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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Levitt, Jonathan B., Robert A. Schumer, S. Murray Sherman, Peter D. Spear, and J. Anthony Movshon. "Visual Response Properties of Neurons in the LGN of Normally Reared and Visually Deprived Macaque Monkeys." Journal of Neurophysiology 85, no. 5 (May 1, 2001): 2111–29. http://dx.doi.org/10.1152/jn.2001.85.5.2111.

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It is now well appreciated that parallel retino-geniculo-cortical pathways exist in the monkey as in the cat, the species in which parallel visual pathways were first and most thoroughly documented. What remains unclear is precisely how many separate pathways pass through the parvo- and magnocellular divisions of the macaque lateral geniculate nucleus (LGN), what relationships—homologous or otherwise—these pathways have to the cat's X, Y, and W pathways, and whether these are affected by visual deprivation. To address these issues of classification and trans-species comparison, we used achromatic stimuli to obtain an extensive set of quantitative measurements of receptive field properties in the parvo- and magnocellular laminae of the LGN of nine macaque monkeys: four normally reared and five monocularly deprived of vision by lid suture near the time of birth. In agreement with previous studies, we find that on average magnocellular neurons differ from parvocellular neurons by having shorter response latencies to optic chiasm stimulation, greater sensitivity to luminance contrast, and better temporal resolution. Magnocellular laminae are also distinguished by containing neurons that summate luminance over their receptive fields nonlinearly (Y cells) and whose temporal response phases decrease with increasing stimulus contrast (indicative of a contrast gain control mechanism). We found little evidence for major differences between magno- and parvocellular neurons on the basis of most spatial parameters except that at any eccentricity, the neurons with the smallest receptive field centers tended to be parvocellular. All parameters were distributed unimodally and continuously through the parvo- and magnocellular populations, giving no indications of subpopulations within each division. Monocular deprivation led to clear anatomical effects: cells in deprived-eye laminae were pale and shrunken compared with those in nondeprived eye laminae, and Cat-301 immunoreactivity in deprived laminae was essentially uniformly abolished. However, deprivation had only subtle effects on the response properties of LGN neurons. Neurons driven by the deprived eye in both magno- and parvocellular laminae had lower nonlinearity indices (i.e., summed signals across their receptive fields more linearly) and were somewhat less responsive. In magnocellular laminae driven by the deprived eye, neuronal response latencies to stimulation of the optic chiasm were slightly shorter than those in the nondeprived laminae, and receptive field surrounds were a bit stronger. No other response parameters were affected by deprivation, and there was no evidence for loss of a specific cell class as in the cat.
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12

Hua, Tianmiao, Guzhou Li, Chuanhong Tang, Zhenhua Wang, and Sheng Chang. "Enhanced adaptation of visual cortical cells to visual stimulation in aged cats." Neuroscience Letters 451, no. 1 (February 2009): 25–28. http://dx.doi.org/10.1016/j.neulet.2008.12.041.

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13

Fang, Marong, Jicheng Li, W. H. Kwong, P. Kindler, Gang Lu, Sen Mun Wai, and David T. Yew. "The complexity of the visual cells and visual pathways of the sturgeon." Microscopy Research and Technique 65, no. 3 (2004): 122–29. http://dx.doi.org/10.1002/jemt.20112.

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14

Priebe, Nicholas J., Ilan Lampl, and David Ferster. "Mechanisms of Direction Selectivity in Cat Primary Visual Cortex as Revealed by Visual Adaptation." Journal of Neurophysiology 104, no. 5 (November 2010): 2615–23. http://dx.doi.org/10.1152/jn.00241.2010.

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In contrast to neurons of the lateral geniculate nucleus (LGN), neurons in the primary visual cortex (V1) are selective for the direction of visual motion. Cortical direction selectivity could emerge from the spatiotemporal configuration of inputs from thalamic cells, from intracortical inhibitory interactions, or from a combination of thalamic and intracortical interactions. To distinguish between these possibilities, we studied the effect of adaptation (prolonged visual stimulation) on the direction selectivity of intracellularly recorded cortical neurons. It is known that adaptation selectively reduces the responses of cortical neurons, while largely sparing the afferent LGN input. Adaptation can therefore be used as a tool to dissect the relative contribution of afferent and intracortical interactions to the generation of direction selectivity. In both simple and complex cells, adaptation caused a hyperpolarization of the resting membrane potential (−2.5 mV, simple cells, −0.95 mV complex cells). In simple cells, adaptation in either direction only slightly reduced the visually evoked depolarization; this reduction was similar for preferred and null directions. In complex cells, adaptation strongly reduced visual responses in a direction-dependent manner: the reduction was largest when the stimulus direction matched that of the adapting motion. As a result, adaptation caused changes in the direction selectivity of complex cells: direction selectivity was reduced after preferred direction adaptation and increased after null direction adaptation. Because adaptation in the null direction enhanced direction selectivity rather than reduced it, it seems unlikely that inhibition from the null direction is the primary mechanism for creating direction selectivity.
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15

Miles, Ömür Budanur, Nadia L. Cerminara, and Dilwyn E. Marple-Horvat. "Purkinje cells in the lateral cerebellum of the cat encode visual events and target motion during visually guided reaching." Journal of Physiology 571, no. 3 (March 2006): 619–37. http://dx.doi.org/10.1113/jphysiol.2005.099382.

