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REPORT
Group in Vision Science, School of Optometry, Helen Wills Neuroscience Institute, University of California, Berkeley, California
Submitted 25 February 2005; accepted in final form 13 April 2005
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ABSTRACT |
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INTRODUCTION |
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). However, an orthogonal mask stimulus can substantially attenuate the response to an optimal test stimulus (Bonds 1989; DeAngelis et al. 1992; Morrone et al. 1987). Although the original demonstration was with orthogonal mask stimuli, subsequent work has shown that cross-orientation suppression (COS) occurs for any mask orientation (DeAngelis et al. 1992). This suppressive effect results when the mask and test stimuli are presented either monoptically (Allison et al. 2001; Bonds 1989; DeAngelis et al. 1992; Freeman et al. 2002; Morrone et al. 1987) or dichoptically (Ohzawa and Freeman 1986a,Ohzawa and Freeman 1986b; Sengpiel et al. 1995a,Sengpiel et al. 1995b, 1998; Walker et al. 1998). Both forms of COS are independent of the mask orientation (DeAngelis et al. 1992; Sengpiel et al. 1995b), broadly tuned to spatial frequency (Bonds 1989; Sengpiel et al. 1995a), independent of spatial phase (DeAngelis et al. 1992), spatially well localized to the classical receptive field (RF) of the cell (DeAngelis et al. 1992), and are established early in the developmental process (Endo et al. 2000; Green et al. 1996). These findings have been interpreted as suggesting similar mechanisms for monoptic and dichoptic COS (Andrews and Purves 1997; Heeger 1992). On the other hand, contrast response functions measured with COS show different types of gain control for monoptic and dichoptic COS (Sengpiel et al. 1998). This result suggests separate mechanisms for monoptic and dichoptic COS.
The physiological basis of COS is not clear. The independence of stimulus orientation (DeAngelis et al. 1992) and dependence on GABA (Morrone et al. 1987; Sillito et al. 1980) suggest inhibition from pools of neurons tuned to different orientations (Bonds 1989; DeAngelis et al. 1992; Heeger 1992; Morrone et al. 1987; Walker et al. 1998). Because peak levels of suppression are obtained at relatively high temporal frequencies, feedback from area 18 may be involved (Allison et al. 2001). A recent study of the temporal frequency and contrast adaptation properties of monoptic COS proposes a feedforward thalamocortical synaptic depression mechanism that occurs at the synapses from the lateral geniculate nucleus (LGN) to the striate cortex (Freeman et al. 2002). This notion is based on similar response characteristics of LGN neurons and the properties of monoptic COS. As with LGN neurons, monoptic COS is not affected by contrast adaptation and is induced at temporal frequencies higher than what will drive most cortical cells. Thalamocortical synaptic depression can also account for a variety of properties exhibited by monoptic COS, such as the lack of orientation tuning and the limited extent of suppression within the classical RF (DeAngelis et al. 1992).
Neurons in the LGN are monocularly driven and do not receive direct binocular input (Hayhow 1958, 1967). Because synaptic depression operates at the level of single synapses, depression at monocular thalamocortical synapses cannot give rise to dichoptic COS (Freeman et al. 2002). Because of its binocular nature, dichoptic COS has been hypothesized to arise from intracortical mechanisms (Blake and Logothetis 2002; Sengpiel et al. 1995b). On the other hand, LGN cells also exhibit dichoptic COS (Moore et al. 1992; Varela and Singer 1987; Xue et al. 1987), so it is possible that dichoptic COS in the striate cortex originates in the LGN. To understand the mechanism of dichoptic COS in visual cortex, we have compared temporal frequency tuning and stimulus adaptation properties of monoptic and dichoptic COS.
A preliminary report of these results has been presented in abstract form (Li et al. 2003).
