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Статті в журналах з теми "Celle visuali"

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Jagadeesh, B., C. Gray, and D. Ferster. "Visually evoked oscillations of membrane potential in cells of cat visual cortex." Science 257, no. 5069 (July 24, 1992): 552–54. http://dx.doi.org/10.1126/science.1636094.

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Gilbert, Cole. "Visual Neuroscience: Hypercomplex Cells in the Arthropod Visual System." Current Biology 17, no. 11 (June 2007): R412—R414. http://dx.doi.org/10.1016/j.cub.2007.03.046.

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TAKAHASHI, Kyoh-Ichi. "Transmitters of vertebrate visual cells." Hikaku seiri seikagaku(Comparative Physiology and Biochemistry) 11, no. 4 (1994): 318–26. http://dx.doi.org/10.3330/hikakuseiriseika.11.318.

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IMAMOTO, Yasushi. "Phototransduction Mechanism in Visual Cells." Seibutsu Butsuri 55, no. 6 (2015): 299–304. http://dx.doi.org/10.2142/biophys.55.299.

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Govardovskii, Victor, Alexander Rotov, Luba Astakhova, Darya Nikolaeva, and Michael Firsov. "Visual cells and visual pigments of the river lamprey revisited." Journal of Comparative Physiology A 206, no. 1 (January 2020): 71–84. http://dx.doi.org/10.1007/s00359-019-01395-5.

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Mower, G. D., and W. G. Christen. "Role of visual experience in activating critical period in cat visual cortex." Journal of Neurophysiology 53, no. 2 (February 1, 1985): 572–89. http://dx.doi.org/10.1152/jn.1985.53.2.572.

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Cats were reared in total darkness from birth until 4-5 mo of age (DR cats, n = 7) or with very brief visual experience (1 or 2 days) during an otherwise similar period of dark rearing [DR(1) cats, n = 3; DR(2) cats, n = 7]. Single-cell recordings were made in area 17 of visual cortex at the end of this rearing period and/or after a subsequent prolonged period of monocular deprivation. Control observations were made in normal cats (n = 3), cats reared with monocular deprivation from birth (n = 4), and cats monocularly deprived after being reared normally until 4 mo of age (n = 2). After rearing cats in total darkness, the majority of visual cortical cells were binocularly driven and the overall distribution of ocular dominance was not different from that of normal cats. Orientation-selective cells were very rare in dark-reared cats. Monocular deprivation imposed after dark rearing resulted in selective development of connections from the open eye. Most cells were responsive only to the open eye and the majority of these were orientation selective. These results were similar to, though less severe than, those found in cats reared with monocular deprivation from birth. Monocular deprivation imposed after 4 mo of normal rearing did not produce selective development of connections from the open eye in terms of either ocular dominance or orientation selectivity. In DR(1) cats visual cortical physiology was degraded in comparison to dark-reared cats after the rearing period. Most cells were binocularly driven but there was a higher frequency of unresponsive cells and a reduced frequency of orientation-selective cells. Subsequent monocular deprivation resulted in a further decrease in the number of binocularly driven cells and an increase in unresponsive cells. However, it did not produce a bias in favor of the open eye in terms of either ocular dominance or orientation selectivity. In DR(2) cats there was a high incidence of unresponsive cells and a marked loss of binocularly driven cells after the rearing period. Subsequent monocular deprivation failed to produce any significant changes.(ABSTRACT TRUNCATED AT 400 WORDS)
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Killian, Nathaniel J., and Elizabeth A. Buffalo. "Grid cells map the visual world." Nature Neuroscience 21, no. 2 (January 25, 2018): 161–62. http://dx.doi.org/10.1038/s41593-017-0062-4.

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Goodsell, David S. "Visual Methods from Atoms to Cells." Structure 13, no. 3 (March 2005): 347–54. http://dx.doi.org/10.1016/j.str.2005.01.012.

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Wiesel, Torsten N. "Dynamic properties of visual cortical cells." Pathophysiology 1 (November 1994): 4. http://dx.doi.org/10.1016/0928-4680(94)90045-0.

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WONG-RILEY, MARGARET T. T., and PAULETTE JACOBS. "AMPA glutamate receptor subunit 2 in normal and visually deprived macaque visual cortex." Visual Neuroscience 19, no. 5 (September 2002): 563–73. http://dx.doi.org/10.1017/s0952523802195022.

