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The discrepancy between monocular and binocular measures of preferred orientation, as a function of disparity selectivity. The pre- ferred orientation is measured separately for the two eyes, so for all of those cells that are tuned for orientation in both eyes ( n ϭ 39), there are two points on the plot. The difference for the dominant eye is indicated by a circle , and the symbol for the difference of the nondominant eye is a square . In those cases where only one of the eyes is tuned for orientation ( n ϭ 16), a single point appears on the plot, also indicated by a circle . The discrepancy between the preferred orientation measured monocularly and binocularly is signi fi cantly correlated with the disparity discrimina- tion index ( r ϭ 0.32; p Ͻ 0.05).
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Interocular differences in orientation occur during binocular viewing of a surface slanted in depth. These orientation disparities could be exploited by the visual system to provide information about surface slant, but gradients of positional disparity provide an equally effective means to the same end. We examined the encoding of orientation dispa...
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Context 1
... does not represent a consistent response to orientation disparities. This is highlighted in Figure 7 B , which shows two cross sections through the two-dimensional surface plot in A and the fi t to this surface using Equation 4. It is obvious that the maximum re- sponse depends on the monocular orientation tuning, not the orientation disparity. The maximum response occurs when the right eye receives 80 ° regardless of whether the left eye stimulus is at 90 ° , where it represents an orientation disparity of Ϫ 10 ° , or 30 ° , an orientation disparity of ϩ 50 ° . In addition to the cells described above, there is a further population that does appear to respond consistently to the same orientation disparity, regardless of the absolute orientation of the left and right stimuli; these responses were left – right inseparable. An example of such a cell is shown in Figure 8 A . In this example, the maximum response occurs when both eyes receive the same orientation; it appears to be selective for an orientation disparity of zero. This pattern of response is left – right inseparable, and the fi t to these data (Fig. 8 B ) is achieved by adding a rotation term to Equation 4. The rotated Gaussian yields a signi fi cantly better fi t ( F test, p Ͻ 0.05) than the left – right separable Gaussian. The neuron response in Figure 8 C was also better fi t ( C ) with a rotated Gaussian, and the preferred IDPO is ϳ 30 ° . A total of 20 neurons showed left – right inseparable response pro fi les, which fell into two groups. One group (10 neurons) were fi t with the inseparable Gaussian model (Eq. 5, the rotated form of the separable re- sponse pro fi le). These tended to respond maximally for orienta- tion disparities near zero, as illustrated in Figure 8 A . The second group of 10 cells tended to show a consistent response minimum for orientation disparities of 0 ° , with two peaks either side, like the example in Figure 8 E . Such response pro fi les cannot be well described by the rotated Gaussian of Equation 5 (this model accounted for Ͻ 75% of the response variance), and so Equation 8 was used, which provided a much better fi t. This fi t accounted for a substantially greater fraction of the response variance than the inseparable model or the separable model described by Equa- tion 5. To summarize, of the 64 neurons that could be well fi t with one of the two surfaces, 44 showed the left – right separable response shown in Figure 6, and 20 were left – right inseparable. These left – right inseparable responses all indicate a tendency to respond consistently to a certain orientation disparity, regardless of the orientation of the stimulus in either eye alone. This suggests a specialization for signaling orientation disparities. However, sev- eral observations indicate that there may be an alternative expla- nation. If neurons are selective for orientation disparity, one would expect that the preferred orientation disparity measured with binocular stimuli would be similar to the difference in RF orientation determined from monocular measures. Figure 9 shows that this is not the case. The monocular measure was calculated from the difference in the peaks of the Gaussians fi tted to monocular tuning curves. The binocular measure is simply the orientation disparity of the peak in the fi tted response pro fi le. These two measures were not signi fi cantly correlated ( r ϭ 0.26; p Ͼ 0.05; n ϭ 45). One factor that could produce discrepancies between monocular and binocular measures is disparity tuning. This may in fl uence the shape of the binocular interaction, without affecting preferred orientation measured monocularly. Figure 10 therefore plots the magnitude of the discrepancy against the extent of disparity tuning. It is clear that the largest discrepancies occur in disparity selective neurons. To quantify this, we measured the variance of the absolute value of the discrepancy between monocular and binocular IDPO. This was calculated separately for the group of disparity selective neurons (determined by one-way ANOVA; p Ͻ 0.05) and for disparity unselective neurons. This variance was signi fi cantly larger for the disparity-selective neurons ( F test; p Ͻ 0.05). This analysis is only possible in neurons that showed signi fi cant orientation tuning in both eyes. A similar analysis can be