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METHODS |
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Extracellular recordings are made with epoxy-coated tungsten microelectrodes (A-M Systems) from cells in the striate cortex of anesthetized and paralyzed cats. Anesthesia was induced with thio-pental sodium intravenously and maintained at an appropriate rate determined individually for each cat. A tracheal cannula was positioned, and the animal was artificially ventilated (25% O2-75% N2O) at a rate adjusted to maintain expired CO2 between 4 and 5%. Temperature was maintained at 38°C. A craniotomy was performed over area 17, and the dura was resected and covered with agar and wax to prevent drying and to reduce pulsation. After surgery, the anesthetic level was stabilized at a constant rate of thiopental sodium as determined for each cat. The animal was paralyzed with an intravenous infusion of pancuronium bromide (0.2 mg/kg/h). EEG, ECG, heart rate, temperature, and end-tidal CO2 were monitored during the experiment. Electrode penetrations were made along the medial bank of the postlateral gyrus, 4 mm posterior and 2 mm lateral from the Horsley-Clarke origin (Horsley and Clarke 1908) at an angle of 10° medial and 20° anterior. All procedures comply with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.
Physiological recordings
Electrodes are advanced into the cortex until a neuron is isolated and the shape of its spike waveform noted. Initial estimates of the tuning parameters and RF size and location were obtained qualitatively using computer-controlled manipulation of drifting sinusoidal gratings. Quantitative measurements of tuning functions for orientation, spatial frequency, temporal frequency, size, ocular dominance, and stimulus contrast were performed. Response amplitude was taken as the mean firing rate for complex cells or as the mean amplitude of the first harmonic of the response of simple cells. For cells that exhibit measurable responses from stimuli presented separately in each eye, both monoptic and dichoptic tests were performed. Otherwise, only the monoptic protocols were run. Optimal spatial and temporal parameters were used for both mask and test gratings. For dichoptic stimulation, the mask and test stimuli were presented to the nondominant and dominant eye, respectively.
Temporal frequency tuning of COS
Orthogonal mask and optimal test gratings were presented (either monoptically or dichoptically) simultaneously for 4 s. The temporal frequency of the test grating was fixed at optimal, whereas that of the mask was varied across conditions from 0.5 to 25 Hz. Test-only and blank conditions were also interleaved with 10-s interstimulus intervals. The temporal frequency tuning properties for monoptic and dichoptic COS and test-only conditions were all fitted with the following Gaussian function (Allison et al. 2001)
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Suppression after contrast adaptation
After an initial 30 s of adaptation to an orthogonal mask stimulus, each test stimulus after the first was preceded by a 4-s "top-up" mask grating (Freeman et al. 2002; Movshon and Lennie 1979; Ohzawa et al. 1985). A 0% (no adaptation) and 30% adapting contrast were used for the mask stimulus, whereas the contrast of the test grating varies from 1% to 30% to obtain contrast response functions both with and without adaptation. Contrast tuning curves were fit by a modified hyperbolic ratio function (Freeman et al. 2002)
 | (2) |
; Heeger 1992). It has been reported that, for dichoptic COS, some cells are best characterized by response-gain control and others by contrast-gain control (Sengpiel et al. 1998). These two types of gain control have different effects on the contrast response function. To make sure that the contrast-gain control function (Eq. 2) can be used to measure the suppression index for dichoptic COS as well, we fit our data with both models and compared their goodness of fits (Fig. 4). Curves were fit by successively varying either Rmax (reflecting response-gain control) or C50 (corresponding to contrast-gain control) while holding the other variables constant at the values calculated from the unsuppressed condition. All data were well fit by the contrast-gain control model.
