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Dissertations / Theses on the topic 'Neuroscience of Learning'
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Muñoz, Moldes Santiago. "Learning, self-awareness and the body: A cognitive neuroscience approach to learning from biofeedback." Doctoral thesis, Universite Libre de Bruxelles, 2019. https://dipot.ulb.ac.be/dspace/bitstream/2013/295591/4/ToC.pdf.
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In this dissertation, we aimed at better understanding the role of learning in shaping the contents of consciousness. To capture variations in consciousness, we took subjective measures as a starting point, and we performed several studies measuring their relation to human behavior, peripheral physiology and brain physiology in about 160 participants. We first focused on the learning mechanisms implicated in learning with feedback from the body, and then investigated how autonomic responses related to several aspects of awareness in associative learning tasks. Our results provide evidence that people can improve in their sensitivity to discriminate between mental states, while their confidence in doing so is unaffected. Our results also indicate no evidence for the malleability of phasic heart rate response by implicit knowledge. Taken together, these results suggest that consciousness is not easily influenced by learning with external feedback from the body. At a more abstract conceptual level, we explored several methodological considerations when interpreting changes in subjective reports and separated the potential contributions of knowledge and direct perception. Finally, we presented a novel taxonomy for categorizing neurofeedback paradigms, which may be of help to disentangle the learning process that is implicated in neurofeedback.<br>Doctorat en Sciences psychologiques et de l'éducation<br>info:eu-repo/semantics/nonPublished
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Banks, Jess M. "Chaos and Learning in Discrete-Time Neural Networks." Oberlin College Honors Theses / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1445945609.
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Batson, Melissa Anne. "Task-irrelevant perceptual learning of crossmodal links: specificity and mechanisms." Thesis, Boston University, 2010. https://hdl.handle.net/2144/42191.
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It is clear that in order to perceive the external environment in its entirety, inputs from multiple sensory systems (i.e. modalities) must be combined with regard to each object in the environment. Humans are highly vision-dependent creatures, with a large portion of the human cortex dedicated to visual perception and many multimodal areas proposed to integrate vision with other modalities. Recent studies of multimodal integration have shown crossmodal facilitation (increased performance at short stimulus onset asynchronies, SOA s) and/or inhibition of return ( IOR ; decreased performance at long SOAs) for detection of a target stimulus in one modality following a location-specific cue in a different modality. It has also been shown that unimodal systems maintain some level of plasticity through adulthood, as revealed through studies of sensory deprivation (i.e. unimodal areas respond to multimodal stimuli), and especially through perceptual learning ( PL )--a well-defined type of cortical plasticity. Few studies have attempted to investigate the specificity and plasticity of crossmodal effects or the contexts in which multimodal processing is necessary for accurate visual perception. This dissertation addresses these unanswered questions of audiovisual ( AV ) crossmodal cuing effects by combining findings from unimodal perceptual learning with those of multimodal cuing effects as follows: (1) the short- and long-term effects of audiovisual crossmodal cuing, as well as the plasticity of these effects were systematically examined using spatially specific audiovisual training to manipulate crossmodal associations using perceptual learning; (2) neural correlates of these plastic crossmodal effects were deduced using monocular viewing tests (discriminating simple and complex stimuli) following monocular and orientation specific crossmodal perceptual training; and (3) psychophysical boundaries of plasticity within and among these mechanisms as dependent on task/training type and difficulty were determined by varying stimulus salience and looking at post-PL changes in response operating characteristics.
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Singer, Annabelle. "Learning, remembering, and relating sequences in the hippocampus." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3390077.
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Karlsson, Mattias P. "Network dynamics in the hippocampus during spatial learning." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3324622.
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Kwon, Hyung-Wook. "Learning and memory in the American cockroach, Periplaneta americana: New behavioral paradigms for associative learning." Diss., The University of Arizona, 2002. http://hdl.handle.net/10150/280108.
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Although there is much information about insect associative learning, less is known about the underlying neural mechanisms. This is partly due to the lack of behavioral paradigms providing a suitable model for studying learning mechanisms at the level of individual neurons. This thesis describes the background to, and the demonstration of, two associative learning paradigms: visual associative learning and spatial learning. Both have been developed on the restrained cockroach so that later these methods can be employed in conjunction with electrophysiology. By projecting their antennae intermittently towards a position of potential food sources, cockroaches sample salient information. Here, this antennal behavior, called an "antennal projection response (APR)," is used to demonstrate long-term memory where an APR is elicited by a conditioning stimulus (CS: green light) paired with a spatially coincident odor (unconditioned stimulus: US). The acquired APR to the green light cue persists for up to 72 hours. Spatial learning is also a vitally important behavior in most animals that must remember locations of food and landmarks and that must navigate. Spatial learning abilities were here tested by observing APRs towards a cue, where the cockroach learns the position of a visual cue (CS) associated with a food odor (US), relative to the position of another visual stimulus in the contralateral visual field (the contralateral visual reference stimulus: ConRS). Memory of positional information, tested by altering the relative positions of the CS and ConRS, was investigated. Cockroaches showed significant APRs to visual cues not only when a position of the visual cue and spatial reference cue were exactly matched during training trials, but also during tests when the relative angles between the visual cue and spatial reference cue were matched but rotated around the head's vertical axis. When these angles were not the same as the angle used for training, the CS was not recognized. These results suggest that cockroaches employ two different mechanisms to find a food source: retinotopic matching and recognition of angular relationships between a source and landmark. The application of these paradigms to studies that could investigate possible neural mechanisms of these behaviors is discussed.
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Davey, Jon Daniel. "A THEORETICAL MODEL OF LEARNING EMPLOYING CONSTRUCTIVISM, NEUROSCIENCE, AND PHENOMENOLOGY: CONSTRUCTIVIST NEUROPHENOMENOLOGY." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/445.
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The purpose of this research study was to propose a new learning theory for career and technical education with a foundation in philosophy and neuroscience. It purports to combine constructivism, phenomenology and neuroscience into a proposed learning theory entitled ‘constructivist neurophenomenology embedded in embodied cognition, that is, the formative role that the environment plays in the development of cognitive processes. The theory represents a trinity of constructivism’s genetic epistemology manifesting itself in (a) accommodation, (b) phenomenology’ intentionality, that is there is always something there for consciousness, and (c) neuroscience cell assembly. These three actions of the brain construct consciousness, memory, and learning via metaphorical thinking.
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Otchy, Timothy Matthew. "Neural Circuit Mechanisms Underlying Skill Learning, Adaptation, and Maintenance." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493332.
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Part I
Mastering a motor skill, such as a playing the guitar, requires precisely controlling both spatial and temporal aspects of motor output – that is, what movements to perform when. While it is generally assumed that these aspects are acquired through the same learning processes and in the same circuits, there is also evidence that the brain can control them independently. But if that’s true, how is such modularity in motor control and learning implemented in neural circuitry? To probe this question, we developed a paradigm that ‘trains’ songbirds to change either spatial or temporal aspects of their vocal output and showed that learning in the two domains is implemented in distinct neural circuits. This dissociation extended to premotor nucleus HVC, which we showed encodes changes to temporal but not spectral song structure. Such functional modularity, i.e. different circuits learning and implementing different aspects of motor control, could serve to overcome the limitations of reinforcement learning algorithms in dealing with large task domains.
Having identified key mechanisms by which an acquired motor skill can be modified, we then turned to investigate the mechanisms underlying the formation of circuits during the initial acquisition of a motor skill. The neural circuits controlling learned behaviors develop under genetic constraints and in response to environmental influences. Recent studies have provided an unprecedentedly detailed view of the circuit- and synaptic-level changes that accompany complex motor learning, but have left unexplored how environmental factors influence the formation of the neural circuits underlying motor skills. To address this, we investigated how the lack of a behavioral model affects normal motor circuit development in songbirds, a question with relevance for developmental disorders associated with deficits in imitation. We found that the primary difference in circuit formation was delayed and decreased pruning at a synapse that is a principal locus of learning. We show that this difference in synapse refinement is consistent with it being the principal mechanism driving reduced temporal precision of song and the underlying motor program. Intriguingly, our finding of impaired synapse formation mirrors what has been suggested in previous studies of autism.
Part II
Assigning function to brain areas is a principal aim of neuroscience that is often pursued by rapidly and reversibly manipulating neural activity in behaving animals. An important assumption underlying this experimental regime is that consequent behavioral changes reflect the function of the targeted circuits. In Part II of this dissertation, we demonstrate that this assumption is problematic in that it fails to account for indirect effects on the independent functions of circuits downstream of the targeted area. Transient inactivation of sensorimotor area Nif in songbirds and motor cortex in rats severely disrupts courtship songs and task-specific movement patterns – learned skills that recover spontaneously after permanent lesions of the same areas. How can a brain area be both essential for behavior execution (as assayed by the now preferred method, transient perturbation) and not (as assayed by the traditional method, lesions)? We resolve this seeming paradox in songbirds, showing that sudden silencing of Nif disrupts song and neural dynamics within HVC, a downstream song control nucleus. In parallel with song recovery, the off-target effects resolved within days of lesion, a recovery consistent with homeostatic regulation of neural activity within HVC. These finding have broad implications for how neural circuit manipulations are interpreted and for understanding the mechanisms supporting functional recovery following brain injury.<br>Medical Sciences
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Vasquez-Cropper, Marie E. "Engaging cognitive neurosciences in the classroom /." See Full Text at OhioLINK ETD Center (Requires Adobe Acrobat Reader for viewing), 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=toledo1103302896.
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Project requirement (M.Ed.)--University of Toledo, 2005.<br>Typescript. "Submitted as partial fulfillment of the requirements of the Master of Education degree in Physical Education" Bibliography: leaves 43-46.
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Wanjogu, Edwin. "Potential relevance of neuroscience to guide consumption of multimedia technologies towards enhancing learning." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/23717.