ex- tended to the whole population by comparing monocular and binocular measures of the preferred stimulus orientation for each eye. The binocular measure is taken from the left and right orientations at the point of maximum binocular response, and the monocular measures are taken from the peaks of the Gaussian fi t to the monocular tuning data. The relationship is examined in Figure 11, in which again it is clear that the largest discrepancies are associated with disparity selectivity. The correlation between the disparity discrimination index and the discrepancy in mea- sures of preferred orientation is signi fi cant ( r ϭ 0.32; p Ͻ 0.05). Figure 11 also shows that the neurons exhibiting inseparable interactions between left and right stimulus orientations ( fi lled symbols ) tend to show large discrepancies. The mean discrepancy between the monocular and binocular measures of preferred orientation is 4.8 ° in neurons that showed separable interactions and 15.6 ° in those that showed inseparable interactions. It is also clear from Figures 10 and 11 that neurons exhibiting left – right inseparable responses tend to show disparity selectivity (signi fi cant at the 5% level on a one-way ANOVA for 15 of 17 cases). In contrast, only 22 of the 40 cells that show a left – right separable response to binocular orientation disparities are dis- parity tuned. Together, Figures 9 – 11 strongly suggest that left – right inseparable responses like those illustrated in Figure 8 are in some way a result of tuning for positional disparity. In a few neurons, we explored this further by measuring binocular re- sponses to orientation disparities with different positional dispar- ities. Figure 12 shows one example in which two complete binoc- ular interaction pro fi les were measured. Changing the stimulus disparity had a dramatic effect on the responses to orientation disparities, inverting the interaction pro fi le. When the stimulus is at the preferred disparity of the neuron ( Ϫ 0.38 ° ), the optimal orientation disparity is 0 ° . When the stimulus is at the positional disparity to which the neuron responds least (0 ° , the null dispar- ity), the preferred orientation disparity is neither at 0 ° nor is it predicted by the monocularly measured IDPO. Instead, stimuli with zero orientation disparity produce a minimum in the response. The phenomenon illustrated in Figure 12 appears to be general in disparity-tuned neurons. In all cases in which there was an inseparable response that was selective for zero orientation dis- parity (seven neurons), the stimulus disparity turned out to be near to the preferred disparity of the neurons. In all cases in which there was a response minimum near 0 ° orientation dispar- ity, the disparity was near the null disparity of the neurons. We quanti fi ed this effect by calculating a simple index of how close a stimulus disparity ( d stim ) fell to the preferred disparity ( d pref ) as a proportion of the distance between preferred and null ( d null ) disparities. This index, ( disparity stim Ϫ disparity pref )/( disparity pref Ϫ disparity null , had a strong negative correlation with the magnitude of preferred orientation disparity determined from our fi ts ( r ϭ Ϫ 0.91; p Ͻ Ͻ 0.01). This correlation between preferred positional disparity and preferred orientation disparity suggests that the positional dis- parity tuning determines the orientation disparity to which each neuron appears selective. All of these observations (binocular IDPO is poorly correlated with monocular IDPO; the discrepancies are largest in disparity- tuned neurons; and the preferred orientation disparity seems to depend on the positional disparity of the stimulus) suggest strongly that the left – right inseparable response comes about because of the positional disparity sensitivity of the neurons. One possible reason for this type of response is illustrated in Figure 13, which shows the consequences of applying an orientation disparity around a center of rotation that is not centered in the RF. The boxes represent vertically oriented receptive fi elds, the dotted line is the stimulus to the left eye, and the solid line is the stimulus to the right eye. For illustrative purposes, lines are used rather than sine-wave gratings, and the orientation disparity is produced by rotating the stimulus shown to the right eye only. On the left panel of Figure 13, the rotation occurs about the center of the receptive fi eld. However, on the right , the rotation is about a point at the bottom of the receptive fi eld. This is equivalent to the on-center rotation plus a translation. Because this translation is only applied to one eye, it constitutes a change in horizontal disparity. The magnitude of the horizontal disparity (illustrated by the arrow ) will increase as the angle of stimulus rotation increases. Thus, off-center rotation leads to a complex interaction between binocular phase and binocular orientation differences. To evaluate the effects of this interaction on our binocular measures of IDPO, we ran a simulation using the energy model of Ohzawa et al. (1990) (H. Bridge, B. G. Cumming, and A. J. Parker, unpublished observations). Our implementation ex- tended the model to two-dimensional monocular receptive fi elds, so that the effects of both orientation differences and positional differences could be assessed. The results of this simulation are shown in Figure 14, in which two important features emerge. First, the combination of off-center rotation and disparity selec- tivity is suf fi cient to produce a response pattern that is left – right inseparable, in a ...
