L'arithmétique est une des inventions majeures de l'humanité, mais il nous manque encore une compréhension globale de la façon dont le cerveau calcule les additions et soustractions. J'ai utilisé une nouvelle méthode comportementale basée sur un suivi de trajectoire capable de disséquer la succession des étapes de traitement impliquées dans les calculs arithmétiques. Les résultats sont compatibles avec un modèle de déplacement pas à pas sur une ligne numérique mentale, en commençant par l'opérande le plus grand et en ajoutant ou soustrayant de manière incrémentielle l'opérande le plus petit. Ensuite, j'ai analysé les signaux électrophysiologiques enregistrés à partir du cortex humain pendant que les sujets résolvaient des additions. L'activité globale dans le sillon intrapariétal augmentait au fur et à mesure que les opérandes grossissaient, prouvant son implication dans le calcul et la prise de décision. Étonnamment, les sites dans le gyrus temporal inférieur postérieur ont montré que l’activation initiale diminuait en fonction de la taille du problème, suggérant un engagement dans l'identification précoce de la difficulté de calcul. Enfin, j'ai enregistré des signaux de magnétoencéphalographie pendant que les sujets vérifiaient les additions et soustractions. En appliquant des techniques d'apprentissage automatique, j'ai étudié l'évolution temporelle des codes de représentation des opérandes et fourni une première image complète d'une cascade d'étapes de traitement en cours sous-jacentes au calcul arithmétique. Ainsi, cette dissertation fournit-elle plusieurs contributions sur la façon dont les concepts mathématiques élémentaires sont mis en œuvre dans le cerveau. / Arithmetic is one of the most important cultural inventions of humanity, however we still lack a comprehensive understanding of how the brain computes additions and subtractions. In the first study, I used a novel behavioral method based on trajectory tracking capable of dissecting the succession of processing stages involved in arithmetic computations. Results supported a model whereby single-digit arithmetic is computed by a stepwise displacement on a spatially organized mental number line, starting with the larger operand and incrementally adding or subtracting the smaller operand. In a second study, I analyzed electrophysiological signals recorded from the human cortex while subjects solved addition problems. I found that the overall activity in the intraparietal sulcus increased as the operands got larger, providing evidence for its involvement in arithmetic computation and decision-making. Surprisingly, sites within the posterior inferior temporal gyrus showed an initial burst of activity that decreased as a function of problem-size, suggesting an engagement in the early identification of the calculation difficulty. Lastly, I recorded magnetoencephalography signals while subjects verified additions and subtractions. By applying machine learning techniques, I investigated the temporal evolution of the representational codes of the operands and provided a first comprehensive picture of a cascade of unfolding processing stages underlying arithmetic calculation. Overall, this dissertation provides several contributions to our knowledge about how elementary mathematical concepts are implemented in the brain.