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Glutamate and its various receptors are known to play an important role in excitatory synaptic transmission throughout the CNS, including the primary visual cortex. Among subunits of the AMPA receptors (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid), subunit 2 (GluR2) is of special significance because it controls their Ca2+ permeability. In the past, this subunit has been studied mostly in conjunction with other AMPA subunits. The present study sought to determine if GluR2 alone has a distinct laminar distribution in the normal macaque visual cortex, and if its pattern correlated with that of cytochrome oxidase (CO) under normal and monocularly deprived conditions. In the normal adult cortex, GluR2 immunoreactivity (ir) had a patchy distribution in layers II/III, in register with CO-rich puffs. GluR2-ir highlighted the upper border of layer II, the lower border of layer IV (previously termed IVCβdark) and, most prominently, layer VI. Labeled neurons were primarily of the pyramidal type present in the upper border and lower half of layer VI, layers II/III, and scattered in layers V and upper IVB. Labeled nonpyramidal cells were large in layer IVB and small in IVCβdark. Notably, the bulk of CO-rich layers IVC and IVA had very low levels of GluR2-ir. At fetal day 13, however, GluR2 labeling showed a honeycomb-like pattern in layer IVA not found in the adult. A fragment of GluR2 cDNA was generated from a human cDNA library, and in situ hybridization revealed an expression pattern similar to that of GluR2 proteins. After 1–4 weeks of monocular impulse blockade with tetrodotoxin (TTX), alternating rows of strong and weak GluR2-ir in layers VI and II/III appeared in register with CO-labeled dark and light ocular dominance columns in layer IVC and puffs in II/III, respectively. Our results indicate that various cortical layers are differentially influenced by glutamate. The bulk of the major geniculate-recipient layers IVC and IVA have low levels of GluR2, presumably favoring synaptic transmission via Ca2+-permeable glutamate receptors. GluR2 plays a more important role in supragranular and infragranular layers, where the initial geniculate signals are further modified and are transmitted to other cortical and subcortical centers. The maintenance of GluR2 in these output layers is governed by visual input and neuronal activity, as monocular impulse blockade induced a down-regulation of this subunit in deprived ocular dominance columns.
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Дисертації з теми "Celle visuali"

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Real, Esteban. "Models of Visual Processing by the Retina." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10210.

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The retina contains neural circuits that carry out computations as complex as object motion sensing, pattern recognition, and position anticipation. Models of some of these circuits have been recently discovered. A remarkable outcome of these efforts is that all such models can be constructed out of a limited set of components such as linear filters, instantaneous nonlinearities, and feedback loops. The present study explores the consequences of assuming that these components can be used to construct models for all retinal circuits. I recorded extracellularly from several retinal ganglion cells while stimulating the photoreceptors with a movie rich in temporal and spatial frequencies. Then I wrote a computer program to fit their responses by searching through large spaces of anatomically reasonable models built from a small set of circuit components. The program considers the input and output of the retinal circuit and learns its behavior without over-fitting, as verified by running the final model against previously unseen data. In other words, the program learns how to imitate the behavior of a live neural circuit and predicts its responses to new stimuli. This technique resulted in new models of retinal circuits that outperform all existing ones when run on complex spatially structured stimuli. The fitted models demonstrate, for example, that for most cells the center--surround structure is achieved in two stages, and that for some cells feedback is more accurately described by two feedback loops rather than one. Moreover, the models are able to make predictions about the behavior of cells buried deep within the retina, and such predictions were verified by independent sharp-electrode recordings. I will present these results, together with a brief collection of ideas and methods for furthering these modeling efforts in the future.
Physics
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Guerreiro, Pedro Miguel Rito. "Visual programming in a heterogeneous multi-core environment." Master's thesis, Universidade de Évora, 2009. http://hdl.handle.net/10174/18505.

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É do conhecimento geral de que, hoje em dia, a tecnologia evolui rapidamente. São criadas novas arquitecturas para resolver determinadas limitações ou problemas. Por vezes, essa evolução é pacífica e não requer necessidade de adaptação e, por outras, essa evolução pode Implicar mudanças. As linguagens de programação são, desde sempre, o principal elo de comunicação entre o programador e o computador. Novas linguagens continuam a aparecer e outras estão sempre em desenvolvimento para se adaptarem a novos conceitos e paradigmas. Isto requer um esforço extra para o programador, que tem de estar sempre atento a estas mudanças. A Programação Visual pode ser uma solução para este problema. Exprimir funções como módulos que recebem determinado Input e retomam determinado output poderá ajudar os programadores espalhados pelo mundo, através da possibilidade de lhes dar uma margem para se abstraírem de pormenores de baixo nível relacionados com uma arquitectura específica. Esta tese não só mostra como combinar as capacidades do CeII/B.E. (que tem uma arquitectura multi­processador heterogénea) com o OpenDX (que tem um ambiente de programação visual), como também demonstra que tal pode ser feito sem grande perda de performance. ABSTRACT; lt is known that nowadays technology develops really fast. New architectures are created ln order to provide new solutions for different technology limitations and problems. Sometimes, this evolution is pacific and there is no need to adapt to new technologies, but things also may require a change every once ln a while. Programming languages have always been the communication bridge between the programmer and the computer. New ones keep coming and other ones keep improving ln order to adapt to new concepts and paradigms. This requires an extra-effort for the programmer, who always needs to be aware of these changes. Visual Programming may be a solution to this problem. Expressing functions as module boxes which receive determined Input and return determined output may help programmers across the world by giving them the possibility to abstract from specific low-level hardware issues. This thesis not only shows how the CeII/B.E. (which has a heterogeneous multi-core architecture) capabilities can be combined with OpenDX (which has a visual programming environment), but also demonstrates that lt can be done without losing much performance.
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Törnquist, Alba Lucia. "Visual outcome, ocular findings, and visual processing skills after allogeneic stem cell transplantation in children /." Stockholm, 2010. http://diss.kib.ki.se/2010/978-91-7409-809-9/.

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Talebi, Vargha. "Spatiotemporal receptive fields of simple cells in early visual cortex." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119418.