Context 2
... ” pattern of responses (Poggio and Fischer, 1977) to posi- tional disparity (like that illustrated in Fig. 4 B ). Both of these patterns can be well fi t by Equation 4. The fi t to Figure 6 A is shown in B . This common type of response that is left – right separable does not represent a consistent response to orientation disparities. This is highlighted in Figure 7 B , which shows two cross sections through the two-dimensional surface plot in A and the fi t to this surface using Equation 4. It is obvious that the maximum re- sponse depends on the monocular orientation tuning, not the orientation disparity. The maximum response occurs when the right eye receives 80 ° regardless of whether the left eye stimulus is at 90 ° , where it represents an orientation disparity of Ϫ 10 ° , or 30 ° , an orientation disparity of ϩ 50 ° . In addition to the cells described above, there is a further population that does appear to respond consistently to the same orientation disparity, regardless of the absolute orientation of the left and right stimuli; these responses were left – right inseparable. An example of such a cell is shown in Figure 8 A . In this example, the maximum response occurs when both eyes receive the same orientation; it appears to be selective for an orientation disparity of zero. This pattern of response is left – right inseparable, and the fi t to these data (Fig. 8 B ) is achieved by adding a rotation term to Equation 4. The rotated Gaussian yields a signi fi cantly better fi t ( F test, p Ͻ 0.05) than the left – right separable Gaussian. The neuron response in Figure 8 C was also better fi t ( C ) with a rotated Gaussian, and the preferred IDPO is ϳ 30 ° . A total of 20 neurons showed left – right inseparable response pro fi les, which fell into two groups. One group (10 neurons) were fi t with the inseparable Gaussian model (Eq. 5, the rotated form of the separable re- sponse pro fi le). These tended to respond maximally for orienta- tion disparities near zero, as illustrated in Figure 8 A . The second group of 10 cells tended to show a consistent response minimum for orientation disparities of 0 ° , with two peaks either side, like the example in Figure 8 E . Such response pro fi les cannot be well described by the rotated Gaussian of Equation 5 (this model accounted for Ͻ 75% of the response variance), and so Equation 8 was used, which provided a much better fi t. This fi t accounted for a substantially greater fraction of the response variance than the inseparable model or the separable model described by Equa- tion 5. To summarize, of the 64 neurons that could be well fi t with one of the two surfaces, 44 showed the left – right separable response shown in Figure 6, and 20 were left – right inseparable. These left – right inseparable responses all indicate a tendency to respond consistently to a certain orientation disparity, regardless of the orientation of the stimulus in either eye alone. This suggests a specialization for signaling orientation disparities. However, sev- eral observations indicate that there may be an alternative expla- nation. If neurons are selective for orientation disparity, one would expect that the preferred orientation disparity measured with binocular stimuli would be similar to the difference in RF orientation determined from monocular measures. Figure 9 shows that this is not the case. The monocular measure was calculated from the difference in the peaks of the Gaussians fi tted to monocular tuning curves. The binocular measure is simply the orientation disparity of the peak in the fi tted response pro fi le. These two measures were not signi fi cantly correlated ( r ϭ 0.26; p Ͼ 0.05; n ϭ 45). One factor that could produce discrepancies between monocular and binocular measures is disparity tuning. This may in fl uence the shape of the binocular interaction, without affecting preferred orientation measured monocularly. Figure 10 therefore plots the magnitude of the discrepancy against the extent of disparity tuning. It is clear that the largest discrepancies occur in disparity selective neurons. To quantify this, we measured the variance of the absolute value of the discrepancy between monocular and binocular IDPO. This was calculated separately for the group of disparity selective neurons (determined by one-way ANOVA; p Ͻ 