Overexpression of the NR2B subunit of the NMDA receptor in the forebrain has been shown to improve learning and memory in mice (Tang et al 1999), which provides exciting implications for the enhancement of human cognition. However, it was first essential to establish replicability, and since the Tang et al (1999) study used only male mice we wished to investigate possible sex differences. On the hidden platform watermaze, we found a trend for male NR2BOE mice to learn the task more quickly than male wildtype mice (as observed by Tang et al. 1999), but the opposite trend in female mice; female NR2BOE mice were slower to reach the hidden platform than female wildtype mice. This pattern of results was also observed on the spatial reference Y memory task and open field task (for anxiety), although not on the spatial working memory T maze task (despite a sex difference). However, wildtype and NR2BOE mice performed at similar levels on the novel object recognition task, the spatial novelty preference task, visible platform watermaze and visual discrimination task. A battery of tests considering some species typical behaviours of mice demonstrated that wildtype and NR2BOE mice were comparable on tests of motor ability, strength, co-ordination, anxiety, burrowing and nesting. This suggests that our behavioural results are not due to a general impairment or enhancement of species typical behaviours. We considered the possibility that the difference between the results of Tang et al (1999) and those we observed may be caused by age differences; hence we attempted to replicate our results on the hidden platform watermaze, spatial reference Y maze and open field test in age matched mice. However, the second cohort of NR2BOE mice performed at similar levels to wildtype mice, and at significantly improved levels compared to the mice of the first cohort. We also considered the effects of knocking out the NR2B subunit on learning and memory, and NR1 subunit deletion within the hippocampus. On the spatial working memory T maze, these mouse strains performed similarly to their respective wildtype strains. Similarly, on a two beacon watermaze (with one indicating the platform position), mice lacking the NR2B subunit were able to locate the platform in a similar length of time. To ensure that the null results we had observed in the second cohort were not due to loss of the NR2B protein overexpression in the forebrain, we performed polymerase chain reactions (PCR), quantitative real-time PCR, and Western blots. We ascertained that the transgene was indeed present and that NR2B mRNA and protein levels were elevated in the hippocampi of the NR2BOE mice. In conclusion, it is unclear why the behaviours we observed in the NR2BOE mice are different to those published in the literature. It is possible that they may be due to differences in environmental enrichment, but the cause of the genotype by sex differences observed in the mice of cohort 1 is unclear. Nonetheless, we have advanced our knowledge of the effects of modifications in the levels of the NR2B subunit of the NMDA receptor on learning and behaviour.

Selective attention is a mechanism used to allocate resources to information processing. Both mood states and emotionally salient stimuli can influence which information is selectively attended. This information is subsequently processed in a more elaborative manner and affects task performance. The experiments presented in this thesis explore the influence of mood and emotional stimuli on selective attention and consequently task performance. Mood induction procedures were used to induce transient neutral, sad, and happy mood states in healthy volunteers. A systematic review and meta-analysis of 41 studies using sad mood induction procedures showed cognitive impairments in performance in the context of task neutral stimuli. In contrast biases in attention towards mood-congruent negative stimuli led to improved task performance. A series of three behavioural experiments with 197 participants demonstrated that participants made decisions on the basis of less information when that information was preceded by emotional but not neutral stimuli. Induced mood state did not affect performance. The behavioural and neural correlates of visual attentional processing to emotional stimuli were explored using magnetoencephalography in 24 healthy participants following sad, happy, and neutral mood induction procedures. The M300, a component associated with selective attention, had greater amplitude following presentation of negative compared with positive stimuli, which was associated with improved task performance. Reduced M300 amplitude and impairments in performance occurred following sad mood induction procedures. The experiments presented in this thesis demonstrate prioritized processing of emotional information and provide some evidence for impaired performance following sad mood induction procedures.

The notion that we are voluntary agents who exercise power to choose and, in doing so, determine some of what happens in the world has been an important notion in certain theological accounts concerning our relationship with God (e.g. 'the freewill defence' for God's goodness and omnipotence in light of moral evil and accounts of human moral responsibility in relation to God). However, it has been claimed that the physicalism supported by contemporary neuroscience research calls into question human voluntary agency and, with it, human power to choose. Emergentist (or non-reductive physicalist) accounts of psychological phenomena have been presented as a way of reconciling the physicalism supported by contemporary neuroscience and the theologically important notion of human power to choose. But there are several issues that remain for the plausibility of the required kind of emergentist account; namely - Does recent neuroscience research show that voluntary agency is an illusion? and Is there evidence for neurophysiological causes which, along with neurophysiological conditions, determine all we do? In this dissertation I set out to address these issues and, in doing so, present an account of voluntary agency as power to choose in the state of being aware of alternatives. I argue that this account allows for the notion that human beings determine some of what happens in a way that is consistent with what contemporary neuroscience shows. Thus, contemporary neuroscience does not undermine this notion of human voluntary agency; or, then, the predominant theological view that we are morally responsible in our relationship with God.

