Cerebral Cortex Advance Access originally published online on May 10, 2007
Cerebral Cortex 2008 18(2):331-336; doi:10.1093/cercor/bhm057
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Contrast-Dependent and Contrast-Independent Spatial Summation of Primary Visual Cortical Neurons of the Cat
1 Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, 2 Graduate School of the Chinese Academy of Sciences, Beijing 100037, China
Address correspondence to Chao-Yi Li, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. Email: cyli{at}sibs.ac.cn.
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Recent studies have reported that the size of the classical receptive field (CRF) and the extent of spatial summation of V1 neurons depend on stimulus contrast. We reexamined these properties for 48 V1 neurons in the cat and found that all the cells had a constant CRF size, whereas their spatial summation properties can be contrast dependent (CD) or contrast independent (CID). Of the 29 CD cells, 17 showed facilitatory summation at low contrast (10%), but suppressive summation at high contrast (80%); the other 12 showed weak suppressive summation at low contrast, whereas the strength of suppression increased significantly at high contrast. The 19 CID cells showed similar facilitative (CIDf) or suppressive (CIDs) summation at low and high contrast, without changes in shape and/or peak location. We successfully labeled 11 CD cells and 10 CID cells with biocytin. The morphological results demonstrated that all the labeled CD cells were pyramidal cells, whereas all labeled CID cells were nonpyramidal cells, in which the CIDf cells were spiny stellates and the CIDs cells, smooth interneurons. There is thus a global distinction between summation properties of pyramidal and nonpyramidal cells, and between the smooth and spiny nonpyramidal cells as well.
Key Words: classical receptive field • dynamic property • extra-receptive field • facilitation • inhibition • pyramidal neuron
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Many studies have indicated that regions beyond the classical receptive field (CRF) of primary visual cortical (V1) neurons, although alone unresponsive to visual stimuli, could modulate the cell's response (Hammond and MacKay 1981
; Allman et al. 1985; Gulyas et al. 1987; DeAngelis et al. 1994; Hammond and Kim 1994; Li and Li 1994; Sillito et al. 1995; Sengpiel et al. 1997). This modulatory effect can be facilitatory or inhibitory, and its extent can be assessed from area summation characteristics (Li and Li 1994). This surrounding field is referred to as the extra-receptive field (ERF) or non-CRF. There has been increasing interest in interactions between CRF and ERF, because they may form the neural basis for a variety of psychophysical phenomena, such as contour integration (von der Heydt and Peterhans 1989; Field et al. 1993; Kapadia et al. 1995; Xu et al. 2005), contextual effects (Levitt and Lund 1997; Li et al. 1999), and figure-ground segregation (Lamme 1995). Previous investigators considered the size of the CRF and the extent of ERF to be fixed (Li and Li 1994; DeAngelis et al. 1995), whereas some recent studies have reported that the extent of spatial summation in V1 neurons depends on stimulus contrast and is, on average, 2–3 times greater at low contrast (Levitt and Lund 1997; Kapadia et al. 1999; Sceniak et al. 1999; Fitzpatrick 2000). By measuring response as a function of stimulus area, we redetermined the spatial summation characteristics of V1 neurons in the cat at various contrasts. Our results demonstrated that all the neurons recorded had a constant CRF size, whereas their spatial summation properties could be contrast dependent (CD) or contrast independent (CID). We labeled a subset of CD and CID cells with biocytin, and their morphological features were then investigated.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Animal Preparation
Acute experiments were performed on 19 adult cats. All procedures complied with the guidelines laid by the Animal Research Advisory Committee at the Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences. Detailed descriptions of procedures for animal surgery, anesthesia, and recording technique are available in an earlier study (Li and Li 1994). Briefly, cats were anesthetized prior to surgery with ketamine hydrochloride (30 mg/kg, I.V.), and then tracheal and venous cannulations were carried out. After the operation, the animal was placed in a stereotaxic frame for performing a craniotomy and subsequent experiments. During recording, anesthesia and paralysis were maintained with urethane (20 mg/kg/h), gallamine triethiodide (10 mg/kg/h), and glucose (200 mg/kg/h) in Ringer's solution (3 mL/kg/h). Heart rate, electrocardiography, electroencephalography (EEG), end-expiratory CO2, and rectal temperature were monitored continuously. Anesthesia was considered sufficient when the EEG indicated a permanent sleep-like state. Reflexes, including cornea, eyelid, and withdrawal reflexes, were tested from time to time. Additional urethane was given immediately I.V. when necessary. The nictitating membranes were retracted and pupils dilated. Artificial pupils of 3 mm diameter were used. Contact lenses and additional corrective lenses were applied to focus the retina on a screen.
