Relevant bibliographies by topics / Cortex in visual stimulus

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cortex in visual stimulus'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Cortex in visual stimulus"

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Földiák, Peter. "Stimulus optimisation in primary visual cortex." Neurocomputing 38-40 (June 2001): 1217–22. http://dx.doi.org/10.1016/s0925-2312(01)00570-7.

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Carandini, M., H. B. Barlow, A. B. Poirson, L. P. O'Keefe, and J. A. Movshon. "Adaptation to Contingencies in Macaque Primary Visual Cortex." Perception 26, no. 1_suppl (August 1997): 106. http://dx.doi.org/10.1068/v970207.

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We tested the hypothesis that neurons in the primary visual cortex adapt selectively to contingencies in the attributes of visual stimuli. We recorded from single neurons in macaque V1 and measured the effects of adaptation either to the sum of two gratings (compound stimulus) or to the individual gratings. According to our hypothesis, there would be a component of adaptation that is specific to the compound stimulus. We performed two sets of experiments. In the first set one grating had optimal orientation and the other was orthogonal to it. In the second set the gratings were parallel, differed in spatial frequency, and were both effective in driving the cell. The first set of experiments, but not the second, provided evidence in favour of our hypothesis. In most cells tested with orthogonal gratings, adaptation to the compound stimulus reduced the responses to the compound stimulus more than the responses to the preferred grating. In addition, in most of these experiments the responses to the compound stimulus were reduced more by adaptation to the compound stimulus than by adaptation to the individual gratings. This suggests that a component of adaptation in the experiments with orthogonal gratings was specific to (and caused by) the contingent presence of the two gratings in the compound stimulus.
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Carandini, Matteo, Horace B. Barlow, Lawrence P. O'keefe, Allen B. Poirson, and J. Anthony Movshon. "Adaptation to contingencies in macaque primary visual cortex." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 352, no. 1358 (August 29, 1997): 1149–54. http://dx.doi.org/10.1098/rstb.1997.0098.

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We tested the hypothesis that neurons in the primary visual cortex adapt selectively to contingencies in the attributes of visual stimuli. We recorded from single neurons in macaque V1 and measured the effects of adaptation either to the sum of two gratings (compound stimulus) or to the individual gratings. According to our hypothesis, there would be a component of adaptation that is specific to the compound stimulus. In a first series of experiments, the two gratings differed in orientation. One grating had optimal orientation and the other was orthogonal to it, and therefore did not activate the neuron under study. These experiments provided evidence in favour of our hypothesis. In most cells adaptation to the compound stimulus reduced responses to the compound stimulus more than it reduced responses to the optimal grating, and adaptation to the optimal grating reduced responses to the optimal grating more than it reduced responses to the compound stimulus. This suggests that a component of adaptation was specific to (and caused by) the simultaneous presence of the two orientations in the compound stimulus. To test whether V1 neurons could adapt to other contingencies in the stimulus attributes, we performed a second series of experiments, in which the component gratings were parallel but differed in spatial frequency, and were both effective in activating the neuron under study. These experiments failed to reveal convincing contingent effects of adaptation, suggesting that neurons cannot adapt equally well to all types of contingency.
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Qin, Wen, and Chunshui Yu. "Neural Pathways Conveying Novisual Information to the Visual Cortex." Neural Plasticity 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/864920.

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The visual cortex has been traditionally considered as a stimulus-driven, unimodal system with a hierarchical organization. However, recent animal and human studies have shown that the visual cortex responds to non-visual stimuli, especially in individuals with visual deprivation congenitally, indicating the supramodal nature of the functional representation in the visual cortex. To understand the neural substrates of the cross-modal processing of the non-visual signals in the visual cortex, we firstly showed the supramodal nature of the visual cortex. We then reviewed how the nonvisual signals reach the visual cortex. Moreover, we discussed if these non-visual pathways are reshaped by early visual deprivation. Finally, the open question about the nature (stimulus-driven or top-down) of non-visual signals is also discussed.
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Kok, Peter, Michel F. Failing, and Floris P. de Lange. "Prior Expectations Evoke Stimulus Templates in the Primary Visual Cortex." Journal of Cognitive Neuroscience 26, no. 7 (July 2014): 1546–54. http://dx.doi.org/10.1162/jocn_a_00562.