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In order to claim that the behaviours of early visual cortex neurons are fully understood, it must be possible to create models of them that can predict responses to any arbitrary type of stimuli. Thus the underlying theme of this thesis is to explore stimuli and implement system identification approaches appropriate for the estimation of receptive field (RF) models, as well as to quantitatively examine their response properties. Specifically, I aim to address the following questions: 1) what types of stimuli provide the most robust and generalizable RF models? 2) are cortical simple cell RF models classified into distinct categories? and 3) what are the spatiotemporal response properties of the RF models?To answer these questions, I use artificial and natural stimuli in conjunction with regularized regression system identification, to estimate RF models of visual cortical neurons. The use of natural stimuli is more appropriate as they drive more ecologically relevant responses. Regularized regression system identification techniques, which have antecedents in the field of machine learning, have a number of advantages: 1) they are based on regression and therefore appropriate for a wide range of stimuli including natural images; 2) they incorporate regularization to prevent overfitting; and 3) they allow for the estimation of full 3D (i.e., space-space-time) spatiotemporal RFs in a computationally tractable manner. I investigate simple cells of a somewhat higher cortical processing area (cat area 18), thereby providing a more challenging medium for our experiments. Results from Chapter 2 showed that white noise stimuli usually elicited weak responses, yielding poor RF models, while short bar and natural image stimuli drove strong responses yielding RF models with high predictive ability. However, RF models derived from natural images better predicted responses to other types of novel stimuli, when compared to models derived from broadband artificial stimuli (i.e., white noise, short bars). Furthermore, natural image-derived RF models performed well when used to predict responses to sinewave gratings.Chapter 3 revealed that early cortical simple cells could be delineated into three distinct categories, based on spatial RF structure and output nonlinearity. These three classes were: 1) non-oriented cells with expansive nonlinearities; 2) oriented cells with expansive nonlinearities; and 3) oriented cells with compressive nonlinearities. Our sample was split between these three types, suggesting that large numbers of non-oriented cells could be readily found in brain areas beyond the lateral geniculate nucleus and layer 4 striate cortex. Additionally, our results suggested that compressive output nonlinearities were much more common than previously believed. In Chapter 4 I identified a number of spatiotemporal response properties that varied amongst the three types of simple cells. These included optimal spatial frequency, latency, duration, responsivity, and direction selectivity. Of these, optimal spatial frequency was the most interesting as it showed segregation of our sample into distinct clusters, suggesting that optimal spatial frequency may be another dimension along which categorically distinct classes of cortical neurons could be established. Results also revealed that the three cell types effectively covered a large range of temporal latencies and durations. Finally, the two classes of oriented cells differed in their levels of responsivity, suggesting that expansive versus compressive nonlinearities may reflect the degree to which a nonlinear gain control mechanism is engaged. Collectively, the three studies in this thesis demonstrate the powerful potential of natural image stimuli and regularized regression system identification techniques, making them ideal candidates for routine use in visual neuroscience studies. RF models derived from natural images have revealed that physiological response...
Afin de prétendre que les comportements des neurones du cortex visuel sont pleinement compris, il doit être possible de créer des modèles de ceux-ci qui peuvent entièrement prédire leurs réponses à tout type arbitraire de stimuli. Le thème sous-jacent de cette thèse est donc d'explorer les stimuli et les approches d'identification de système appropriés pour l'estimation de tels modèles de champ récepteur (CR), ainsi que d'examiner de façon quantitative les propriétés de leur réponse. Plus précisément, je cherche à répondre aux questions suivantes: 1) quels types de stimuli donnent des modèles de CR les plus robustes et généralisables?; 2) est-ce que les modèles de CR des cellules corticales simples sont classés en catégories distinctes?; et 3) quelles sont les propriétés des réponses spatiotemporelles des modèles de CR?Pour répondre à ces questions, j'utilise des stimuli artificiels et naturels en conjonction avec l'identification de système par régression régularisée, pour estimer les modèles de CR des neurones du cortex visuel. L'utilisation de stimuli naturels est plus appropriée, car elle entraîne des réponses plus écologiquement pertinentes. Les techniques d'identification de système par régression régularisée, qui ont des antécédents dans le domaine de l'apprentissage automatique, comportent un certain nombre d'avantages: 1) elles sont basées sur la régression et donc appropriées pour un large éventail de stimuli, y compris les images naturelles; 2) elles incorporent la régularisation afin d'éviter le sur-ajustement; et 3) elles permettent l'estimation de CR spatiotemporels 3D complets (c.-à-d., espace-espace-temps) de manière calculable par ordinateur. J'étudie les cellules simples d'une région corticale de niveau de traitement légèrement plus haut (chat, aire 18), offrant ainsi un milieu plus stimulant pour nos expériences. Les résultats du Chapitre 2 ont démontré que l'utilisation de bruit blanc comme stimuli suscitait généralement de faibles réponses, produisant de pauvres modèles de CR, tandis que l'utilisation de barres courtes et d'images naturelles comme stimuli provoquait de fortes réponses, ce qui donne des modèles de CR ayant une grande capacité prédictive. Toutefois, les modèles de CR dérivés d'images naturelles ont mieux prédit les réponses à d'autres types de nouveaux stimuli, par rapport aux modèles dérivés de stimuli artificiels à large bande (c.-à-d., bruit blanc, barres courtes). De plus, les modèles de CR dérivés d'images naturelles ont bien performé lorsqu'utilisés pour prédire les réponses aux grilles sinusoïdales. Le Chapitre 3 a révélé que les cellules corticales simples pouvaient être délimitées en trois catégories distinctes, basées sur la structure spatiale des CR et sur la non-linéarité de sortie. Ces trois catégories étaient: 1) les cellules non-orientées avec des non-linéarités à expansion; 2) les cellules orientées avec des non-linéarités à expansion; et 3) les cellules orientées avec des non-linéarités à compression. Notre échantillon a été réparti entre ces trois types, ce qui suggère qu'un grand nombre de cellules non-orientées peuvent être facilement trouvées dans les zones du cerveau au-delà du corps genouillé latéral et de la couche 4 du cortex strié. De plus, nos résultats suggèrent que les non-linéarités à compression de sortie sont beaucoup plus fréquentes qu'on ne le croyait auparavant. Dans le Chapitre 4, j'ai identifié un certain nombre de propriétés des réponses spatiotemporelles qui variaient entre les trois types de cellules simples. Il s'agissait notamment de la fréquence spatiale optimale, de la latence, de la durée, de la réactivité et de la sélectivité directionnelle. Parmi celles-ci, la fréquence spatiale optimale était la plus intéressante, car elle a démontré la ségrégation de notre échantillon en grappes distinctes. Ceci suggère que la fréquence spatiale optimale peut être une autre dimension au long de laquelle des classes de neurones corticaux...
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Gillett-Cooper, Anita M. "Development and degeneration in visual pathways." Thesis, University of Oxford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670398.