Single Unit Recordings
Extracellular recordings were made with a fine-tipped (about 1 µm) glass microelectrode containing a filament, which was pulled on a P-97 (Sutter Instrument Company, USA) microelectrode puller and was filled with 1.5% biocytin in 0.5 M NaCl. The micropipette was connected to the input of an intracellular recording amplifier (World Precision Instruments, USA), and was moved down into the primary visual cortex with a hydraulic microdriver (Narishige, Japan). After amplification, neural signals were band-pass-filtered between 300 and 5000 Hz, and fed into a computer for on-line analysis. All measurements were made during stimulation of the neuron's dominant eye with the other eye occluded.
Determination of CRF Size and Center Location
Once the action potentials of a single cell were isolated, the preferred orientation, spatial frequency, and temporal frequency of the cell were determined. Then the center location of CRF was carefully determined by placing a narrow sine-wave grating patch (80% contrast) at successive positions along the axes perpendicular (inset in Fig. 1A) or parallel to (inset in Fig. 1B) the optimal orientation of the cell, and measuring the response to its drift. The grating was set at the optimal orientation and spatial frequency and drifted in the preferred direction with a speed of 2–4 cycles per second. The peak of the response profiles for both axes was defined as the center of the CRF (Fig. 1A,B). All the recorded cells had receptive fields centered within 10° of the visual axis. As accurate determination of CRF size is essential for the present study, we did this using 2 different tests: 1) the response profiles obtained by placing a drifting sine-wave grating patch at different positions across the CRF, as were used in determining the center location of CRF. The response field above the significant level (P < 0.01, t-test) is defined as one measure of the CRF size (Fig. 1A,B), 2) The response-elimination curves obtained by masking the CRF with a circular blank patch of increasing dimensions (occlusion test). Beyond this masking area is a background grating of optimal stimulus parameters drifting continuously over its surround (insets in Fig. 2). The minimum diameter of the mask, which just reduced the firing of the cell to spontaneous level, is defined as another measure of the CRF size (arrow in Fig. 2). Our results demonstrated that these 2 measurements are in good agreement with each other (see also Fig. 2B of Li and Li 1994), but the size determined by occlusion test is, by our experience, more accurate and reliable than the conventional mapping procedure. It has been reported in an earlier study (Fig. 16 of Li and Li 1994), and was confirmed in the present work, that for most of the V1 cells, the length and width of the CRFs were of approximately similar dimension, and thus the CRFs can be broadly described as a circular area for most of the cells. To simplify the testing procedure, the mask we used in the present study was always circular.
|
|
Determination and Classification of Spatial Summation Properties of V1 Neurons
We determined the spatial summation characteristics at various contrasts level (10–80%) by measuring the neuronal response as a function of stimulus area. Circular drifting sinusoidal grating patches of different diameters were used as the stimulus. The gratings were presented at the optimal orientation and spatiotemporal frequency; each patch size was presented for 5–10 cycles of the grating drift, and standard deviations (SD) were calculated for 3–10 repeats. Outside the grating patches, the screen (40° x 30°) was kept at the mean luminance of 10 cd/m2. The spatial summation curve thus obtained reflects the influence of the surrounding area on the CRF response. We identified 2 classes of ERF effects based on the shape of the spatial summation curve. The major class is the inhibitory ERF depicted by the examples showing in Figure 3B1,B2. Maximum neuronal response was found for stimuli with a diameter corresponding to that of the CRF (1x CRF, Fig. 3B1,B2), and the response decreased with increasing grating size beyond the CRF. The minor class is the facilitatory ERF, which showed increasing neuronal response as the stimulus size increased beyond the CRF, with no peak response but asymptote at about 4-fold of the size of CRF (Fig. 3C1,C2).
|
To quantitatively estimate ERF properties of the cortical neurons, we defined a summation index (SI) by SI = (Rsum – Rcrf)/(Rcrf – Rspt), where Rsum represents the mean response to the grating stimulus at 3x, 4x and 5x CRF size and Rcrf represents the response to CRF grating stimulation alone, Rspt represents the spontaneous discharge rate. For neurons with inhibitory ERF, SI is less than 0. For facilitatory ERF neurons, SI is greater than 0.