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Sensory processing is strongly influenced by prior expectations. Valid expectations have been shown to lead to improvements in perception as well as in the quality of sensory representations in primary visual cortex. However, very little is known about the neural correlates of the expectations themselves. Previous studies have demonstrated increased activity in sensory cortex following the omission of an expected stimulus, yet it is unclear whether this increased activity constitutes a general surprise signal or rather has representational content. One intriguing possibility is that top–down expectation leads to the formation of a template of the expected stimulus in visual cortex, which can then be compared with subsequent bottom–up input. To test this hypothesis, we used fMRI to noninvasively measure neural activity patterns in early visual cortex of human participants during expected but omitted visual stimuli. Our results show that prior expectation of a specific visual stimulus evokes a feature-specific pattern of activity in the primary visual cortex (V1) similar to that evoked by the corresponding actual stimulus. These results are in line with the notion that prior expectation triggers the formation of specific stimulus templates to efficiently process expected sensory inputs.
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van Es, Daniel, and Tomas Knapen. "Attention Improves Stimulus Encoding in Early Visual Cortex." Journal of Vision 16, no. 12 (September 1, 2016): 1306. http://dx.doi.org/10.1167/16.12.1306.

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Hermes, Dora, Kai J. Miller, Brian A. Wandell, and Jonathan Winawer. "Gamma oscillations in visual cortex: the stimulus matters." Trends in Cognitive Sciences 19, no. 2 (February 2015): 57–58. http://dx.doi.org/10.1016/j.tics.2014.12.009.

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Mante, Valerio, and Matteo Carandini. "Mapping of Stimulus Energy in Primary Visual Cortex." Journal of Neurophysiology 94, no. 1 (July 2005): 788–98. http://dx.doi.org/10.1152/jn.01094.2004.

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A recent optical imaging study of primary visual cortex (V1) by Basole, White, and Fitzpatrick demonstrated that maps of preferred orientation depend on the choice of stimuli used to measure them. These authors measured population responses expressed as a function of the optimal orientation of long drifting bars. They then varied bar length, direction, and speed and found that stimuli of a same orientation can elicit different population responses and stimuli with different orientation can elicit similar population responses. We asked whether these results can be explained from known properties of V1 receptive fields. We implemented an “energy model” where a receptive field integrates stimulus energy over a region of three-dimensional frequency space. The population of receptive fields defines a volume of visibility, which covers all orientations and a plausible range of spatial and temporal frequencies. This energy model correctly predicts the population response to bars of different length, direction, and speed and explains the observations made with optical imaging. The model also readily explains a related phenomenon, the appearance of motion streaks for fast-moving dots. We conclude that the energy model can be applied to activation maps of V1 and predicts phenomena that may otherwise appear to be surprising. These results indicate that maps obtained with optical imaging reflect the layout of neurons selective for stimulus energy, not for isolated stimulus features such as orientation, direction, and speed.
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K. Aguirre, Geoffrey. "Variation in Temporal Stimulus Integration Across Visual Cortex." Journal of Vision 18, no. 10 (September 1, 2018): 1371. http://dx.doi.org/10.1167/18.10.1371.

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Alink, A., C. M. Schwiedrzik, A. Kohler, W. Singer, and L. Muckli. "Stimulus Predictability Reduces Responses in Primary Visual Cortex." Journal of Neuroscience 30, no. 8 (February 24, 2010): 2960–66. http://dx.doi.org/10.1523/jneurosci.3730-10.2010.

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Dissertations / Theses on the topic "Cortex in visual stimulus"

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Husain, M. "On hemispheric specialisation and visual direction sensing." Thesis, University of Oxford, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382681.

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Baker, Pamela Mary. "The contribution of cortical microcircuitry to stimulus masking effects in cat primary visual cortex /." Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17615.

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Lin, Yan. "Investigating stimulus induced metabolic changes in human visual cortex using functional magnetic resonance spectroscopy at 7T." Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/14589/.