0.05) and for disparity unselective neurons. This variance was signi fi cantly larger for the disparity-selective neurons ( F test; p Ͻ 0.05). This analysis is only possible in neurons that showed signi fi cant orientation tuning in both eyes. A similar analysis can be ex- tended to the whole population by comparing monocular and binocular measures of the preferred stimulus orientation for each eye. The binocular measure is taken from the left and right orientations at the point of maximum binocular response, and the monocular measures are taken from the peaks of the Gaussian fi t to the monocular tuning data. The relationship is examined in Figure 11, in which again it is clear that the largest discrepancies are associated with disparity selectivity. The correlation between the disparity discrimination index and the discrepancy in mea- sures of preferred orientation is signi fi cant ( r ϭ 0.32; p Ͻ 0.05). Figure 11 also shows that the neurons exhibiting inseparable interactions between left and right stimulus orientations ( fi lled symbols ) tend to show large discrepancies. The mean discrepancy between the monocular and binocular measures of preferred orientation is 4.8 ° in neurons that showed separable interactions and 15.6 ° in those that showed inseparable interactions. It is also clear from Figures 10 and 11 that neurons exhibiting left – right inseparable responses tend to show disparity selectivity (signi fi cant at the 5% level on a one-way ANOVA for 15 of 17 cases). In contrast, only 22 of the 40 cells that show a left – right separable response to binocular orientation disparities are dis- parity tuned. Together, Figures 9 – 11 strongly suggest that left – right inseparable responses like those illustrated in Figure 8 are in some way a result of tuning for positional disparity. In a few neurons, we explored this further by measuring binocular re- sponses to orientation disparities with different positional dispar- ities. Figure 12 shows one example in which two complete binoc- ular interaction pro fi les were measured. Changing the stimulus disparity had a dramatic effect on the responses to orientation disparities, inverting the interaction pro fi le. When the stimulus is at the preferred disparity of the neuron ( Ϫ 0.38 ° ), the optimal orientation disparity is 0 ° . When the stimulus is at the positional disparity to which the neuron responds least (0 ° , the null dispar- ity), the preferred orientation disparity is neither at 0 ° nor is it predicted by the monocularly measured IDPO. Instead, stimuli with zero orientation disparity produce a minimum in the response. The phenomenon illustrated in Figure 12 appears to be general in disparity-tuned neurons. In all cases in which there was an inseparable response that was selective for zero orientation dis- parity (seven neurons), the stimulus disparity turned out to be near to the preferred disparity of the neurons. In all cases in which there was a response minimum near 0 ° orientation dispar- ity, the disparity was near the null disparity of the neurons. We quanti fi ed this effect by calculating a simple index of how close a stimulus disparity ( d stim ) fell to the preferred disparity ( d pref ) as a proportion of the distance between preferred and null ( d null ) disparities. This index, ( disparity stim Ϫ disparity pref )/( disparity pref Ϫ disparity null , had a strong negative correlation with the magnitude of preferred orientation disparity determined from our fi ts ( r ϭ Ϫ 0.91; p Ͻ Ͻ 0.01). This correlation between preferred positional disparity and preferred orientation disparity suggests that the positional dis- parity tuning determines the orientation disparity to which each neuron appears selective. All of these observations (binocular IDPO is poorly correlated with monocular IDPO; the discrepancies are largest in disparity- tuned neurons; and the preferred orientation disparity seems to depend on the positional disparity of the stimulus) suggest strongly that the left – right inseparable response comes about because of the positional disparity sensitivity of the neurons. One possible reason for this type of response is illustrated in Figure 13, which shows the consequences of applying an orientation disparity around a center of rotation that is not centered in the RF. The boxes represent vertically oriented