Labeling of Neurons and Histological Procedures
After collection of functional data, the electrode was advanced toward the cell, which was then labeled juxtacellularly with biocytin by applying negative current steps (Pinault 1996). The shape and amplitude of spikes were monitored during recording and current injection to ensure that the recorded responses originated from the same neuron that was labeled.
At the end of the experiment, the animals were given an overdose of barbiturate, and was perfused transcardially with fixative 24 h after labeling, first with 0.9% saline and then with 4% paraformaldehyde in 0.1 M phosphate buffered (PB), pH 7.4. Tissue blocks containing the injected cells were removed and postfixed overnight by submersion in cold (4 °C) 4% paraformaldehyde in 0.1 M PB. The tissue was sectioned on a vibratome at a thickness of 50 µm. The injected cells were identified with streptavidin–FITC (1:1000, Vector Laboratories, USA) in a 0.3% solution of Triton X 100 in 0.01 M PBS at 4 °C overnight.
The labeled neurons were examined with a fluorescent microscope and some of them were reconstructed using a confocal microscope (LSM510, Zeiss, Germany). The layer localization of the injected cells was determined with the Nissel-stain method.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Determination of CRF Size at Different Stimulus Contrasts
Using the occlusion test (see Material and Method), we measured the size of the CRF accurately for a total of 59 V1 neurons at different stimulus contrast. For all the cells tested, the sizes of the CRFs were extremely constant, independent of the stimulus contrast used. An example is shown in Figure 2. The size of CRF for this cell was determined repeatedly at 3 different contrasts (10%, 40%, 80%). Although the response amplitude increased systematically with increasing contrast, the boundary of the CRF determined by center occlusion was fairly constant, always at 2° diameter.
Suppressive and Facilitative Spatial Summation Characteristics
In Figure 3A2,B2,C2 the population responses of 48 cells as function of stimulus area at a high contrast level (80%) are shown. At the initial segment of the summation curves, all cells increased responses with increasing size of the stimulus. Then some cells (37 out of 48) showed response suppression and the response decreased with increasing grating size (Fig. 3A2,B1,B2). The peak location for these curves coincides with the size of CRF (1x CRF size). Others (11/48) showed facilitation (Fig. 3C1,C2): the response continued to increase beyond the CRF with increasing stimulus size. There was no peak for the facilitatory curves, and the asymptotic value of the curves was defined as the extent of the facilitatory area which was, on average, 3–5 times the size of CRF (see also Li and Li 1994).
Relationship between Spatial Summation Characteristics and Stimulus Contrast
To obtain a measurement of the changes in spatial summation over the recorded population, we calculated population curves by averaging the individual curves from many cells. The individual summation curves were normalized in response rates, and the stimulus size was chosen to be multiples (1x to 5x) of the size of CRF for each cell. Figure 3 is a summary of all 48 cells for which at least one curve was obtained at a contrast of 80% (lower row) and another curve was obtained at a contrast of 10% (upper row). Each curve represents responses of one cell and the colors represent individual cells. Each bold line indicates the mean response of each group of cells. Based on the changes of spatial summation curves in relation to stimulus contrasts, we subdivided the dynamics of spatial summation into 3 categories.
- CD summation: This characteristic was found for 29 cells (60%). Out of this category, 17 cells showed suppressive summation (SI < 0) at high contrast (80%), the sign of summation reversed and turned into facilitative (SI > 0) at low contrast (10%). The other 12 cells showed weak suppressive summation at low contrast, whereas the strength of suppression increased significantly at high contrast. Meanwhile, the maximum of the individual curves shifted from 1x CRF at high contrast (Fig. 3A2) to 2x, 3x, or 4x CRF (2x CRF for the mean curve) at low contrast (Fig. 3A1). The mean summation index (SImean) for this group of cells was 0.66 ± 0.21 standard error of the mean (SEM) at low contrast, and it became –0.48 ± 0.03 SEM when tested at high contrast (Fig. 3D).The difference in SI between 80% and 10% contrast is significant (P < 0.001, t-test).