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16

Hartveit, E., and P. Heggelund. "Neurotransmitter receptors mediating excitatory input to cells in the cat lateral geniculate nucleus. II. Nonlagged cells." Journal of Neurophysiology 63, no. 6 (June 1, 1990): 1361–72. http://dx.doi.org/10.1152/jn.1990.63.6.1361.

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1. We studied the type of receptor for excitatory amino acids (EAA) that mediates visual responses of nonlagged cells in the dorsal lateral geniculate nucleus (LGN) by recording the visual response of single cells to a stationary flashing spot before, during, and after iontophoretical application of antagonists and agonists to EAA receptors. 2. The visual response of the nonlagged cells was strongly suppressed, in a dose-dependent manner, by the specific quisqualate/kainate receptor antagonist 6,7-dinitroquinoxaline-2,3-dione (DNQX). The average degree of suppression was 74%. Quisqualate enhanced the visual response. 3. Specific antagonists to the N-methyl-D-aspartate (NMDA) receptor had a weak suppressing effect on most nonlagged cells. The average degree of suppression was 22%. Measurement of such weak effects was complicated by the considerable spontaneous fluctuations of responsivity in the LGN cells. In the majority of cells where the visual response was suppressed by NMDA antagonists, the tonic response component was more strongly suppressed than the initial transient response component. The visual response was enhanced by NMDA, and this enhancement was antagonized by NMDA antagonists. 4. These findings suggest that the excitatory input from the retina to nonlagged LGN cells is mainly mediated by non-NMDA receptors. The non-NMDA receptors mediate fast EPSPs, and this can explain the fast onset and offset of the visual response of the nonlagged cells. 5. The generally small contribution from NMDA receptors to the visual response of the nonlagged cells might reflect a minor involvement of these receptors in the retinal input, or it could be related to the excitatory input to LGN from the visual cortex. 6. To study whether the expression of NMDA receptors was related to modulatory brain stem input to LGN, we examined the effects of the NMDA antagonists when the visual response was enhanced with gamma-aminobutyric acid (GABA) antagonists or acetylcholine (ACh). Neither of these pharmacologic manipulations consistently increased the relative contribution of NMDA receptors to the visual response. 7. No pharmacologic difference was found between nonlagged X- and Y-cells, or between ON- and OFF-center cells.(ABSTRACT TRUNCATED AT 400 WORDS)
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17

Reinhard, Katja, and Thomas A. Münch. "Visual properties of human retinal ganglion cells." PLOS ONE 16, no. 2 (February 16, 2021): e0246952. http://dx.doi.org/10.1371/journal.pone.0246952.

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The retinal output is the sole source of visual information for the brain. Studies in non-primate mammals estimate that this information is carried by several dozens of retinal ganglion cell types, each informing the brain about different aspects of a visual scene. Even though morphological studies of primate retina suggest a similar diversity of ganglion cell types, research has focused on the function of only a few cell types. In human retina, recordings from individual cells are anecdotal or focus on a small subset of identified types. Here, we present the first systematic ex-vivo recording of light responses from 342 ganglion cells in human retinas obtained from donors. We find a great variety in the human retinal output in terms of preferences for positive or negative contrast, spatio-temporal frequency encoding, contrast sensitivity, and speed tuning. Some human ganglion cells showed similar response behavior as known cell types in other primate retinas, while we also recorded light responses that have not been described previously. This first extensive description of the human retinal output should facilitate interpretation of primate data and comparison to other mammalian species, and it lays the basis for the use of ex-vivo human retina for in-vitro analysis of novel treatment approaches.
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18

RENTSCHLER, INGO. "Symmetry-coded cells in the visual cortex?" Nature 317, no. 6038 (October 1985): 581–82. http://dx.doi.org/10.1038/317581c0.

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19

Crook, J. M., B. Lange-Malecki, B. B. Lee, and A. Valberg. "Visual resolution of macaque retinal ganglion cells." Journal of Physiology 396, no. 1 (February 1, 1988): 205–24. http://dx.doi.org/10.1113/jphysiol.1988.sp016959.

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20

Bushnell, B. N., P. J. Harding, Y. Kosai, W. Bair, and A. Pasupathy. "Equiluminance Cells in Visual Cortical Area V4." Journal of Neuroscience 31, no. 35 (August 31, 2011): 12398–412. http://dx.doi.org/10.1523/jneurosci.1890-11.2011.

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21

Narayanan, K., and A. A. Khan. "The visual cells of the corsula mullet." Journal of Fish Biology 47, no. 3 (September 1995): 367–76. http://dx.doi.org/10.1111/j.1095-8649.1995.tb01906.x.

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22

Rimmer, J., T. Beale, and V. J. Lund. "Visual loss in patients with sphenoethmoidal cells." Journal of Laryngology & Otology 129, no. 2 (February 2015): 198–201. http://dx.doi.org/10.1017/s0022215114003454.

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AbstractBackground:A sphenoethmoidal cell is a posterior ethmoid cell that pneumatises superiorly and/or laterally to the sphenoid sinus. Disease within such a cell may cause visual symptoms because of the close relationship of the optic nerve.Case reports:This paper reports four cases of chronic rhinosinusitis involving a sphenoethmoidal cell, two with visual loss. The management of such cases is discussed and the current literature is reviewed.Conclusion:Pathology within a sphenoethmoidal cell must be considered in cases of optic neuropathy. The presence of these cells may be relevant even in cases of seemingly uncomplicated rhinosinusitis as they are associated with a higher rate of optic nerve protrusion and dehiscence.
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23

SAUL, ALAN B. "Visual cortical simple cells: Who inhibits whom." Visual Neuroscience 16, no. 4 (July 1999): 667–73. http://dx.doi.org/10.1017/s095252389916406x.