receptive fi elds, the dotted line is the stimulus to the left eye, and the solid line is the stimulus to the right eye. For illustrative purposes, lines are used rather than sine-wave gratings, and the orientation disparity is produced by rotating the stimulus shown to the right eye only. On the left panel of Figure 13, the rotation occurs about the center of the receptive fi eld. However, on the right , the rotation is about a point at the bottom of the receptive fi eld. This is equivalent to the on-center rotation plus a translation. Because this translation is only applied to one eye, it constitutes a change in horizontal disparity. The magnitude of the horizontal disparity (illustrated by the arrow ) will increase as the angle of stimulus rotation increases. Thus, off-center rotation leads to a complex interaction between binocular phase and binocular orientation differences. To evaluate the effects of this interaction on our binocular measures of IDPO, we ran a simulation using the energy model of Ohzawa et al. (1990) (H. Bridge, B. G. Cumming, and A. J. Parker, unpublished observations). Our implementation ex- tended the model to two-dimensional monocular receptive fi elds, so that the effects of both orientation differences and positional differences ...
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... However, simultaneous and successive depth contrast may involve different mechanisms, as might also be the case for planar versus modulated stereo-depth surfaces. Stereo-slanted planar surfaces are believed to be processed by channels sensitive to disparity gradients (i.e., the first derivative of disparity) (Bridge & Cumming, 2001;Gillam, Flagg, & Finlay, 1984;Nguyenkim & DeAngelis, 2003;Orban, Janssen, & Vogels, 2006;Parker, 2007;Rogers et al., 1988;Wardle & Gillam, 2016), whereas stereo-modulated surfaces are likely processed by channels sensitive to the second derivative of disparity (Howard & Rogers, 2002). Second-derivative channels are presumably underpinned by neurons whose receptive fields are matched in size to the scale or spatial frequency of the disparity modulation. ...
The perceived slant of a stereoscopic surface is altered by the presence of a surrounding surface, a phenomenon termed stereo slant contrast. Previous studies have shown that a slanted surround causes a fronto-parallel surface to appear slanted in the opposite direction, an instance of "bidirectional" contrast. A few studies have examined slant contrast using slanted as opposed to fronto-parallel test surfaces, and these also have shown slant contrast. Here, we use a matching method to examine slant contrast over a wide range of combinations of surround and test slants, one aim being to determine whether stereo slant contrast transfers across opposite directions of test and surround slant. We also examine the effect of the test on the perceived slant of the surround. Test slant contrast was found to be bidirectional in virtually all test-surround combinations and transferred across opposite test and surround slants, with little or no decline in magnitude as the test-surround slant difference approached the limit. There was a weak bidirectional effect of the test slant on the perceived slant of the surround. We consider how our results might be explained by four mechanisms: (a) normalization of stereo slant to vertical; (b) divisive normalization of stereo slant channels in a manner analogous to the tilt illusion; (c) interactions between center and surround disparity-gradient detectors; and (d) uncertainty in slant estimation. We conclude that the third of these (interactions between center and surround disparity-gradient detectors) is the most likely cause of stereo slant contrast.
... In addition to binocular integration, another major transformation takes place when visual information reaches the cortex, where V1 neurons become selective for stimulus features such as orientation (Hubel and Wiesel, 1962). It has been shown in many species that binocular V1 neurons show similar orientation preference through the two eyes (Hubel and Wiesel, 1962;Nelson et al., 1977;Ferster, 1981;Bridge and Cumming, 2001;Wang et al., 2010; Figure 1B, middle panel), a feature presumably important for binocular integration. Finally, "disparitytuned" neurons are first seen along the visual pathway in V1. ...