- Contrast-independent suppressive (CIDs) summation: In Figure 3B1,B2 spatial summation curves of 8 cells (17%) are shown. Response peaks of all the curves were located at 1x CRF size (the size of CRF). The peak location, as well as the strength of surround inhibition remained unchanged at different contrast values. The SImean at high contrast was –0.71 ± 0.05 SEM, and at low contrast, –0.69 ± 0.07 SEM (Fig. 3E). No statistically significant difference was found in SI between the high and low contrast conditions (P > 0.05, t-test).
- Contrast-independent facilitative (CIDf) summation: Eleven cells (23%) illustrated facilitative summation (SImean =1.55 ± 0.27 SEM) at high contrast (Fig. 3C2), and the shape of each of the curves, as well as the mean curve (bold line) of the population, remained facilitative (SImean = 2.64 ± 0.73 SEM) at low contrast (Fig. 3C1). The difference in SI between the high and low contrast is not significant statistically (P > 0.05, t-test).
Morphological Features of the 3 Types of Neurons
We successfully labeled 11 cells from the CD group. All of the labeled cells in this group were identified to be pyramidal neurons characterized by the triangular soma, vertically oriented apical dendrite, and branching basal dendrites. These cells were located in layer II–VI, including one inverted pyramidal cell in layer II–III. The morphological features and characteristic changes in spatial summation of 2 of these cells are illustrated in Figure 4, which are located in layer II–III and layer IV, respectively.
|
We labeled 4 cells from the 11 CIDf neurons. All the cells labeled were spiny stellate neurons; they had a star-like dendritic arborization with a high spine density and differed from pyramidal neurons in lacking a prominent apical dendrite. Two were located in layers II–III, and the other 2 in layer IV. The morphology and spatial summation curves for one such cells are shown in Figure 5A.
|
Of the 8 CIDs cells, 6 cells were successfully labeled. Interestingly, all of the labeled cells were smooth-dendrite interneurons. There were 3 small basket neurons in layer IV and 3 bipolar neurons: 2 in layer II–III and the other in layer V. In Figure 5B,C are shown the morphology and spatial summation properties of a small basket neuron (in layer IV) and a bipolar neuron (in layer II–III), respectively.
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
CD changes in receptive-field size and spatial summation have been reported for V1 neurons of the cat and the monkey in a number of studies (Levitt and Lund 1997
; Kapadia et al. 1999; Sceniak et al. 1999; Fitzpatrick 2000). Others have reported a change only in response strength, but no measurable change in receptive-field size (DeAngelis et al. 1995). The reason for this discrepancy may be the lack of an agreed definition of CRF and confusion about the boundary between center excitation and surround facilitation. In the present study, we used an occlusion test to delimit the boundary between CRF and the facilitatory summation area. With this method, when the CRF was covered with a blank mask and the entire facilitatory surround was exposed to an optimal stimulus, no cell was found to be able to respond to the surround stimuli. In such cases, however, spatial summation characteristics illustrated a further increase in response with increasing dimension of stimulus, and a maximum was reached at a size, which was 3–5 times the size of the CRF (Figs 3C1,C2 and 5A). Comparing the results obtained from the occlusion test with those from spatial summation measurements, one can recognize that the facilitatory summation area beyond the CRF can only enhance (facilitate) the response of CRF, but cannot drive the cell when stimulated in isolation. We therefore divide the excitatory spatial summation into 2 components: the suprathreshold CRF and the subthreshold ERF. We measured the size of CRF for 59 V1 cells using the occlusion test at different stimulus contrasts. Our results demonstrate that regardless of whether the spatial summation properties of the cells are dynamic or static, their CRF size determined by the occlusion test is highly constant, independent of stimulus contrast. These findings support the notion that receptive-field centers and surrounds are mediated by different cortical circuits. The properties of the CRF are thought to arise from the cortical column and nearby regions of cortex, whereas surround effects are supposed to be mediated by long-distance horizontal connections, and/or by feedback connections from extrastriate areas (Gilbert 1992, 1998; Angelucci et al. 2002; Series et al. 2003).