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Simple cells display a specific adaptation aftereffect when tested with drifting gratings. The onset of the response to each cycle of the grating is delayed after adapting, but the offset is unaffected. Testing with stationary bars whose luminance was modulated in time revealed that aftereffects occur only at certain points in both space and time. The aftereffects seen with moving stimuli were predicted from those seen with stationary stimuli. These adaptation experiments suggest a model that consists of mutually inhibitory simple cells that are in spatiotemporal quadrature. The inhibition is appropriately localized in space and time to create the observed aftereffects. In this model, inhibition onto direction-selective simple cells arises from simple cells with the same preferred direction.
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Kim, DM, ME Brecher, LA Bland, TJ Estes, RA Carmen, and EJ Nelson. "Visual identification of bacterially contaminated red cells." Transfusion 32, no. 3 (March 1992): 221–25. http://dx.doi.org/10.1046/j.1537-2995.1992.32392213804.x.

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25

Marigold, Daniel S., and Trevor Drew. "Contribution of cells in the posterior parietal cortex to the planning of visually guided locomotion in the cat: effects of temporary visual interruption." Journal of Neurophysiology 105, no. 5 (May 2011): 2457–70. http://dx.doi.org/10.1152/jn.00992.2010.

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In the present study, we determined whether cells in the posterior parietal cortex (PPC) may contribute to the planning of voluntary gait modifications in the absence of visual input. In two cats we recorded the responses of 41 neurons in layer V of the PPC that discharged in advance of the gait modification to a 900-ms interruption of visual information (visual occlusion). The cats continued to walk without interruption during the occlusion, which produced only minimal changes in step cycle duration and paw placement. Visual occlusion applied during the period of cell discharge was without significant effect on discharge frequency in 57% of cells. In the other cells, the visual occlusion produced either significant decreases (18%) or increases (21%) of discharge activity (in 1 cell there was both an increase and a decrease). The mean latency of the changes was 356 ms for decreases and 252 ms for increases. In most neurons, discharge frequency, when modified, returned to the same levels as during unoccluded locomotion when vision was restored. In some cells, there were significant changes in discharge activity after the restoration of vision; these were associated with corrections of gait. These results suggest that the PPC is more involved in the visuomotor transformations necessary to plan gait modifications than in continual sensory processing of visual information. We further propose that cells in the PPC contribute both to the planning of gait modifications on the basis of only intermittent visual sampling and to visually guided online corrections of gait.
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Bruce, C. J., and M. E. Goldberg. "Primate frontal eye fields. I. Single neurons discharging before saccades." Journal of Neurophysiology 53, no. 3 (March 1, 1985): 603–35. http://dx.doi.org/10.1152/jn.1985.53.3.603.

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We studied the activity of single neurons in the frontal eye fields of awake macaque monkeys trained to perform several oculomotor tasks. Fifty-four percent of neurons discharged before visually guided saccades. Three different types of presaccadic activity were observed: visual, movement, and anticipatory. Visual activity occurred in response to visual stimuli whether or not the monkey made saccades. Movement activity preceded purposive saccades, even those made without visual targets. Anticipatory activity preceded even the cue to make a saccade if the monkey could reliably predict what saccade he had to make. These three different activities were found in different presaccadic cells in different proportions. Forty percent of presaccadic cells had visual activity (visual cells) but no movement activity. For about half of the visual cells the response was enhanced if the monkey made saccades to the receptive-field stimulus, but there was no discharge before similar saccades made without visual targets. Twenty percent of presaccadic neurons discharged as briskly before purposive saccades made without a visual target as they did before visually guided saccades, and had weak or absent visual responses. These cells were defined as movement cells. Movement cells discharged much less or not at all before saccades made spontaneously without a task requirement or an overt visual target. The remaining presaccadic neurons (40%) had both visual and movement activity (visuomovement cells). They discharged most briskly before visually guided eye movements, but also discharged before purposive eye movements made in darkness and responded to visual stimuli in the absence of saccades. There was a continuum of visuomovement cells, from cells in which visual activity predominated to cells in which movement activity predominated. This continuum suggests that although visual cells are quite distinct from movement cells, the division of cell types into three classes may be only a heuristic means of describing the processing flow from visual input to eye-movement output. Twenty percent of visuomovement and movement cells, but fewer than 2% of visual cells, had anticipatory activity. Only one cell had anticipatory activity as its sole response. When the saccade was delayed relative to the target onset, visual cells responded to the target appearance, movement cells discharged before the saccade, and visuomovement cells discharged in different ways during the delay, usually with some discharge following the target and an increase in rate immediately before the saccade. Presaccadic neurons of all types were actively suppressed following a saccade into their response fields.(ABSTRACT TRUNCATED AT 400 WORDS)
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27

Yim, Annie, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, Cecilia Garcia-Perez, Jose Villaveces, et al. "mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations." Nucleic Acids Research 48, no. 2 (December 4, 2019): 605–32. http://dx.doi.org/10.1093/nar/gkz1128.