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This thesis concerns the investigation of metabolic changes in 1H metabolite levels in the human visual cortex due to visual stimulation using proton magnetic resonance spectroscopy (1H-MRS) at 7T. The work described in this thesis has been undertaken by the author and collaborators at the Sir Peter Mansfield Magnetic Resonance Centre at the University of Nottingham. Detection of functional changes in 1H metabolites may enable a greater understanding of neurotransmitter activity and metabolic pathways used for energy synthesis during activation of brain tissue. Previous 1H MRS studies of the activated human brain mainly focused on observing lactate (Lac) changes. More recent studies by Mangia et al, taking advantage of the increased signal and spectral resolution at 7T, have investigated the change in the level of Lac, glutamate (Glu), Aspartate (Asp) and Glucose (Glc) during activation. However, Mangia, did not measure significant change in the level of gamma aminobutyric acid (GABA) and Glutamine (Gln), which might be expected to change due to increased neurotransmitter cycling rates during activation. Given that the metabolite changes observed due to visual stimulation were relatively small. We used a long, intense visual stimulus, designed to retain attention, to confirm and quantify the changes in the levels of Glu, GABA, and Gln, and to further investigate the Lac and Asp response to visual stimulation. Our present results using a moving stimulus of full-screen flickering contrast-defined wedges, have demonstrated many more metabolic changes throughout two different time scales of stimulation. Small (2~11%) but significant stimulation induced increases in Lac, Glu and glutathione (GSH) were observed along with decreases in Asp, GIn and glycine (Gly). In addition, decreases in (intracellular) Glc and increases in GABA were seen but did not reach significance. The opposite changes in Glu and Asp are indicative of increased activity of the malate-aspartate shuttle, which taken together with the opposite changes in Glc and Lac reflect the expected increase in brain energy metabolism. The increases in Glu and GABA coupled with the decrease in GIn can be interpreted in terms of increased activity of the Glu/Gln and Gln/Glu/GABA neurotransmitter cycles. An entirely new observation is the increase of GSH during prolonged visual stimulation. The similarity of its time course to that of Glu suggests that it may be a response to the increased release of Glu or to the increased production of reactive oxygen species. Gly is also a precursor of GSH and a decrease on activation is consistent with increased GSH synthesis. Together these observations constitute the most detailed analysis to date of functional changes in human brain metabolites. Interestingly, the Lac response was confined to the first visual stimulus. It is possible that processes triggered during the first period of visual stimulation, could continue for a while after stimulation has ended. If this is an important mechanism of the activity-stimulated brain Lac response, shortening the duration of the first stimulus might lead to an increase in Lac response during the second period of stimulation. With this in mind, we designed a repeated visual stimulation paradigm, varying the duration of the first stimulation (shorter than 9.9-min, based on our previous results), to see the effect on the Lac response during the second visual stimulation period. A gradual increase in Lac under the prolonged stimulation, following the first brief stimulation (1s, 16s and 48s, respectively), was observed and maintained until the end of these periods. Lac responses during the second stimulation period looked similar whether the first stimulation was 1s or 16s. With the increase of first visual stimulus duration (48s), the Lac response under the second stimulation period was slightly diminished. No significant Lac accumulation can be evident to the second stimulation, when the initial stimulation was 288s. The averaged Lac level was considerably below baseline after cessation of the first 288s stimulus. It is possible that the increased glycolytic flux, triggered during the initial longer stimulation, would still continue for a while during recovery, accounting for the decreased brain Lac level during resting periods from stimulation. Further experiments are ongoing, varying the duration of the second resting periods, to see the effect on the Lac response to the second stimulation.
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Pietravalle, Nadia. "How well does a linear model predict the responses of primary visual cortex neurons to a natural scene stimulus?" Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/30518.

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The goal was to test how well a linear model of the responses of neurons in area 18 of cat visual cortex, derived from recordings made in anaesthetized adult cats, predicts responses to natural scene stimuli. Methods: Estimates of the spatio-temporal receptive field profile of the neurons were obtained by reverse correlation to an m-sequence stimulus (Reid et al., 1997). The receptive field estimate, together with a non-linear response function, was then used to give the expected probability, or rate, of spike firing (Chichilnisky, 2001; Ringach & Malone, 2007) during a time-varying natural scene stimulus. The ability of the model to describe the responses was assessed by computing the correlation coefficient between the rates predicted by the model and those observed during stimulation with a natural scene (Willmore & Smyth, David & Gallant, 2005). For each LN functional model identified for all real A18 neurons using m-sequence responses, a Poisson spike generator was added (Heeger, 2000) to simulate ‘LNP’ responses to m-sequence and natural scene stimuli, and was used to assess the statistical significance of the results. Results: The LN model, with parameters derived from responses to m-sequence stimuli, was able to predict responses to m-sequence stimuli with fairly high reliability (correlation coefficients in the range 0.84 – 0.96). However the model was only able to weakly predict responses to natural scene stimuli. This result was confirmed by comparing the correlation coefficients between predicted and observed firing rates obtained for actual and for simulated responses to the natural scene stimulus; values ranged from 0.14 to 0.59, in marked contrast to the simulated ones ranging from 0.47 to 0.88. Reasons for the inability of the LNP model to predict responses to natural scene stimuli are discussed.
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Keemink, Sander Wessel. "Coding of multivariate stimuli and contextual interactions in the visual cortex." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/28969.