The mechanisms underlying the dynamic change in spatial summation are likely to depend on the balance between excitation and inhibition over the field. The relative strength of these 2 processes can differ from cell to cell and can be modified by stimulus contrast. Sceniak et al. (1999) have tried to describe the spatial summation properties by a difference of Gaussian (DoG) model composed of 2 overlapping Gaussians. The narrower Gaussian is the excitatory center mechanism and the broader Gaussian represents the surround inhibitory mechanism. Under the assumption that the center and surround signals sum linearly, this model allows one to separate the relative contributions of inhibition and excitation. In terms of the DoG model, increasing the gain of inhibition may shift the peak of summation curve and strongly suppress the responses. For the cells showing CD characteristics (Fig. 3A1, A2), increasing stimulus contrast may lead to an increase in suppression gain, and thereby the reversal of sign from facilitation to suppression and a shift of summation peak. Other models (Stemmler et al. 1995; Somers et al. 1998) explained the reversal of the summation curve by making the assumption that there is an asymmetry of the functional threshold and response gain between excitatory and inhibitory inputs such that, for weak visual inputs (low contrast), inhibitory connections are essentially silent, whereas, for strong inputs (high contrast), the activity of inhibitory inputs rapidly increases, provoking the response saturation of excitatory inputs.
In the case of Figure 3C1,C2, the summation area of the cells may receive predominant excitatory inputs, whereas the inhibitory inputs were negligible. The shape of spatial summation curves for the CIDf cells thus remains unaffected by changing stimulus contrast. The reverse is true for cells showing CIDs characteristics (Fig. 3B1,B2), where inhibitory inputs predominate in the cells and the balance cannot be changed by stimulus contrast.
Our morphological studies demonstrate that cells showing dynamic spatial summation properties (CD neurons) are all pyramidal neurons. In contrast, cells showing static inhibitory spatial summation (CIDs) are all inhibitory interneurons, characterized by having small spherical or oval soma and aspiny dendrites. An early study by Gilbert and Wiesel (1979, Fig. 2b) also reported one smooth stellate cell in layer IVc showing an end-inhibition surround. On the other hand, the cells showing static facilitatory spatial summation (CIDf) are spiny stellate cells, and a proportion of this type of cells is thought to be excitatory interneurons. Based on our observations, it can be suggested that the long-range horizontal connections formed by pyramidal neurons in V1 may play an important role in the dynamics of spatial summation properties and that static summation is likely to be mediated by a variety of interneurons.
In conclusion, our results demonstrate that 1) stimulus contrast may change spatial summation properties for most (60%) of V1 neurons, but their CRF size determined by an occlusion test remains constant, 2) the other 40% of the cells showed invariant spatial summation characteristics, and 3) morphologically, contrast-depended spatial summation is characterized by pyramidal cells, and the neurons showing CID summation are all nonpyramidal cells.
|
Acknowledgments |
|---|
We gratefully acknowledge the expert technical assistance of Ms Xing-Zhen Xu. We also thank Dr D. A. Tigwell for comments on the manuscript. This research was supported by grants from the National Science Foundation of China (90208006), the Knowledge Innovation Program of the Chinese Academy of Sciences (KJCX-07), and the National Key Laboratory of Cognitive Neuroscience, Institute of Biophysics, Chinese Academy of Sciences. Conflict of Interest: None declared.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Allman J, Miezin F, McGuinness E. Stimulus specific responses from beyond the classical receptive field: neurophysiological mechanisms for local-global comparisons in visual neurons. Annu Rev Neurosci (1985) 8:407–430.[CrossRef][Web of Science][Medline]
Angelucci A, Levitt JB, Walton EJ, Hupe JM, Bullier J, Lund JS. Circuits for local and global signal integration in primary visual cortex. J Neurosci (2002) 22:8633–8646.
DeAngelis GC, Anzai A, Ohzawa I, Freeman RD. Receptive field structure in the visual cortex: does selective stimulation induce plasticity? Proc Natl Acad Sci USA (1995) 92:9682–9686.
DeAngelis GC, Freeman RD, Ohzawa I. Length and width tuning of neurons in the cat's primary visual cortex. J Neurophysiol (1994) 71:347–374.