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Abstract Mitochondria participate in metabolism and signaling. They adapt to the requirements of various cell types. Publicly available expression data permit to study expression dynamics of genes with mitochondrial function (mito-genes) in various cell types, conditions and organisms. Yet, we lack an easy way of extracting these data for mito-genes. Here, we introduce the visual data mining platform mitoXplorer, which integrates expression and mutation data of mito-genes with a manually curated mitochondrial interactome containing ∼1200 genes grouped in 38 mitochondrial processes. User-friendly analysis and visualization tools allow to mine mitochondrial expression dynamics and mutations across various datasets from four model species including human. To test the predictive power of mitoXplorer, we quantify mito-gene expression dynamics in trisomy 21 cells, as mitochondrial defects are frequent in trisomy 21. We uncover remarkable differences in the regulation of the mitochondrial transcriptome and proteome in one of the trisomy 21 cell lines, caused by dysregulation of the mitochondrial ribosome and resulting in severe defects in oxidative phosphorylation. With the newly developed Fiji plugin mitoMorph, we identify mild changes in mitochondrial morphology in trisomy 21. Taken together, mitoXplorer (http://mitoxplorer.ibdm.univ-mrs.fr) is a user-friendly, web-based and freely accessible software, aiding experimental scientists to quantify mitochondrial expression dynamics.
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Kambe, Yusuke, Katsura Kojima, Naohide Tomita, Yasushi Tamada, and Tetsuji Yamaoka. "PS2-12 Development of FRET mechanical sensor to visualize cell-material interactions(PS2: Poster Short Presentation II,Poster Session)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2015.8 (2015): 254. http://dx.doi.org/10.1299/jsmeapbio.2015.8.254.

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Modrzejewska, Monika, Michał Post, and Marcin Milchert. "Zaburzenie krążenia pozagałkowego i funkcji układu wzrokowego w przebiegu olbrzymiokomórkowego zapalenia tętnic współistniejącego z druzami tarczy nerwu wzrokowego – opis przypadku." Journal of Ultrasonography 13, no. 54 (September 30, 2013): 337–43. http://dx.doi.org/10.15557/jou.2013.0034.

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30

Asrory, VDO. "Comparison of the Effect of 1000mg and 500mg Oral Citicoline on Visual Field and Ganglion Cell Layer Thickness in Primary Open Angle Glaucoma." Open Access Journal of Ophthalmology 7, no. 1 (January 31, 2022): 1–10. http://dx.doi.org/10.23880/oajo-16000234.

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Purpose: To compare the effects of 1000 mg and 500 mg oral citicoline on the visual field, retinal nerve fiber layer and ganglion cells layer thickness in well controlled primary open angle glaucoma. Methods: A double blind randomized controlled trial was conducted on 50 subjects (75 eyes). The randomization divided the subjects into two groups, the 1000 mg group and the 500 mg group. The evaluations were performed after 30 days and 60 days intervention by assessing Mean Deviation (MD) and Pattern Standard Deviation (PSD) of Humphrey Visual field as well as retinal nerve fiber layer (RNFL) and Ganglion Cell-Inner Plexiform Layer (GCIPL) on ocular imaging. Results: After 60 days, there was no significant difference between both groups in the MD, PSD, RNFL, and GCIPL values. The median MD increased in the 1000 mg group from -9.96 dB at baseline to -5.0 dB after 60 days and from the intragroup analysis, there was a significant difference (p=0.008). Based on subgroup analysis, there was also significant difference before and after the intervention in the mild glaucoma receiving 500 mg citicoline and in moderate-severe glaucoma receiving 1000 mg citicoline. RNFL and GCIPL thickness in both groups were tended to be stable. A side effect of nausea was found in two subjects who each received a dose of 500 mg and 1000 mg citicoline. Conclusion: There was an improvement in the MD and PSD values in both groups after 60 days of oral citicoline administration, but a significant difference was found in mild glaucoma group receiving 500 mg citicoline and in moderate-severe glaucoma receiving 1000 mg citicoline. The thickness of RNFL and GCIPL in both groups did not decrease after 60 days of citicoline administration.
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Hawken, M. J., R. M. Shapley, and D. H. Grosof. "Temporal-frequency selectivity in monkey visual cortex." Visual Neuroscience 13, no. 3 (May 1996): 477–92. http://dx.doi.org/10.1017/s0952523800008154.

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AbstractWe investigated the dynamics of neurons in the striate cortex (V1) and the lateral geniculate nucleus (LGN) to study the transformation in temporal-frequency tuning between the LGN and V1. Furthermore, we compared the temporal-frequency tuning of simple with that of complex cells and direction-selective cells with nondirection-selective cells, in order to determine whether there are significant differences in temporal-frequency tuning among distinct functional classes of cells within V1. In addition, we compared the cells in the primary input layers of V1 (4a, 4cα, and 4cβ) with cells in the layers that are predominantly second and higher order (2, 3, 4b, 5, and 6). We measured temporal-frequency responses to drifting sinusoidal gratings. For LGN neurons and simple cells, we used the amplitude and phase of the fundamental response. For complex cells, the elevation of impulse rate (F0) to a drifting grating was the response measure. There is significant low-pass filtering between the LGN and the input layers of V1 accompanied by a small, 3-ms increase in visual delay. There is further low-pass filtering between V1 input layers and the second- and higher-order neurons in V1. This results in an average decrease in high cutoff temporal-frequency between the LGN and V1 output layers of about 20 Hz and an increase in average visual latency of about 12–14 ms. One of the most salient results is the increased diversity of the dynamic properties seen in V1 when compared to the cells of the lateral geniculate, possibly reflecting specialization of function among cells in V1. Simple and complex cells had distributions of temporal-frequency tuning properties that were similar to each other. Direction-selective and nondirection-selective cells had similar preferred and high cutoff temporal frequencies, but direction-selective cells were almost exclusively band-pass while nondirection-selective cells distributed equally between band-pass and low-pass categories. Integration time, a measure of visual delay, was about 10 ms longer for V1 than LGN. In V1 there was a relatively broad distribution of integration times from 40–80 ms for simple cells and 60–100 ms for complex cells while in the LGN the distribution was narrower.
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32