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The primary visual cortex (V1) has long been considered the main low level visual analysis area of the brain. The classical view is of a feedfoward system functioning as an edge detector, in which each cell has a receptive field (RF) and a preferred orientation. Whilst intuitive, this view is not the whole story. Although stimuli outside a neuron’s RF do not result in an increased response by themselves, they do modulate a neuron’s response to what’s inside its RF. We will refer to such extra-RF effects as contextual modulation. Contextual modulation is thought to underlie several perceptual phenomena, such as various orientation illusions and saliency of specific features (such as a contour or differing element). This gives a view of V1 as more than a collection of edge detectors, with neurons collectively extracting information beyond their RFs. However, many of the accounts linking psychophysics and physiology explain only a small subset of the illusions and saliency effects: we would like to find a common principle. So first, we assume the contextual modulations experienced by V1 neurons is determined by the elastica model, which describes the shape of the smoothest curve between two points. This single assumption gives rise to a wide range of known contextual modulation and psychophysical effects. Next, we consider the more general problem of encoding and decoding multi-variate stimuli (such as center surround gratings) in neurons, and how well the stimuli can be decoded under substantial noise levels with a maximum likelihood decoder. Although the maximum likelihood decoder is widely considered optimal and unbiased in the limit of no noise, under higher noise levels it is poorly understood. We show how higher noise levels lead to highly complex decoding distributions even for simple encoding models, which provides several psychophysical predictions. We next incorporate more updated experimental knowledge of contextual modulations. Perhaps the most common form of contextual modulations is center surround modulation. Here, the response to a center grating in the RF is modulated by the presence of a surrounding grating (the surround). Classically this modulation is considered strongest when the surround is aligned with the preferred orientation, but several studies have shown how many neurons instead experience strongest modulation whenever center and surround are aligned. We show how the latter type of modulation gives rise to stronger saliency effects and unbiased encoding of the center. Finally, we take an experimental perspective. Recently, both the presence and the underlying mechanisms of contextual modulations has been increasingly studied in mice using calcium imaging. However, cell signals extracted with calcium imaging are often highly contaminated by other sources. As contextual effects beyond center surround modulation can be subtle, a method is needed to remove the contamination. We present an analysis toolbox to de-contaminate calcium signals with blind source separation. This thesis thus expands our understanding of contextual modulation, predicts several new experimental results, and presents a toolbox to extract signals from calcium imaging data which should allow for more in depth studies of contextual modulation.
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Giacherio, Brenna. "Evaluation of Functional Near Infrared Spectroscopy (fNIRS) for Assessment of the Visual and Motor Cortices in Adults." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401816241.

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Tigwell, D. A. "Directional and orientational tuning in the striate cortex of the cat for contrast and textured stimuli." Thesis, Keele University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.237754.

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Shaw, Lynda Joan. "Emotional processing of natural visual images in brief exposures and compound stimuli : fMRI and behavioural studies." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3203.