The brain creates a single visual percept of the world with inputs from two eyes. This means that downstream structures must integrate information from the two eyes coherently. Not only does the brain meet this challenge effortlessly, it also uses small differences between the two eyes’ inputs, i.e., binocular disparity, to construct depth information in a perceptual process called stereopsis. Recent studies have advanced our understanding of the neural circuits underlying stereoscopic vision and its development. Here, we review these advances in the context of three binocular properties that have been most commonly studied for visual cortical neurons: ocular dominance of response magnitude, interocular matching of orientation preference, and response selectivity for binocular disparity. By focusing mostly on mouse studies, as well as recent studies using ferrets and tree shrews, we highlight unresolved controversies and significant knowledge gaps regarding the neural circuits underlying binocular vision. We note that in most ocular dominance studies, only monocular stimulations are used, which could lead to a mischaracterization of binocularity. On the other hand, much remains unknown regarding the circuit basis of interocular matching and disparity selectivity and its development. We conclude by outlining opportunities for future studies on the neural circuits and functional development of binocular integration in the early visual system.
... Nevertheless, orientationally-selective cells provide the input for stereo so, at a minimum, both positional disparity and orientation -one orientation for the right eye and (possibly) another for the left -should be involved. While it is traditional to assume only "like" orientations are matched [40,60,13,16,66], our sensitivity to orientation disparity questions this, making orientation disparity another putative variable. We shall show that orientations do play a deep role in stereo, but that it is not necessarily efficent to represent them as a disparity. ...
... Proposition 3.1. The binocular interaction term can be associated with the cross product of the left and right directions defined through (13), namely ω L and ω R of monocular simple cells: ...
... Proposition B.1. The binocular interaction term O L O R can be associated with the cross product of the left and right directions defined through (13), namely ω p L and ω p R of monocular simple cells: ...
Classical good continuation for image curves is based on $2D$ position and orientation. It is supported by the columnar organization of cortex, by psychophysical experiments, and by rich models of (differential) geometry. Here we extend good continuation to stereo. We introduce a neurogeometric model, in which the parametrizations involve both spatial and orientation disparities. Our model provides insight into the neurobiology, suggesting an implicit organization for neural interactions and a well-defined $3D$ association field. Our model sheds light on the computations underlying the correspondence problem, and illustrates how good continuation in the world generalizes good continuation in the plane.
... Nevertheless, orientationally-selective cells provide the input for stereo so, at a minimum, both positional disparity and orientation -one orientation for the right eye and (possibly) another for the left -should be involved. While it is traditional to assume only "like" orientations are matched [40,60,13,16,66], our sensitivity to orientation disparity questions this, making orientation disparity another putative variable. We shall show that orientations do play a deep role in stereo, but that it is not necessarily efficent to represent them as a disparity. ...
... Proposition 3.1. The binocular interaction term can be associated with the cross product of the left and right directions defined through (13), namely ω L and ω R of monocular simple cells: ...
... Proposition B.1. The binocular interaction term O L O R can be associated with the cross product of the left and right directions defined through (13), namely ω p L and ω p R of monocular simple cells: ...
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... Our goal is to examine how monocular and binocular synaptic networks contribute to interocular response alignment in binocular cells. However, our dataset includes binocular cells with poor alignment, similar to previous reports in visually experienced animals (Bridge and Cumming, 2001;Chang et al., 2020). Thus, we focus exclusively on binocular cells with congruent (r C-I > 0.5) somatic orientation tuning between the two eyes (n = 16/28) and their synapses (n = 2,933, binocular spines n = 1,920, median congruency = 0.5) for the remainder of this study. ...
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In visual cortex, signals from the two eyes merge to form a coherent binocular representation. Here we investigate the synaptic interactions underlying the binocular representation of stimulus orientation in ferret visual cortex with in vivo calcium imaging of layer 2/3 neurons and their dendritic spines. Individual neurons with aligned somatic responses received a mixture of monocular and binocular synaptic inputs. Surprisingly, monocular pathways alone could not account for somatic alignment because ipsilateral monocular inputs poorly matched somatic preference. Binocular inputs exhibited different degrees of interocular alignment, and those with a high degree of alignment (congruent) had greater selectivity and somatic specificity. While congruent inputs were similar to others in measures of strength, simulations show that the number of active congruent inputs predicts aligned somatic output. Our study suggests that coherent binocular responses derive from connectivity biases that support functional amplification of aligned signals within a heterogeneous binocular intracortical network.
