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Relevant bibliographies by topics / Sensory plasticity

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Academic literature on the topic 'Sensory plasticity'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Sensory plasticity"

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Giasson, Claude J., and Christian Casanova. "Plasticity and Sensory Substitution." Canadian Journal of Optometry 71, no. 4 (August 1, 2009): 39. http://dx.doi.org/10.15353/cjo.71.654.

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Doty, R. W. "Sensory Neurons: Diversity, Development, Plasticity." Archives of Neurology 51, no. 6 (June 1, 1994): 539. http://dx.doi.org/10.1001/archneur.1994.00540180017006.

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Ptito, Maurice, Ron Kupers, Steve Lomber, and Pietro Pietrini. "Sensory Deprivation and Brain Plasticity." Neural Plasticity 2012 (2012): 1–2. http://dx.doi.org/10.1155/2012/810370.

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Calford, M. B. "Dynamic representational plasticity in sensory cortex." Neuroscience 111, no. 4 (June 2002): 709–38. http://dx.doi.org/10.1016/s0306-4522(02)00022-2.

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Ostry, David J., and Paul L. Gribble. "Sensory Plasticity in Human Motor Learning." Trends in Neurosciences 39, no. 2 (February 2016): 114–23. http://dx.doi.org/10.1016/j.tins.2015.12.006.

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Davidoff, R. "Sensory Neurons: Diversity, Development, and Plasticity." Neurology 43, no. 8 (August 1, 1993): 1633. http://dx.doi.org/10.1212/wnl.43.8.1633-d.

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Butko, Nicholas J., and Jochen Triesch. "Learning sensory representations with intrinsic plasticity." Neurocomputing 70, no. 7-9 (March 2007): 1130–38. http://dx.doi.org/10.1016/j.neucom.2006.11.006.

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Frank, Eric. "Sensory Neurons: Diversity, Development and Plasticity." Trends in Neurosciences 16, no. 12 (December 1993): 534–35. http://dx.doi.org/10.1016/0166-2236(93)90201-v.

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Fox, Kevin, Helen Wallace, and Stanislaw Glazewski. "Is there a thalamic component to experience–dependent cortical plasticity?" Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1428 (December 29, 2002): 1709–15. http://dx.doi.org/10.1098/rstb.2002.1169.

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Sensory deprivation and injury to the peripheral nervous system both induce plasticity in the somatosensory system of adult animals, but in different places. While injury induces plasticity at several locations within the ascending somatosensory pathways, sensory deprivation appears only to affect the somatosensory cortex. Experiments have been performed to detect experience–dependent plasticity in thalamic receptive fields, thalamic domain sizes and convergence of thalamic receptive fields onto cortical cells. So far, plasticity has not been detected with sensory deprivation paradigms that cause substantial cortical plasticity. Part of the reason for the lack of thalamic plasticity may lie in the synaptic properties of afferent systems to the thalamus. A second factor may lie in the differences in the organization of cortical and thalamic circuits. Many deprivation paradigms induce plasticity by decreasing phasic lateral inhibition. Since lateral inhibition appears to be far weaker in the thalamus than the cortex, sensory deprivation may not cause large enough imbalances in thalamic activity to induce plasticity in the thalamus.

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Desgent, Sébastien, and Maurice Ptito. "Cortical GABAergic Interneurons in Cross-Modal Plasticity following Early Blindness." Neural Plasticity 2012 (2012): 1–20. http://dx.doi.org/10.1155/2012/590725.

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Early loss of a given sensory input in mammals causes anatomical and functional modifications in the brain via a process called cross-modal plasticity. In the past four decades, several animal models have illuminated our understanding of the biological substrates involved in cross-modal plasticity. Progressively, studies are now starting to emphasise on cell-specific mechanisms that may be responsible for this intermodal sensory plasticity. Inhibitory interneurons expressing γ-aminobutyric acid (GABA) play an important role in maintaining the appropriate dynamic range of cortical excitation, in critical periods of developmental plasticity, in receptive field refinement, and in treatment of sensory information reaching the cerebral cortex. The diverse interneuron population is very sensitive to sensory experience during development. GABAergic neurons are therefore well suited to act as a gate for mediating cross-modal plasticity. This paper attempts to highlight the links between early sensory deprivation, cortical GABAergic interneuron alterations, and cross-modal plasticity, discuss its implications, and further provide insights for future research in the field.