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Can the brain register the emotional valence of brief exposures of complex natural stimuli under conditions of forward and backward masking, and under conditions of attentional competition between foveal and peripheral stimuli? To address this question, three experiments were conducted. The first, a behavioural experiment, measured subjective valence of response (pleasant vs unpleasant) to test the perception of the valence of natural images in brief, masked exposures in a forward and backward masking paradigm. Images were chosen from the International Affective Picture System (IAPS) series. After correction for response bias, responses to the majority of target stimuli were concordant with the IAPS ratings at better than chance, even when the presence of the target was undetected. Using functional magnetic resonance imaging (fMRI), the effects of IAPS valence and stimulus category were objectively measured on nine regions of interest (ROIs) using the same strict temporal restrictions in a similar masking design. Evidence of affective processing close to or below conscious threshold was apparent in some of the ROIs. To further this line of enquiry, a second fMRI experiment mapping the same ROIs and using the same stimuli were presented in a foveal (‘attended’) peripheral (‘to-be-ignored’) paradigm (small image superimposed in the centre of a large image of the same category, but opposite valence) to investigate spatial parameters and limitations of attention. Results are interpreted as showing both valence and category specific effects of ‘to-be-ignored’ images in the periphery. These results are discussed in light of theories of the limitations of attentional capacity and the speed in which we process natural images, providing new evidence of the breadth of variety in the types of affective visual stimuli we are able to process close to the threshold of conscious perception.
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Kara, Prakash. "Processing of transient stimuli by the visual system of the rat." Master's thesis, University of Cape Town, 1993. http://hdl.handle.net/11427/26626.

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While three decades of intensive cortical electrophysiology using a variety of sustained visual stimuli has made a significant contribution to many aspects of visual function, it has not supported the existence of intracortical circuit operations in cortical processing. This study investigated cortical processing by a comparison of the response of primary visual cortical neurones to transient electrical and strobe-flash stimulation. Experiments were performed on 74 anaesthetised Long Evans rats. Standard stereotaxic and extracellular electrophysiological techniques were employed. Continuous (on-line) raster plots and peri-stimulus time histograms (PSTHs) of the extracellular spikes from 81 visual cortical and 55 lateral geniculate nucleus (LGN) neurones were compiled. The strobe-flash stimuli (0.05 ms) were applied to the contralateral eye while the monopolar or bipolar electrical stimuli (0.2 ms, 80-400 μA) were applied to the ipsilateral LGN. 60 of the 81 (74%) tested cortical units were found to be responsive to visual stimuli. A distinct and consistent difference in the cortical response to the two types of transient stimuli was found: (a) Electrical stimulation evoked a prolonged period (197 ± 61 ms) of inhibition in all cortical neurones tested (n=20). This was the case even in those cortical units that were completely unresponsive to visual stimulation. The protracted inhibition was usually followed by a 100-200 ms phase of rebound excitation. (b) Flash stimulation evoked a prominent excitatory discharge (5-30 ms duration) after a latency of 30-60 ms from the onset of the stimulus (n = 59). This was followed by either moderate inhibition or return to a firing rate similar to control activity, for a maximum of 40 ms. Thereafter, cortical neurones showed a sustained increased level of activity with superimposed secondary excitatory phases. The duration of this late re-excitatory phase was 200-300 ms. In 17 of 20 (85%) tested units, the temporal profile of the cortical response to flash stimulation was modulated by small changes in the level of background illumination. In 16 of the 17 units, this sensitivity was reflected primarily as an emergence of a brief secondary inhibitory phase at the lowest level of background illumination (0 lux). Only 1 of the 17 cortical units displayed a flash-evoked primary inhibitory phase at O lux. We explored the possibility that neurones in the lateral geniculate nucleus (LGN) of the thalamus were responsible for the late phase of cortical reexcitation. 49 of the 55 (89%) LGN neurones could be classified as either of the "ON type" i.e. excited by visual stimuli, or the "OFF type" i.e. inhibited by visual stimuli. The response of ON-like LGN neurones to strobe-flash stimulation of the contralateral eye was characterised by a primary excitatory or early discharge (ED) phase after a latency of 25-40 ms. Thereafter, a 200- 400 ms period of inhibition was observed. In 57% of the sample, a rebound excitatory or late discharge (LD) phase completed the response. OFF-like LGN neurones were inhibited by the strobe-flash stimuli after a latency of 30- 35 ms. This flash-evoked inhibition was maintained for 200-400 ms. The sensitivity of the flash-evoked LGN response to the level of background illumination was tested in 11 ON-like and 10 OFF-like neurones. No sustained secondary excitatory events, as observed in visual cortical neurones, were found in any of the ON- and OFF-like LGN neurones, irrespective of the level of background illumination. In conclusion, the data show that the late re-excitatory phase evoked in cortical neurones upon strobe-flash stimulation, is not due to sustained LGN (thalamic) input. Rather, it suggests that these re-excitatory phases are due to intracortical processing of the transient stimuli. These findings emphasize the independent role of the cortex in computing the response to visual stimuli, and cast doubt on traditional theories that have emphasised the role of the thalamus in shaping cortical responses. The difference in the flash and electrically evoked cortical response suggests that even though substantial inhibition is available to the cortex, only a small fraction of this inhibitory capacity is utilised during natural stimulation.
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Killian, Nathaniel J. "Bioelectrical dynamics of the entorhinal cortex." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52148.