... During early postnatal development, the binocular neurons in primary visual cortex (V1) undergo a profound maturation process called binocular integration (Hubel and Wiesel, 1962). Binocular matching of orientation preference, one representative form of binocular integration, has been found in multiple species from rodents to primates, including humans (Bridge and Cumming, 2001;Gu and Cang, 2016). The current study elaborated that short-term critical period prolonging could transiently prevent binocular matching, which is accompanied by changes in neuronal synaptic structural properties. ...
Binocular matching of orientation preference between the two eyes is a common form of binocular integration that is regarded as the basis for stereopsis. How critical period plasticity enables binocular matching under the guidance of normal visual experience has not been fully demonstrated. To investigate how critical period closure affects the binocular matching, a critical period prolonged mouse model was constructed through the administration of bumetanide, an NKCC1 transporter antagonist. Using acute in vivo extracellular recording and molecular assay, we revealed that binocular matching was transiently disrupted due to heightened plasticity after the normal critical period, together with an increase in the density of spines and synapses, and the upregulation of GluA1 expression. Diazepam (DZ)/[(R, S)-3-(2-carboxypiperazin-4-yl) propyl-1-phosphonic acid (CPP)] could reclose the extended critical period, and rescue the deficits in binocular matching. Furthermore, the extended critical period, alone, with normal visual experience is sufficient for the completion of binocular matching in amblyopic mice. Similarly, prolonging the critical period into adulthood by knocking out Nogo-66 receptor can prevent the normal maturation of binocular matching and depth perception. These results suggest that maintaining an optimal plasticity level during adolescence is most beneficial for the systemic maturation. Extending the critical period provides new clues for the maturation of binocular vision and may have critical implications for the treatment of amblyopia.
... In carnivores and primates, binocular convergence first occurs in the primary visual cortex (V1) where individual cortical neurons respond selectively to sensory stimulation of one or both eyes Wiesel, 1962, 1965;Ohzawa and Freeman, 1986a;Priebe, 2008). Cortical neurons are also selective for edge orientation (Hubel and Wiesel, 1962;Priebe and Ferster, 2012), and in all mammals investigated, most binocular neurons exhibit matched orientation preferences for stimuli viewed through each eye (Bridge and Cumming, 2001;Chang et al., 2020;Ferster, 1981;Hubel and Wiesel, 1962;Nelson et al., 1977;Skottun and Freeman, 1984;Wang et al., 2010). While interocular alignment of response properties is considered to be a prerequisite for binocular vision (Marr and Poggio, 1979), the synaptic basis of this phenomenon is poorly understood. ...
... Our goal is to examine how monocular and binocular synaptic networks contribute to interocular response alignment in binocular cells. However, our dataset includes binocular cells with poor alignment, similar to previous reports in visually-mature animals (Bridge and Cumming, 2001;Chang et al., 2020). Thus, we focus exclusively on binocular cells with congruent (r C-I > 0.5) somatic orientation tuning between the two eyes (n = 16/28) and their synapses (n = 2933, binocular spines n = 1920, median congruency = 0.5) for the remainder of this study. ...
... However, a number of studies of V1 neurons report fairly large interocular orientation preference differences (which is directly related to congruency) (Blakemore et al., 1972) from a sizeable fraction of cells. Given that an orientation preference difference of ~20 degree corresponds to our congruency cut-off (r c-l = 0.5), about 25-30% of neurons in visually-mature ferrets (Chang et al., 2020) and ~10% of neurons in adult primates (Bridge and Cumming, 2001) are classified as noncongruent. This suggests that noncongruent populations reflect more than a mere measurement error. ...