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Hesam, Shariati Nastaran. "A functional model for primary visual cortex." Thesis, The University of Sydney, 2012. http://hdl.handle.net/2123/8753.

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Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. This thesis describes a model that accounts for many of the empirical observations concerning direction selectivity. The model comprises a single column of cat primary visual cortex and a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small interval (~4 ms), and it is this difference that confers direction selectivity on model neurons. I show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.
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Field, Gregory Darin. "The limits to absolute visual sensitivity /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/10552.

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Folsom, Tyler C. "Neural networks modeling cortical cells for machine vision /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/6135.

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Tarczy-Hornoch, Kristina. "Physiology of synaptic inputs to layer IV of cat visual cortex." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337608.

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Rudiger, Philipp John Frederic. "Development and encoding of visual statistics in the primary visual cortex." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25469.

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How do circuits in the mammalian cerebral cortex encode properties of the sensory environment in a way that can drive adaptive behavior? This question is fundamental to neuroscience, but it has been very difficult to approach directly. Various computational and theoretical models can explain a wide range of phenomena observed in the primary visual cortex (V1), including the anatomical organization of its circuits, the development of functional properties like orientation tuning, and behavioral effects like surround modulation. However, so far no model has been able to bridge these levels of description to explain how the machinery that develops directly affects behavior. Bridging these levels is important, because phenomena at any one specific level can have many possible explanations, but there are far fewer possibilities to consider once all of the available evidence is taken into account. In this thesis we integrate the information gleaned about cortical development, circuit and cell-type specific interactions, and anatomical, behavioral and electrophysiological measurements, to develop a computational model of V1 that is constrained enough to make predictions across multiple levels of description. Through a series of models incorporating increasing levels of biophysical detail and becoming increasingly better constrained, we are able to make detailed predictions for the types of mechanistic interactions required for robust development of cortical maps that have a realistic anatomical organization, and thereby gain insight into the computations performed by the primary visual cortex. The initial models focus on how existing anatomical and electrophysiological knowledge can be integrated into previously abstract models to give a well-grounded and highly constrained account of the emergence of pattern-specific tuning in the primary visual cortex. More detailed models then address the interactions between specific excitatory and inhibitory cell classes in V1, and what role each cell type may play during development and function. Finally, we demonstrate how these cell classes come together to form a circuit that gives rise not only to robust development but also the development of realistic lateral connectivity patterns. Crucially, these patterns reflect the statistics of the visual environment to which the model was exposed during development. This property allows us to explore how the model is able to capture higher-order information about the environment and use that information to optimize neural coding and aid the processing of complex visual tasks. Using this model we can make a number of very specific predictions about the mechanistic workings of the brain. Specifically, the model predicts a crucial role of parvalbumin-expressing interneurons in robust development and divisive normalization, while it implicates somatostatin immunoreactive neurons in mediating longer range and feature-selective suppression. The model also makes predictions about the role of these cell classes in efficient neural coding and under what conditions the model fails to organize. In particular, we show that a tight coupling of activity between the principal excitatory population and the parvalbumin population is central to robust and stable responses and organization, which may have implications for a variety of diseases where parvalbumin interneuron function is impaired, such as schizophrenia and autism. Further the model explains the switch from facilitatory to suppressive surround modulation effects as a simple by-product of the facilitating response function of long-range excitatory connections targeting a specialized class of inhibitory interneurons. Finally, the model allows us to make predictions about the statistics that are encoded in the extensive network of long-range intra-areal connectivity in V1, suggesting that even V1 can capture high-level statistical dependencies in the visual environment. The final model represents a comprehensive and well constrained model of the primary visual cortex, which for the first time can relate the physiological properties of individual cell classes to their role in development, learning and function. While the model is specifically tuned for V1, all mechanisms introduced are completely general, and can be used as a general cortical model, useful for studying phenomena across the visual cortex and even the cortex as a whole. This work is also highly relevant for clinical neuroscience, as the cell types studied here have been implicated in neurological disorders as wide ranging as autism, schizophrenia and Parkinson’s disease.
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Книги з теми "Celle visuali"

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Hilfer, S. Robert, and Joel B. Sheffield, eds. Cell Interactions in Visual Development. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4612-3920-8.