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The entorhinal cortex (EC) in the medial temporal lobe plays a critical role in memory formation and is implicated in several neurological diseases including temporal lobe epilepsy and Alzheimer’s disease. Despite the known importance of this brain region, little is known about the normal bioelectrical activity patterns of the EC in awake, behaving primates. In order to develop effective therapies for diseases affecting the EC, we must first understand its normal properties. To contribute to our understanding of the EC, I monitored the activity of individual neurons and populations of neurons in the EC of rhesus macaque monkeys during free-viewing of photographs using electrophysiological techniques. The results of these experiments help to explain how primates can form memories of, and navigate through, the visual world. These experiments revealed neurons in the EC that represent visual space with triangular grid receptive fields and other neurons that prefer to fire near image borders. These properties are similar to those previously described in the rodent EC, but here the neuronal responses relate to viewing of remote space as opposed to representing the physical location of the animal. The representation of visual space may be aided by another EC neuron type that was discovered, free-viewing saccade direction cells, neurons that signaled the direction of upcoming saccades. Such a signal could be used by other cells to prepare to fire according to the future gaze location. Many of these spatially-responsive neurons also represented memory for images, suggesting that they may be useful for associating items with their locations. I also examined the neuronal circuitry of recognition memory for visual stimuli in the EC, and I found that population synchronization within the gamma-band (30-140 Hz) in superficial layers of the EC was modulated by stimulus novelty, while the strength of memory formation modulated gamma-band synchronization in the deep layers and in layer III. Furthermore, the strength of connectivity in the gamma-band between different layers was correlated with the strength of memory formation, with deep to superficial power transfer being correlated with stronger memory formation and superficial to deep transfer correlated with weaker memory formation. These findings support several previous investigations of hippocampal-entorhinal connectivity in the rodent and advance our understanding of the functional circuitry of the medial temporal lobe memory system. Finally, I explored the design of a device that could be used to investigate properties of brain tissue in vitro, potentially aiding in the development of treatments for disorders of the EC and other brain structures. We designed, fabricated, and validated a novel device for long-term maintenance of thick brain slices and 3-dimensional dissociated cell cultures on a perforated multi-electrode array. To date, most electrical recordings of thick tissue preparations have been performed by manually inserting electrode arrays. This work demonstrates a simple and effective solution to this problem by building a culture perfusion chamber around a planar perforated multi-electrode array. By making use of interstitial perfusion, the device maintained the thickness of tissue constructs and improved cellular survival as demonstrated by increased firing rates of perfused slices and 3-D cultures, compared to unperfused controls. To the best of our knowledge, this is the first thick tissue culture device to combine forced interstitial perfusion for long-term tissue maintenance and an integrated multi-electrode array for electrical recording and stimulation.
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Books on the topic "Cortex in visual stimulus"

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1929-, Peters Alan, ed. The cat primary visual cortex. San Diego: Academic Press, 2002.

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Peters, Alan, and Kathleen S. Rockland, eds. Primary Visual Cortex in Primates. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4757-9628-5.

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Harris, Jessica M. Visual cortex: Anatomy, functions, and injuries. Hauppauge, N.Y: Nova Science Publishers, 2011.

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Suner, Ivan Jose. Influences of the lateral geniculate nucleus in the specification of primary visual cortex in macaca mulatta. [s.l: s.n.], 1992.

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A vision of the brain. Oxford: Blackwell Scientific Publications, 1993.

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Bedford, James Lewis. Neuro-electromagnetic imaging of the human visual cortex. Birmingham: Aston University. Department of Vision Sciences, 1995.

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A, Goodale Melvyn, ed. The visual brain in action. Oxford: Oxford University Press, 1995.

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Tovée, Martin J. The speed of thought: Information processing in the cerebral cortex. Berlin: Springer, 1998.

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Andrei, Gorea, ed. Representations of vision: Trends and tacit assumptions in vision research. Cambridge [England]: Cambridge University Press, 1991.

