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1 Department of Psychology, University of Connecticut, Storrs, Connecticut 06269; 2 Department of Biological Sciences, State University of New York, State College of Optometry, New York, New York 10036
Submitted 30 April 2003; accepted in final form 28 May 2003
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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; Sherman 1985; Stone 1979 for reviews). Within the contralateral eye, X retinal ganglion cells project mostly to layer A, whereas Y cells diverge to project to layers C and A, which are the two main layers receiving contralateral input in cat LGN (Bowling and Michael 1980, 1984; Sur et al. 1982b, 1987; Tamamaki et al. 1995).
The divergence of Y retinal afferents into layers C and A could be designed to generate two different types of Y receptive fields: YC (Y geniculate cell in layer C) and YA (Y geniculate cell in layer A). In support of this hypothesis, YC and YA cells have different contrast sensitivities, different linearity of spatial summation (Frascella and Lehmkuhle 1984; Lee et al. 1992), and are likely to target different cortical structures (Boyd et al. 1998; Garey and Powell 1967; Gilbert and Kelly 1975; Holländer and Vanegas 1977; Humphrey et al. 1985b; LeVay et al. 1976, 1977). Against this hypothesis, YC and YA cells have similar morphologies (Guillery class 1; Friedlander et al. 1981; Guillery 1966; but see Ferster and LeVay 1978) and are not known to differ significantly in receptive-field size and response timing. Therefore whether YC and YA cells are "different enough" to be considered as separate functional types remains an open question.
One drawback of previous physiological comparisons between YC and YA cells is that only one cell was recorded at a given time. Because cell response properties depend substantially on retinal eccentricity (Frishman et al. 1983; Hoffmann et al. 1972; Wilson and Sherman 1976) and the state of the animal (Wörgötter et al. 1998), accurate comparisons can be better made by simultaneously recording from YC and YA cells with overlapping receptive fields. By using this technical approach, here we demonstrate that YC and YA cells differ in response time course (e.g., latency, transiency) and receptive-field size. In addition, we confirm that YC and YA cells differ in the linearity of spatial summation, as was previously shown by Frascella and Lehmkuhle (1984). Therefore our results along with results from previous studies (Boyd et al. 1998; Ferster 1990a,b; Frascella and Lehmkuhle 1984; Garey and Powell 1967; Gilbert and Kelly 1975; Holländer and Vanegas 1977; Humphrey et al. 1985b; Lee et al. 1992; LeVay et al. 1976, 1977; Mitzdorf and Singer 1978) strongly suggest that Y retinal afferents diverge into two separate channels at the level of the thalamus. Preliminary results have appeared in abstract form (Yeh et al. 2000, 2001).
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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Cats were initially anesthetized with ketamine [10 mg/kg, intramuscular (im)] and thiopental sodium [20 mg/kg, intravenous (iv) supplemented as needed]. Lidocaine was administered topically or injected subcutaneously at all possible sources of pain and pressure. The animal was intubated and placed in a stereotaxic apparatus. The anesthesia was maintained with a continuous infusion of thiopental sodium (2–6 mg · kg–1 · h–1, in 0.9% saline, iv during surgery; 1–2 mg · kg–1 · h–1, in 0.9% saline, iv during recordings; additional doses supplemented as needed). Electrocardiogram (EKG), electroencephalogram (EEG), oxygen (O2) in blood, expired carbon dioxide (CO2), rectal temperature, heart rate, and blood pressure were monitored continuously and maintained within normal physiological limits throughout the experiment. Body temperature was kept between 37 and 38°C by using a thermostatically controlled heating blanket.
A craniotomy was made in the skull (anterior, 5.5; lateral, 10.5) and the dura mater removed to access the LGN. The animal was then paralyzed with a continuous infusion of norcuron (0.2 mg · kg–1 · h–1, iv) to minimize eye movements and was artificially ventilated to keep the expired CO2 between 27 and 33 mmHg. Neosynephrine (10%) and atropine sulfate (1%) were applied to both eyes to retract the nictitating membranes and dilate the pupils. The eyes were covered with contact lenses to protect the corneas and focus visual stimuli presented at 114 cm in front of the animal. The positions of the optic disk and the area centralis were plotted on the tangent screen by using a fiber-optic light source (Pettigrew et al. 1979). All surgical and experimental procedures followed the guidelines of the U.S. Department of Agriculture and were approved by the Institutional Animal Care and Use Committee at the University of Connecticut.