In everyday life we regularly update our expectations about the locations at which sensory events may occur, and about the motor responses that are appropriate in a given situation. The experiments in this thesis investigated the neural correlates of perceptual processes and motor preparation during human decision making, and the regions that causally contribute to decision making in the human brain. In Chapter 3, I used electroencephalography (EEG) to investigate whether alpha-band (~8-14 Hz) oscillations provide a graded index of participants’ preparatory attentional states. Time-frequency analysis revealed that manipulating spatial certainty regarding the location of an upcoming visual target led to parametric changes in the lateralization of preparatory occipito-parietal alpha oscillations, and to parametric modulation of parieto-central beta-band (~15-25 Hz) power typically associated with response preparation. In Chapter 4, I used EEG to investigate whether evolution of lateralization of sensorimotor alpha- and beta-band activity reflected participants’ evolving expectations about an upcoming motor response. Lateralization of activity in both frequency bands varied parametrically with the available evidence, suggesting such lateralized activity correlates with participants’ internal decision variables. Further analysis identified unique contributions to lateralized and non-lateralized oscillatory activity due to the prior evidence, evidence update, and surprise related to the observed information at each stage of the task. In Chapter 5, I extended the paradigm developed in Chapter 4 for use with online repetitive transcranial magnetic stimulation (TMS) and concurrent EEG recording. Delivery of TMS during decision making allowed investigation of the causal role played by a left hemisphere medial intraparietal region that is the putative human homologue of the macaque medial intraparietal cortex (MIP). MIP stimulation disrupted decision-making behaviour by biasing participants’ decisions against contralateral-to-stimulation (i.e., right-handed) responses. Comparison of the magnitude of TMS-induced changes in behaviour and beta-band activity demonstrated that the intraparietal cortex plays a causal role both in decision making and in the appearance of beta-band activity over the motor cortex. In Chapter 6, the broader consequences of the experimental work presented in this thesis are discussed, in addition to promising directions for future research.

Accelerated long-term forgetting (ALF) is a recently described memory impairment associated with epilepsy. Patients with ALF appear to learn and initially retain new information normally, but forget it at an accelerated rate over subsequent days. ALF can have a profound impact on the lives of the people who suffer from it, but it is also of theoretical interest. In particular, the study of this disorder may provide insight into the mechanisms of memory consolidation. ALF is especially prevalent in transient epileptic amnesia (TEA), an epileptic syndrome in which the seizure focus is thought to be the medial temporal lobes (MTL). The MTL house the hippocampus and a number of other structures critical for declarative memory function. The aims of this doctoral thesis were to investigate which aspects of memory function are disrupted in patients with TEA-associated ALF, and to shed light on the neural basis of the memory impairment. Slow wave sleep (i.e. deep sleep) is known to exacerbate epileptic activity. It is also thought to play a key role in the consolidation of declarative memory. The most commonly posited explanation of ALF is the disruption of sleep- dependent memory consolidation. However, it remains possible that ALF is caused by a subtle problem with encoding that usually goes undetected until delayed memory tests. The results of this thesis demonstrate that sleep can actually benefit memory retention in TEA ALF patients just as much as it does in healthy people, and that it is not necessary for the retention interval to contain sleep in order for ALF to be seen. However, the relationship between slow wave sleep and memory was found to be abnormal in these patients. The amount of slow wave sleep, and the power in the slow oscillation frequency range, during the post-learning night correlated negatively with the benefit of that night of sleep for memory retention. Furthermore, resting-state brain activity patterns thought to reflect post-encoding memory reprocessing were found to correlate negatively with subsequent memory performance in these patients. Another chapter of this thesis provides evidence that TEA ALF patients encode memories abnormally; these patients showed reduced activity in the left hippocampus while viewing stimuli that they went on to forget. Furthermore, this encoding-related brain activity correlated with their long-term forgetting. The final experimental chapter reports a correlation in these patients between grey matter in the left hippocampus and long-term forgetting, which cannot entirely account for the encoding-related brain activity results. The hippocampus and its surrounding structures are thought to be critical to our ability to discriminate between similar stimuli and events. An intriguing hypothesis consistent with the pattern of results in this thesis is that ALF is caused by a functional impairment of the MTL that results in a diminished capacity to distinguish between similar experiences, ultimately causing memory problems; abnormally formed memories may interact with new material and memory consolidation processes in an aberrant manner, leading to retrieval deficits.