Field DJ, Hayes A, Hess RF. Contour integration by the human visual system: evidence for a local "association field". Vision Res (1993) 33:173–193.[CrossRef][Web of Science][Medline]
Fitzpatrick D. Seeing beyond the receptive field in primary visual cortex. Curr Opin Neurobiol (2000) 10:438–443.[CrossRef][Web of Science][Medline]
Gilbert CD. Horizontal integration and cortical dynamics. Neuron (1992) 9:1–13.[CrossRef][Web of Science][Medline]
Gilbert CD. Adult cortical dynamics. Physiol Rev (1998) 78:467–485.
Gilbert CD, Wiesel TN. Morphology and intracortical projections of functionally characterized neurons in the cat visual cortex. Nature (1979) 280:120–125.[CrossRef][Medline]
Gulyas B, Orban GA, Duysens J, Maes H. The suppressive influence of moving textured backgrounds on responses of cat striate neurons to moving bars. J Neurophysiol (1987) 57:1767–1791.
Hammond P, Kim JN. Spatial correlation of suppressive and excitatory receptive fields with direction selectivity of complex cells in cat striate cortex. Proc Biol Sci (1994) 257:179–184.
Hammond P, MacKay DM. Modulatory influences of moving textured backgrounds on responsiveness of simple cells in feline striate cortex. J Physiol (1981) 319:431–442.
Kapadia MK, Ito M, Gilbert CD, Westheimer G. Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys. Neuron (1995) 15:843–856.[CrossRef][Web of Science][Medline]
Kapadia MK, Westheimer G, Gilbert CD. Dynamics of spatial summation in primary visual cortex of alert monkeys. Proc Natl Acad Sci USA (1999) 96:12073–12038.
Lamme VA. The neurophysiology of figure-ground segregation in primary visual cortex. J Neurosci (1995) 15:1605–1615.[Abstract]
Levitt JB, Lund JS. Contrast dependence of contextual effects in primate visual cortex. Nature (1997) 387:73–76.[CrossRef][Medline]
Li CY, Lei JJ, Yao HS. Shift in speed selectivity of visual cortical neurons: a neural basis of perceived motion contrast. Proc Natl Acad Sci USA (1999) 96:4052–4056.
Li CY, Li W. Extensive integration field beyond the classical receptive field of cat's striate cortical neurons-classification and tuning properties. Vision Res (1994) 34:2337–2355.[CrossRef][Web of Science][Medline]
Pinault D. A novel single-cell staining procedure performed in vivo under electrophysiological control: morpho-functional features of juxtacellularly labeled thalamic cells and other central neurons with biocytin or Neurobiotin. J Neurosci Methods (1996) 65:113–136.[CrossRef][Web of Science][Medline]
Sceniak MP, Ringach DL, Hawken MJ, Shapley R. Contrast's effect on spatial summation by macaque V1 neurons. Nat Neurosci (1999) 2:733–739.[CrossRef][Web of Science][Medline]
Sengpiel F, Sen A, Blakemore C. Characteristics of surround inhibition in cat area 17. Exp Brain Res (1997) 116:216–228.[CrossRef][Web of Science][Medline]
Series P, Lorenceau J, Fregnac Y. The "silent" surround of V1 receptive fields: theory and experiments. J Physiol Paris (2003) 97:453–474.[CrossRef][Web of Science][Medline]
Somers DC, Todorov E, Siapas AG, Toth LJ, Kim D, Sur M. A local circuit approach to understanding integration of long-range inputs in primary visual cortex. Cereb Cortex (1998) 8:204–217.
Sillito AM, Grieve KL, Jones HE, Cudeiro J, Davis J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature (1995) 378:492–496.[CrossRef][Medline]
Stemmler M, Usher M, Niebur E. Lateral interactions in primary visual cortex: a model bridging physiology and psychophysics. Science (1995) 269:1877–1880.
von der Heydt R, Peterhans E. Mechanisms of contour perception in monkey visual cortex. I. Lines of pattern discontinuity. J Neurosci (1989) 9:1731–1748.[Abstract]
Xu WF, Shen ZM, Li CY. Spatial phase sensitivity of V1 neurons in alert monkey. Cereb Cortex (2005) 15:1697–1702.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||