty influenced the degree of frontal and parietal cortex involvement, such that fronto-parietal activity decreased as a function of ease of identification. This is interpreted as evidence of the non-necessity of these regions for conscious perception in situations where the stimuli are distinct and apparent. Based on these results a model is proposed where sensory regions interact with controlling regions to enable conscious perception. The amount and type of required interaction depend on stimuli and task characteristics, to the extent that higher-order cortical involvement may not be required at all for easily recognizable stimuli.

This work improved the radiosynthesis of a known M2 muscarinic receptor imaging agent, [18F]FP-TZTP, and subsequent syntheses and in vitro evaluation of several novel TZTP derivatives highlighted a lead compound which exhibited M4 potency and selectivity, the thioether fluoro-polyethyleneglycol, which was then adapted for radiolabelling (23% radiochemical yield (uncorrected), >99% radiochemical purity, reaction time of 37 minutes). The present study also seeked to utilize aziridines as intermediates in [18F]-radiolabelling chemistry for the facile radiosynthesis of [18F]-labelled beta-blockers. Novel [18F]-labelled amines were synthesized via ring-opening and deprotection to yield the [18F]-1-fluoro-2-propanamine moiety (85%) favourably over the regioisomer [18F]-2-fluoro-1-propanamine (15%). Subsequent attempts to use these amine synthons in the synthesis of the beta-blocker [18F]Exaprolol resulted in poor radiochemical yields (1-3%). The chemistry of aziridine ring-opening with 19F-fluoride sources was thoroughly explored in order to understand the fundamentals of this chemistry, and the 1-fluoro-2-propanamine moiety was characterized by X-ray crystallography and NMR spectroscopy.

This work improved the radiosynthesis of a known M2 muscarinic receptor imaging agent, [18F]FP-TZTP, and subsequent syntheses and in vitro evaluation of several novel TZTP derivatives highlighted a lead compound which exhibited M4 potency and selectivity, the thioether fluoro-polyethyleneglycol, which was then adapted for radiolabelling (23% radiochemical yield (uncorrected), >99% radiochemical purity, reaction time of 37 minutes). The present study also seeked to utilize aziridines as intermediates in [18F]-radiolabelling chemistry for the facile radiosynthesis of [18F]-labelled beta-blockers. Novel [18F]-labelled amines were synthesized via ring-opening and deprotection to yield the [18F]-1-fluoro-2-propanamine moiety (85%) favourably over the regioisomer [18F]-2-fluoro-1-propanamine (15%). Subsequent attempts to use these amine synthons in the synthesis of the beta-blocker [18F]Exaprolol resulted in poor radiochemical yields (1-3%). The chemistry of aziridine ring-opening with 19F-fluoride sources was thoroughly explored in order to understand the fundamentals of this chemistry, and the 1-fluoro-2-propanamine moiety was characterized by X-ray crystallography and NMR spectroscopy.

The aim of this essay is to give an overview of the topic of intrinsic motivation based on psychological an neuroimaging research. More specifically, the objective is to give an overview of the various benefits of intrinsic motivation, discuss its relationship to extrinsic rewards, and review the existing neuroimaging research that has explicitly explored intrinsic motivatoin. A positive relationship betweeen intrinsic motivation and persistence, conceptual learning, creativity, and both hedonic and eudaimonic well-being has been demonstrated. A wealth of studies has shown that extrinsic rewards undermine intrinsic motivation, while the validity of these findings has been debated. Initial neuroimaging studies concerning the neural basis of intrinsic motivation have been conducted, showing unique activations in the intrinsic motivation conditions in e.g. the anterior precuneus and the right insular cortex. Conceptual and methodological problems have been discussed, and it is suggested that the neuroscientific findings mentioned above can be interpreted in terms of the neural distinction between wanting and liking, rather than in terms of intrinsic and extrinsic motivation, and that psychological research can draw on neuroscientific findings in order to make its research more precise.

Brain decoding involves the determination of a subject’s cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a finite set, and the neuroimaging data comprise voluminous amounts of spatiotemporal data measuring some aspect of the neural signal. The associated statistical problem is one of classification from high-dimensional data. We explore the use of functional principal component analysis, mutual information networks, and persistent homology for examining the data through exploratory analysis and for constructing features characterizing the neural signal for brain decoding. We review each approach from this perspective, and we incorporate the features into a classifier based on symmetric multinomial logistic regression with elastic net regularization. The approaches are illustrated in an application where the task is to infer from brain activity measured with magnetoencephalography (MEG) the type of video stimulus shown to a subject. / Graduate

Patients with Amyotrophic lateral sclerosis (ALS) often experience cognitive impairment that accompanies degeneration of the motor system. A valuable tool for assessing cognitive control over behaviour is the antisaccade task which requires: 1) inhibition of the automatic response to look towards an eccentric visual stimulus (prosaccade) to instead 2) redirect gaze in the opposite direction of the stimulus (antisaccade). Psychometric tests were used to quantify the degree of impairment, while eye tracking, functional magnetic resonance imaging (fMRI) and structural MRI were combined to identify the neural correlates of cognitive impairment in ALS. We predict ALS patients will have executive dysfunction and grey matter loss in executive and oculomotor control areas that will affect antisaccade performance and will alter the corresponding brain activation. ALS patients and age-matched controls participated in a rapid-event-related fMRI design with interleaved pro- and antisaccade trials. Catch trials (no stimulus presented after instructional cue to prepare pro- or antisaccade) allowed us to discern the preparatory period from the execution period. ALS patients were biased towards automatic saccade responses, and had greater difficulty with antisaccades relative to controls in terms of correct and timely responses. We found that worsened antisaccade performance in ALS correlated with the degree of cognitive impairment. Generally, we found trends of increased brain activation during the preparatory period of antisaccades in ALS patients compared to controls in most oculomotor areas; meanwhile few differences were seen during execution. Structural analyses revealed ALS patients had decreased grey matter thickness in frontotemporal and oculomotor regions such as the frontal and supplementary eye fields (FEF, SEF) and the dorsolateral prefrontal cortex (DLPFC). These findings suggest that loss of structural integrity and executive dysfunction may elicit compensation mechanisms to improve functional and behavioural performance. Despite this compensation, ALS patients still performed worse on antisaccades than controls. Further investigation to expand the current data set should improve our ability to assuredly identify the neural correlates of cognitive decline in ALS, and may provide a model system to use for critical evaluation of future therapies and interventions for ALS. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2011-09-22 14:20:39.704