The natural world provides sensory systems with noisy and ambiguous information, which is often transformed into a more stable categorical percept. This thesis aims to investigate the nature of the neural representations in the visual system that support this transformation. To do so, we will employ a behavioural task that requires participants to average several independent sources of perceptual information. This task allows for the dissociation of two theoretically orthogonal sources of decision uncertainty: the mean distance of the perceptual information from a category boundary and the variability of the evidence under consideration. Behaviourally, both decreasing the mean distance to bound of information and increasing information variability are associated with increased errors and prolonged response times. We will present a computational model that can account for the independent behavioural effects of these two sources of uncertainty by assuming that categorical decisions are made on the basis of a probabilistic transformation of perceptual evidence. BOLD measurements demonstrate that these effects of mean and variability are supported by a partially dissociable network of brain regions. Electroencephalography demonstrates the differential influence of mean and variance in the pre- and post-decision period. Furthermore, we show that there is adaptation at the level of the perceptual representation to the information variance. Not only does this show that the visual system must represent information at the summary level, in addition to individual feature-based representation, but it also suggests that the costs associated with this form of perceptual uncertainty can be largely mitigated by the adoption of a more suitable representational range.

Catechol-O-methyltransferase (COMT) metabolises catechol-containing compounds, including dopamine. The aim of this thesis was to investigate whether COMT is involved in hippocampal function. This thesis also explored the role of functional polymorphisms within the COMT gene in the pathogenesis of schizophrenia and schizophrenia-related phenotypes. First, as part of a study investigating the role of COMT in schizophrenia, human hippocampal COMT mRNA levels were shown to be neither altered in schizophrenia or bipolar disease, nor affected by COMT genotype. Hence, functional COMT polymorphisms do not appear to operate by altering gross COMT mRNA expression. Importantly, this study showed that COMT is expressed in the human hippocampus. Second, the role of COMT in hippocampal neurochemistry was explored by studying the effect of pharmacological COMT inhibition on catecholamines and metabolites in rat hippocampal homogenates, and extracellularly, using microdialysis. Both demonstrated that COMT modulates hippocampal dopamine metabolism. Thus, hippocampal COMT is of functional significance with respect to dopamine. Third, the effect of COMT inhibition on hippocampus-dependent behaviour was investigated. The results suggested a memory-enhancing effect of pharmacological COMT inhibition on hippocampus-dependent associative and non-associative forms of short-term memory in rats. In contrast, acute COMT inhibition appeared to have no effect on behavioural correlates of ventral hippocampal function i.e. anxiety-like behaviour. In summary, the expression of COMT mRNA in the human hippocampus, as well as the effect of COMT inhibition on rat hippocampal neurochemistry and hippocampus-dependent behaviour provide evidence for a functional role of COMT in the hippocampus. Moreover, changes in COMT activity alter hippocampal dopamine metabolism, which could be a potential mechanism for the role of COMT in hippocampus-dependent short-term memory.