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Dissertations / Theses on the topic "Sensory plasticity"

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Bennett, David Lawrence Harvey. "Neurotrophins and sensory neuron development and plasticity." Thesis, University of London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267645.

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McNair, Nicolas A. "Input-specificity of sensory-induced neural plasticity in humans." Thesis, University of Auckland, 2008. http://hdl.handle.net/2292/3285.

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The aim of this thesis was to investigate the input-specificity of sensory-induced plasticity in humans. This was achieved by varying the characteristics of sine gratings so that they selectively targeted distinct populations of neurons in the visual cortex. In Experiments 1-3, specificity was investigated with electroencephalography using horizontally- and vertically-oriented sine gratings (Experiment 1) or gratings of differing spatial frequency (Experiments 2 & 3). Increases in the N1b potential were observed only for sine gratings that were the same in orientation or spatial frequency as that used as the tetanus, suggesting that the potentiation is specific to the visual pathways stimulated during the induction of the tetanus. However, the increase in the amplitude of the N1b in Experiment 1 was not maintained when tested again at 50 minutes post-tetanus. This may have been due to depotentiation caused by the temporal frequency of stimulus presentation in the first post-tetanus block. To try to circumvent this potential confound, immediate and maintained (tested 30 minutes post-tetanus) spatial-frequency-specific potentiation were tested separately in Experiments 2 and 3, respectively. Experiment 3 demonstrated that the increased N1b was maintained for up to half an hour post-tetanus. In addition, the findings from Experiment 1, as well as the pattern of results from Experiments 2 and 3, indicate that the potentiation must be occurring in the visual cortex rather than further upstream at the lateral geniculate nucleus. In Experiment 4 functional magnetic resonance imaging was used to more accurately localise where these plastic changes were taking place using sine gratings of differing spatial frequency. A small, focal post-tetanic increase in the blood-oxygen-level-dependent (BOLD) response was observed for the tetanised grating in the right temporo-parieto-occipital junction. For the non-tetanised grating, decreases in BOLD were found in the primary visual cortex and bilaterally in the cuneus and pre-cuneus. These decreases may have been due to inhibitory interconnections between neurons tuned to different spatial frequencies. These data indicate that tetanic sensory stimulation selectively targets and potentiates specific populations of neurons in the visual cortex.

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Dunfield, Derek James. "Sensory experience driven network plasticity in the awake developing brain." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/13655.

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During embryonic activity‐dependent brain circuit refinement, neurons receiving the same natural sensory input may undergo either long‐term potentiation (LTP) or depression (LTD). While the origin of variable plasticity in vivo is unknown, the type of plasticity induced plays a key role in shaping dynamic neural circuit synaptogenesis and growth. Here, we investigate the effects of natural visual stimuli on functional neuronal firing within the intact and awake developing brain using calcium imaging of 100s of central neurons in the Xenopus retinotectal system. We find that specific patterns of visual stimuli shift population responses towards either potentiation or depression in an N‐methyl‐D‐aspartate receptor (NMDAR)‐dependent manner. In agreement with the Bienenstock‐Cooper‐Munro (BCM) theory, our results show that functional potentiation or depression in individual neurons can be predicted by their specific receptive field properties and endogenous firing rates prior to plasticity induction. Enhancing pre‐training activity shifts plasticity outcomes as predicted by BCM, and this induced metaplasticity is also NMDAR dependent. Furthermore, network analysis reveals an increase in correlated firing of neurons that undergo potentiation. These findings implicate metaplasticity as a natural property governing experience‐dependent refinement of nascent embryonic brain circuits.