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2

Robert, Hilfer S., Sheffield Joel B, and Symposium on Ocular and Visual Development (11th : 1987 : Temple University), eds. Cell interactions in visual development. New York: Springer-Verlag, 1988.

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3

Flow cytometry in hematopathology: A visual approach to data analysis and interpretation. 2nd ed. Totowa, NJ: Humana Press, 2007.

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4

iPhone visual quick tips. Indianapolis, IN: Wiley, 2008.

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Nguyen, Doyen T. Flow cytometry in hematopathology: A visual approach to data analysis and interpretation. Totowa, NJ: Humana Press, 2002.

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Nguyen, Doyen T. Flow cytometry in hematopathology: A visual approach to data analysis and interpretation. Totowa, NJ: Humana Press, 2003.

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7

B, Sheffield Joel, Hilfer S. Robert, and Symposium on Ocular and Visual Development (9th : 1984 : Philadelphia, Pa.), eds. Development of order in the visual system. New York: Springer-Verlag, 1986.

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8

M, Shapley R., and Lam Dominic Man-Kit, eds. Contrast sensitivity. Cambridge, Mass: MIT Press, 1993.

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9

Visual population codes: Toward a common multivariate framework for cell recording and functional imaging. Cambridge, Mass: MIT Press, 2011.

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1957-, Castellano Bernardo, and Nieto-Sampedro Manuel 1944-, eds. Glial cell function. Amsterdam: Elsevier, 2001.

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Частини книг з теми "Celle visuali"

1

Peskin, Adele P., Daniel J. Hoeppner, and Christina H. Stuelten. "Segmentation and Cell Tracking of Breast Cancer Cells." In Advances in Visual Computing, 381–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24028-7_35.

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Edelstein-Keshet, Leah. "Pattern Formation Inside Living Cells." In SEMA SIMAI Springer Series, 79–95. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86236-7_5.

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AbstractWhile most of our tissues appear static, in fact, cell motion comprises an important facet of all life forms, whether in single or multicellular organisms. Amoeboid cells navigate their environment seeking nutrients, whereas collectively, streams of cells move past and through evolving tissue in the development of complex organisms. Cell motion is powered by dynamic changes in the structural proteins (actin) that make up the cytoskeleton, and regulated by a circuit of signaling proteins (GTPases) that control the cytoskeleton growth, disassembly, and active contraction. Interesting mathematical questions we have explored include (1) How do GTPases spontaneously redistribute inside a cell? How does this determine the emergent polarization and directed motion of a cell? (2) How does feedback between actin and these regulatory proteins create dynamic spatial patterns (such as waves) in the cell? (3) How do properties of single cells scale up to cell populations and multicellular tissues given interactions (adhesive, mechanical) between cells? Here I survey mathematical models studied in my group to address such questions. We use reaction-diffusion systems to model GTPase spatiotemporal phenomena in both detailed and toy models (for analytic clarity). We simulate single and multiple cells to visualize model predictions and study emergent patterns of behavior. Finally, we work with experimental biologists to address data-driven questions about specific cell types and conditions.
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Cela, Carlos J., and Gianluca Lazzi. "Retinal Cell Excitation Modeling." In Visual Prosthetics, 159–72. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-0754-7_8.

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Sharma, Akriti, Mette H. Stensen, Erwan Delbarre, Momin Siddiqui, Trine B. Haugen, Michael A. Riegler, and Hugo L. Hammer. "Detecting Human Embryo Cleavage Stages Using YOLO V5 Object Detection Algorithm." In Communications in Computer and Information Science, 81–93. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17030-0_7.

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AbstractAssisted reproductive technology (ART) refers to treatments of infertility which include the handling of eggs, sperm and embryos. The success of ART procedures depends on several factors, including the quality of the embryo transferred to the woman. The assessment of embryos is mostly based on the morphokinetic parameters of their development, which include the number of cells at a given time point indicating the cell stage and the duration of each cell stage. In many clinics, time-lapse imaging systems are used for continuous visual inspection of the embryo development. However, the analysis of time-lapse data still requires the evaluation, by embryologists, of the morphokinetic parameters and cleavage patterns, making the assessment subjective. Recently the application of object detection in the field of medical imaging enabled the accurate detection of lesion or object of interest. Motivated by this research direction, we proposed a methodology to detect and track cells present inside embryos in time-lapse image series. The methodology employed an object detection technique called YOLO v5 and annotated the start of observed cell stages based on the cell count. Our approach could identify cell division to detect cell cleavage or start of next cell stage accurately up to the 5-cell stage. The methodology also highlighted instances of embryos development with abnormal cell cleavage patterns. On an average the methodology used 8 s to annotate a video frame (20 frames per second), which will not pose any delay for the embryologists while assessing embryo quality. The results were validated by embryologists, and they considered the methodology as a useful tool for their clinical practice.
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Sarthy, P. Vijay. "Photoreceptor-Müller Cell Interactions: Effects of Photoreceptor Degeneration on GFAP Expression in Müller Cells." In Cell Interactions in Visual Development, 1–10. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4612-3920-8_1.