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RESULTS |
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Temporal frequency tuning of COS
We measured the temporal frequency tuning of monoptic and dichoptic COS for an overlapping subset of cells in our sample (n = 47/85 for monoptic and n = 67/85 for dichoptic). Data from an example cell are shown in Fig. 1A, where response amplitude is plotted as a function of the orthogonal mask temporal frequency. The triangles and squares represent responses under monoptic and dichoptic COS, respectively. For reference, the temporal frequency tuning of the cell's excitatory response (i.e., test only) is also plotted (
). The test grating was presented at the optimal temporal frequency, and the mean response of the test alone is shown by horizontal dotted line. It is evident for this cell that the peak high-frequency cut-off of dichoptic COS is at roughly the same value as that of the excitatory tuning. However, for monoptic COS, this cell is highly suppressed at all temporal frequencies, even at the highest tested temporal frequency of 25 Hz. The temporal frequency tuning of monoptic COS for this cell is consistent with previous reports (Freeman et al. 2002), which show that the suppression is robust at temporal frequencies higher than what will drive most area 17 cells. A summary scatter plot for all cells tested (Fig. 1B) shows clearly that the peak () and high temporal frequency cut-offs (
) for monoptic (vertical axis) are higher than those for dichoptic (horizontal axis) COS (Wilcoxon test, P < 0.01 for temporal frequency peaks and P < 0.00001 for high temporal frequency cut-offs respectively).
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) or subcortical (Freeman et al. 2002) source of the suppression. In the cat, both areas are selective to higher temporal frequencies than area 17 (Lehmkuhle et al. 1980; Movshon et al. 1978; Saul and Humphrey 1990). To determine which area exhibits tuning characteristics most similar to that of monoptic COS, we compared population distributions of temporal frequency tuning parameters for cells in our database of recordings from areas 17 and 18 and the LGN (Fig. 2). The distributions of peak frequencies and high-frequency cut-offs for monoptic COS (Fig. 2, A and B) are most similar to those of cells in the LGN (Fig. 2, I and J). Cells in area 18 (Fig. 2, G and H) tend to be tuned to frequencies only marginally higher than those in area 17 (Fig. 2, E and F). It is interesting to note that the temporal frequency tuning properties of dichoptic COS (Fig. 2, C and D) are significantly higher (P < 0.05) than those found in area 17 and similar to that of area 18, suggesting a possible role for area 18 in dichoptic COS.
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Another similarity that has been observed between monoptic COS and the LGN is the lack of susceptibility to contrast adaptation (Freeman et al. 2002). Prolonged visual stimulation attenuates the responses of cells in the cortex, but this aftereffect is weak in LGN cells (Ohzawa et al. 1982, 1985). It has recently been shown that long exposure to the orthogonal mask does not reduce monoptic COS (Freeman et al. 2002). This is consistent with a thalamocortical synaptic depression mechanism. If dichoptic COS originates from LGN cells and propagates to the visual cortex, we would expect to observe a similar adaptation effect for both modes of COS. Otherwise, if dichoptic COS depends on an intracortical suppressive mechanism, the suppression should be greatly reduced after prolonged adaptation to mask gratings. To investigate these possibilities, we compared the contrast adaptation susceptibility of monoptic and dichoptic COS.
The effects of adaptation on monoptic and dichoptic COS are shown in Fig. 3, A and B, for a representative cell. Response magnitude is plotted as a function of the test stimulus contrast for the test alone (), for the test and mask together with no adaptation (
), and for the test and mask after 30 s of adaptation to the mask (
). For this cell, the suppressive effects of COS on the contrast response curve are apparent for both monoptic (Fig. 3A) and dichoptic (Fig. 3B) conditions. As reported previously (Freeman et al. 2002), monoptic COS remains unchanged after adaptation to the mask (compare with in Fig. 3A). In contrast, dichoptic COS is almost completely eliminated after adaptation (Fig. 3B). Summary scatter plots comparing the magnitude of suppression with and without adaptation are shown in Fig. 3, C and D, for monoptic and dichoptic conditions. The suppression strength of the mask stimulus is represented by the suppression index (see METHODS), which is a measure of the increase in contast-gain control. The effect of prolonged adaptation by the mask stimulus on monoptic and dichoptic COS is reflected by changes in the suppression indices. Consistent with the example cell, adaptation has no affect on the magnitude of monoptic COS (Fig. 3C), but greatly reduces dichoptic COS (Fig. 3D). These data further support the thalamic and intracortical sources for monoptic and dichoptic COS, respectively.