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Vahdat, Shahabeddin. "Training-induced plasticity in resting-state sensory and motor networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114465.

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Research on plasticity in motor systems has for the most part developed separately from work on sensory plasticity, as if training-induced changes to the brain affected each of these systems in isolation. The aim of this thesis is to explore the association between the sensory and motor systems when a new skill is acquired. The experiments reported in this dissertation systematically examine two hypotheses about neuroplasticity: (i) that motor learning changes perceptual function and the function of somatosensory areas of the brain, and (ii) that somatosensory training changes both motor function and motor areas of the brain. The first study aimed at providing a unified approach to test the first hypothesis. We combined both psychophysical and neuroimaging procedures to examine the connection between changes in the behavior and brain as a result of motor learning. We used a dynamics adaptation task as a model of motor learning in conjunction with somatosensory discrimination of the limb's movement direction which permits quantification of perceptual changes that occurs in conjunction with motor learning. We used functional magnetic resonance imaging (fMRI) to calculate measures of functional connectivity during resting-state periods following learning. This technique allowed us to study longer lasting plasticity in the sensorimotor system, during the period in which the motor memory is being consolidated. We developed a new hypothesis-driven technique which enables us to incorporate psychophysical measures in functional connectivity analysis to identify behaviorally-related neuroplasticity as a result of learning. Using this technique, we identified a new network in motor learning involving second somatosensory cortex, ventral premotor cortex and supplementary motor area whose activation is specifically related to perceptual changes that occur in conjunction with motor learning. Subjects who showed greater change in functional connectivity within this network, also showed a greater change in perceptual function. In study two, we proposed and implemented a new analytic data-driven method based on independent component analysis (ICA), which enabled us to systematically extract and classify shared and condition-specific networks corresponding to the pre-learning and post-learning conditions. The proposed algorithm was specifically designed to solve the problems of the regular ICA approach in conducting between-condition comparisons. Using this method we identified a specific network corresponding to the post-learning condition comprising clusters in contralateral superior parietal lobule, second somatosensory cortex, premotor cortex, and supplementary motor area. The third study was aimed at testing the second hypothesis described above. Using similar procedures and techniques to those used in the first study, we found that somatosensory discrimination training combined with periods of passive movement as short as 45 minutes increased functional connectivity between sensory and motor areas of the brain and, importantly, in motor areas alone. In behavioral terms, somatosensory training facilitates motor learning. Improvements were seen in both the rate and extent of learning and they persisted for at least one day. Sensory repetition without perceptual learning was less able to induce plasticity in the motor system. This suggests that somatosensory training can induce reorganization in the motor system and benefits from cognitive involvement and skill acquisition in the sensory domain. Overall, our studies point to a unified model of sensorimotor plasticity in which the effects of learning are not local to either sensory or motor systems, but rather each has effects that spread into functionally related areas of the brain beyond the base modality.