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Sato, Moritoshi, and Yoshio Umezawa. "Cell-Based Biosensor to Visualize from Living Cells for." In Toxicity Assessment, 57–64. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1091-6_5.

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O’Day, Peter M., Juan Bacigalupo, Cecilia Vergara, Gonzalo Ugarte, Diana M. Bautista, and Joan E. Haab. "Multiple Pathways in Invertebrate Visual Transduction." In From Ion Channels to Cell-to-Cell Conversations, 285–306. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-1795-9_17.

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Bos, Philip. "The π-Cell." In Handbook of Visual Display Technology, 2381–86. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-14346-0_99.

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Bos, Philip. "The π-Cell." In Handbook of Visual Display Technology, 1–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-35947-7_99-2.

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Bos, Philip. "The π-Cell." In Handbook of Visual Display Technology, 1675–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-79567-4_99.

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Тези доповідей конференцій з теми "Celle visuali"

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Watson, Andrew B. "Constraints on sensitivity of linear visual neurons." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.tuh4.

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Many visual neurons linearly combine signals from the receptors or from other cells which themselves form linear combinations of receptor signals. In both cases, if the noise that limits cell performance is confined to the receptors, the peak sensitivity of the cell is entirely determined by the magnitude of the receptor noise and the normalized shape of the cells’ receptive field. This simple result may be used to estimate the receptor noise from the sensitivity of retinal or geniculate cells as well as to predict sensitivity of higher-order cells from that of lower-order cells. Consequences of this constraint are illustrated for actual primate geniculate and cortical cells and for model cortical cells.
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Schein, Stanley J. "Neural magnifications and visual performance." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.wd3.

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Limits on visual performance may be established at different neural stages, from photoreceptors (Williams) through ganglion cells (Rodieck) to visual cortex. To help identify the limiting types of neuron, one may compare changes with the eccentricity of their spatial density and receptive-field dimensions with change in performance. Cones form a monolayer, thus measurement of their spatial density should be straightforward. The measurement of ganglion cell spatial density in cells/deg2 is more difficult, since central ganglion cells are displaced laterally from their cone inputs.
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Seiple, William, Karen Holopigian, and Monica Lorenzo. "ERG Flicker Sensitivity as a Function of Retinal Eccentricity and Adaptation Level." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/navs.1993.nmd.1.

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Both temporal modulation sensitivity and flicker fusion frequency (CFF) increase with increasing eccentricity. Based upon correlations between temporal sensitivity and cone outer segment diameter, it has been proposed that these temporal frequency changes may be due to differences in receptor morphology.1,2 Alternatively, CFF can be made independent of retinal eccentricity by M-scaling (scaling for the number of ganglion cells) and F-scaling (scaling for the luminous flux per ganglion cell). These findings suggested that changes in sensitivity may be correlated with post-receptoral factors such as the number of ganglion cells stimulated, their average receptive field size, and cortical magnification.3,4,5
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Bullimore, Mark A., Joanne M. Wood, and Kirk Swenson. "Motion Perception in Glaucoma." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/navs.1992.sub1.

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The early detection of optic nerve damage is a prerequisite for effective therapy in primary open-angle glaucoma (Kass et al., 1990). An alarmingly large proportion of retinal ganglion cells may be damaged, however, before visual field defects are observed with conventional manual or automated perimetry (Quigley et al., 1982; Quigley et al., 1989). This implies that either there is widespread redundancy within the retina such that substantial cell death can occur without loss of visual performance or that our current clinical procedures do not test the function of the cells that are damaged in early glaucoma. Recent studies lead us to believe that the latter of these two hypotheses may be correct.
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Hamilton, David B., Wilson S. Geisler, and Duane C. Albrecht. "Analysis of the differences between striate cell responses and their current modeling: do the differences really matter?" In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.fv5.

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For the most part, the modeling of visual cortical neurons has preceded complete measurement of their response characteristics. However our recent measurement of the phase transfer of striate neurons provides us the most complete description of their response to date. Our purpose in this paper is to enumerate the differences between striate cell responses and current models of these visual mechanisms. Further we describe the significance of these differences to further visual processing. Our laboratory has recently quantified striate cell response phase to drifting sinusoidal gratings. Within the linear systems framework, these measurements allow us to uniquely determine the response of cells to arbitrary visual stimuli in space and time. The phase transfer of striate cells differs from most theoretical work in two ways. First, response phase increases as a function of velocity but remains constant as a function of spatial frequency. Second, the absolute phase transfer varies from cell to cell and does not always land at the canonical phase positions often modeled in the literature. The consequences of these differences will be more fully detailed in the paper. Finally, although current theoretical work often models a Gaussian shaped response to linear increases in spatial frequency, our work indicates that the frequency response of striate cells is much better described by a Gaussian in log spatial frequency. The consequences of this have heretofore been unexplained.
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Grosof, David H., and Vasudevan Lakshminarayanan. "Scanning laser ophthalmoscope imaging of the papillomacular bundle of the nerve fiber layer." In Vision Science and its Applications. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/vsia.1995.sae2.