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In the wake of rapidly progressing technology, educational institutions are searching for more innovative uses of educational technologies to teach the new kind of students who are entering into these institutions. The Net Generation (NG), are believed to have grown up surrounded by technology and this poses a challenge of understanding how well-designed technology improvements can enhance a student's educational experience. The main reason as to incorporating technology with education is without a doubt to improve a student's engagement and learning. There is increasing interest in the application of cognitive neuroscience in educational practice to advice on how to improve the learning content to have a more positive impact on the NG with an understanding of the brain. Research does show that if technology is not weaned correctly, can have negative effects and addictive behaviours emerge such as craving, concealing, and lying. There is no link, to the author's knowledge, between these scientific findings of neuroscience and advising institutions on changes and implementations necessary to the learning material. This study sets out to link the three; using Piaget's Theory of Cognitive Development as the guide of the different categories of the NG and a detailed literature review of other theories of this phenomenon, the three elements (Learning, Technology and Neuroscience) were investigated. Using secondary analysis the researcher was able to analyse different data sets of the different age groups as stipulated by Piaget's Theory. Each study sought to investigate the NG with different learning MTs and the effects it had on them. The results were ran through different statistical tests revealing positive links of the three aforementioned elements. The findings asserted that students learning with these multimedia obtained significantly greater learning achievement in comparison to those who were not. Not only so, but these same students were also more motivated by using technology in the classroom for learning and exhibited increased functional connectivity during their engagement. Finally, the three elements were linked by developing a life-stage technology consumption model that will be capable of guiding instructors, NG and the consumers of various MTs.
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Quinn, Connor. "Learning to read : effects of memory consolidation on orthographic and lexical learning." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/278394.
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In recent years the role of offline consolidation in supporting word learning has attracted great interest and has provided valuable insight into how novel spoken and written words are learned. Relatively little attention has focused on whether offline consolidation supports the learning and generalisation of novel orthographic knowledge. Meanwhile, laboratory-based approaches have proven valuable in overcoming the methodological challenges of studying reading acquisition, i.e. learning letter-sound knowledge. This thesis combines laboratory-based orthographic learning with an overnight consolidation framework to track the effects of sleep on learning novel letters and novel written words in six experiments. Experiment 1 validated the artificial orthography paradigm by using fMRI to show the novel orthography activated similar neural regions to pseudowords written in familiar orthography. Comparing recently learned words and objects additionally highlighted the componential and holistic processes that distinguish reading from object naming. Experiments 2, 3, and 4 investigated whether overnight consolidation had contrasting effects on learning novel letters and learning novel written words. All three studies showed overnight improvements in the ability to use and generalise knowledge of letters. Experiment 3 further assessed whether consolidation supported the formation of bigram representations. While the results did not show bigram consolidation, a recognition memory task indicated participants had consolidated the novel spoken words. Experiment 4 manipulated the internal statistical structure of the novel words finding, in contrast to Experiment 3, participants had consolidated the written forms of the novel words. Experiments 5 and 6 asked whether consolidated and unconsolidated spoken words would support orthographic learning. These studies failed to observe previous findings of spoken word consolidation and did not demonstrate clear effects of lexical knowledge on orthographic learning. The findings of the thesis demonstrate the importance of letter-level learning and consolidation during reading acquisition as well as highlighting the value of laboratory-based studies for understanding the interdependent trajectories of the skills involved in reading.
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Makena, Nokuthula. "The effect of exercise on spatial learning and hippocampal proteins in maternally separated adult rats." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13340.
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Includes bibliographical references.<br>Repeated maternal separation (MS) has been reported to induce changes in hypothalamic-pituitary- adrenal (HPA) axis activity leading to abnormal stress responses later in life. Such alterations have also been linked to poor cognitive function. In contrast, exercise enhances cognitive function. Previously, we reported that MS improved object location memory. However, exercise had no effect on object location memory despite increases in levels of synaptophysin and phospho-extracellular signal-regulated protein kinase (pERK) in the hippocampus of non-separated-exercised rats. In the current study, the same MS technique and three-week voluntary exercise regimen were tested to determine their effect on spatial learning in young adult Sprague-Dawley (SD) rats. A total of 144 rats were either maternally separated from postnatal day 2 to 14 or designated as controls. At postnatal day 50, rats were transferred to cages with attached running wheels. Approximately half of the rats were allowed to exercise voluntarily in the wheels whilst the wheels attached to the cages of the remaining non-exercising rats were immobilised. Rats were divided into 3 cohorts. Cohort 1 provided baseline levels of pERK, mitogen-activated protein kinase phosphatase-1 (MKP-1) and brain derived neurotrophic factor (BDNF) after exercise. Cohorts 2 and 3 were trained in the Morris Water Maze (MWM) 1 and 15 days post-exercise, respectively. Consistent with our previous findings, pERK was increased in non-separated-exercised rats post-exercise. MKP-1, the regulator of pERK, was also increased in the non-separated-exercised group. BDNF was decreased in the MS non-exercised group but augmented by exercise. All groups trained immediately after exercise performed similarly in the MWM but MS rats from cohort 3 had better reversal spatial memory. According to these results, repeated MS decreased neurotrophic factors but did not alter the plasticity-related proteins measured in this study. However, this phenomenon was not associated with performance in the spatial learning and memory task in the MWM. These current observations support our previous findings that MS can cause adaptations that lead to improved learning and memory in adulthood.
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Evans, Benjamin D. "Learning transformation-invariant visual representations in spiking neural networks." Thesis, University of Oxford, 2012. https://ora.ox.ac.uk/objects/uuid:15bdf771-de28-400e-a1a7-82228c7f01e4.
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This thesis aims to understand the learning mechanisms which underpin the process of visual object recognition in the primate ventral visual system. The computational crux of this problem lies in the ability to retain specificity to recognize particular objects or faces, while exhibiting generality across natural variations and distortions in the view (DiCarlo et al., 2012). In particular, the work presented is focussed on gaining insight into the processes through which transformation-invariant visual representations may develop in the primate ventral visual system. The primary motivation for this work is the belief that some of the fundamental mechanisms employed in the primate visual system may only be captured through modelling the individual action potentials of neurons and therefore, existing rate-coded models of this process constitute an inadequate level of description to fully understand the learning processes of visual object recognition. To this end, spiking neural network models are formulated and applied to the problem of learning transformation-invariant visual representations, using a spike-time dependent learning rule to adjust the synaptic efficacies between the neurons. The ways in which the existing rate-coded CT (Stringer et al., 2006) and Trace (Földiák, 1991) learning mechanisms may operate in a simple spiking neural network model are explored, and these findings are then applied to a more accurate model using realistic 3-D stimuli. Three mechanisms are then examined, through which a spiking neural network may solve the problem of learning separate transformation-invariant representations in scenes composed of multiple stimuli by temporally segmenting competing input representations. The spike-time dependent plasticity in the feed-forward connections is then shown to be able to exploit these input layer dynamics to form individual stimulus representations in the output layer. Finally, the work is evaluated and future directions of investigation are proposed.
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Ko, Raymond. "The Role of the Basal Ganglia in Executing and Learning Complex Motor Sequences." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493272.
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We learn and perform precise motor sequences to interact with the environment. This ability underlies much of what we do, from playing musical instruments and using new tools to producing fluent speech. Understanding the neural circuits involved in producing these sequences is a central objective of the field of motor learning.
In this dissertation, I study the role of the basal ganglia in complex motor sequence learning and execution, and how they coordinate with the rest of the brain to fulfill both functions. First, I investigate whether the striatum is involved in complex sequence execution by lesioning the dorsolateral striatum (DLS, or sensorimotor striatum) and the dorsomedial striatum (DMS, or associative striatum) in rats trained to execute spatiotemporally precise lever-pressing sequences. Kinematics analysis revealed that DLS lesions significantly disrupted performance, while the DMS was largely dispensable for executing the motor skill. Next, I examined the role of the basal ganglia output in the same task by lesioning the globus pallidus interna (GPi). Third, I explored the role of the DLS and DMS in learning by lesioning the structures prior to training. DLS lesions severely disrupted learning in the task, whereas DMS lesions did not abort learning. Lastly, I examined the role of primary and secondary motor cortices in tutoring the basal ganglia by lesioning them before training. Both cortices have, to at least a degree, redundant functions with respect to learning the task. Overall, this dissertation suggests that the sensorimotor part of the basal ganglia is critical for both executing and learning complex motor sequences.<br>Biology, Organismic and Evolutionary
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Milano, Isabel. "The Characterization of Alzheimer’s Disease and the Development of Early Detection Paradigms: Insights from Nosology, Biomarkers and Machine Learning." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2192.
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Alzheimer’s Disease (AD) is the only condition in the top ten leading causes of death for which we do not have an effective treatment that prevents, slows, or stops its progression. Our ability to design useful interventions relies on (a) increasing our understanding of the pathological process of AD and (b) improving our ability for its early detection. These goals are impeded by our current reliance on the clinical symptoms of AD for its diagnosis. This characterizations of AD often falsely assumes a unified, underlying AD-specific pathology for similar presentations of dementia that leads to inconsistent diagnoses. It also hinges on postmortem verification, and so is not a helpful method for identifying patients and research subjects in the beginning phases of the pathophysiological process. Instead, a new biomarker-based approach provides a more biological understanding of the disease and can detect pathological changes up to 20 years before the clinical symptoms emerge. Subjects are assigned a profile according to their biomarker measures of amyloidosis (A), tauopathy (T) and neurodegeneration (N) that reflects their underlying pathology in vivo. AD is confirmed as the underlying pathology when subjects have abnormal values of both amyloid and tauopathy biomarkers, and so have a biomarker profile of A+T+(N)- or A+T+(N)+. This new biomarker based characterization of AD can be combined with machine learning techniques in multimodal classification studies to shed light on the elements of the AD pathological process and develop early detection paradigms. A guiding research framework is proposed for the development of reliable, biologically-valid and interpretable multimodal classification models.