Murphy, Allison J., J. Michael Hasse, and Farran Briggs. "Physiological characterization of a rare subpopulation of doublet-spiking neurons in the ferret lateral geniculate nucleus." Journal of Neurophysiology 124, no. 2 (August 1, 2020): 432–42. http://dx.doi.org/10.1152/jn.00191.2020.

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Interest in visual system homologies across species has recently increased. Across species, retinas contain diverse retinal ganglion cells including cells with unusual visual response properties. It is unclear whether rare retinal ganglion cells in carnivores project to and drive similarly unique visual responses in the visual thalamus. We discovered a rare subpopulation of thalamic neurons defined by unique spike shape and visual response properties, suggesting that nonstandard visual computations are common to many species.
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33

Hikosaka, K., E. Iwai, H. Saito, and K. Tanaka. "Polysensory properties of neurons in the anterior bank of the caudal superior temporal sulcus of the macaque monkey." Journal of Neurophysiology 60, no. 5 (November 1, 1988): 1615–37. http://dx.doi.org/10.1152/jn.1988.60.5.1615.

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1. We examined the sensory properties of cells in the anterior bank of the caudal part of the superior temporal sulcus (caudal STS) in anesthetized, paralyzed monkeys to visual, auditory, and somesthetic stimuli. 2. In the anterior bank of the caudal STS, there were three regions distinguishable from each other and also from the middle temporal area (MT) in the floor of the STS and area Tpt in the superior temporal gyrus. The three regions were located approximately in the respective inner, middle, and outer thirds of the anterior bank of the caudal STS. These three regions are referred to, from the inner to the outer, as the medial superior temporal region (MST), the mostly unresponsive region, and the caudal STS polysensory region (cSTP), respectively. 3. The extent of MST and its response properties agreed with previous studies. Cells in MST responded exclusively to visual stimuli, had large visual receptive fields (RFs), and nearly all (91%) showed directional selectivity. 4. In the mostly unresponsive region, three quarters of cells were unresponsive to any stimulus used in this study. A quarter of the cells responded to only visual stimuli and most did not show directional selectivity for moving stimuli. Several directionally selective cells responded to movements of three-dimensional objects, but not of projected stimuli. 5. The response properties of cells in the superficial cortex of the caudal superior temporal gyrus, a part of area Tpt, external to cSTP were different from those of cells in the three regions in the anterior bank of the STS. Cells in Tpt were exclusively auditory, and had much larger auditory RFs (mean = 271 degrees) than those of acoustically-driven cSTP cells (mean = 138 degrees). 6. The cSTP contained unimodal visual, auditory, and somesthetic cells as well as multimodal cells of two or all three modalities. The sensory properties of cSTP cells were as follows. 1) Out of 200 cells recorded, 102 (51%) cells were unimodal (59 visual, 33 auditory, and 10 somesthetic), 36 (18%) cells were bimodal (21 visual+auditory, 7 visual+somesthetic, and 8 auditory+somesthetic), and four (2%) cells were trimodal. Visual and auditory responses were more frequent than somesthetic responses: the ratio of the population of cells driven by visual: auditory: somesthetic stimuli was 3:2:1. 2) Visual RFs were large (mean diameter, 59 degrees), but two-thirds were limited to the contralateral visual hemifield. About half the cells showed directional selectivity for moving visual stimuli. None showed selectivity for particular visual shapes.(ABSTRACT TRUNCATED AT 400 WORDS)
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34

Hartveit, E., and P. Heggelund. "Brain-stem influence on visual response of lagged and nonlagged cells in the cat lateral geniculate nucleus." Visual Neuroscience 10, no. 2 (March 1993): 325–39. http://dx.doi.org/10.1017/s0952523800003722.

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AbstractThis study examined the influence of the pontomesencephalic peribrachial region (PBR) on the visual response properties of cells in the dorsal lateral geniculate nucleus (LGN). The response of single cells to a stationary flashing light spot was recorded with accompanying electrical stimulation of the PBR. The major objectives were to compare the effects of PBR stimulation on lagged and nonlagged cells, to examine how the visual response pattern of lagged cells could be modified by PBR stimulation and to examine whether the physiological criteria used to classify lagged and nonlagged cells are applicable during increased PBR input to the LGN. During PBR stimulation, the visual response was enhanced to a similar degree for lagged and nonlagged cells and the latency to half-rise of the visual response was reduced, particularly for the lagged X cells. The latency to half-fall of the visual response of lagged cells was not changed by PBR stimulation. Accordingly, the division of LGN cells into lagged and nonlagged cells based on visual response latencies was maintained during PBR stimulation. The initial suppression that a visual stimulus evokes in lagged cells was resistant to the effects of PBR stimulation. For the lagged cells, the largest response increase occurred for the initial part of the visual response. For the nonlagged cells, the largest increase occurred for the tonic part of the response. The results support the hypothesis that the differences in temporal response properties between lagged and nonlagged cells belong to the basic distinctions between these cell classes.
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35

Johnson, Elizabeth N., Michael J. Hawken, and Robert Shapley. "Cone Inputs in Macaque Primary Visual Cortex." Journal of Neurophysiology 91, no. 6 (June 2004): 2501–14. http://dx.doi.org/10.1152/jn.01043.2003.