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The nerve fiber layer (NFL), consisting of the axons of ganglion cells sweeping across the inner surface of the retina to the disc, transmits all the visual information from the eye to the brain. The normal, topographically regular pattern of nerve fibers is illustrated in Figure 1. Ophthalmoscopically, the nerve fiber layer is recognized as a pattern of subtle striations emanating from the disc a short distance; the striations are evidently bundles of axons contained within glial tunnels formed by Muller's cell processes6. Glaucoma and other optic neuropathies damage the nerve fibers and cause defects within the pattern. The bundles are fairly easy to see near the disc, and the circumpapillary nerve fibers have proved useful to image, because fiber damage and defects in the striation pattern sometimes precede detectable visual field defects. It has previously proved impossible, however, to image non-invasively the details of the perifoveally originating papillomacular bundles. Because the visual information from the perifoveal area is crucial to visual performance and because some neuropathies affect central vision preferentially (e.g., Leber's optic neuropathy), it may be useful to visualize the papillomacular bundle near the fovea, where a focal pattern of loss might be noticeable and well-correlated to focal visual deficits.
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7

Delori, François C. "Fluorophotometer for Noninvasive Measurement of RPE Lipofuscin." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/navs.1992.tuc3.

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Lipofuscin is a fluorescent pigment that accumulates throughout life preferentially in the macular RPE. At old age, lipofuscin is the major constituent of the cell as it occupies most of the free cytoplasmic [1]. It has been hypothesized that cell congestion by lipofuscin affects the normal metabolic activity of the RPE [1-3], and that this process plays a role in the pathogenesis of age-related macular degeneration (AMD). Massively engorged RPE cells are found adjacent to areas where the RPE is absent secondary to atrophy in AMD [3]. Although the evidence for lipofuscin involvement in AMD is circumstantial, the possibility of quantifying lipofuscin concentration in old subjects and in patients with AMD offers the potential of a meaningful clinical evaluation of the role of lipofuscin in the development of degenerative diseases such as AMD.
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8

Drum, Bruce, Michael Breton, Robert Massof, David O'Leary, and Matthew Severn. "Early Glaucoma Detection with Pattern Discrimination Perimetry." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/navs.1987.wb3.

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The task in conventional perimetry is to detect an incremental spot of light on a uniform background. The recent work of Quigley, et al.1 indicates that conventional perimetry can be insensitive to large amounts of optic nerve damage in glaucoma. This lack of sensitivity is not surprising, considering that individual ganglion cells can respond to light intensities close to normal psychophysical thresholds.2,3 A single functioning ganglion cell receptive field at the test stimulus position might therefore yield a nearly normal sensitivity measurement, even though as many as ten receptive field centers would normally cover that position.4
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Volkov, Uryi P., Nikolai P. Konnov, and Olga V. Novikova. "Bacteria cell ultra structure three-dimensional image." In European Conference on Biomedical Optics. Washington, D.C.: Optica Publishing Group, 2001. http://dx.doi.org/10.1364/ecbo.2001.4434_251.

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The vast majority information about cells and cell organellae structure were obtained by means of transmission electron microscopy investigation of cells serial thin sections. However often it is very difficult to derive information about 3-D structure of specimens from such electron micrographs. A new program restoring 3-D image of cells from the serial thin sections micrographs have been developed in our lab. The program makes it possible to visualize a 3-D image of cell and obtain image of inner cell structure in arbitrary plane. The plague bacteria and anthrax cells with spore were visualized with resolution about 70 nm by means of the program.
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Fairchild, Mark D., and Peter Lennie. "Ganglion cell pathways for rod acuity." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.tuh1.

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We examined the acuity of the human rod system pyschophysically to establish whether the parvocellar P or magnocellular M pathway carries high-frequency spatial information in scotopic vision. We measured visual acuity for smalt patches of sinusoidal grating at a range of eccentricities in temporal retina. When the targets were detected via rods, visual acuity ranged from 5.3 cycles/deg at an eccentricity of 5-2.9 cycles/deg at an eccentricity of 30°. We also calculated the highest spatial frequency that could be reliably resolved by the mosaics of Pand M cells and found that visual acuity of the rod system is too high to be supported by the M-ganglion cells. The psychophysical acuity is also lower than the Nyquist limit for P-ganglion cells. This implies that the high-frequency information for scotopic vision is carried in the P-cell pathway and that visual acuity is limited by the sizes of the receptive fields of individual cells, not by their separation. This conclusion is corroborated by our failure to find aliasing in scotopic vision, despite our finding clear aliases when corresponding measurements of acuity were made in photopic conditions.
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Звіти організацій з теми "Celle visuali"

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Pitner, A. L., and T. D. ,. Fluor Daniel Hanford Pyecha. IN-CELL visual examinations of K east fuel elements. Office of Scientific and Technical Information (OSTI), March 1997. http://dx.doi.org/10.2172/326426.

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de Sousa, Eduardo, Renata Matsui, Leonardo Boldrini, Leandra Baptista, and José Mauro Granjeiro. Mesenchymal stem cells for the treatment of articular cartilage defects of the knee: an overview of systematic reviews. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2022. http://dx.doi.org/10.37766/inplasy2022.12.0114.