La recherche sur la plasticité dans les systèmes moteurs a été développée en grande partie séparément des travaux sur la plasticité sensorielle, comme si des changements au cerveau apportés par l'apprentissage affectaient chacun de ces systèmes séparément. Le but de cette these est d'explorer le lien entre le système sensoriel et le système moteur lorsqu'une nouvelle aptitude est acquise. Les expériences rapportées dans cette dissertation examinant systématiquement deux hypothèses sur la neuroplasticité: (i) l'apprentissage moteur modifie le fonction perceptuelle, ainsi que la fonction des régions somesthésiques du cerveau, et (ii) que l'apprentissage somestésique modifie les fonctions motrices et des régions motrices du cerveau.La première étude vise à donner une approche unifiée pour tester la première hypothèse. Nous avons combiné des procédures psychophysiques et de neuroimagerie pour observer le lien entre les changements de comportement et ceux au niveau du cerveau suite à de l'apprentissage moteur. Nous avons utilisé une tâche d'adaptation dynamique comme modèle d'apprentissage moteur ainsi que de la discrimination somesthésique de la direction de mouvement du membre, ce qui permet la quantification des changements perceptuels qui se produisent suite à l'apprentissage moteur. Nous avons utilisé l'imagerie par resonance magnétique fonctionnelle (IRMf) pour calculer des measures de connectivité fonctionnelle lors de péridoes de repos suivant l'apprentissage. Cette technique nous a permis d'étudier la plasticité de plus longue durée dans le système sensori-moteur, lors de la période pendant laquelle la mémoire motrice est en train de se consolider. Nous avons développé une nouvelle technique fondée à partir d'hypothèses qui nous permet d'inclure des mesures psychophysiques dans l'analyse de connectivité fonctionnelle pour identifier la neuroplasticité liée au comportement comme résultat de l'apprentissage. En utilisant cette technique, nous avons identifié un nouveau réseaux d'apprentissage moteur impliquant le deuxième cortex somesthésique, le cortex prémoteur ventral et une région motrice supplémentaire dont l'activation est spécifiquement reliée aux changements perceptuels qui se produisent suite à l'apprentissage moteur. Les sujets qui démontraient de plus grands changements de connectivité fonctionnelle démontraient aussi un plus grand changement au niveau de la fonction perceptuelle. Dans la deuxième étude, nous avons proposé et implémenté une nouvelle méthode analytique fondée sur des données et basée sur l'analyse en composantes indépendantes (ACI), ce qui nous a permis de systématiquement extraire et classer des réseaux partagés et spécifiques à la condition correspondant aux conditions avant et après l'apprentissage. La troisième étude visait à tester la deuxième hypothèse décrite ci-dessus. En utilisant des procédures et des techniques similaires à celles utilisées dans la première étude, nous avons trouvé que l'apprentissage somesthésique discriminatoire, combiné avec des périodes de mouvements passifs pouvant duré seulement 45 minutes, augmentait la connectivité fonctionnelle entre les régions sensorielles et motrices du cerveau, et, notamment, dans des régions motrices. En termes comportementaux, l'entrainement somesthésique facilite l'apprentissage moteur. Des ameliorations ont été constatées au niveau du taux et de l'étendue de l'apprentissage, et elles demeuraient pour au moins une journée. La repetition sensorielle sans apprentissage perceptuel était moins apte à induire de la plasticité dans le système moteur. En général, nos études mènent vers un modèle unifié de plasticité sensori-moteur dans laquelle les effets de l'apprentissage ne sont pas spécifiques aux systèmes moteurs ou sensoriels, mais chacun des systèmes a des effets qui s'étendent dans des régions du cerveau fonctionnellement reliées, au-delà de la modalité de base.