Electrophysiological recordings and data acquisition
A matrix of 7 independently movable electrodes arranged circularly was introduced into the LGN (Eckhorn and Thomas 1993). The electrodes were very thin (80 µm rod; 25 µm at the shaft) and had impedance values of 3–6 M
(Thomas Recording, Marburg, Germany). A glass guide tube with an ID about 300 µm at the tip was attached to the shaft probe of the multielectrode to reduce the interelectrode distances to approximately 80–300 µm. The matrix of electrodes was then lowered into the brain, leaving the tip of the guide tube approximately 3 mm above the LGN. Each electrode was moved independently within the LGN; some electrodes were positioned in layer C and others in layer A. The angle of the multielectrode was adjusted precisely for each experiment (25–30° anterior–posterior; 2–5° lateral–central) to simultaneously record from cells with spatially overlapping receptive fields in both layers A and C. Figure 1A shows the retinotopic map of cat LGN (left) and the alignment of the electrodes used to record from cells with overlapping receptive fields (right). Throughout the text, X cells are represented in blue, YA cells in orange, and YC cells in green. All cells were recorded within 5–10° of the area centralis. Recorded signals from all 7 electrodes were amplified, filtered, and collected by a computer running the Discovery software package (Datawave Systems, Longmont, CO). For each cell, spike waveforms were identified initially during the experiment and verified off-line carefully by using cluster analysis software. Visual stimuli were generated with an AT-vista graphics card (Truevision, Indianapolis, IN) and shown on a 20-in. monitor (Nokia 445Xpro, Salo, Finland; frame rate, 128 Hz).
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Receptive-field mapping
Geniculate receptive fields were mapped with white-noise stimuli and calculated by reverse correlation (Alonso et al. 2001; Reid et al. 1995, 1997, 2002; Sutter 1987, 1992). The white-noise stimulus was derived from a binary m-sequence (Reid et al. 1997; Sutter 1987, 1992), and spatially consisted of a 16 x 16 grid of black or white squares (pixels). Each frame (a 16 x 16 grid) was presented for 15.5 ms and the entire white-noise sequence lasted about 510 s. Each pixel in the white-noise stimulus was 0.81 deg2 in size (0.9 x 0.9°) to allow simultaneous mapping of multiple geniculate cells with both small and large receptive fields. With this stimulus size, most of our receptive-field centers (97%) had at least two pixels. The average spatial stimulus was calculated for each delay between stimulus onset and neural response, and then normalized in units of spikes/s. For a given pixel and delay, a value of +1 indicates that the instantaneous rate of the neuron increased on average 1.0 spike/s after a white pixel and a value of –1 indicates that the instantaneous rate of the neuron increased on average 1.0 spike/s after a black pixel. Throughout the study receptive-field centers are shown as contour plots smoothed with a cubic spline. Each contour line represents from center to periphery 100 to 20%, with respect to the maximum response (Matlab, MathWorks, Natick, MA). In the reverse correlation map, ON-responses are usually followed by OFF-rebounds and OFF-responses are followed by ON-rebounds (see following text under Time course of the visual response). The ON-responses and rebounds are shown as continuous lines; OFF-responses and rebounds are shown as discontinuous lines (Fig. 1B, left).
Receptive-field size and overlap
Both receptive-field size and overlap were calculated from responses to white-noise stimuli. The 20% contour line was chosen to determine the position of the receptive-field center, the receptive-field size, and the overlap with other receptive-field centers consistent with previous studies (Alonso et al. 2001). The time frame with the highest average firing rate was used for all of the measurements. The receptive-field size was quantified as the number of contiguous pixels within the 20% contour line (Fig. 1C, left). The receptive-field overlap between two cells was quantified as the percentage of pixels from the cell with the smaller receptive field that were superimposed with pixels from the cell with the larger receptive field (within the 20% contour line). The 20% contour line was used because it defines quite precisely the size of the geniculate center (measurements below 20% would be less accurate because of the presence of surround responses and background noise). It should be emphasized that the receptive-field size and overlap in this study refer exclusively to the receptive-field center and not the surround.
Time course of the visual response
The time course of the visual response was also calculated from responses to white-noise stimuli by reverse correlation. The "impulse response" was defined as the time course of the response evoked by the most effective stimulus pixel within the receptive-field center (the pixel that generated the maximum response). Most impulse responses were biphasic. For example, the impulse response of an ON-center geniculate cell had a positive first phase (ON-response) followed by a negative second phase (OFF-rebound); the impulse response of an OFF-center geniculate cell had a negative first phase (OFF-response) followed by a positive phase (ON-rebound). It is not totally clear what is the mechanism that generates OFF- and ON-rebounds. DeAngelis et al. (1995) indicated that the biphasic nature of the impulse response was attributed to "intrinsic properties of geniculate neurons." Biphasic impulse responses are also likely to reflect the fact that geniculate neurons respond to sequences of white-noise pixels. For example, an ON-center geniculate cell responds to sequences of black pixels immediately followed by white pixels (black-to-white sequence). Therefore its response will be correlated with both white pixels (short delay, ON-response) and the preceding black pixels (longer delay, OFF-rebound). Throughout this study, ON-responses and ON-rebounds are represented by positive values; OFF-responses and OFF-rebounds are represented by negative values.