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, 1991; Speed et al. 1991; Sengpiel et al. 1998). To quantify how well the effects are accounted for by contrast and response gain control models, we fit the contrast response curves of the test-only and test + mask conditions with hyperbolic ratio functions. The goodnesses of fit (R2) for the response and contrast gain control modes are plotted against each other in Fig. 4. Here it is apparent that for monoptic COS (), contrast gain control provides a better fit than response gain control. As with the example cell, dichoptic COS () is well fit by a response gain control model; however, contrast gain control seems to provide an equally good fit over the population of cells. |
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DISCUSSION |
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) for monoptic COS and suggest an intracortical inhibitory mechanism for dichoptic COS.
A long-standing model of contrast-gain control posits that monoptic COS is mediated by inhibitory connections within the visual cortex (Allison et al. 2001; Bonds 1989; Carandini and Heeger 1994; DeAngelis et al. 1992; Heeger 1992; Morrone et al. 1987; Sengpiel et al. 1998), resulting in the sharpness of functional properties (e.g., orientation selectivity) of cells in the visual cortex (Chapman and Stryker 1992; Vidyasagar et al. 1996). This widely held view has been challenged by Freeman et al. (2002) based on the temporal frequencies and adaptation properties of monoptic COS. Our results are consistent with their hypothesis that monoptic COS originates from a feedforward thalamocortical mechanism. This mechanism is an ideal substrate for monoptic COS because it can explain the main characteristics of COS, i.e., suppression is not tuned to orientation (Bonds 1989; DeAngelis et al. 1992; Morrone et al. 1982), is broadly tuned for spatial frequency (Bonds 1989; DeAngelis et al. 1992; Morrone et al. 1982), occurs at very high temporal frequencies (Allison et al. 2001; Freeman et al. 2002), and is immune to prolonged adaptation (Freeman et al. 2002). The transformation from LGN to cortical response properties is masked by a low-pass filtering of temporal frequency sensitivity (Hawken et al. 1996; Saul and Feidler 2002) and the emergence of contrast adaptation (Ohzawa et al. 1985). It is interesting to note that the mechanism underlying monoptic COS might actually be the cause of these changes. Since monoptic COS exhibits maximum suppression at high temporal frequencies, it could be involved in temporal low-pass filtering (Allison et al. 2001; Chance et al. 1998). Furthermore, synaptic depression has been suggested as the mechanism responsible for cortical contrast adaptation (Abbott et al. 1997; Chance et al. 1998). Therefore monoptic COS might not only have similar characteristics to LGN neurons, but its mechanism may be responsible for the differences in characteristics of cortical neurons.
Dichoptic COS is a form of binocular rivalry that is an important paradigm for the study of visual perception. Because dichoptic COS is likely to contribute to the perceptual experience of binocular rivalry (Blake 1989; Lehky 1988), it is important to understand its underlying mechanism. It has been reported that some LGN cells exhibit dichoptic COS (Funke and Eysel 1998; Moore et al. 1992; Sanderson et al. 1969; Varela and Singer 1987; Xue et al. 1987). Therefore it's possible that dichoptic COS originates in the LGN and propagates to the visual cortex. However, cells in the LGN respond to stimuli with very high temporal frequencies (Saul and Humphrey 1990) and are mostly immune to adaptation (Ohzawa et al. 1982, 1985). If dichoptic COS in area 17 was derived from cells in the LGN, we would have observed similar temporal frequency and adaptation properties for dichoptic COS and LGN cells. We have shown in Figs. 2 and 3 that dichoptic COS exhibits significantly different temporal frequency and adaptation properties than LGN cells. Therefore it is unlikely that LGN is the main source of dichoptic COS.
Results from previous studies of dichoptic COS (DeAngelis et al. 1992; Ferster 1981; Freeman et al. 1987; Sengpiel and Blakemore 1994; Sengpiel et al. 1995a) show fairly consistent but weak effects. The reason for the mixed results is probably due to the stimulus parameters used in their experiments. In this study, we found that the actual degree of dichoptic COS depends on the temporal frequency of the mask grating. On average, the suppressive effect of dichoptic COS was 38.7 ± 20.1% in area 17 at the temporal frequencies exhibiting maximum suppression for the mask gratings. This effect is greater than that reported in previous studies in which temporal frequency was not optimized (DeAngelis et al. 1992; Walker et al. 1998). Furthermore, we found that dichoptic COS is optimal at slightly higher temporal frequencies than those for neurons in area 17 (Fig. 2). The average cut-off and peak temporal frequency for dichoptic COS resembles cells in area 18 in our database and also results from other laboratories (Allison et al. 2001; Movshon et al. 1978). These results suggest a possible role for area 18 in the dichoptic COS. In fact, previous experiments reported that blockade of area 18 layers 2/3 or layer 5 resulted in increased or decreased responses in some area 17 cells (Alonso et al. 1993; Martinez-Conde et al. 1999; Mignard and Malpeli 1991). These observations suggest that feedback from area 18 can be excitatory and inhibitory to the cells in area 17. Although anatomical evidence suggests that inputs from area 18 are excitatory (Gilbert and Kelly 1975), it is possible that inhibitory modulation (e.g., dichoptic COS) from area 18 to area 17 exists through inhibitory interneurons. GABAergic inhibitory interneurons have been shown to play a major role in shaping functional properties (e.g., orientation selectivity) of visual cortical cells (Chapman and Stryker 1992; Vidyasagar et al. 1996) and are therefore a likely candidate for the source of dichoptic COS.
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GRANTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: R. D. Freeman, 360 Minor Hall, Univ. of California, Berkeley, CA 94720-2020 (E-mail: freeman{at}neurovision.berkeley.edu)
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REFERENCES |
|---|
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Allison JD, Smith KR, and Bonds AB. Temporal-frequency tuning of cross-orientation suppression in the cat striate cortex. Vis Neurosci 18: 941–948, 2001.[Web of Science][Medline]
Alonso JM, Cudeiro J, Perez R, Gonzalez F, and Acuna C. Orientational influences of layer V of visual area 18 upon cells in layer V of area 17 in the cat cortex. Exp Brain Res 96: 212–220, 1993.[Web of Science][Medline]
Andrews TJ and Purves D. Similarities in normal and binocularly rivalrous viewing. Proc Natl Acad Sci USA 94: 9905–9908, 1997.
Blake R. A neural theory of binocular rivalry. Psychol Rev 96: 145–167, 1989.[CrossRef][Web of Science][Medline]
Blake R and Logothetis NK. Visual competition. Nat Rev Neurosci 3: 13–21, 2002.[CrossRef][Web of Science][Medline]
Bonds AB. Role of inhibition in the specification of orientation selectivity of cells in the cat striate cortex. Vis Neurosci 2: 41–55, 1989.[Web of Science][Medline]
Carandini M and Ferster D. A tonic hyperpolarization underlying contrast adaptation in cat visual cortex. Science 276: 949–952, 1997.
Carandini M and Heeger DJ. Summation and division by neurons in primate visual cortex. Science 264: 1333–1336, 1994.
Chance FS, Nelson SB, and Abbott LF. Synaptic depression and the temporal response characteristics of V1 cells. J Neurosci 18: 4785–4799, 1998.
Chapman B and Stryker MP. Origin of orientation tuning in the visual cortex. Curr Opin Neurobiol 2: 498–501, 1992.[CrossRef][Medline]
DeAngelis GC, Robson JG, Ohzawa I, and Freeman RD. Organization of suppression in receptive fields of neurons in cat visual cortex. J Neurophysiol 68: 144–163, 1992.
Endo M, Kaas JH, Jain N, Smith EL III, and Chino Y. Binocular cross-orientation suppression in the primary visual cortex (V1) of infant rhesus monkeys. Invest Ophthalmol Vis Sci 41: 4022–4031, 2000.
Ferster D. A comparison of binocular depth mechanisms in areas 17 and 18 of the cat visual cortex. J Physiol 311: 623–655, 1981.