Dopamine is an important neurotransmitter that is involved in several human functions such as reward, cognition, emotions and movement. Abnormalities of the neurotransmitter itself, or the dopamine receptors through which it exerts its actions, contribute to a wide range of psychiatric and neurological disorders such as Parkinson’s disease and schizophrenia. Thus far, despite the great interest and extensive research, the exact role of dopamine and the causalities of dopamine related disorders are not fully understood. Here we have developed multimodal imaging methods, to investigate the release of dopamine and the distribution of the dopamine D2-like receptor family in-vivo in healthy humans. We use the [¹¹C]PHNO PET ligand, which enables exploration of dopamine-related parameters in striatal regions, and for the first time in extrastriatal regions, that are known to be associated with distinctive functions and disorders. Our methods involve robust approaches for the manual and automated delineation of these brain regions, in terms of structural and functional organisation, using information from structural and diffusion MRI images. These data have been combined with [¹¹C]PHNO PET data for quantitative dopamine imaging. Our investigation has revealed the distribution and the relative density of the D3R and D2R sites of the dopamine D2-like receptor family, in healthy humans. In addition, we have demonstrated that the release of dopamine has a functional rather than a structural specificity and that the relative densities of the D3R and D2R sites do not drive this specificity. We have also shown that the dopamine D3R receptor is primarily distributed in regions that have a central role in reward and addiction. A finding that supports theories that assigns a primarily limbic role to the D3R.

Neurodegeneration is a progressive loss of neuron function or structure, including death of neurons, and occurs at many different levels of neuronal circuitry. In this thesis I discuss Parkinson’s Disease (PD), the second most common neurodegenerative disease (NDD). PD is a devastating progressive NDD often with delayed diagnosis due to detection methods that depend on the appearance of visible motor symptoms. By the time cardinal symptoms manifest, 60 to 80 percent or more of the dopamine-producing cells in the substantia nigra are irreversibly lost. Although there is currently no cure, earlier detection would be highly beneficial to manage treatment and track disease progression. However, today’s clinical diagnosis methods are limited to subjective evaluations and observation. Onset, symptoms and progression significantly vary from patient to patient across stages and subtypes that exceed the scope of a standardized diagnosis. The goal of this thesis is to provide the basis of a more general approach to study the brain, investigating early detection method for NDD with focus on PD. It details the preliminary development, testing and validation of tools and methods to objectively quantify and extrapolate motor and non-motor features of PD from behavioral and cognitive output during everyday life. Measures of interest are categorized within three domains: the motor system, cognitive function, and brain activity. This thesis describes the initial development of non-intrusive tools and methods to obtain high-resolution movement and speech data from everyday life and feasibility analysis of facial feature extraction and EEG for future integration. I tested and validated a body sensor system and wavelet analysis to measure complex movements and object interaction in everyday living situations. The sensor system was also tested for differentiating between healthy and impaired movements. Engineering and design criteria of the sensor system were tested for usability during everyday life. Cognitive processing was quantified during everyday living tasks with varying loaded conditions to test methods for measuring cognitive function. Everyday speech was analyzed for motor and non-motor correlations related to the severity of the disease. A neural oscillation detection (NOD) algorithm was tested in pain patients and facial expression was analyzed to measure both motor and non-motor aspects of PD. Results showed that the wearable sensor system can measure complex movements during everyday living tasks and demonstrates sensitivity to detect physiological differences between patients and controls. Preliminary engineering design supports clothing integration and development of a smartphone sensor platform for everyday use. Early results from loaded conditions suggest that attentional processing is most affected by cognitive demands and could be developed as a method to detect cognitive decline. Analysis of speech symptoms demonstrates a need to collect higher resolution spontaneous speech from everyday living to measure speech motor and non-motor speech features such as language content. Facial expression classifiers and the NOD algorithm indicated feasibility for future integration with additional validation in PD patients. Thus this thesis describes the initial development of tools and methods towards a more general approach to detecting PD. Measuring speech and movement during everyday life could provide a link between motor and cognitive domains to characterize the earliest detectable features of PD. The approach represents a departure from the current state of detection methods that use single data entities (e.g.one-off imaging procedures), which cannot be easily integrated with other data streams, are time consuming and economically costly. The long-term vision is to develop a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease.