980 resultados para Object Memory


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Cette étude porte sur la dimension intersubjective de la souffrance qui affecte le rapport du souffrant à son corps, au temps et à l’espace vécus de même que son identité narrative et sa mémoire narrative. Mon argument principal est que la voix narrative constitue le rapport intersubjectif dans les récits de maladie que les proches écrivent sur leurs partenaires souffrant de cancer de cerveau ou de la maladie d’Alzheimer. Ma discussion est basée sur l’éthique, la phénoménologie, les théories de l’incorporation, les études des récits de vie, la sociologie et l’anthropologie médicales et la narratologie. L’objet de mon étude est l’expérience incorporée de la souffrance dans les récits de maladie et je me concentre sur la souffrance comme perte de la mémoire et du soi narratif. J’analyse le journal How Linda Died de Frank Davey et les mémoires de John Bayley, Iris: A Memoir of Iris Murdoch et Iris and Her Friends: A Memoir of Memory and Desire. J’explore comment les récits de maladie constituent le rapport éthique à l’Autre souffrant de la rupture de la mémoire. La discussion de la voix est située dans le contexte des récits de vie et se propose de dépasser les limites des approches sociologiques et anthropologiques de la voix dans les récits de maladie. Dans ce sens, dans un premier temps je porte mon attention sur des études narratologiques de la voix en indiquant leurs limites. Ma propre définition de la voix narrative est basée sur l’éthique dans la perspective d’Emmanuel Levinas et de Paul Ricœur, sur l’interprétation du temps, de la mémoire et de l’oubli chez St-Augustin et la discussion levinasienne de la constitution intersubjective du temps. J’avance l’idée que la “spontanéité bienveillante” (Ricœur, Soi-même comme un autre 222) articule la voix narrative et l’attention envers l’Autre souffrant qui ne peut plus se rappeler, ni raconter sa mémoire. En reformulant la définition augustinienne du temps qui met en corrélation les modes temporels avec la voix qui récite, j’avance l’idée que la voix est distendue entre la voix présente de la voix présente, la voix présente de la voix passée, la voix présente de la voix future. Je montre comment la voix du soignant est inscrite par et s’inscrit dans les interstices d’une voix interrompue, souffrante. Je définis les récits de vies comme des interfaces textuelles entre le soi et l’Autre, entre la voix du soi et la voix du souffrant, comme un mode de restaurer l’intégrité narrative de l’Autre.

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This paper sketches a hypothetical cortical architecture for visual 3D object recognition based on a recent computational model. The view-centered scheme relies on modules for learning from examples, such as Hyperbf-like networks. Such models capture a class of explanations we call Memory-Based Models (MBM) that contains sparse population coding, memory-based recognition, and codebooks of prototypes. Unlike the sigmoidal units of some artificial neural networks, the units of MBMs are consistent with the description of cortical neurons. We describe how an example of MBM may be realized in terms of cortical circuitry and biophysical mechanisms, consistent with psychophysical and physiological data.

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Human object recognition is generally considered to tolerate changes of the stimulus position in the visual field. A number of recent studies, however, have cast doubt on the completeness of translation invariance. In a new series of experiments we tried to investigate whether positional specificity of short-term memory is a general property of visual perception. We tested same/different discrimination of computer graphics models that were displayed at the same or at different locations of the visual field, and found complete translation invariance, regardless of the similarity of the animals and irrespective of direction and size of the displacement (Exp. 1 and 2). Decisions were strongly biased towards same decisions if stimuli appeared at a constant location, while after translation subjects displayed a tendency towards different decisions. Even if the spatial order of animal limbs was randomized ("scrambled animals"), no deteriorating effect of shifts in the field of view could be detected (Exp. 3). However, if the influence of single features was reduced (Exp. 4 and 5) small but significant effects of translation could be obtained. Under conditions that do not reveal an influence of translation, rotation in depth strongly interferes with recognition (Exp. 6). Changes of stimulus size did not reduce performance (Exp. 7). Tolerance to these object transformations seems to rely on different brain mechanisms, with translation and scale invariance being achieved in principle, while rotation invariance is not.

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The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been used for a variety of tasks, the most popular being real-time pattern recognition, and they can be implemented easily in hardware as they use standard random access memories. In operation, a series of images of an object are shown to the network, each being processed suitably and effectively stored in a memory called a discriminator. Then, when another image is shown to the system, it is processed in a similar manner and the system reports whether it recognises the image; is the image sufficiently similar to one already taught? If the system is to be able to recognise and discriminate between m-objects, then it must contain m-discriminators. This can require a great deal of memory. This paper describes various ways in which memory requirements can be reduced, including a novel method for multiple discriminator n-tuple networks used for pattern recognition. By using this method, the memory normally required to handle m-objects can be used to recognise and discriminate between 2^m — 2 objects.

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Recent evidence from animal and adult human subjects has demonstrated potential benefits to cognition from flavonoid supplementation. This study aimed to investigate whether these cognitive benefits extended to a sample of school-aged children. Using a cross-over design, with a wash out of at least seven days between drinks, fourteen 8-10 year old children consumed either a flavonoid-rich blueberry drink or matched vehicle. Two hours after consumption, subjects completed a battery of five cognitive tests comprising the Go-NoGo, Stroop, Rey’s Auditory Verbal Learning Task, Object Location Task, and a Visual N-back. In comparison to vehicle, the blueberry drink produced significant improvements in the delayed recall of a previously learned list of words, showing for the first time a cognitive benefit for acute flavonoid intervention in children. However, performance on a measure of proactive interference indicated that the blueberry intervention led to a greater negative impact of previously memorised words on the encoding of a set of new words. There was no benefit of our blueberry intervention for measures of attention, response inhibition or visuo-spatial memory. While findings are mixed, the improvements in delayed recall found in this pilot study suggest that, following acute flavonoid-rich blueberry interventions, school aged children encode memory items more effectively.

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Rationale Cannabidiol, the main nonpsychotropic constituent of Cannabis sativa, possesses a large number of pharmacological effects including anticonvulsive, sedative, hypnotic, anxiolytic, antipsychotic, anti-inflammatory, and neuroprotective, as demonstrated in clinical and preclinical studies. Many neurodegenerative disorders involve cognitive deficits, and this has led to interest in whether cannabidiol could be useful in the treatment of memory impairment associated to these diseases. Objectives We used an animal model of cognitive impairment induced by iron overload in order to test the effects of cannabidiol in memory-impaired rats. Methods Rats received vehicle or iron at postnatal days 12-14. At the age of 2 months, they received an acute intraperitoneal injection of vehicle or cannabidiol (5.0 or 10.0 mg/kg) immediately after the training session of the novel object recognition task. In order to investigate the effects of chronic cannabidiol, iron-treated rats received daily intraperitoneal injections of cannabidiol for 14 days. Twenty-four hours after the last injection, they were submitted to object recognition training. Retention tests were performed 24 h after training. Results A single acute injection of cannabidiol at the highest dose was able to recover memory in iron-treated rats. Chronic cannabidiol improved recognition memory in iron-treated rats. Acute or chronic cannabidiol does not affect memory in control rats. Conclusions The present findings provide evidence suggesting the potential use of cannabidiol for the treatment of cognitive decline associated with neurodegenerative disorders. Further studies, including clinical trials, are warranted to determine the usefulness of cannabidiol in humans suffering from neurodegenerative disorders.

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Introduction and aims of the research Nitric oxide (NO) and endocannabinoids (eCBs) are major retrograde messengers, involved in synaptic plasticity (long-term potentiation, LTP, and long-term depression, LTD) in many brain areas (including hippocampus and neocortex), as well as in learning and memory processes. NO is synthesized by NO synthase (NOS) in response to increased cytosolic Ca2+ and mainly exerts its functions through soluble guanylate cyclase (sGC) and cGMP production. The main target of cGMP is the cGMP-dependent protein kinase (PKG). Activity-dependent release of eCBs in the CNS leads to the activation of the Gαi/o-coupled cannabinoid receptor 1 (CB1) at both glutamatergic and inhibitory synapses. The perirhinal cortex (Prh) is a multimodal associative cortex of the temporal lobe, critically involved in visual recognition memory. LTD is proposed to be the cellular correlate underlying this form of memory. Cholinergic neurotransmission has been shown to play a critical role in both visual recognition memory and LTD in Prh. Moreover, visual recognition memory is one of the main cognitive functions impaired in the early stages of Alzheimer’s disease. The main aim of my research was to investigate the role of NO and ECBs in synaptic plasticity in rat Prh and in visual recognition memory. Part of this research was dedicated to the study of synaptic transmission and plasticity in a murine model (Tg2576) of Alzheimer’s disease. Methods Field potential recordings. Extracellular field potential recordings were carried out in horizontal Prh slices from Sprague-Dawley or Dark Agouti juvenile (p21-35) rats. LTD was induced with a single train of 3000 pulses delivered at 5 Hz (10 min), or via bath application of carbachol (Cch; 50 μM) for 10 min. LTP was induced by theta-burst stimulation (TBS). In addition, input/output curves and 5Hz-LTD were carried out in Prh slices from 3 month-old Tg2576 mice and littermate controls. Behavioural experiments. The spontaneous novel object exploration task was performed in intra-Prh bilaterally cannulated adult Dark Agouti rats. Drugs or vehicle (saline) were directly infused into the Prh 15 min before training to verify the role of nNOS and CB1 in visual recognition memory acquisition. Object recognition memory was tested at 20 min and 24h after the end of the training phase. Results Electrophysiological experiments in Prh slices from juvenile rats showed that 5Hz-LTD is due to the activation of the NOS/sGC/PKG pathway, whereas Cch-LTD relies on NOS/sGC but not PKG activation. By contrast, NO does not appear to be involved in LTP in this preparation. Furthermore, I found that eCBs are involved in LTP induction, but not in basal synaptic transmission, 5Hz-LTD and Cch-LTD. Behavioural experiments demonstrated that the blockade of nNOS impairs rat visual recognition memory tested at 24 hours, but not at 20 min; however, the blockade of CB1 did not affect visual recognition memory acquisition tested at both time points specified. In three month-old Tg2576 mice, deficits in basal synaptic transmission and 5Hz-LTD were observed compared to littermate controls. Conclusions The results obtained in Prh slices from juvenile rats indicate that NO and CB1 play a role in the induction of LTD and LTP, respectively. These results are confirmed by the observation that nNOS, but not CB1, is involved in visual recognition memory acquisition. The preliminary results obtained in the murine model of Alzheimer’s disease indicate that deficits in synaptic transmission and plasticity occur very early in Prh; further investigations are required to characterize the molecular mechanisms underlying these deficits.

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In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

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Visual imagery – similar to visual perception – activates feature-specific and category-specific visual areas. This is frequently observed in experiments where the instruction is to imagine stimuli that have been shown immediately before the imagery task. Hence, feature-specific activation could be related to the short-term memory retrieval of previously presented sensory information. Here, we investigated mental imagery of stimuli that subjects had not seen before, eliminating the effects of short-term memory. We recorded brain activation using fMRI while subjects performed a behaviourally controlled guided imagery task in predefined retinotopic coordinates to optimize sensitivity in early visual areas. Whole brain analyses revealed activation in a parieto-frontal network and lateral–occipital cortex. Region of interest (ROI) based analyses showed activation in left hMT/V5+. Granger causality mapping taking left hMT/V5+ as source revealed an imagery-specific directed influence from the left inferior parietal lobule (IPL). Interestingly, we observed a negative BOLD response in V1–3 during imagery, modulated by the retinotopic location of the imagined motion trace. Our results indicate that rule-based motion imagery can activate higher-order visual areas involved in motion perception, with a role for top-down directed influences originating in IPL. Lower-order visual areas (V1, V2 and V3) were down-regulated during this type of imagery, possibly reflecting inhibition to avoid visual input from interfering with the imagery construction. This suggests that the activation in early visual areas observed in previous studies might be related to short- or long-term memory retrieval of specific sensory experiences.

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People remember moving objects as having moved farther along in their path of motion than is actually the case; this is known as representational momentum (RM). Some authors have argued that RM is an internalization of environmental properties such as physical momentum and gravity. Five experiments demonstrated that a similar memory bias could not have been learned from the environment. For right-handed Ss, objects apparently moving to the right engendered a larger memory bias in the direction of motion than did those moving to the left. This effect, clearly not derived from real-world lateral asymmetries, was relatively insensitive to changes in apparent velocity and the type of object used, and it may be confined to objects in the left half of visual space. The left–right effect may be an intrinsic property of the visual operating system, which may in turn have affected certain cultural conventions of left and right in art and other domains.

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Effects of the dihydropyridine, nimodipine, an antagonist at L-type calcium channels, on the memory loss in rats caused by long term alcohol consumption were examined. Either a single dose of nimodipine or 2 weeks of repeated administration was given prior to withdrawal from 8 months of alcohol consumption. Memory was measured by the object recognition test and the T maze. Both nimodipine treatments prevented the memory deficits when these were measured between 1 and 2 months after alcohol withdrawal. At the end of the memory testing, 2 months after cessation of chronic alcohol consumption, glucocorticoid concentrations were increased in specific regions of rat brain without changes in plasma concentrations. Both nimodipine treatment schedules substantially reduced these rises in brain glucocorticoid. The data indicate that blockade of L-type calcium channels prior to alcohol withdrawal protects against the memory deficits caused by prolonged alcohol intake. This shows that specific drug treatments, such as nimodipine, given over the acute withdrawal phase, can prevented the neuronal changes responsible for subsequent adverse effects of long term consumption of alcohol. The results also suggest the possibility that regional brain glucocorticoid increases may be involved in the adverse effects of long term alcohol intake on memory. Such local changes in brain glucocorticoid levels would have major effects on neuronal function. The studies indicate that L-type calcium channels and brain glucocorticoid levels could form new targets for the treatment of cognitive deficits in alcoholics.

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Back-in-time debuggers are extremely useful tools for identifying the causes of bugs, as they allow us to inspect the past states of objects no longer present in the current execution stack. Unfortunately the "omniscient" approaches that try to remember all previous states are impractical because they either consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach to back-in-time debugging that attempts to keep track of only the relevant past data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that past data that is not reachable from current application objects (and hence, no longer relevant) is automatically garbage collected. In this paper we describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore since our approach works at the virtual machine level, the performance penalty is significantly better than with other approaches.

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A large body of research demonstrated that participants preferably look back to the encoding location when retrieving visual information from memory. However, the role of this 'looking back to nothing' is still debated. The goal of the present study was to extend this line of research by examining whether an important area in the cortical representation of the oculomotor system, the frontal eye field (FEF), is involved in memory retrieval. To interfere with the activity of the FEF, we used inhibitory continuous theta burst stimulation (cTBS). Before stimulation was applied, participants encoded a complex scene and performed a short-term (immediately after encoding) or long-term (after 24 h) recall task, just after cTBS over the right FEF or sham stimulation. cTBS did not affect overall performance, but stimulation and statement type (object vs. location) interacted. cTBS over the right FEF tended to impair object recall sensitivity, whereas there was no effect on location recall sensitivity. These findings suggest that the FEF is involved in retrieving object information from scene memory, supporting the hypothesis that the oculomotor system contributes to memory recall.

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Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier

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When administered intracerebroventricularly to mice performing various learning tasks involving either short-term or long-term memory, secreted forms of the β-amyloid precursor protein (APPs751 and APPs695) have potent memory-enhancing effects and block learning deficits induced by scopolamine. The memory-enhancing effects of APPs were observed over a wide range of extremely low doses (0.05-5,000 pg intracerebroventricularly), blocked by anti-APPs antisera, and observed when APPs was administered either after the first training session in a visual discrimination or a lever-press learning task or before the acquisition trial in an object recognition task. APPs had no effect on motor performance or exploratory activity. APPs695 and APPs751 were equally effective in the object recognition task, suggesting that the memory-enhancing effect of APPs does not require the Kunitz protease inhibitor domain. These data suggest an important role for APPss on memory processes.