Freeman RD, Ohzawa I, and Robson JG. A comparison of monocular and binocular inhibitory processes in the visual cortex of the cat. J Physiol 396: 69P, 1987.
Freeman TC, Durand S, Kiper DC, and Carandini M. Suppression without inhibition in visual cortex. Neuron 35: 759–771, 2002.[CrossRef][Web of Science][Medline]
Funke K and Eysel UT. Inverse correlation of firing patterns of single topographically matched perigeniculate neurons and cat dorsal lateral geniculate relay cells. Vis Neurosci 15: 711–729, 1998.[CrossRef][Web of Science][Medline]
Gilbert CD and Kelly JP. The projections of cells in different layers of the cat's visual cortex. J Comp Neurol 163: 81–105, 1975.[CrossRef][Web of Science][Medline]
Green ES, DeAngelis GC, and Freeman RD. Development of inhibitory mechanisms in the kitten's visual cortex. Vis Neurosci 13: 1109–1117, 1996.[Web of Science][Medline]
Hawken MJ, Shapley RM, and Grosof DH. Temporal-frequency selectivity in monkey visual cortex. Vis Neurosci 13: 477–492, 1996.[Web of Science][Medline]
Hayhow WR. The cytoarchitecture of the lateral geniculate body in the cat in relation to the distribution of the crossed and uncrossed optic fibres. J Comp Neurol 110: 1–64, 1958.[CrossRef][Web of Science][Medline]
Hayhow WR. The lateral geniculate nucleus of the marsupial phalanger, Trichosurus vulpecula. An experimental study of cytoarchitecture in relation to the intranuclear optic nerve projection fields. J Comp Neurol 131: 571–604, 1967.[CrossRef][Web of Science][Medline]
Heeger DJ. Normalization of cell responses in cat striate cortex. Vis Neurosci 9: 181–197, 1992.[Web of Science][Medline]
Horsley V and Clarke RH. The structure and functions of the cerebellum examined by a new method. Brain 31: 45–124, 1908.
Hubel DH and Wiesel TN. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol 160: 106–154, 1962.
Lehky SR. An astable multivibrator model of binocular rivalry. Perception 17: 215–228, 1988.[Web of Science][Medline]
Lehmkuhle S, Kratz KE, Mangel SC, and Sherman SM. Spatial and temporal sensitivity of X- and Y-cells in dorsal lateral geniculate nucleus of the cat. J Neurophysiol 43: 520–541, 1980.
Li B, Peterson MR, Thompson JK, and Freeman RD. Different Mechanism for Monoptic and Dichoptic Cross-Orientation Suppression. 33rd Neuroscience Annual Conference, New Orleans, LA, Oct. 2003.
Martinez-Conde S, Cudeiro J, Grieve KL, Rodriguez R, Rivadulla C, and Acuna C. Effects of feedback projections from area 18 layers 2/3 to area 17 layers 2/3 in the cat visual cortex. J Neurophysiol 82: 2667–2675, 1999.
Mignard M and Malpeli JG. Paths of information flow through visual cortex. Science 251: 1249–1251, 1991.
Moore RJ, Spear PD, Kim CB, and Xue JT. Binocular processing in the cat's dorsal lateral geniculate nucleus. III. Spatial frequency, orientation, and direction sensitivity of nondominant-eye influences. Exp Brain Res 89: 588–598, 1992.[Web of Science][Medline]
Morrone MC and Burr DC. Evidence for the existence and development of visual inhibition in humans. Nature 321: 235–237, 1986.[CrossRef][Medline]
Morrone MC, Burr DC, and Maffei L. Functional implications of cross-orientation inhibition of cortical visual cells. Proc R Soc Lond B Biol Sci 216: 335–354, 1982.[Medline]
Morrone MC, Burr DC, and Speed HD. Cross-orientation inhibition in cat is GABA mediated. Exp Brain Res 67: 635–644, 1987.[Web of Science][Medline]
Morrone MC, Speed HD, and Burr DC. Development of inhibitory interactions in kittens. Vis Neurosci 7: 321–334, 1991.[Web of Science][Medline]
Movshon JA and Lennie P. Pattern-selective adaptation in visual cortical neurones. Nature 278: 850–852, 1979.[CrossRef][Medline]
Movshon JA, Thompson ID, and Tolhurst DJ. Spatial and temporal contrast sensitivity of neurones in areas 17 and 18 of the cat's visual cortex. J Physiol 283: 101–120, 1978.