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Popp, Michael M. Spontanaktivität, Latenzen und Assemblies: Latenzmessungen als Beitrag zur Analyse der Verarbeitung im primären visuellen Cortex. Regensburg: S. Roderer, 1988.

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Book chapters on the topic "Cortex in visual stimulus"

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Krüger, J., and J. D. Becker. "Is Spike Frequency the Critical Factor in Recognising the Visual Stimulus?" In Information Processing in the Cortex, 161–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49967-8_8.

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Ulinski, Philip S. "Neural Mechanisms Underlying the Analysis of Moving Visual Stimuli." In Cerebral Cortex, 283–399. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4903-1_6.

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Jancke, Dirk, Fréderic Chavane, and Amiram Grinvald. "Stimulus Localization by Neuronal Populations in Early Visual Cortex: Linking Functional Architecture to Perception." In Dynamics of Visual Motion Processing, 95–116. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0781-3_5.

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Eckhorn, R., and H. J. Reitboeck. "Stimulus-Specific Synchronization in Cat Visual Cortex and Its Possible Role in Visual Pattern Recognition." In Springer Series in Synergetics, 99–111. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-48779-8_6.

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Eckhorn, Reinhard. "Stimulus-Specific Synchronizations in the Visual Cortex: Linking of Local Features Into Global Figures?" In Neuronal Cooperativity, 184–224. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-84301-3_9.

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Eckhorn, Reinhard, Thomas Schanze, Michael Brosch, Wageda Salem, and Roman Bauer. "Stimulus-Specific Synchronizations in Cat Visual Cortex: Multiple Microelectrode and Correlation Studies from Several Cortical Areas." In Induced Rhythms in the Brain, 47–80. Boston, MA: Birkhäuser Boston, 1992. http://dx.doi.org/10.1007/978-1-4757-1281-0_3.

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Strisciuglio, Nicola, and Nicolai Petkov. "Brain-Inspired Algorithms for Processing of Visual Data." In Lecture Notes in Computer Science, 105–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82427-3_8.

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AbstractThe study of the visual system of the brain has attracted the attention and interest of many neuro-scientists, that derived computational models of some types of neuron that compose it. These findings inspired researchers in image processing and computer vision to deploy such models to solve problems of visual data processing.In this paper, we review approaches for image processing and computer vision, the design of which is based on neuro-scientific findings about the functions of some neurons in the visual cortex. Furthermore, we analyze the connection between the hierarchical organization of the visual system of the brain and the structure of Convolutional Networks (ConvNets). We pay particular attention to the mechanisms of inhibition of the responses of some neurons, which provide the visual system with improved stability to changing input stimuli, and discuss their implementation in image processing operators and in ConvNets.
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Fillbrandt, Antje, and Frank W. Ohl. "Modulations of Single-Trial Interactions between the Auditory and the Visual Cortex during Prolonged Exposure to Audiovisual Stimuli with Fixed Stimulus Onset Asynchrony." In Detection and Identification of Rare Audiovisual Cues, 155–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24034-8_13.

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van Dijk, Bob W., Peter C. M. Vijn, and Henk Spekreijse. "Low Temporal Frequency Desynchronization and High Temporal Frequency Synchronization Accompany Processing of Visual Stimuli in Anaesthetized Cat Visual Cortex." In Oscillatory Event-Related Brain Dynamics, 183–204. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1307-4_14.

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Tani, Toshiki, Isao Yokoi, Minami Ito, Shigeru Tanaka, and Hidehiko Komatsu. "Neural Responses to the Uniform Surface Stimuli in the Visual Cortex of the Cat." In The Neural Basis of Early Vision, 236–37. Tokyo: Springer Japan, 2003. http://dx.doi.org/10.1007/978-4-431-68447-3_79.

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Conference papers on the topic "Cortex in visual stimulus"

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Roth, Zvi, David Heeger, and Elisha Merriam. "Orientation selectivity and stimulus vignetting in human visual cortex." In 2018 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1245-0.

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Garasto, Stef, Wilten Nicola, Anil A. Bharath, and Simon R. Schultz. "Neural Sampling Strategies for Visual Stimulus Reconstruction from Two-photon Imaging of Mouse Primary Visual Cortex." In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019. http://dx.doi.org/10.1109/ner.2019.8716934.