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Ramer, Matthew Stephen. "Sympathetic and sensory neuronal plasticity, peripheral substrates of neuropathic pain." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ31950.pdf.

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He, Haiyan. "Molecular mechanisms of synaptic plasticity in adult mammalian sensory cortex." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/6712.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.
Thesis research directed by: Biology. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Dolan, Sharron. "Plasticity in the adult rat somatosensory system following sensory deprivation." Thesis, University of Stirling, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244606.

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Eilers, Wouter. "Sensory pathways of muscle phenotypic plasticity : calcium signalling through CaMKII." Thesis, Manchester Metropolitan University, 2012. http://e-space.mmu.ac.uk/315671/.

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Skeletal muscle can adapt its structure to cope with the mechanical and metabolic stresses placed on it by various amounts and patterns of human movement. The release of calcium into the cytoplasm of muscle fibres is thought to have an important role in these adaptations, yet the calcium-dependent signalling pathways involved haven’t been fully defined. Calcium/calmodulin-dependent protein kinase II (CaMKII) has been presumed to drive mitochondrial biogenesis in skeletal muscle, but this has not been investigated in vivo. The experiments in this thesis aimed to address how CaMKII is activated in response to electrical stimulation of skeletal muscle and how CaMKII affects the muscle phenotype. A rat model was used for two main reasons: 1) it allowed for imposing well-defined stimulation patterns onto phenotypically homogenous muscle fibre populations under controlled conditions in situ, and investigating the molecular response to these stimulation patterns, and 2) it allowed for manipulation of CaMKII signalling in muscle fibres in vivo through the use of electro-assisted somatic gene transfer. It was hypothesised that CaMKII would be activated in a muscle and recruitment pattern specific manner. Furthermore, it was hypothesised that CaMKII overexpression would increase the expression of mitochondrial markers. In chapter 2, the effect of recruitment frequency on CaMKII phosphorylation in slow-twitch m. soleus and fast-twitch m. gastrocnemius medialis is investigated. Furthermore, the time course of CaMKII phosphorylation after muscle stimulation is studied. Chapter 3 presents a study into the effects of in vivo CaMKII overexpression in m. soleus and m. gastrocnemius on mitochondrial gene expression and muscle contractile function. The effects of CaMKII overexpression on skeletal alpha-actin transcription are presented in chapter 4. In chapter 5, a mathematical model of CaMKII activation in sarcomeres is described, and used to investigate the effects of CaMKII overexpression on calcium handling and on contractile properties of a muscle fibre. It was concluded that CaMKII is activated by very brief stimulation in a recruitment frequency-independent manner, and that increased CaMKII protein levels increase SERCA expression, but not mitochondrial gene expression.

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Fasthén, Patrick. "The Virtual Self : Sensory-Motor Plasticity of Virtual Body-Ownership." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-10501.

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The distinction between the sense of body-ownership and the sense of agency has attracted considerable empirical and theoretical interest lately. However, the respective contributions of multisensory and sensorimotor integration to these two varieties of body experience are still the subject of ongoing research. In this study, I examine the various methodological problems encountered in the empirical study of body-ownership and agency with the use of novel immersive virtual environment technology to investigate the interplay between sensory and motor information. More specifically, the focus is on testing the relative contributions and possible interactions of visual-tactile and visual-motor contingencies implemented under the same experimental protocol. The effect of this is supported by physiological measurements obtained from skin conductance responses and heart rate. The findings outline a relatively simple method for identifying the necessary and sufficient conditions for the experience of body-ownership and agency, as studied with immersive virtual environment technology.

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Neumann, Simona. "A-fibre plasticity : phenotype switch and regenerative capacity." Thesis, University College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267611.

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Books on the topic "Sensory plasticity"

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Plasticity in sensory systems. Cambridge: Cambridge University Press, 2013.

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Steeves, Jennifer K. E., and Laurence R. Harris, eds. Plasticity in Sensory Systems. Cambridge: Cambridge University Press, 2009. http://dx.doi.org/10.1017/cbo9781139136907.

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Erzurumlu, Reha, William Guido, and Zoltán Molnár, eds. Development and Plasticity in Sensory Thalamus and Cortex. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/978-0-387-38607-2.

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International Symposium on Sensorimotor Plasticity (1st 1984 Tel-Aviv, Israel). Sensorimotor plasticity: Theoretical, experimental and clinical aspects : selected/edited proceedings of the first International Symposium on Sensorimotor Plasticity, Tel-Aviv, Israel, 1-4 October 1974. Paris: INSERM, 1986.

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A, Scott Sheryl, ed. Sensory neurons: Diversity, development, and plasticity. New York: Oxford University Press, 1992.

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Scott, Sheryl A. Sensory Neurons: Diversity, Development, and Plasticity. Oxford University Press, USA, 1992.

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Pyza, Elzbieta M., ed. Plasticity in the sensory systems of invertebrates. Frontiers Media SA, 2014. http://dx.doi.org/10.3389/978-2-88919-281-6.

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(Editor), Reha Erzurumlu, William Guido (Editor), and Zoltán Molnár (Editor), eds. Development and Plasticity in Sensory Thalamus and Cortex. Springer, 2006.

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Development and Plasticity in Sensory Thalamus and Cortex. Springer, 2010.

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Neural plasticity in adult somatic sensory-motor systems. Boca Raton, FL: Taylor & Francis/CRC Press, 2005.

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Book chapters on the topic "Sensory plasticity"

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Lehman, Maria Lorena. "Plasticity for growth." In Adaptive Sensory Environments, 68–74. New York : Routledge, 2016.: Routledge, 2016. http://dx.doi.org/10.4324/9781315630519-11.

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Grobstein, Paul, and Kao Liang Chow. "Visual System Development, Plasticity." In Sensory System I, 107–9. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4899-6647-6_47.

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Miles, Frederick A., and Reuben S. Gellman. "Gaze, Plasticity in the Control of." In Sensory System I, 31–32. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4899-6647-6_16.

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Kelley, Matthew W., and Jennifer S. Stone. "Development and Regeneration of Sensory Hair Cells." In Auditory Development and Plasticity, 17–48. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-21530-3_2.

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Xerri, C., M. Lacour, and L. Borel. "Multimodal Sensory Substitution Process in Vestibular Compensation." In Post-Lesion Neural Plasticity, 357–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73849-4_32.

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Pallas, Sarah L. "Cross-Modal Plasticity in Sensory Cortex." In The Neocortex, 205–18. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-0652-6_19.

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Rauschecker, J. P. "Auditory Cortical Plasticity and Sensory Substitution." In Neuronal Plasticity: Building a Bridge from the Laboratory to the Clinic, 53–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-59897-5_4.

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Shuvalov, Victor F. "Plasticity of Phonotaxis Specificity in Crickets." In Sensory Systems and Communication in Arthropods, 341–44. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-6410-7_60.

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Lakes, Reinhard. "Plasticity of the Nervous System of Orthopterans." In Sensory Systems and Communication in Arthropods, 280–84. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-6410-7_48.

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Sonnier, B. J. "Animal Models of Plasticity and Sensory Substitution." In Electronic Spatial Sensing for the Blind, 359–64. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-017-1400-6_21.

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Conference papers on the topic "Sensory plasticity"

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Enikov, Eniko T., Juan-Antonio Escareno, and Micky Rakotondrabe. "Image Schema Based Landing and Navigation for Rotorcraft MAV-s." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51450.

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To date, most autonomous micro air vehicles (MAV-s) operate in a controlled environment, where the location of and attitude of the aircraft are measured with an infrared (IR) tracking systems. If MAV-s are to ever exit the lab, their flight control needs to become autonomous and based on on-board image and attitude sensors. To address this need, several groups are developing monocular and binocular image based navigation systems. One of the challenges of these systems is the need for exact calibration in order to determine the vehicle’s position and attitude through the solution of an inverse problem. Body schemas are a biologically-inspired approach, emulating the plasticity of the animal brain, which allows it to learn non-linear mappings between the body configurations, i.e. its generalized coordinates and the resulting sensory outputs. The advantages of body schemas has long been recognized in the cognitive robotic literature and resulting studies on human-robot interactions based on artificial neural networks, however little effort has been made so far to develop avian-inspired flight control strategies utilizing body and image schemas. This paper presents a numerical experiment of controlling the trajectory of a miniature rotorcraft during landing maneuvers suing the notion of body and image schemas. More specifically, we demonstrate how trajectory planning can be executed in the image space using gradient-based maximum seeking algorithm of a pseudo-potential. It is demonstrated that a neural-gas type artificial neural network (ANN), trained through Hebbian-type learning algorithm, can be effective in learning a mapping between the rotorcraft’s position/attitude and the output of its vision sensors. Numerical simulation of the landing performance, including resulting landing errors are presented using an experimentally validated rotorcraft model.

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Azghadi, Mostafa Rahimi, Omid Kavehei, Said Al-Sarawi, Nicolangelo Iannella, and Derek Abbott. "Novel VLSI implementation for triplet-based spike-timing dependent plasticity." In 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). IEEE, 2011. http://dx.doi.org/10.1109/issnip.2011.6146525.