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To understand the role of primary visual cortex (V1) in color vision, we measured directly the input from the 3 cone types in macaque V1 neurons. Cells were classified as luminance-preferring, color-luminance, or color-preferring from the ratio of the peak amplitudes of spatial frequency responses to red/green equiluminant and to black/white (luminance) grating patterns, respectively. In this study we used L-, M-, and S-cone–isolating gratings to measure spatial frequency response functions for each cone type separately. From peak responses to cone-isolating stimuli we estimated relative cone weights and whether cone inputs were the same or opposite sign. For most V1 cells the relative S-cone weight was <0.1. All color-preferring cells were cone opponent and their L/M cone weight ratio was clustered around a value of –1, which is roughly equal and opposite L and M cone signals. Almost all cells (88%) classified as luminance cells were cone nonopponent, with a broad distribution of cone weights. Most cells (73%) classified as color-luminance cells were cone opponent. This result supports our conclusion that V1 color-luminance cells are double-opponent. Such neurons are more sensitive to color boundaries than to areas of color and thereby could play an important role in color perception. The color-luminance population had a broad distribution of L/M cone weight ratios, implying a broad distribution of preferred colors for the double-opponent cells.
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36

Knierim, James J., Hemant S. Kudrimoti, and Bruce L. McNaughton. "Interactions Between Idiothetic Cues and External Landmarks in the Control of Place Cells and Head Direction Cells." Journal of Neurophysiology 80, no. 1 (July 1, 1998): 425–46. http://dx.doi.org/10.1152/jn.1998.80.1.425.

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Knierim, James J., Hemant S. Kudrimoti, and Bruce L. McNaughton. Interactions between idiothetic cues and external landmarks in the control of place cells and head direction cells. J. Neurophysiol. 80: 425–446, 1998. Two types of neurons in the rat brain have been proposed to participate in spatial learning and navigation: place cells, which fire selectively in specific locations of an environment and which may constitute key elements of cognitive maps, and head direction cells, which fire selectively when the rat's head is pointed in a specific direction and which may serve as an internal compass to orient the cognitive map. The spatially and directionally selective properties of these cells arise from a complex interaction between input from external landmarks and from idiothetic cues; however, the exact nature of this interaction is poorly understood. To address this issue, directional information from visual landmarks was placed in direct conflict with directional information from idiothetic cues. When the mismatch between the two sources of information was small (45°), the visual landmarks had robust control over the firing properties of place cells; when the mismatch was larger, however, the firing fields of the place cells were altered radically, and the hippocampus formed a new representation of the environment. Similarly, the visual cues had control over the firing properties of head direction cells when the mismatch was small (45°), but the idiothetic input usually predominated over the visual landmarks when the mismatch was larger. Under some conditions, when the visual landmarks predominated after a large mismatch, there was always a delay before the visual cues exerted their control over head direction cells. These results support recent models proposing that prewired intrinsic connections enable idiothetic cues to serve as the primary drive on place cells and head direction cells, whereas modifiable extrinsic connections mediate a learned, secondary influence of visual landmarks.
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Koyanagi, Mitsumasa, Kosuke Takano, Hisao Tsukamoto, Kohzoh Ohtsu, Fumio Tokunaga, and Akihisa Terakita. "Jellyfish vision starts with cAMP signaling mediated by opsin-Gs cascade." Proceedings of the National Academy of Sciences 105, no. 40 (October 1, 2008): 15576–80. http://dx.doi.org/10.1073/pnas.0806215105.

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Light sensing starts with phototransduction in photoreceptor cells. The phototransduction cascade has diverged in different species, such as those mediated by transducin in vertebrate rods and cones, by Gq-type G protein in insect and molluscan rhabdomeric-type visual cells and vertebrate photosensitive retinal ganglion cells, and by Go-type G protein in scallop ciliary-type visual cells. Here, we investigated the phototransduction cascade of a prebilaterian box jellyfish, the most basal animal having eyes containing lens and ciliary-type visual cells similar to vertebrate eyes, to examine the similarity at the molecular level and to obtain an implication of the origin of the vertebrate phototransduction cascade. We showed that the opsin-based pigment functions as a green-sensitive visual pigment and triggers the Gs-type G protein-mediated phototransduction cascade in the ciliary-type visual cells of the box jellyfish lens eyes. We also demonstrated the light-dependent cAMP increase in the jellyfish visual cells and HEK293S cells expressing the jellyfish opsin. The first identified prebilaterian cascade was distinct from known phototransduction cascades but exhibited significant partial similarity with those in vertebrate and molluscan ciliary-type visual cells, because all involved cyclic nucleotide signaling. These similarities imply a monophyletic origin of ciliary phototransduction cascades distributed from prebilaterian to vertebrate.
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38

Han, Kun, Dewei Wu, and Lei Lai. "A Brain-Inspired Adaptive Space Representation Model Based on Grid Cells and Place Cells." Computational Intelligence and Neuroscience 2020 (August 11, 2020): 1–12. http://dx.doi.org/10.1155/2020/1492429.