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Topalidou, Meropi. "Neuroscience of decision making : from goal-directed actions to habits." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0174/document.
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Les processus de type “action-conséquence” (orienté vers un but) et stimulus-réponse sont deux composants importants du comportement. Le premier évalue le bénéfice d’une action pour choisir la meilleure parmi celles disponibles (sélection d’action) alors que le deuxième est responsable du comportement automatique, suscitant une réponse dès qu’un stimulus connu est présent. De telles habitudes sont généralement associées (et surtout opposées) aux actions orientées vers un but qui nécessitent un processus délibératif pour évaluer la meilleure option à prendre pour atteindre un objectif donné. En utilisant un modèle computationnel, nous avons étudié l’hypothèse classique de la formation et de l’expression des habitudes au niveau des ganglions de la base et nous avons formulé une nouvelle hypothèse quant aux rôles respectifs des ganglions de la base et du cortex. Inspiré par les travaux théoriques et expérimentaux de Leblois et al. (2006) et Guthrie et al. (2013), nous avons conçu un modèle computationnel des ganglions de la base, du thalamus et du cortex qui utilise des boucles distinctes (moteur, cognitif et associatif) ce qui nous a permis de poser l’hypothèse selon laquelle les ganglions de la base ne sont nécessaires que pour l’acquisition d’habitudes alors que l’expression de telles habitudes peut être faite par le cortex seul. En outre, ce modèle a permis de prédire l’existence d’un apprentissage latent dans les ganglions de la base lorsque leurs sorties (GPi) sont inhibées. En utilisant une tâche de bandit manchot à 2 choix, cette hypothèse a été expérimentalement testée et confirmée chez le singe; suggérant au final de rejeter l’idée classique selon laquelle l’automatisme est un trait subcortical<br>Action-outcome and stimulus-response processes are two important components of behavior. The former evaluates the benefit of an action in order to choose the best action among those available (action selection) while the latter is responsible for automatic behavior, eliciting a response as soon as a known stimulus is present. Such habits are generally associated (and mostly opposed) to goal-directed actions that require a deliberative process to evaluate the best option to take in order to reach a given goal. Using a computational model, we investigated the classic hypothesis of habits formation and expression in the basal ganglia and proposed a new hypothesis concerning the respective role for both the basal ganglia and the cortex. Inspired by previous theoretical and experimental works (Leblois et al., 2006; Guthrie et al., 2013), we designed a computational model of the basal ganglia-thalamus-cortex that uses segregated loops (motor, cognitive and associative) and makes the hypothesis that basal ganglia are only necessary for the acquisition of habits while the expression of such habits can be mediated through the cortex. Furthermore, this model predicts the existence of covert learning within the basal ganglia ganglia when their output is inhibited. Using a two-armed bandit task, this hypothesis has been experimentally tested and confirmed in monkey. Finally, this works suggest to revise the classical idea that automatism is a subcortical feature
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Van, Vugt Floris. "Sounds on time: auditory feedback in motor learning, re-learning and over-learning of timing regularity." Phd thesis, Université Claude Bernard - Lyon I, 2013. http://tel.archives-ouvertes.fr/tel-00915893.
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Le feedback auditif se définit comme un signal auditif qui contient de l'information sur un mouvement. Il a été montré que le feedback auditif peut guider le mouvement en temps réel, mais son influence sur l'apprentissage moteur est moins clair. Cette thèse a pour but d'examiner l'influence du feedback auditif sur l'apprentissage moteur, en se focalisant sur le contrôle temporel des mouvements. Premièrement, nous étudions l'apprentissage moteur chez les non-musiciens sains et montrons qu'ils bénéficient de l'information temporelle contenue dans le feedback auditif et qu'ils sont sensibles aux distortions de cette information temporelle. Deuxièmement, nous appliquons ces connaissances à la rehabilitation de patients cérébro-lésés. Nous trouvons que ces patients améliorent leurs capacités de mouvement mais ne dépendent pas de la correspondance temporelle entre le mouvement et le son. Paradoxalement, ces patients ont même benéficié des distortions temporelles dans le feedback. Troisièmement, nous étudions les experts musicaux, car ils ont établi des liens particulièrement forts entre leur mouvement et le son. Nous développons de nouveaux outils d'analyse qui nous permettent de séparer les déviations temporelles en variation systématique et non-systématique. Le résultat principal est que ces experts sont devenu largement indépendents du feedback auditif. La proposition centrale de cette thèse est que le feedback auditif joue un rôle dans l'apprentissage moteur de la regularité, mais la façon dont le cerveau l'utilise dépend de la population étudiée. Ces résultats donnent une nouvelle perspective sur l'intégration audio-motrice et contribuent au développement de nouvelles approches pour l'apprentissage de la musique et la réhabilitation.
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Ferrando, Esteve Lara. "Neuroscience in algebraic problem solving: Studying the reversal error." Doctoral thesis, Universitat Jaume I, 2021. http://hdl.handle.net/10803/670747.
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En aquest treball s’ha aportat coneixement a la societat d’un dels errors més comuns durant la resolució de problemas matemàtics, com és l’error d’inversió (EI). A més s’ha aportat coneixement a tres grans camps com son la neurociència i la didàctica de la matemàtica (conegudes com Neuroeducació matemàtica) i l’estadística. Al camp de la Neuroeducació matemàtica aporta més coneixement sobre l’EI. Sent el primer estudi que utilitza imatges de ressonància magnètica per a estudiar els processos cerebrals durant la realització de tasques amb EI. Al camp de les matemàtiques s'han aportat noves metodologies de classificació que es poden aplicar tant a problemes neuroeducatius com d’altres tipus, i on s'ha vist que les àrees cerebrals són bons biomarcadors per a fer la classificació. A més s’han aplicat les metodologies tant per a classificació nominal com ordinal.<br>This thesis has provided society with knowledge of one of the most common errors when carrying out mathematical problem solving, such as the reversal error (RE). In addition, there have been contributions in three main fields: neuroscience and mathematics didactics (known as mathematical neuroeducation) and statistics.
In the field of mathematical neuroeducation, this thesis improves the knowledge about RE. It is the first work to use magnetic resonance imaging to study brain processes during RE tasks. In the field of mathematics, new classification methodologies have been proposed, which can be applied both to neuroeducational problems and to other fields. Furthemore, it has been seen that brain areas are good biomarkers for classification. In addition, methodologies have been proposed for nominal and ordinal classification.
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Sampaio, Baptista Silvia Cassandra. "Imaging structural and functional brain changes associated with long-term learning." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:eec1c1ac-f951-4133-aa2e-53a1eeab4fae.
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Learning induces functional and structural plasticity. This thesis used a range of neuroimaging approaches in both humans and rodents to address three main questions: (1) Can we predict learning performance using baseline imaging measures? (2) To what extent do performance outcomes or training amount determine experience-dependent plastic changes? (3) What biological mechanisms underlie white matter plasticity detected using MRI? Effects of performance and amount of practice on brain structure were studied by varying the amount of juggling practice. Brain structure was found to predict performance on a complex juggling task before learning acquisition. Both performance and practice were found to affect brain structure after learning. Overall, participants that achieved higher performances had higher grey matter (GM) and WM matter change. Also, participants that trained juggling for longer had higher positive brain changes than participants that practiced less. The effects of juggling performance and practice in functional connectivity and GABA levels as measured by MR spectroscopy (MRS) were also investigated. High intensity training was found to decrease the motor resting-state network strength while lower intensity increased the network strength. The increase in strength was associated with a decrease in GABA concentration. A correlation was also found between motor resting-state strength change and GABA concentration change after learning. Finally, since WM plasticity has not been thoroughly investigated and to understand which cellular events underlie WM change, an animal model of motor learning was combined with diffusion tensor imaging (DTI) and immunohistochemistry. Learning a novel motor task increased WM fractional anisotropy, an indirect measure of WM microstructure, in the contralateral hemisphere to the used paw. Immunohistochemistry staining with myelin basic protein (MBP) antibody of this region revealed higher myelin stain intensity for the learning group that correlated with performance in the task.
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Smith, Benjamin R. "Inhibitory learning in Hermissenda crassicornis photoreceptors light responses, conductance changes, and computer modeling /." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3278465.
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Thesis (Ph.D.)--Indiana University, Dept. of Neuroscience, 2007.<br>Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6516. Adviser: Joseph Farley. Title from dissertation home page (viewed May 21, 2008).
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Shen, Jiemin 1968. "The aging hippocampus: Neural mechanisms underlying learning and memory deficits in old rats." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290678.
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This dissertation focuses on the effect of aging on two functional aspects of rat hippocampus: cholinergic synaptic transmission and place specific firing of CA1 pyramidal cells. The effect of age on the cholinergic slow EPSP was studied in hippocampal slices of young, adult and old rats. The old rats were impaired on the spatial version of the Morris water task. The amplitude of the slow EPSP was significantly reduced in old rats in all hippocampal subregions (CA1 59%; CA3 55%; and DG 56%). Few statistically significant correlations, however, were found between the age-related deficit in spatial learning and the cholinergic deficit. In the subsequent study, effects of selective neurotoxic lesions of cholinergic afferents to the hippocampus on performance on two versions (spatial working memory and spatial reference memory) of the radial-8-arm maze task were examined. The lesioned rats were impaired in acquisition, but not retention, of the working memory task. There was no treatment effect, however, on acquisition of the reference memory task. The results suggest that the age-related deficits in hippocampal cholinergic function may contribute to behavioral deficits of old rats in working memory situations, but may not be primarily responsible for the spatial reference memory problem in the Morris water task. The spatial and temporal firing characteristics of CA1 neurons were studied in young and old rats performing a simple spatial task on a rectangular track. The average place fields of young rats were larger than those of old rats. Precession of spike discharge relative to the theta rhythm proceeded faster in old rats, while the total phase change remained constant. These age-related changes were apparently due to a loss of experience dependent place field expansion of old rats during the first few laps around the track for a given recording session. The field sizes were not different between groups on lap 1. Because experience-dependent place field expansion is a prediction of two recent theories which invoke asymmetric Hebbian LTP, the present observations point towards a substantial deficit in an LTP-like process in old rats.
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Sanderson, David John. "The hippocampus and structural learning." Thesis, Cardiff University, 2005. http://orca.cf.ac.uk/55382/.
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The hippocampus has been implicated in the learning and memory of arrays of spatial cues. Certain theories of the function of the hippocampus have stressed the importance of the hippocampus in learning about configurations of stimuli that have non-linear associations. Recent evince has suggested that the hippocampus may not be responsible for learning about unique configurations but rather the unique spatial relationships formed by a configuration of visual cues. This thesis examines the effects of hippocampal lesions on visual configural discriminations, in which the solution relies on learning the features that are necessary for configural learning, and also discriminations in which the solution of the task relies on learning the spatial structure of the features that form the configurations. It was found that hippocampal lesions made after acquisition impaired performance of a structural discrimination. Hippocampal lesions did not impair performance of previously acquired configural discriminations. A probe test revealed that although hippocampal lesioned and control rats do not differ on performance of a configural discrimination that does not require learning structural information, control rats learn the structural features of the configurations to a greater extent than hippocampal lesioned rats. Hippocampal lesioned rats were impaired at learning structural information when a task explicitly demanded, and when the structural features were incidental to the requirements of a task. The results are discussed with regards to a configural account of hippocampal dependent allocentric spatial learning, and also theories of hippocampal dependent stimulus representation
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Croft, Katie Elizabeth. "Exploring the role of ventromedial prefrontal cortex in human social learning: a lesion study." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/350.
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Converging evidence suggests a critical role for the ventromedial prefrontal cortex (vmPFC) in social cognition, but its specific contribution to various aspects of social cognition, including the acquisition and updating of complex social information, is not well understood or documented via a systematic experimental approach. The primary aim of this dissertation is to determine whether the vmPFC is necessary for the integration of complex social information in order to form normal moral and social judgments about people. In the first of two studies presented here, I examined the roles of the vmPFC and the hippocampus in updating one's moral judgment of others. I hypothesized that both the vmPFC and the hippocampus are critical--but in different ways--for updating character judgments in light of new social and moral information. To test this hypothesis, I used a novel moral "updating" task and compared the performances of patients with bilateral vmPFC damage to patients with bilateral hippocampal damage (HC), and brain-damaged comparison (BDC) patients. The results suggest that the vmPFC may attribute emotional salience to moral information, whereas the hippocampus may provide necessary contextual information from which to make appropriate character judgments. In the second study, I specifically examined whether the vmPFC is necessary for the integration of simple versus complex, and social versus nonsocial information in order to form normal judgments about people. I hypothesized that patients with circumscribed damage to the vmPFC would be impaired in integrating complex social information. To test this prediction, I employed a novel decision making task and compared the performances of vmPFC patients with BDC patients, and a group of normal, healthy individuals. I also explored which anatomical sectors within the vmPFC system are responsible for normal social information integration. Going against my predictions, most participants were better at making the best choice when more information was available. On the whole, all groups were more accurate in choosing the best nonsocial choice versus the social choice, and this is attributed to the fact that the nonsocial trials were much easier for the participants. Overall, vmPFC patients were inferior to the other groups in choosing the best option for both the social and nonsocial conditions, which suggests that vmPFC patients may have a general impairment in integrating information. The subjective ratings data revealed that the vmPFC patients: perceived the choices to be more difficult overall, had difficulty discriminating between the best and worse options, did not provide the same subjective influence weights as the comparison groups, and endorsed social choices being overall more difficult than nonsocial choices. The neuroanatomical data revealed that unilateral left vmPFC damage may have contributed the most to impairment in making the correct choice for the social condition, and overall, left hemisphere vmPFC lesion volume correlated negatively with percentage correct on my experimental task.
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Vahie, Sankait 1968. "Dynamic neuronal ensembles: A new paradigm for learning." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290699.
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This document presents a new paradigm for learning, based on an abstraction of the mechanisms found in biological neural networks. Biologically motivated neurons, referred to as Dynamic Neurons are connected together in a knowledge-bearing topology to create Dynamic Neuronal Ensembles. The neurons are developed by first identifying key mechanisms and analyzing their computational significance. These mechanisms are then incorporated into the implementation of the dynamic neurons that make up the dynamic neuronal ensemble. While almost all these mechanisms have been studied and incorporated into the development of models of biological neurons in isolation or as subgroups, a single model incorporating these mechanisms in their computationally abstract form has not been implemented and analyzed. The motivation for this research is two-fold. Firstly, to provide biologists with a modular, flexible tool, incorporating current state-of-the-art modeling and simulation capabilities for use in hypothesis testing, development and analysis. Conversely, to provide engineers with a new paradigm for the development of adaptable, evolutionary systems capable of learning in a dynamic environment. Preliminary results of an implementation of the DNE models in DEVS are presented. A biological model of the Snail Aplysia and an application of its behavioral functionality for engineering are also demonstrated.
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Gold, Brian J. "Quantifying expert and impaired imitative learning." Waltham, Mass. : Brandeis University, 2008. http://dcoll.brandeis.edu/handle/10192/22925.
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Oliver, Jason A. "Effects of Nicotine Withdrawal on Motivation, Reward Sensitivity and Reward-Learning." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5754.
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Research on addictive behavior has traditionally emphasized the role that primary reinforcing effects of drugs of abuse plays in the development and maintenance of dependence. However, contemporary behavioral economic theory and animal models of nicotine dependence suggest the need for greater attention to the impact that response to alternative rewards may have on smoking behavior. The present study sought to investigate the impact of nicotine withdrawal on self-report, behavioral and neural indices of motivation, immediate response to rewards and the capacity to learn and modify behavior in response to positive and negative feedback. Heavy smokers (n = 48) completed two laboratory sessions following overnight deprivation, during which they smoked either nicotinized or denicotinized cigarettes. At each session, they completed a reward prediction and feedback learning task while electro-encephalographic recordings were obtained, as well as resting state recordings which were used to extract global indices of motivational state. Results confirmed that nicotine withdrawal produced an avoidant motivational state. This effect was strongly related to numerous indices of smoking motivation. Exploratory analyses also revealed numerous moderators of these effects. Behavioral data from tasks provided some support for the impact of nicotine withdrawal on reward and feedback processing, though minimal impact was observed for neural indices. Together, results confirm the manifestation of a broad-spanning impact of nicotine withdrawal on motivational state, but effects on specific reward systems remains unknown. Future research should examine the impact of nicotine withdrawal on other reward-related constructs to better delineate these effects.
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Groves, Adrian R. "Bayesian learning methods for modelling functional MRI." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:fe46e696-a1a6-4a9d-9dfe-861b05b1ed33.
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Bayesian learning methods are the basis of many powerful analysis techniques in neuroimaging, permitting probabilistic inference on hierarchical, generative models of data. This thesis primarily develops Bayesian analysis techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function, perfusion, and structure in the human brain. The first part of this work fits nonlinear biophysical models to multimodal functional MRI data within a variational Bayes framework. Simultaneously-acquired multimodal data contains mixtures of different signals and therefore may have common noise sources, and a method for automatically modelling this correlation is developed. A Gaussian process prior is also used to allow spatial regularization while simultaneously applying informative priors on model parameters, restricting biophysically-interpretable parameters to reasonable values. The second part introduces a novel data fusion framework for multivariate data analysis which finds a joint decomposition of data across several modalities using a shared loading matrix. Each modality has its own generative model, including separate spatial maps, noise models and sparsity priors. This flexible approach can perform supervised learning by using target variables as a modality. By inferring the data decomposition and multivariate decoding simultaneously, the decoding targets indirectly influence the component shapes and help to preserve useful components. The same framework is used for unsupervised learning by placing independent component analysis (ICA) priors on the spatial maps. Linked ICA is a novel approach developed to jointly decompose multimodal data, and is applied to combined structural and diffusion images across groups of subjects. This allows some of the benefits of tensor ICA and spatially-concatenated ICA to be combined, and allows model comparison between different configurations. This joint decomposition framework is particularly flexible because of its separate generative models for each modality and could potentially improve modelling of functional MRI, magnetoencephalography, and other functional neuroimaging modalities.
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Henderson, Amy 1980. "Motor learning in stroke : imaging training induced plasticity." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101716.
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Stroke is a leading cause of death and disability in Western countries and it is estimated that up to 70% of stroke survivors have a long-lasting disability of the upper limb. The purpose of this study was to examine plasticity at the neuronal level to distinguish between recovery and compensation and how this relates to recovery of arm movement at the behavioural and functional levels in five chronic stroke patients. Brain activation patterns associated with a pointing movement involving the whole arm were identified over two baselines and one post-training intervention evaluation. At each evaluation, a clinical physical and cognitive evaluation, and a recording of the movement kinematics was performed. Analysis was performed on three regions of interest (ROI) bilaterally; primary motor cortices (M1), premotor cortices (PMC) and the primary sensorimotor cortices (S1). A measure of signal intensity, the location of peak activation, and a measure of the contribution of each hemisphere in the ROIs was examined on a case-by-case basis. We found a trend for increased contralesional involvement, changes in signal strength in each ROI and shifts in the peak activation in many directions, which paralleled increases in motor functioning. Our results seem to suggest that contralesional involvement in our ROIs may be sustaining recovery in these patients, and we can confirm that the more the activation in the stroke brain returns to the activation seen in healthy individuals, the better the recovery. Although it is possible that an absolute distinction between recovery and compensation at the neuronal level cannot be made, our results show that recovery at the behavioural and functional levels are accompanied by changes in brain activity. A relationship must be determined if we are to venture into using fMRI as a tool to influence clinical decisions during recovery from stroke.