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Yang, Shengyuan, Scott Siechen, Jie Sun, Akira Chiba, and Taher Saif. "Learning by Tension." In ASME 2007 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2007. http://dx.doi.org/10.1115/sbc2007-176719.

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Memory and learning in animals is mediated by neurotransmission at the synaptic junctions (end point of axons). Neurotransmitters are carried by synaptic vesicles which cluster at the junctions, ready to be dispatched for transmission. The more a synapse is used, higher is the clustering, and higher is the neurotransmission efficiency (plasticity), i.e., the junction “remembers” its use in the near past, and modifies accordingly. This usage dependent plasticity offers the basic mechanism of memory and learning. A central dogma in neuroscience is that, clustering is the result of a complex biochemical signaling process. We show, using MEMS sensors and fruit fly (Drosophila) embryo nervous system, that mechanical tension in axons is essential for clustering. Without tension, clustering disappears, but reappears with application of tension. Nature maintains a rest tension of 1nN in axons of Drosophila for learning and memory.

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Servetnik, Anton N., and Evgeny P. Kuzmin. "Yield Surface Investigation of Alloys During Model Disk Spin Tests." In ASME 2014 Gas Turbine India Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gtindia2014-8119.

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Results of quasi-static numerical simulation of spin tests of model disk made from high-temperature forged alloy are presented. To determine stress-strain state of disk during loading finite element analysis is used. Simulation of elastic-plastic strain fields was carried out using incremental theory of plasticity with isotropic hardening. Model sensitivity from Von mises and Tresca yield conditions and hardening conditions was investigated. To identify the material model parameters an experimental approach of rim radial displacement measurement by eddy currents sensor during the load-unload of spin test was used. Calculation made using different material models were compared with the experimental results.

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Amarasinghe, Ruslan S., Dharma Wijewickreme, and Hisham T. Eid. "Some Observations on Soil-Pipe Interface Shear Strength in Direct Shear Under Low Effective Normal Stresses and Large Displacements." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64100.

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Experimental work is undertaken at the University of British Columbia (UBC) to study the soil-pipe interface shear strength at levels of shear displacements and effective normal stresses typically encountered in offshore soil-pipe interaction problems. A macro-scale interface direct shear apparatus having a test specimen footprint of 1.72 m × 1.75 m was designed and built for this purpose. The apparatus is capable of testing various soil-pipe interfaces under effective normal stresses in the range of 3 kPa to 6 kPa. A maximum shear displacement of 1.2 m is achievable at rates ranging from 0.1 μm/s to 1 mm/s. Sensors mounted at the interface enable the accurate determination of the effective normal stress at the interface when fully saturated fine-grained soils are tested. This paper presents some observations arising from a series of interface direct shear tests involving fine-grained soils of different plasticity against bare and epoxy coated steel surfaces.

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Berselli, Giovanni, Rocco Vertechy, Marco Fontana, and Marcello Pellicciari. "An Experimental Assessment of the Thermo-Elastic Response in Acrylic Elastomers and Natural Rubbers for Application on Electroactive Polymer Transducers." In ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/smasis2014-7604.

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Dielectric Elastomers (DEs) are deformable dielectrics, which are currently used as active materials in mechatronic transducers, such as actuators, sensors and generators. Nonetheless, at the present state of the art, the industrial exploitation of DE-based devices is still hampered by the irregular electro-mechanical behavior of the employed materials, also due to the unpredictable effects of environmental changes in real world applications. In many cases, DE transducers are still developed via trial-and-error procedures rather than through a well-structured design practice, one reason being the lack of experimental data along with reliable constitutive parameters of many potential DE materials. Therefore, in order to provide the practicing engineer with some essential information, an open-access database for DE materials has been recently created and presented in [1]. Following the same direction, this paper addresses the temperature effect on the visco-hyperelastic behavior of two DE candidates, namely a natural rubber (ZRUNEK A1040) and a well-known acrylic elastomer (3M VHB 4905). Measurements are performed on pure shear specimens placed in a climactic chamber. Experimental stress-strain curves are then provided, which makes it possible to predict hyperelasticity, plasticity, viscosity, and Mullins effect as function of the environmental temperature. Properties of these commercial elastomeric membranes are finally entered in the database and made available to the research community.