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Albrecht, Duane G., and Wilson S. Geisler. "Visual cortex neurons in monkey and cat: contrast response nonlinearities and stimulus selectivity." In Computational Vision Based on Neurobiology, edited by Teri B. Lawton. SPIE, 1994. http://dx.doi.org/10.1117/12.171147.

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Tripp, Bryan P. "Similarities and differences between stimulus tuning in the inferotemporal visual cortex and convolutional networks." In 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2017. http://dx.doi.org/10.1109/ijcnn.2017.7966303.

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Tolkiehn, Marie, and Simon R. Schultz. "Multi-Unit Activity contains information about spatial stimulus structure in mouse primary visual cortex." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319214.

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Han, XingLiang, Jun Xie, AiLing Luo, GuangHua Xu, XiaoDong Zhang, Jing Wang, and Min Li. "Comparison of Visual Cortex Functional Connectivity Patterns Based on Steady-state Monochromatic Flicker and Oscillating Checkerboard Visual Stimulus." In 2018 15th International Conference on Ubiquitous Robots (UR). IEEE, 2018. http://dx.doi.org/10.1109/urai.2018.8441841.

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Goto, Yoshinobu, Takao Yamasaki, and Shozo Tobimatsu. "Innovation for visual stimuli: From the retina to primary visual cortex." In 2010 IEEE/ICME International Conference on Complex Medical Engineering - CME 2010. IEEE, 2010. http://dx.doi.org/10.1109/iccme.2010.5558856.

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Eckhorn, Reitboeck, Arndt, and Dicke. "Feature linking via stimulus-evoked oscillations: experimental results from cat visual cortex and functional implications from a network model." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118659.

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Chizhov, Anton. "PREFERENCE OF HORIZONTAL ORIENTATION OF A MOVING NON-ORIENTED STIMULUS BY VISUAL CORTEX NEURONS PREFERRING HORIZONTAL ORIENTATION OF GRATINGS: MATHEMATICAL MODELING." In XVII INTERNATIONAL INTERDISCIPLINARY CONGRESS NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY. LCC MAKS Press, 2021. http://dx.doi.org/10.29003/m2403.sudak.ns2021-17/424-425.

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Sharpee, Tatyana, Hiroki Sugihara, A. V. Kurgansky, S. Rebrik, M. P. Stryker, and Kenneth D. Miller. "Probing feature selectivity of neurons in primary visual cortex with natural stimuli." In Second International Symposium on Fluctuations and Noise, edited by Derek Abbott, Sergey M. Bezrukov, Andras Der, and Angel Sanchez. SPIE, 2004. http://dx.doi.org/10.1117/12.548513.

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Reports on the topic "Cortex in visual stimulus"

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Intrator, Nathan, Mark F. Bear, Leon N. Cooper, and Michael A. Paradiso. Theory of Synaptic Plasticity in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada260052.

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Intrator, Nathan, Mark F. Bear, Leon N. Cooper, and Michael A. Paradiso. Theory of Synaptic Plasticity in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada260322.

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Serre, Thomas, Lior Wolf, and Tomaso Poggio. Object Recognition with Features Inspired by Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada454604.

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Sajda, Paul, and Leif H. Finkel. Computer Simulations of Object Discrimination by Visual Cortex,. Fort Belvoir, VA: Defense Technical Information Center, January 1992. http://dx.doi.org/10.21236/ada253345.

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Klein, David J., Jonathan Z. Simon, Didier A. Depireux, and Shihab A. Shamma. Linear Stimulus-Invariant Processing and Spectrotemporal Reverse Correlation in Primary Auditory Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada438561.

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Neve, Rachael L., and Mark F. Bear. Visual Experience Regulates Gene Expression in the Developing Striate Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1989. http://dx.doi.org/10.21236/ada216149.

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Poggio, Tomaso, and Stephen Smale. Hierarchical Kernel Machines: The Mathematics of Learning Inspired by Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, February 2013. http://dx.doi.org/10.21236/ada580529.

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Cooper, Leon N. Synaptic Plasticity in Visual Cortex. From Synaptic Properties to Membranes and Receptors. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada304169.

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Artun, Omer B., Harel Z. Shouval, and Leon N. Cooper. The Effect of Dynamic Synapses on Spatio-temporal Receptive Fields in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada333497.

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Sajda, Paul, and Leif H. Finkel. A Neural Network Model of Object Segmentation and Feature Binding in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada248100.

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