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Kyle, Robert. "Models and metaphors in neuroscience : the role of dopamine in reinforcement learning as a case study." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6263.
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Neuroscience makes use of many metaphors in its attempt to explain the relationship between our brain and our behaviour. In this thesis I contrast the most commonly used metaphor - that of computation driven by neuron action potentials - with an alternative view which seeks to understand the brain in terms of an agent learning from the reward signalled by neuromodulators. To explore this reinforcement learning model I construct computational models to assess one of its key claims — that the neurotransmitter dopamine signals unexpected reward, and that this signal is used by the brain to learn control of our movements and drive goal-directed behaviour. In this thesis I develop a selection of computational models that are motivated by either theoretical concepts or experimental data relating to the effects of dopamine. The first model implements a published dopamine-modulated spike timing-dependent plasticity mechanism but is unable to correctly solve the distal reward problem. I analyse why this model fails and suggest solutions. The second model, more closely linked to the empirical data attempts to investigate the relative contributions of firing rate and synaptic conductances to synaptic plasticity. I use experimental data to estimate how model neurons will be affected by dopamine modulation, and use the resulting computational model to predict the effect of dopamine on synaptic plasticity. The results suggest that dopamine modulation of synaptic conductances is more significant than modulation of excitability. The third model demonstrates how simple assumptions about the anatomy of the basal ganglia, and the electrophysiological effects of dopamine modulation can lead to reinforcement learning like behaviour. The model makes the novel prediction that working memory is an emergent feature of a reinforcement learning process. In the course of producing these models I find that both theoretically and empirically based models suffer from methodological problems that make it difficult to adequately support such fundamental claims as the reinforcement learning hypothesis. The conclusion that I draw from the modelling work is that it is neither possible, nor desirable to falsify the theoretical models used in neuroscience. Instead I argue that models and metaphors can be valued by how useful they are, independently of their truth. As a result I suggest that we ought to encourage a plurality of models and metaphors in neuroscience. In Chapter 7 I attempt to put this into practice by reviewing the other transmitter systems that modulate dopamine release, and use this as a basis for exploring the context of dopamine modulation and reward-driven behaviour. I draw on evidence to suggest that dopamine modulation can be seen as part of an extended stress response, and that the function of dopamine is to encourage the individual to engage in behaviours that take it away from homeostasis. I also propose that the function of dopamine can be interpreted in terms of behaviourally defining self and non-self, much in the same way as inflammation and antibody responses are said to do in immunology.
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Smith, Hannah. "A developmental cognitive neuroscience approach to the investigation of conduct problems and classroom behaviour for learning." Thesis, Goldsmiths College (University of London), 2017. http://research.gold.ac.uk/20630/.
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With a high prevalence of conduct problems (CP) in school-aged children, effective interventions for these youths are of great importance. This thesis considers CP in the context of the classroom, including examinations of executive function (EF) and emotion-related skills; the development and evaluation of a classroom-based intervention to improve behaviours for learning; and an EEG investigation of cognitive control and emotion regulation (ER). The heterogeneous nature of CP is considered throughout, with an examination of the callous-unemotional (CU) traits subtype. In two experimental studies, pupils with CP (with and without CU traits) were found to have deficits in EF and emotion-related skills. Low behavioural and academic self-perceptions and poor student-teacher relationships (STR) were also identified. For the first time, emotion lability/negativity was identified as a mechanism through which CP is associated with student-teacher conflict. A systematic review of intervention outcomes for CU traits indicated generally poorer outcomes for these youths, but demonstrated the potential for behaviour change. Based on this work, a cognitive neuroscience informed intervention for mainstream pupils with CP was developed and evaluated. The intervention yielded mixed results, with poor fidelity from teaching staff possibly accounting for this. Finally, a direct measure of cognitive and emotional control was addressed through a pilot study with adults, using an EEG emotion-induction go/no-go paradigm. A distinct N2 component was found, providing support for this tool as a measure of ER. Self-reported EF and ER were not associated with the N2 response; possible reasons for this are discussed. The results in this thesis advance our understanding of CP in the school context, provide support for the utility of the CU traits distinction, and examine the effectiveness of intervention approaches for these pupils. Furthermore, measurement issues in EF and ER research are highlighted and related to a novel EEG measurement tool.
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Chan, Alexander Mark. "Extracting Spatiotemporal Word and Semantic Representations from Multiscale Neurophysiological Recordings in Humans." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10251.
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With the recent advent of neuroimaging techniques, the majority of the research studying the neural basis of language processing has focused on the localization of various lexical and semantic functions. Unfortunately, the limited time resolution of functional neuroimaging prevents a detailed analysis of the dynamics involved in word recognition, and the hemodynamic basis of these techniques prevents the study of the underlying neurophysiology. Compounding this problem, current techniques for the analysis of high-dimensional neural data are mainly sensitive to large effects in a small area, preventing a thorough study of the distributed processing involved for representing semantic knowledge. This thesis demonstrates the use of multivariate machine-learning techniques for the study of the neural representation of semantic and speech information in electro/magneto-physiological recordings with high temporal resolution. Support vector machines (SVMs) allow for the decoding of semantic category and word-specific information from non-invasive electroencephalography (EEG) and magnetoenecephalography (MEG) and demonstrate the consistent, but spatially and temporally distributed nature of such information. Moreover, the anteroventral temporal lobe (avTL) may be important for coordinating these distributed representations, as supported by the presence of supramodal category-specific information in intracranial recordings from the avTL as early as 150ms after auditory or visual word presentation. Finally, to study the inputs to this lexico-semantic system, recordings from a high density microelectrode array in anterior superior temporal gyrus (aSTG) are obtained, and the recorded spiking activity demonstrates the presence of single neurons that respond specifically to speech sounds. The successful decoding of word identity from this firing rate information suggests that the aSTG may be involved in the population coding of acousto-phonetic speech information that is likely on the pathway for mapping speech-sounds to meaning in the avTL. The feasibility of extracting semantic and phonological information from multichannel neural recordings using machine learning techniques provides a powerful method for studying language using large datasets and has potential implications for the development of fast and intuitive communication prostheses.<br>Engineering and Applied Sciences
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Wittmann, Marco. "From actions to agents : value representation in frontal cortex." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:37387351-cd95-4f24-ad16-1cc67d181a7b.
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In this thesis, I investigated computational and neural mechanisms underlying foraging-related behavior in humans. A consideration of the ecological constraints under which mammalian behavior first evolved guided my investigation of learning and decision-making in frontal cortex. When engaged in foraging, animals have to figure out how profitable their actions are and whether it is better to continue foraging in their current environment or to switch to an alternative. They have to track the reward income of their actions over time and also take into account that the actions of other foraging animals have a direct influence on their reward income (Chapter 1). Based on these observations, I looked at similar types of behavior in humans using computational modeling and functional magnetic resonance imaging. I studied how people evaluate the profitability of their actions over time (Chapter 2). Dorsal anterior cingulate cortex carried a detailed representation of the value of the current foraging action, which was influenced by reward memories with different time constants (Chapter 3). Tracking the reward income of one's actions is not only important in order to learn about the profitability of the environment, it can also inform estimates of one's own and other people's abilities. Ability estimates can be used in a direct way to predict the reward outcome that the actions of one's own self and others will have. I found that people learn about their own and others' abilities in a rational manner but also that ability estimates of self and other were partly confused with each other, depending on whether subjects cooperated or competed with each other (Chapter 4). The confusion effect is reflected in Brodmann area 9 activity indicating that area 9 integrates self and other related information. Perigenual anterior cingulate tracked the ability estimates for oneself, suggesting that it might compute the success expectation of an action independent of particular features of the environment (Chapter 5). In sum, different subregions of medial frontal cortex carried different types of action-related value representations that can guide decision-making.
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Vanes, Lucy Denise. "A systems neuroscience perspective on treatment resistant schizophrenia : the role of cognitive control, reinforcement learning, and myelination." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/a-systems-neuroscience-perspective-on-treatment-resistant-schizophrenia(b453e9a9-03f2-42fd-a676-614b032f7de7).html.
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Approximately a third of patients with schizophrenia do not respond to antipsychotic treatment targeting the dopamine system, suggesting that a separable neural dysfunction may drive psychosis in these patients. This thesis aims to probe the mechanisms underlying treatment response by investigating two cognitive processes which have been implicated in schizophrenia – cognitive control and reinforcement learning – as well as brain myelination. The key hypotheses are that 1) treatment resistant schizophrenia emerges due to a failure to exert cognitive control, characterised by prefrontal hypoactivation and functional dysconnectivity, 2) treatment responsive schizophrenia is selectively associated with a subcortical dopaminergic dysfunction, evident in an abnormal neural signature of reward prediction error (RPE) during reinforcement learning, and 3) treatment resistant schizophrenia is characterised by exacerbated structural dysconnectivity as indexed by myelin content. To dissect these mechanisms, performance and neural activation during a cognitive control task and a reinforcement learning task, as well as myelin water fraction (MWF) were compared between 22 treatment resistant patients, 21 treatment responsive patients, and 24 healthy controls. Treatment resistant and responsive patients showed similarly impaired performance on both tasks compared to controls. During the cognitive control task, resistant patients showed an inverse correlation between frontal activation and psychotic symptoms as well as reduced functional fronto-thalamic connectivity compared to controls. During the reinforcement learning task, responsive patients showed reduced cortical and subcortical RPE related activation compared to controls and treatment resistant patients. MWF was reduced in patients compared to controls in several white matter regions but did not differ between the two patient groups. The findings support distinct neural mechanisms underlying treatment resistant and responsive schizophrenia despite similar behaviour. Functional dysconnectivity within the cognitive control network and a deterioration of frontal activation as a function of symptom severity may perpetuate psychosis despite dopaminergic treatment in treatment resistant schizophrenia, although this is not reflected in an exacerbated myelin dysfunction. The results highlight the importance of stratifying patient samples by treatment response status in future research.
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Wood, David A. "Effects of environmental experience on behavior and neuronal activity in nucleus accumbens core and shell in an appetitive learning task." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?urlv_er=Z39.88-2004&rftv_alf_mt=info:ofi/fmt:kev:mtx:dissertation&resd_at=xri:pqdiss&rftd_at=xri:pqdiss:3219918.
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Thesis (Ph.D.)--Indiana University, Program in Neuroscience and Dept. of Psychological and Brain Sciences, 2006.<br>Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 2993. Adviser: George V. Rebec. "Title from dissertation home page (viewed Jan. 9, 2007)."
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Carrere, Maxime. "Combiner les apprentissages motivés et associatifs." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0191/document.
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Pour pouvoir être autonomes dans un environnement complexe, les humains comme les systèmes artificiels doivent posséder un apprentissage souple et capable de s’adapter au changement. Dans cette thèse, nous nous intéressons à comment cette autonomie peut être obtenue par interactions entre les différents systèmes d’apprentissage de notre cerveau. Pour cela, nous modélisons dans une approche inspirée de la biologie le comportement de certaines des parties du cerveau impliquées dans les apprentissages répondant et opérant, et observons comment leurs interactions permettent un apprentissage flexible dans des tâches impliquant des changements comme l’extinction et le reversal<br>In a complex environment, humans and artificials systems need a flexible learning system to adapt themselves to situations which can change. In this thesis, we study how autonomy can be the result of interactions between the different learning systems of our brain. In particular, in a biologically inspired approach, we model different parts of the brain involved in respondant and operant conditioning, et show how their interactions can promote flexible learning in tasks in which situation can change, like extinction or reversal
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Bouchacourt, Flora. "Hebbian mechanisms and temporal contiguity for unsupervised task-set learning." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066379/document.
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L'homme est capable d'utiliser des stratégies ou règles concurrentes selon les contraintes environnementales. Nous étudions un modèle plausible pour une tâche nécessitant l'apprentissage de plusieurs règles associant des stimuli visuels à des réponses motrices. Deux réseaux de populations neurales à sélectivité mixte interagissent. Le réseau décisionnel apprend les associations stimulus-réponse une à une, mais ne peut gérer qu'une règle à la fois. Son activité modifie la plasticité synaptique du second réseau qui apprend les statistiques d'évènements sur une échelle de temps plus longue. Lorsque des motifs entre les associations stimulus-réponse sont détectés, un biais d'inférence vers le réseau décisionnel guide le comportement futur. Nous montrons que le mécanisme de Hebb non-supervisé dans le second réseau est suffisant pour l'implémentation des règles. Leur récupération dans le réseau de décision améliore la performance. Le modèle prédit des changements comportementaux en fonction de la séquence des réponses précédentes, dont les effets sur la performance peuvent être positifs ou négatifs. Les prédictions sont confirmées par les données, et permettent d'identifier les sujets ayant appris la structure de la tâche. Le signal d'inférence corrèle avec l'activité BOLD dans le réseau fronto-pariétal. Au sein de ce réseau, les n¿uds préfrontaux dorsomédial et dorsolatéral sont préférentiellement recrutés lorsque les règles sont récurrentes: l'activité dans ces régions pourrait biaiser les circuits de décision lorsqu'une règle est récupérée. Ces résultats montrent que le mécanisme de Hebb peut expliquer l'apprentissage de comportements complexes en contrôle cognitif<br>Depending on environmental demands, humans performing in a given task are able to exploit multiple concurrent strategies, for which the mental representations are called task-sets. We examine a candidate model for a specific human experiment, where several stimulus-response mappings, or task-sets, need to be learned and monitored. The model is composed of two interacting networks of mixed-selective neural populations. The decision network learns stimulus-response associations, but cannot learn more than one task-set. Its activity drives synaptic plasticity in a second network that learns event statistics on a longer timescale. When patterns in stimulus-response associations are detected, an inference bias to the decision network guides successive behavior. We show that a simple unsupervised Hebbian mechanism in the second network is sufficient to learn an implementation of task-sets. Their retrieval in the decision network improves performance. The model predicts abrupt changes in behavior depending on the precise statistics of previous responses, corresponding to positive (task-set retrieval) or negative effects on performance. The predictions are borne out by the data, and enable to identify subjects who have learned the task structure. The inference signal correlates with BOLD activity in the fronto-parietal network. Within this network, dorsomedial and dorsolateral prefrontal nodes are preferentially recruited when task-sets are recurrent: activity in these regions may provide a bias to decision circuits when a task-set is retrieved. These results show that Hebbian mechanisms and temporal contiguity may parsimoniously explain the learning of rule-guided behavior
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Wolff, Gabriella Hannah. "Genealogical Correspondence of Learning and Memory Centers across Phyla." Diss., The University of Arizona, 2015. http://hdl.handle.net/10150/556847.
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Across bilaterian phyla, learning and memory allows animals to benefit from central-place foraging, return to ideal food sources, choose mates and avoid dangerous or harmful external stimuli. Although these behaviors are comparable in both vertebrate and invertebrate animals, it is unknown whether or not they are mediated by homologous brain structures. In insects, paired, lobate forebrain structures called mushroom bodies receive input from primary sensory neuropils and are necessary for learning and memory, whereas in crustaceans, this behavior is mediated by paired, compact forebrain structures called hemiellipsoid bodies. Mammalian learning and memory is mediated by the paired, horn-shaped hippocampi, which also receive sensory input and are likewise situated in the forebrain. Did these structures evolve independently along with the ability for animals to learn and remember associations and places? Alternatively, the hypothesis posited in this dissertation is that the last bilaterian ancestor already possessed the ability to learn and adapt to its environment, behavior mediated by paired forebrain structures that evolved divergently into the elaborated forms we observe in extant, crown-group taxa. This hypothesis is investigated and discussed in the following reports: 1) a review of insect brain anatomy and functional connectivity, including a description of mushroom bodies, in the context of arthropod evolution; 2) a comparison of neuroanatomy, circuitry, and protein expression between insect mushroom bodies and Malacostracan crustacean hemiellipsoid bodies, using cockroaches and Caribbean hermit crabs as representatives of their classes; 3) a deeper investigation of the fine structure of neuronal organization in the hemiellipsoid body of the Caribbean hermit crab, focusing on electron microscopical observations and comparisons to the ultrastructure of the fruit fly mushroom body; 4) a survey of four invertebrate Phyla, employing the strategy of comparing neuroanatomy and protein expression to investigate whether higher order forebrain structures in these animals were inherited from a common ancestor; 5) a comparison of neuroanatomy, connectivity, and protein expression in insect mushroom bodies and mammalian hippocampus, including a survey of PKA-Cα in these and corresponding structures across the Chordata. The total evidence suggests that a common Bilaterian ancestor possessed a center that evolved to become mushroom bodies in invertebrates and hippocampus in vertebrates.
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Hoon, A. C. "The effect of manipulating the expression of the NR2B subunit of the NMDA receptor on learning and memory." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:eae324a3-873f-4b50-9bcc-8c43b72866a3.
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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.
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Rapp, Hannes Andreas [Verfasser], Martin Paul [Gutachter] Nawrot, Silvia [Gutachter] Daun, and Thomas [Gutachter] Nowotny. "Spiking neural models & machine learning for systems neuroscience: Learning, Cognition and Behavior. / Hannes Andreas Rapp ; Gutachter: Martin Paul Nawrot, Silvia Daun, Thomas Nowotny." Köln : Universitäts- und Stadtbibliothek Köln, 2020. http://d-nb.info/1215293658/34.
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Dagioglou, Maria. "The role of cerebellum in action acquisition and motor learning." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/5146/.
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The aim of the present thesis was to investigate the role of cerebellum in motor learning and action acquisition. This question was pursued by means of behavioural studies on healthy population. In a first study, the role of cerebellum in motor skill learning was explored by perturbing cerebellar activation with transcranial direct current stimulation. The involvement of cerebellum in action acquisition was studied in a paradigm that combined a visuomotor tracking task and an exploration task. The results of this study lead to chapter 4, where we investigated the impact of the tracking task in proprioceptive uncertainty. In a final study, the role of cerebellum, motor cortex and dorsolateral prefrontal cortex in action acquisition were investi- gated by modulating these brain areas using transcranial direct current stimulation. The results suggested that the cerebellum could be contributing in motor learning, not just by providing a state estimation but also by providing the uncertainty related to the estimates. However, based on the results of the final experimental chapter, we can conclude that, at least in the framework of the exploration task, motor cortex is more heavily involved than the cerebellum, perhaps via the cortico–basal–ganglia pathway, in reinforcement learning.
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Fernando, Kayla Dana. "Sex Differences in Serotonin (5-HT) Activity During Safety Learning." Thesis, Boston College, 2018. http://hdl.handle.net/2345/bc-ir:108020.
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Thesis advisor: John P. Christianson<br>Patients with posttraumatic stress disorder (PTSD) often show impaired ability to discriminate between “danger” and “safety” cues. Women are more than twice as likely to be diagnosed with PTSD as compared to men; however, translational research has largely relied on the use of male subjects despite evidence of sex differences in fear-motivated behaviors. Serotonergic activity, originating in the dorsal raphe nucleus (DRN) of the central nervous system (CNS), has been found to modulate fear discrimination in males and may contribute to sex differences observed in a Pavlovian fear discrimination paradigm. In this study, male and intact female Sprague-Dawley rats were exposed to fear conditioning with (CS+/CS-) or without (CS+) a safe conditioned stimulus, then subsequently sacrificed for immunohistochemical analysis of serotonergic activity via quantification of tryptophan hydroxylase (TPH) and Fos in the DRN. Females exhibited more rapid and robust discrimination between the CS+ danger cue and CS- safety cue as compared to males. Regardless of condition, females had more double-labeled TPH+Fos cells compared to males, but males had larger variation in TPH+Fos expression compared to females. A parabolic function for TPH+Fos counts predicted fear discrimination in males, but not females, reinforcing the view that serotonin is a modulator of safety-related behavior in males<br>Thesis (BS) — Boston College, 2018<br>Submitted to: Boston College. College of Arts and Sciences<br>Discipline: Arts and Sciences Honors Program<br>Discipline: Biology
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Clifton, Nicholas. "The role of schizophrenia susceptibility genes in associative learning." Thesis, Cardiff University, 2016. http://orca.cf.ac.uk/97209/.
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Schizophrenia is highly heritable, indicating that a large proportion of one’s susceptibility to developing the disorder is attributable to genetics. Recent large-scale genomic studies have revealed that genetic variants in patients with schizophrenia affect genes involved in synaptic plasticity processes, which are required for learning and memory, including genes encoding protein complexes associated with the NMDA receptor and the postsynaptic density. Further evidence suggests that associative learning may be particularly affected, although it is unclear which components of this cognitive process are implicated in schizophrenia. The present studies investigated the relationship between particular phases of associative learning, represented by the consolidation, retrieval and extinction of contextual fear memory in rats, with genetic variants, psychoactive drugs and postsynaptic density proteins associated with schizophrenia. I tested associative learning-related gene expression datasets for enrichment in genetic copy number variants from a large cohort of patients with schizophrenia and demonstrated that only genes associated with extinction learning are enriched in patient variants (Chapter 3). I report that fear extinction in rats was impaired by administration of the NMDA antagonist and psychotomimetic, ketamine (Chapter 4). The expression of activity- induced, postsynaptic density products of the Homer1 gene, which has been linked to psychiatric disease, was differentially regulated in specific hippocampal subregions following extinction learning (Chapter 5), and the effect of a partial knockdown of these genes during different phases of associative learning was investigated (Chapter 6). These results build on clinical studies linking abnormalities in associative and, specifically, extinction learning with schizophrenia and support the notion that genetic variants associated with the disorder impact particular cognitive domains. My findings are consistent with the theory that altered inhibitory-type learning processes contribute to the manifestation of schizophrenia.
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Armstrong, Paul. "Associative learning in a mouse model of Alzheimer's disease." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/41014/.
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Alzheimer’s disease (AD) is a progressive neurodegenerative disease defined by severe memory loss and the accumulation of amyloid plaques and neurofibrillary tangles in the brain. The experiments presented in this thesis examined cognitive performance in a well-‐characterised mouse model of AD, the APPswe/PS1dE9 (TG) mouse, at 4-‐5 months old prior to extensive amyloid plaque deposition. The experiments employed were associative learning tasks, which are not often used to measure cognitive performance in classical neuroscience research into neurodegenerative disease. Chapter 1 looked at appetitive Pavlovian cue and context conditioning and extinction, and found some evidence of impaired contextual discrimination during conditioning. Cue conditioning and extinction was found to be intact in the TG mouse model. Chapter 2 looked at appetitive Pavlovian delay and trace conditioning before examining the ability to time the arrival of the unconditioned stimulus (US). No genotype differences were found during delay or trace conditioning; however, TG mice were impaired (lost precision) in their ability to time the arrival of the US during test trials. Chapter 3 examined recognition memory performance, via the spontaneous novel object recognition (sNOR), relative recency (RR) and context priming (CP) tasks, interpreting the results in terms of Wagner’s SOP model of memory. No genotype differences were found in the sNOR or RR tasks, supporting intact stimulus-‐generated priming; however, evidence from Bonardi et al. (2016) and non-‐significant trends in the CP task supported impaired retrieval-generated priming. Chapter 4 looked at the levels of neuro-‐inflammation (microglia) in the cortex, hippocampus and striatum to assess the possible early contribution of inflammation on the development of AD. This chapter reported greater levels of microglia in the hippocampus and striatum of TG mice compared to wild types. Greater microglia clusters were also seen in the cortex and hippocampus of TG mice compared to wild types. The results from this thesis show evidence of impaired cognitive performance, prior to extensive plaque deposition, in associative learning tasks that are not routinely employed in neuroscience research. Further work is required in these learning tasks to establish whether they could be effectively used to diagnose AD at an early stage.
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Diaz, Jessica Ann. "The neural correlates of the influence of learning on perceptual decision making." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/30795/.
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Perceptual decision making involves the classification of sensory information, usually followed by an overt behavioural response. Any decision making, and perceptual decision making in particular, can be understood both theoretically and neurologically as a process of an accumulation of evidence to some threshold, at which point a commitment to a choice is made. This process can be examined in human subjects by analysing EEG data during perceptual decision making and identifying temporal components that are the neural signatures of the accumulation-to-bound decision making (see Philiastides & Sajda, 2006; Philiastides, Ratcliff, & Sajda, 2006a; Philiastides et al., 2006a; Ratcliff, Philiastides, & Sajda, 2009b). It may also be statistically modelled using sequential sampling models (see Ratcliff & Smith, 2004; Ratcliff, Gomez, & McKoon, 2004; Ratcliff & McKoon, 2008; Ratcliff & Van Dongen, 2011). Taken together, these provide us with a experimental and theoretical framework for the study of the neuroscience of human decision making. In this thesis, our aim is to address some open questions with respect to human perceptual decision making using the theoretical framework of sequential sampling models and the experimental paradigm of measuring temporal components in single-trial EEG discriminant analysis. In Chapter 2, we will describe our studies of the role of learning on perceptual decision making. In particular, here we address competing hypotheses about the nature and location of perceptual learning in the brain. We provide evidence that perceptual learning arises from changes in higher level brain areas that are related to decision-making, rather than from perceptually earlier areas that are related to the encoding of sensory stimuli. In Chapter 3, we provide a specific mechanistic account of how learning affects perceptual decision making. This work follows from the work of others who have applied reinforcement learning theories (see Sutton & Barto, 1998) to the study of perceptual learning. In Chapter 4, we will describe our studies of the interaction of prior expectation and learning on decision making. In this study, we particularly aim to address whether prior expectation affects baseline activation or evidence accumulation in the decision making system, and how this changes with training. Here, we obtain evidence showing how the effects of prior expectation are more related to evidence accumulation rather than baseline activation. In Chapter 5, we provide sequential sampling models, particularly drift diffusion models, of the data that we’ve obtained in the main experiments described in Chapter 2 and Chapter 4. The principal results here show how learning and prior expectation primarily have their effect on perceptual decision making by increasing the rate of evidence accumulation. Our general conclusion is that using a combination of the theoretical framework of sequential sampling models and the experimental paradigm of measuring temporal components in single-trial EEG discriminant analysis provides an effective and comprehensive means to address open questions with respect to human perceptual decision making.
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Berthet, Pierre. "Computational Modeling of the Basal Ganglia : Functional Pathways and Reinforcement Learning." Doctoral thesis, Stockholms universitet, Numerisk analys och datalogi (NADA), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-123747.
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We perceive the environment via sensor arrays and interact with it through motor outputs. The work of this thesis concerns how the brain selects actions given the information about the perceived state of the world and how it learns and adapts these selections to changes in this environment. Reinforcement learning theories suggest that an action will be more or less likely to be selected if the outcome has been better or worse than expected. A group of subcortical structures, the basal ganglia (BG), is critically involved in both the selection and the reward prediction. We developed and investigated a computational model of the BG. We implemented a Bayesian-Hebbian learning rule, which computes the weights between two units based on the probability of their activations. We were able test how various configurations of the represented pathways impacted the performance in several reinforcement learning and conditioning tasks. Then, following the development of a more biologically plausible version with spiking neurons, we simulated lesions in the different pathways and assessed how they affected learning and selection. We observed that the evolution of the weights and the performance of the models resembled qualitatively experimental data. The absence of an unique best way to configure the model over all the learning paradigms tested indicates that an agent could dynamically configure its action selection mode, mainly by including or not the reward prediction values in the selection process. We present hypotheses on possible biological substrates for the reward prediction pathway. We base these on the functional requirements for successful learning and on an analysis of the experimental data. We further simulate a loss of dopaminergic neurons similar to that reported in Parkinson’s disease. We suggest that the associated motor symptoms are mostly causedby an impairment of the pathway promoting actions, while the pathway suppressing them seems to remain functional.<br><p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p><p> </p>
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Johnson, Louise. "Explicit and implicit motor learning during early gait rehabilitation post stroke." Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/369974/.
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Learning can be explicit or implicit. Explicit learning takes place intentionally, in the presence of factual task-relevant knowledge; whereas implicit learning takes place unintentionally, without concurrent acquisition of knowledge about task performance. The relative benefits of implicit learning have been well investigated within healthy populations. Research consistently demonstrates that skills learnt implicitly are more likely to be retained, and are more robust under secondary task load. However, study protocols tend to involve laboratory based activities, which do not take into account the complexities of motor learning in natural settings. Direct transferability of the findings to stroke rehabilitation is therefore questionable. Two factors in explicit and implicit learning are the concepts of attentional capacity and attentional focus. Attentional capacity refers to the ability to attend to and process incoming information, whereas attentional focus refers to the location of attention in relation to specific aspects of the task being performed. Theories propose that focussing on specific movements (internal focus) may actually constrain or interfere with automatic control processes that would normally regulate movement, whereas if attention is focussed towards the movement effect (external focus) the motor system is able to more naturally self-organize, resulting in more effective performance, and learning. An internal focus of attention is therefore allied to explicit learning; whilst an external focus of attention is allied to implicit learning. This research aimed to improve understanding of explicit and implicit learning within early gait rehabilitation post stroke; primarily through the development and testing of explicit and implicit models of learning interventions. It has comprised three phases; a review of the literature; an observational study to gain insight into current practice; and a feasibility study to test the ability of therapists to deliver interventions with a bias towards either an explicit or implicit approach. Therapists were found to favour the use of explicit techniques; internally focussed instructions and feedback statements were used in high quantities. Practice therefore appeared to be at odds with current evidence; albeit primarily from healthy populations. Guidance for the delivery of explicit and implicit learning models in clinical practice was developed, and then tested in a feasibility study. Therapists demonstrated the ability to change their practice to bias either explicit or implicit learning; both approaches were found to be acceptable to patients and therapists. Recommendations are made on the content and evaluation of explicit and implicit learning models in future research, and specifically, in a Phase II pilot study.
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Bissland, Val. "Ways of learning in later life : older adults' voices. An exploration into older adults' preferred learning and communication styles and how these fit with recent neuroscience insights into adult learning." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=16918.
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This study explored older adults’ preferred learning and communication styles to identify the types of classroom experiences which could best contribute to wellbeing and mental capital. Growing evidence from the brain sciences points to associations between learning and well-being, and between learning and protection from cognitive decline (Foresight Mental Capital and Wellbeing Project, 2008; Field, 2009; Frith, 2011). The mixed method study has an equivalent status design (Creswell, 1995) which used Honey and Mumford’s (1986) Learning Styles Questionnaire, followed by a supplementary questionnaire. Then, it moved to a social constructionist/interpretive framework (Gergen, 2004), which involved conversations to determine older adults’ subjective understanding of learning now and in the past. The main framework for thematic analysis came from neuroscience which has uncovered knowledge about lifelong brain plasticity and the interconnectivity of emotions and memory. Also, of importance were the theoretical frameworks of Yang’s (2003) holistic theory of knowledge and adult learning and, to a lesser extent, Gee’s (2005) Discourse analysis. The study found a range of learning styles, encompassing 14 combinations, from activists to theorists. Therefore, this indicates the need for a wide range of imaginative classroom practices. The participants conveyed a sense that they wished to build on their existing understanding in open and interactive modes, which contrasted strongly with early memories of learning. This also chimes with developments at the interface of neuroscience and adult learning, where constructing one’s own knowledge in a social context has been shown to activate multiple brain networks and build stronger memory. In essence, the older adults were seeking enrichment, not acquisition. While there is no single right way to learn, this study provides evidence that insights from neuroscience indicate that classrooms where social dimensions and active engagement are intertwined, create learning spaces attractive to older learners, and can offer opportunities to build cognitive reserve, wellbeing and mental capital, which is vital with the new timeframe of possibilities that longer lives afford.
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Puigbò, Llobet Jordi-Ysard. "Learning mechanisms of uncertainty and neuromodulation." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/667643.
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Learning systems are, by default, adaptive. Experience shapes the parame- ters of artificial systems, as well as it changes the connectivity of biological brains. Nonetheless, our attempts to create artificial learning systems have shown that continuous learning leads to overfitting recent data at the ex- pense of the older. While the field compensated this loss by segregating training from exploitation phases, this comes at the cost of sacrificing the adaptation to uncertain or new situations. How do animals robustly forage for food, find their lairs or flee from predators in ever-changing conditions and, sometimes unfamiliar situations? This dissertation proposes that our brains flexibly change between learning modes, favoring exploitation of previous knowledge or the incorporation/adaptation of new one. From the perspective of fine-tuning perception, this thesis presents a framework to unveil some of the mechanisms that biology can use to learn from uncertain situations rapidly. First, we identify two components of rapid learning by exploring how learning speed can be modulated not just explicitly (i.e., changing a learning rate parameter) but also implicitly (i.e., changing network dynamics) by the modulation of recurrent inhibitory networks. Studying the interactions of cholinergic neuromodulation with local and global inhibition allows us to differentiate between two operation modes that switch between robust exploitation of existing representations and flexibly exploring potential alternatives. To disambiguate the learning mechanisms behind this learning mode switching by a neuromodulator like acetylcholine, we take a step back and propose a neural model to estimate the input uncertainty. The resulting dynamical system minimizes the squared error relative to the input variance, as a proxy of how much an input was unexpected. We show how this kind of system uses two forms of inhibitory populations to estimate the input, and modulate the learning speed, in synthetic datasets and machine learning benchmarks. Altogether, this model illustrates a neural microcircuit, capable of flexibly incorporating new evidence when inputs are unexpected, facilitating learn- ing speed and providing a mechanism to externally regulating learning speed implicitly.<br>Els sistemes d’aprenentatge son, per defecte, adaptatius. L’experiència dona forma als paràmetres dels sistemes artificials de la mateixa manera que canvia la connectivitat dels cervells biològics. Tot i aixı́, els intents per crear sistemes artificials d’aprenentatge ens ha ensenyat que l’aprenentatge continuat porta a el sobre-ajust de les dades més recents, al cost del més antic. Com poden els animals buscar menjar de forma robusta, trobar els seus caus o fugir dels depredadors? Aquesta tesi proposa que els cervells canvien de forma flexible entre modes d’aprenentatge, afavorint l’explotació del coneixement ja adquirit o la incorporació o adaptació amb nou coneixement.
Des de la perspectiva del refinament de la percepció, aquesta tesi pre- senta un marc per desvelar alguns dels mecanismes que utilitza la biologia per a aprendre de situacions amb incertesa, de forma ràpida. Primer, iden- tifiquem dues components que permeten aprendre més ràpid, explorant com la velocitat d’aprenentatge pot ser modulada no només de forma explı́cita (i.e., modulant un paràmetre de velocitat d’aprenentatge) sinó també implı́cita (i.e., canviant les dinàmiques de la xarxa) a través de la modulació de les xarxes inhibitories amb recurrència. Mitjançant l’estu- di de les interaccions entre la neuromodulació colinèrgica i la inhibició local i global del cervell podem diferenciar entre dos modes d’operació que canvien entre l’explotació robusta de les representacions existents i l’exploració flexible de les potencials alternatives. Per a desambiguar els mecanismes d’aprenentatge que fan això possible, fem un pas enrere i proposem un model neuronal per estimar l’incertesa de la informació d’entrada a la xarxa. Aixı́ mostrem com un sistema com aquest requereix de l’us de dos poblacions inhibitòries diferents que prediuen les dades d’entrada i modulen la velocitat d’aprenentatge, tant en tasques sintètiques com benchmarks del camp d’aprenentatge automàtic (Machine Learning). En resum, aquest model esbossa un microcircuit neuronal capaç d’incor- porar nova evidència de forma flexible, quan les dades son inesperades, facilitant la velocitat d’aprenentatge i oferint un mecanisme per regular de forma externa però implicita, aquesta velocitat.
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Gudberg, Christel Alessandra. "Effects of age on sleep and consolidation of motor learning." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:4537a396-3947-4afb-be46-92105d17000a.
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<strong>Background:</strong> Our ability to consolidate what we learn changes with age. However, little is known about the neurophysiological underpinnings of consolidation of motor learning in ageing. This is largely because studies have repeatedly demonstrated a deficit in sleep-dependent consolidation of motor learning in older adults. This thesis aims to reassess commonly held assumptions about consolidation in ageing, as well as to examine the neurophysiological and neurochemical mechanisms that support the learning and consolidation processes. <strong>Methods:</strong> Most of the studies in this thesis are based on the design of a novel whole-hand task for use in older adults, which reduces dependency on fine motor skill. This thesis adopts a number of converging measures to examine learning and memory including electroencephalograhy (EEG), magnetic resonance spectroscopy (MRS), actigraphy recordings, as well as behavioural and self-reported measures of sleep. <strong>Results:</strong> Findings show significant improvements in learning with the adapted motor task in older adults. Importantly, this task reveals significant sleep- dependent enhancements in older adults, which are comparable to those seen in younger controls. Functional changes in sleep architecture with ageing show overall decline in slow wave sleep. Sleep-dependent improvements were specifically associated with activity in stage 3 slow wave sleep and increased hemispheric differences regardless of age. Changes in GABA concentrations with learning on a visuomotor tracking task showed marked variability across participants, and no clear associations were found between GABA and consolidation. <strong>Conclusion:</strong> The evidence presented in this thesis highlight the complex dynamics underlying sleep consolidation, and challenges a commonly held assumption about consolidation in older adults. Specifically, the studies presented here show that observed declines in motor consolidation with ageing may be contaminated by age-related deficits fine motor skill. By removing such kinematic constraints, it was possible to detect marked improvements in motor performance also in older adults despite age-related changes in sleep architecture.
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Marini, Michela. "Representation learning and applications in neuronal imaging." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19776/.
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Confocal fluorescence microscopy is a microscopic technique that provides true three-dimensional (3D) optical resolution and that allows the visualization of molecular expression patterns and morphological structures. This technique has therefore become increasingly more important in neuroscience, due to its applications in image-based screening and profiling of neurons. However, in the last two decades, many approaches have been
introduced to segment the neurons automatically. With the more recent advances in the field of neural networks and Deep Learning, multiple methods have been implemented with focus on the segmentation and delineation of the neuronal trees and somas. Deep Learning methods, such as the Convolutional Neural Networks (CNN), have recently become one of the new trends in the Computer Vision area. Their ability to find strong
spatially local correlations in the data at different abstraction levels allows them to learn a set of filters that are useful to correctly segment the data, when given a labeled training
set. The overall aim of this thesis was to develop a new algorithm for automated segmentation of confocal neuronal images based on Deep Learning techniques.
In order to realize this goal, we implemented a U-Net-based CNN and realized the dataset necessary to train the Neural Network. The results show how satisfactory segmentations are achieved for all the test images given in input to our algorithm, by obtaining a Dice coefficient, as average of all the images of the test dataset, greater than 0.9.