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Avile´s, F., L. Llanes, A. I. Oliva, J. E. Corona, M. Aguilar-Vega, and M. I. Lori´a-Bastarrachea. "Elasto-Plastic Properties of Thin Gold Films Over Polymeric Substrates." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-66319.

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Metallic thin films have been extensively used as coatings, interconnections, sensors and as part of micro and nano-electromechanical devices (MEMS and NEMS). The conventional substrates utilized to deposit those films are normally rigid, such as silicon. However, for applications where the substrate is subjected to significant mechanical strain (e.g. automotive coatings, electronic textiles, bioengineering, etc.) the film-substrate system needs to be flexible and conformable. Compliant polymeric substrates are ideal candidates for such a task. Some interesting mechanical properties not achieved with conventional rigid substrates can be transmitted to the film by the use of polymeric substrates. In this work, mechanical properties of 50 to 300 nm gold films deposited by thermal deposition over two thermoplastic substrates are investigated. A commercial thermoplastic, Polysulfone (“PSF”), and a home-synthesized isophthalic polyester based on the reaction of 4, 4′-(1-hydroxyphenylidene) phenol and isophthaloyl dichloride (“BAP”) [1] were used as raw materials for substrate production. Substrates were selected based on their good mechanical properties and flexibility. The use of two different substrates allows us to investigate the influence of the substrate mechanical properties in the bimaterial response. Substrates of 80 μm thickness were prepared by solution casting and cut to rectangular shapes of nominal dimensions of 30 mm × 5 mm. High purity (99.999%) commercial gold splatters were used for film deposition. Gold films with thickness of 50, 100, 200, and 300 nm were deposited onto PSF substrates by thermal evaporation inside a vacuum chamber at 3×10−5 Torr. Au films with 100 nm thickness were also deposited over BAP substrates. Four replicates of each type were deposited (at the same time) and used for tensile testing. Tensile testing of Au/PSF (film thickness 50–300 nm) and Au/BAP (film thickness 100 nm) specimens was conducted. Tests of the neat PSF and BAP substrates (6 replicates) were also conducted as a baseline. Tensile testing was conducted in a small universal testing machine with a load cell of 200 N and a cross head speed of 0.05 mm/min. The film mechanical properties were extracted from the tensile response of the film/substrate system, considered as a bimaterial. Based on sum of forces and strain compatibility, the film modulus (Ef) and stress (σf) can be extracted from characteristics of the bimaterial (EBim, σBim) and substrate (Es, σs), to generate a stress-strain curve for the film, see e.g. [2], Ef=1Af[ABimEBim−AsEs]=1+tstfEBim−tstfEs(1a)σf=1Af[P−Ps]=1+tstfσBim−tstfσs(1b) where P is the applied load, A = wt is the cross sectional area and sub-index “Bim” corresponds to the film-substrate bimaterial (ABim = w(ts+tf)). Figure 1 shows film stress (σ)-strain (ε) representative curves for Au films with different thicknesses extracted from the Au/PSF bimaterials. The film behavior presents only a small region of plasticity close to the ultimate strain. Thus, the numerical value of the maximum stress (strength) is close to its yield strength. The large plasticity of the substrate may hinder the plasticity of gold when acting as a bimaterial. As observed from this figure, the film modulus, strength and ultimate strain increase as the film thickness decreases, evidencing a “thickness-effect” not observed in bulk materials. Slightly different properties were obtained for the Au films deposited over the BAP substrate, which evidences some substrate-dependency of the film properties.

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