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Grid cells and place cells are important neurons in the animal brain. The information transmission between them provides the basis for the spatial representation and navigation of animals and also provides reference for the research on the autonomous navigation mechanism of intelligent agents. Grid cells are important information source of place cells. The supervised learning and unsupervised learning models can be used to simulate the generation of place cells from grid cell inputs. However, the existing models preset the firing characteristics of grid cell. In this paper, we propose a united generation model of grid cells and place cells. First, the visual place cells with nonuniform distribution generate the visual grid cells with regional firing field through feedforward network. Second, the visual grid cells and the self-motion information generate the united grid cells whose firing fields extend to the whole space through genetic algorithm. Finally, the visual place cells and the united grid cells generate the united place cells with uniform distribution through supervised fuzzy adaptive resonance theory (ART) network. Simulation results show that this model has stronger environmental adaptability and can provide reference for the research on spatial representation model and brain-inspired navigation mechanism of intelligent agents under the condition of nonuniform environmental information.
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39

Wiesel, T. "Neural Mechanisms of Visual Perception." Perception 26, no. 1_suppl (August 1997): 43. http://dx.doi.org/10.1068/v970003.

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It is more than half a century ago since Keffer H Hartline published his classical receptive fields studies of single optic nerve fibres in the frog. World War II intervened and the full impact of his work did not become apparent until the early fifties, when Horace Barlow extended Hartline's analysis in the frog and Stephen W Kuffler showed the on-centre and off-centre type ganglion cells in the cat retina. The next advances were made in the late fifties when Jerome Lettvin and Humberto Maturana described cells in the frog tectum with very complex response properties and when David Hubel and I discovered that cells in the cat striate cortex were sensitive to orientation of contours and binocular stimulation. Vision research has gone a long distance since that time—nonetheless we have just begun the long journey towards a detailed mechanistic understanding of the neural basis of visual perception. In this lecture I discuss the processing of visual information at the level of the striate cortex in the cat and monkey, and describe technical advances that have greatly facilitated the analysis of the neural mechanisms of visual perception.
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40

Imamoto, Yasushi, and Yoshinori Shichida. "Cone visual pigments." Biochimica et Biophysica Acta (BBA) - Bioenergetics 1837, no. 5 (May 2014): 664–73. http://dx.doi.org/10.1016/j.bbabio.2013.08.009.

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41

Stuart, Geoffrey W., and Terence R. J. Bossomaier. "Cooperative Representation of Visual Borders." Perception 21, no. 2 (April 1992): 185–93. http://dx.doi.org/10.1068/p210185.

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Recently it has been reported that the visual cortical cells which are engaged in cooperative coding of global stimulus features, display synchrony in their firing rates when both are stimulated. Alternative models identify global stimulus features with the coarse spatial scales of the image. Versions of the Munsterberg or Café Wall illusions which differ in their low spatial frequency content were used to show that in all cases it was the high spatial frequencies in the image which determined the strength and direction of these illusions. Since cells responsive to high spatial frequencies have small receptive fields, cooperative coding must be involved in the representation of long borders in the image.
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42

NAKATANI, Kei. "Mechanism of photo-signal transduction in visual cells." Dobutsu seiri 6, no. 1 (1989): 25–31. http://dx.doi.org/10.3330/hikakuseiriseika1984.6.25.

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43

von der Heydt, R., E. Peterhans, and MR Dursteler. "Periodic-pattern-selective cells in monkey visual cortex." Journal of Neuroscience 12, no. 4 (April 1, 1992): 1416–34. http://dx.doi.org/10.1523/jneurosci.12-04-01416.1992.

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44

BORST, A. "How do nerve cells compute fly visual interneurones." Acta Physiologica Scandinavica 157, no. 3 (July 1996): 403–7. http://dx.doi.org/10.1046/j.1365-201x.1996.30250000.x.

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45

Miorin, Lisa, Paolo Maiuri, and Alessandro Marcello. "Visual detection of Flavivirus RNA in living cells." Methods 98 (April 2016): 82–90. http://dx.doi.org/10.1016/j.ymeth.2015.11.002.

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46

SHICHIDA, Yoshinori, and Tôru YOSHIZAWA. "Visual Pigments in Photoreceptor Cells of Color Vision." Kagaku To Seibutsu 30, no. 6 (1992): 351–59. http://dx.doi.org/10.1271/kagakutoseibutsu1962.30.351.

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47

Demeulemeester, H., F. Vandesande, GA Orban, C. Brandon, and JJ Vanderhaeghen. "Heterogeneity of GABAergic cells in cat visual cortex." Journal of Neuroscience 8, no. 3 (March 1, 1988): 988–1000. http://dx.doi.org/10.1523/jneurosci.08-03-00988.1988.

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48

Newsome, W. T., R. H. Wurtz, and H. Komatsu. "Relation of cortical areas MT and MST to pursuit eye movements. II. Differentiation of retinal from extraretinal inputs." Journal of Neurophysiology 60, no. 2 (August 1, 1988): 604–20. http://dx.doi.org/10.1152/jn.1988.60.2.604.