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Review question / Objective: Population: adults (aged between 18 and 50 years) with traumatic knee lesions who underwent treatment with mesenchymal stem cells; Intervention: defined by the treatment with mesenchymal stem cells; The comparison group: treatment with autologous chondrocytes or microfracture treatments; Primary outcome: formation of cartilage neo tissue in the defect area, determined by magnetic resonance imaging (MRI) or by direct visualization in second-look knee arthroscopy.; Secondary outcomes: based on clinical scores such as visual analog scale (VAS) for pain, Western Ontario and McMaster universities score (WOMAC), knee society score (KSS), Tegner and Lysholm.
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Almasri, Malaz, Amjad Ghareeb, Abdulrahman Ismaiel, Daniel-Corneliu Leucuta, and Simona Delia Nicoara. The role of Nepafenac in the prevention of macular swelling and its repercussions on visual outcome after cataract surgery - A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2022. http://dx.doi.org/10.37766/inplasy2022.9.0004.

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Review question / Objective: P – diabetic and non-diabetic patients undergoing phacoemulsification without macular edema; I – Nepafenac 0.1% or Nepafenac 0.3% in addition to topical steroids; C – topical steroids alone; O – Mean Differences of Foveal thickness (FT), total macular volume (TMV), best corrected visual acuity (BCVA), and intraocular pressure (IOP); S – Randomized controlled trials (RCTs). Condition being studied: Macular swelling or macular edema after cataract surgery when uncontrolled may compromise the blood-ocular barrier and allow inflammatory cells and cytokines to enter the aqueous humor, resulting in discomfort for the patient, a slower rate of recovery, subpar visual results, and even more complications like the development of synechiae, increased IOP, macular edema (ME), corneal edema, and so forth.
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4

Lurie, Susan, John Labavitch, Ruth Ben-Arie, and Ken Shackel. Woolliness in Peaches and Nectarines. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570557.bard.

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The overall goal of the research was to understand the processes involved in the development of woolliness in peaches and nectarines. Four specific hypotheses were proposed and in the course of the research evidence was gathered t support two of them and to not support two others. The hypotheses and a summary of the evidence are outlined below. 1. That woolliness arises from an imbalance between the activities of the cell wall pectin degrading enzymes. Using 'Flavortop' nectarines and 'Hermoza' peaches as model systems, storage regimes were manipulated to induce or prevent woolliness. The expression (mRNA abundance), protein content (Western blotting), and activity of polygalacturonase (PG) and pectin esterase (PE) were followed. Expression of the enzymes was not different, but activity and the ratio between PG and PE activities were quite different in fruits developing woolliness or ripening normally. This was also examined by looking at the substrate, the pectin moiety of the cell wall, and i woolly fruit there were more high molecular weight pectins with regions of non-methylated galacturonic acid residues. Taking an in vitro approach it was found a) that PE activity was stable at 0oC while PG activity decreased; b) incubating the calcium pectate fraction of the cell wall with PE extracted from peaches caused the polymers to form a gel characteristic of the visual woolly symptoms in peaches. 2. That continued cell wall synthesis occurs during storage and contributes to structural changes i cell walls and improper dissolution and softening after storage. We tried to adapt our technique of adding 13C-glucose to fruit discs, which was used successfully to follow cell wall synthesis during tomato ripening. However, the difference in sugar content between the two fruits (4% in tomato and 12% in peach) meant that the 13C-glucose was much more diluted within the general metabolite pool. We were unable to see any cell wall synthesis which meant that either the dilution factor was too great, or that synthesis was not occurring. 3. That controlled atmosphere (CA) prevents woolliness by lowering all enzyme activities. CA was found to greatly reduce mRNA abundance of the cell wall enzymes compared to regular air storage. However, their synthesis and activity recovered during ripening after CA storage and did not after regular air storage. Therefore, CA prevented the inhibition of enzyme activation found in regular air storage. 4. That changes in cell wall turgor and membrane function are important events in the development of woolliness. Using a micro pressure probe, turgor was measured in cells of individual 'O'Henry' and 'CalRed' peaches which were woolly or healthy. The relationship between firmness and turgor was the same in both fruit conditions. These data indicate that the development and expression of woolliness are not associated with differences in membrane function, at least with regard to the factors that determine cell turgor pressure. In addition, during the period of the grant additional areas were explored. Encoglucanase, and enzyme metabolizing hemicellulose, was found to be highly expressed air stored, but not in unstored or CA stored fruit. Activity gels showed higher activity in air stored fruit as well. This is the first indication that other components of the cell wall may be involved in woolliness. The role of ethylene in woolliness development was also investigated at it was found a) that woolly fruits had decreased ability to produce ethylene, b) storing fruits in the presence of ethylene delayed the appearance of woolliness. This latter finding has implication for an inexpensive strategy for storing peaches and nectarines.
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Koch, Christof. Controlling the Flow of Visual Information through the Lateral Geniculate Nucleus: From Single Cells to Neural Networks. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada250578.

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Moore, R. C., J. M. Simonson, and R. E. Mesmer. A visual cell for measuring the solubility of prograde soluble salts in water at high temperatures and pressures. Office of Scientific and Technical Information (OSTI), October 1994. http://dx.doi.org/10.2172/10191476.

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