In the visual system, signals from the two eyes are combined to form a coherent representation through the convergence of synaptic input populations onto individual cortical neurons. As individual synapses originate from either monocular (representing one eye) or binocular (representing both eyes) cortical networks, it has been unclear how these inputs are integrated coherently. Here, we imaged dendritic spines on layer 2/3 binocular cells in ferret visual cortex with in vivo two-photon microscopy to examine how monocular and binocular synaptic networks contribute to the interocular alignment of orientation tuning. We found that binocular synapses varied in degree of "congruency", namely response correlation between left and right eye visual stimulation. Binocular congruent inputs were functionally distinct from binocular noncongruent and monocular inputs, exhibiting greater tuning selectivity and connection specificity. Using correlative light and electron microscopy, we found no difference in ultrastructural anatomy and instead, observed strength in numbers using a simple model simulating aggregate synaptic input. This model demonstrated a predominate contribution of binocular congruent inputs in sculpting somatic orientation preference and interocular response alignment. Our study suggests that, in layer 2/3 cortical neurons, a binocular network is responsible for forming a coherent representation in individual neurons through recurrent intracortical interactions.
... A critical function of neural circuits that represent sensory stimuli is the integration of information from different sources to build coherent representations of the external world (Duhamel et al., 1998;King and Hutchings, 1987;Knudsen and Brainard, 1991;Wallace and Stein, 1997). The binocular representation of orientation in visual cortex provides an excellent example of this integrative process, with segregated inputs from the two eyes coming together to yield a unified binocular representation, so that visual stimuli presented to either eye yield similar population responses (Bridge and Cumming, 2001;Sarnaik et al., 2014;Crair et al., 1998;Wang et al., 2010). ...
Across sensory areas, neural microcircuits consolidate streams of information into unified representations of the external world. In the carnivore visual cortex, where eye-specific inputs first converge, it has been posited that a single, binocularly aligned modular orientation representation develops independent of sensory experience. In this study of ferret visual cortex using in vivo calcium imaging, we find evidence for a different developmental process. Early in development, contralateral, ipsilateral, or binocular stimulation each yield well-organized modular representations of orientation that display features of mature cortex. However, comparison of these representations reveals considerable misalignment that is evident at both modular and cellular scales. Experience-dependent processes drive reorganization of these three representations toward a single binocularly aligned representation resembling the early binocular representation through shifts in cellular orientation preference. Thus, while orderly modular networks of orientation preference initially arise independent of visual experience, experience is critical for the alignment of these early representations.
... To achieve this, neural circuits combine information from different sensory sources to generate unified unisensory or multisensory representations (Duhamel et al., 1998;King and Hutchings, 1987;Knudsen and Brainard, 1991;Wallace and Stein, 1997). The binocular and monocular representations of stimulus orientation in visual cortex provide an excellent example of this integrative process (Bridge and Cumming, 2001;Crair et al., 1998;Wang et al., 2010). Segregated inputs from the two eyes first come together in the visual cortex to yield a unified binocular representation of stimulus orientation, such that visual stimuli presented to either eye yield similar orientation selective responses (Bridge and Cumming, 2001;Sarnaik et al., 2014). ...
... The binocular and monocular representations of stimulus orientation in visual cortex provide an excellent example of this integrative process (Bridge and Cumming, 2001;Crair et al., 1998;Wang et al., 2010). Segregated inputs from the two eyes first come together in the visual cortex to yield a unified binocular representation of stimulus orientation, such that visual stimuli presented to either eye yield similar orientation selective responses (Bridge and Cumming, 2001;Sarnaik et al., 2014). ...
Across sensory areas, neural microcircuits consolidate diverse streams of sensory information into unified, representations of the external world, but the developmental process underlying alignment of sensory representations remains poorly understood. Using two-photon and widefield epifluorescence calcium imaging in developing ferret visual cortex, we find an early developmental period in which monocular stimulation reveals two divergent representations of orientation at the network and cellular-scales. During the period of monocular network misalignment, binocular stimulation drives a third orientation representation, distinct from the constituent monocular representations. Alignment towards a single, binocularly unified representation requires binocular visual experience shortly after eye-opening. Chronic imaging demonstrates that the monocular and binocular orientation representations functionally reorganize towards a single representation resembling the early binocular representation through concerted shifts in preferred orientation across the cellular-scale and network-scale representations. Thus, we propose that an experience-dependent learning process drives the emergence of a unified binocular representation of orientation.