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1. We investigated cells in the middle temporal visual area (MT) and the medial superior temporal area (MST) that discharged during smooth pursuit of a dim target in an otherwise dark room. For each of these pursuit cells we determined whether the response during pursuit originated from visual stimulation of the retina by the pursuit target or from an extraretinal input related to the pursuit movement itself. We distinguished between these alternatives by removing the visual motion stimulus during pursuit either by blinking off the visual target briefly or by stabilizing the target on the retina. 2. In the foveal representation of MT (MTf), we found that pursuit cells usually decreased their rate of discharge during a blink or during stabilization of the visual target. The pursuit response of these cells depends on visual stimulation of the retina by the pursuit target. 3. In a dorsal-medial region of MST (MSTd), cells continued to respond during pursuit despite a blink or stabilization of the pursuit target. The pursuit response of these cells is dependent on an extraretinal input. 4. In a lateral-anterior region of MST (MST1), we found both types of pursuit cells; some, like those in MTf, were dependent on visual inputs whereas others, like those in MSTd, received an extraretinal input. 5. We observed a relationship between pursuit responses and passive visual responses. MST cells whose pursuit responses were attributable to extraretinal inputs tended to respond preferentially to large-field random-dot patterns. Some cells that preferred small spots also had an extraretinal input. 6. For 92% of the pursuit cells we studied, the pursuit response began after onset of the pursuit eye movement. A visual response preceding onset of the eye movement could be observed in many of these cells if the initial motion of the target occurred within the visual receptive field of the cell and in its preferred direction. In contrast to the pursuit response, however, this visual response was not dependent on execution of the pursuit movement. 7. For the remaining 8% of the pursuit cells, the pursuit discharge began before initiation of the pursuit eye movement. This occurred even though the initial motion of the target was outside the receptive field as mapped during fixation trials. Our data suggest, however, that such responses may be attributable to an expansion of the receptive field that accompanies enhanced visual responses.(ABSTRACT TRUNCATED AT 400 WORDS)
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49

Hochstrate, Peter. "Photoresponses from Cells in the Fly’s Eye which are not Visual Cells." Zeitschrift für Naturforschung C 44, no. 9-10 (October 1, 1989): 867–75. http://dx.doi.org/10.1515/znc-1989-9-1029.

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Abstract It is shown that light elicits distinct responses from cells in the fly’s eye which are different from photoreceptors. These cells are designated as “slow cells” because of their sluggish response characteristics. Like the visual cells the slow cells depolarize upon light stimulation, but the time course of their responses is clearly different from that of the photoreceptors. Furthermore, the intensity necessary to evoke a given response amplitude is considerably higher in slow cells than in photoreceptors. Several lines of evidence indicate that the slow cell response is caused by light absorption through the visual pigment rhodopsin in the peripheral photoreceptors R 1 -6. The slow cells are electrically coupled among each other, as demonstrated by application of local light stimuli and injection of the fluorescent dye Lucifer Yellow . The identity of the slow cells and the mechanism of response generation are discussed.
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50

Brown, V. J., R. Desimone, and M. Mishkin. "Responses of cells in the tail of the caudate nucleus during visual discrimination learning." Journal of Neurophysiology 74, no. 3 (September 1, 1995): 1083–94. http://dx.doi.org/10.1152/jn.1995.74.3.1083.

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1. The tail of the caudate nucleus and adjacent ventral putamen (ventrocaudal neostriatum) are major projection sites of the extrastriate visual cortex. Visual information is then relayed, directly or indirectly, to a variety of structures with motor functions. To test for a role of the ventrocaudal neostriatum in stimulus-response association learning, or habit formation, neuronal responses were recorded while monkeys performed a visual discrimination task. Additional data were collected from cells in cortical area TF, which serve as a comparison and control for the caudate data. 2. Two monkeys were trained to perform an asymmetrically reinforced go-no go visual discrimination. The stimuli were complex colored patterns, randomly assigned to be either positive or negative. The monkey was rewarded with juice for releasing a bar when a positive stimulus was presented, whereas a negative stimulus signaled that no reward was available and that the monkey should withhold its response. Neuronal responses were recorded both while the monkey performed the task with previously learned stimuli and while it learned the task with new stimuli. In some cases, responses were recorded during reversal learning. 3. There was no evidence that cells in the ventrocaudal neostriatum were influenced by the reward contingencies of the task. Cells did not fire preferentially to the onset of either positive or negative stimuli; neither did cells fire in response to the reward itself or in association with the motor response of the monkey. Only visual responses were apparent. 4. The visual properties of cells in these structures resembled those of cells in some of the cortical areas projecting to them. Most cells responded selectively to different visual stimuli. The degree of stimulus selectivity was assessed with discriminant analysis and was found to be quantitatively similar to that of inferior temporal cells tested with similar stimuli. Likewise, like inferior temporal cells, many cells in the ventrocaudal neostriatum had large, bilateral receptive fields. Some cells had "doughnut"-shaped receptive fields, with stronger responses in the periphery of both visual fields than at the fovea, similar to the fields of some cells in the superior temporal polysensory area. Although the absence of task-specific responses argues that ventrocaudal neostriatal cells are not themselves the mediators of visual learning in the task employed, their cortical-like visual properties suggest that they might relay visual information important for visuomotor plasticity in other structures. (ABSTRACT TRUNCATED AT 400 WORDS)
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