Ohzawa I and Freeman RD. The binocular organization of complex cells in the cat's visual cortex. J Neurophysiol 56: 243–259, 1986a.
Ohzawa I and Freeman RD. The binocular organization of simple cells in the cat's visual cortex. J Neurophysiol 56: 221–242, 1986b.
Ohzawa I, Sclar G, and Freeman RD. Contrast gain control in the cat visual cortex. Nature 298: 266–268, 1982.[CrossRef][Medline]
Ohzawa I, Sclar G, and Freeman RD. Contrast gain control in the cat's visual system. J Neurophysiol 54: 651–667, 1985.
Sanderson KJ, Darian-Smith I, and Bishop PO. Binocular corresponding receptive fields of Single units in the cat dorsal lateral geniculate nucleus. Vision Res 9: 1297–1303, 1969.[CrossRef][Web of Science][Medline]
Saul AB and Feidler JC. Development of response timing and direction selectivity in cat visual thalamus and cortex. J Neurosci 22: 2945–2955, 2002.
Saul AB and Humphrey AL. Spatial and temporal response properties of lagged and nonlagged cells in cat lateral geniculate nucleus. J Neurophysiol 64: 206–224, 1990.
Sengpiel F, Baddeley RJ, Freeman TC, Harrad R, and Blakemore C. Different mechanisms underlie three inhibitory phenomena in cat area 17. Vision Res 38: 2067–2080, 1998.[CrossRef][Web of Science][Medline]
Sengpiel F and Blakemore C. Interocular control of neuronal responsiveness in cat visual cortex. Nature 368: 847–850, 1994.[CrossRef][Medline]
Sengpiel F, Blakemore C, and Harrad R. Interocular suppression in the primary visual cortex: a possible neural basis of binocular rivalry. Vision Res 35: 179–195, 1995a.[CrossRef][Web of Science][Medline]
Sengpiel F, Freeman TC, and Blakemore C. Interocular suppression in cat striate cortex is not orientation selective. Neuroreport 6: 2235–2239, 1995b.[Web of Science][Medline]
Sillito AM, Kemp JA, and Patel H. Inhibitory interactions contributing to the ocular dominance of monocularly dominated cells in the normal cat striate cortex. Exp Brain Res 41: 1–10, 1980.[Web of Science][Medline]
Speed HD, Morrone MC, and Burr DC. The effects of monocular deprivation on the development of visual inhibitory interactions in kittens. Vis Neurosci 7: 335–344, 1991.[Web of Science][Medline]
Varela FJ and Singer W. Neuronal dynamics in the visual corticothalamic pathway revealed through binocular rivalry. Exp Brain Res 66: 10–20, 1987.[Web of Science][Medline]
Vidyasagar TR, Pei X, and Volgushev M. Multiple mechanisms underlying the orientation selectivity of visual cortical neurones. Trends Neurosci 19: 272–277, 1996.[CrossRef][Web of Science][Medline]
Walker GA, Ohzawa I, and Freeman RD. Binocular cross-orientation suppression in the cat's striate cortex. J Neurophysiol 79: 227–239, 1998.
Xue JT, Ramoa AS, Carney T, and Freeman RD. Binocular interaction in the dorsal lateral geniculate nucleus of the cat. Exp Brain Res 68: 305–310, 1987.[Web of Science][Medline]
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ABSTRACT
INTRODUCTION
) and dichoptic (
) COS is plotted on top of the excitatory TF tuning curve (