Impulse responses were normalized and fitted with a cubic spline to compare timing differences between simultaneously recorded cells (Fig. 1B, right). Each impulse response was normalized by its peak amplitude. The peak was defined as the maximum absolute value at the first phase of the impulse response (positive for ON-center cells, negative for OFF-center cells). Because of this normalization procedure, throughout the study the peak values of the impulse responses are either 1 (ON-center) or –1 (OFF-center). The rebound was defined as the maximum absolute value at the second phase of the impulse response (negative for OFF-rebounds, positive for ON-rebounds). The zero crossing was defined as the zero value between both phases.
Four different temporal parameters were compared: peak time, rebound time, zero crossing time, and half-duration (Fig. 1C, middle- and right). The half-duration was defined as the difference between the rebound time and the peak time (we use the half-duration of the impulse response as an estimate of response transience). We also calculated a ratio between the amplitude of the first and the second phase of the impulse response either as a biphasic index (Cai et al. 1997) or rebound index (Alonso et al. 2001; Usrey et al. 2000). The biphasic index was defined as –1·(rebound amplitude)/(peak amplitude). The rebound index was defined as –1·(rebound area)/(peak area), where the peak area is the integral of the impulse response before the zero crossing and the rebound area the integral of the impulse response after the zero crossing. Differences in biphasic index were all nonsignificant with one exception: in YAXA cell pairs the biphasic index was smaller for the XA cell (P < 0.01, Wilcoxon test). Differences in rebound index were all nonsignificant with one exception: in YCXA cell pairs the rebound index was smaller for the YC cell (P < 0.01, Wilcoxon test). Because differences in the biphasic index or the rebound index were relatively rare, for the sake of simplicity, these two parameters will not be mentioned in the rest of the text.
Classification of geniculate cells
Geniculate cells were classified as Y or X based on the linearity of spatial summation measured with contrast reversing sinusoidal gratings (Enroth-Cugell and Robson 1966; Hochstein and Shapley 1976; Shapley and Hochstein 1975; So and Shapley 1979). We used at least two different spatial frequencies that were higher than the optimal; usually 0.55 cycle/deg and 1.1 cycle/deg. Because some Y cells can generate linear responses when tested with very low spatial frequencies, high spatial frequencies were used to unambiguously classify groups of Y and X geniculate cells that were simultaneously recorded (Hochstein and Shapley 1976; So and Shapley 1979). Each spatial frequency was tested at 8 different phases. The gratings were presented at 0.4 Hz and repeated 
8 times at each spatial phase. The Y/X identification was always made from the responses to the highest spatial frequency that generated a significant response (5 spikes/50-ms bin). Cells that responded poorly (<5 spikes/50-ms bin) were labeled as unclassified. The linearity of spatial summation was quantified as the ratio between the first and second Fourier harmonics (F2/F1). If the F2/F1 ratio was higher than 1 in more than half of the different spatial phases tested, the cell was classified as Y; otherwise the cell was classified as X. We also used the mean ratio (from 8 different phases) to represent spatial linearity in several figures of this report.
Cells recorded deep in the C layers (more than 500 µm below the transition A1–C) were discarded as possible W cells (n = 10; Stanford et al. 1983; Sur and Sherman 1982a; Wilson et al. 1976). All 10 discarded cells responded poorly to contrast reverse gratings (n = 3: linear; n = 7: nonlinear) and had very slow impulse responses (peak times slower than 36 ms and 4.5 ms slower than the slowest layer A cell simultaneously recorded). It is highly unlikely that the 7 nonlinear slow cells were Y-lagged, given that Y-lagged cells are very rare and have never been found in the C layers (Humphrey and Murthy 1999; Mastronarde et al. 1991). Overall, we recorded from 88 layer C cells and 146 layer A cells. In layer C, 75% of the cells were classified as Y (n = 66), 5.7% as X (n = 5), and 19.3% were unclassified (n = 17). In layer A, 39.7% of the cells were classified as Y (n = 58), 50.7% as X (n = 74), and 9.6% were unclassified (n = 14). In this study, we focus on three possible cell types: Y cell in layer C (YC), Y cell in layer A (YA), and X cell in layer A (XA), and three different cell pairs: YCYA (n = 63), YAXA (n = 62), and YCXA (n = 66). A cell pair means two cells with overlapping receptive-field centers that were simultaneously recorded. In addition, 34 cell triplets of YC – YA – XA were used to demonstrate further differences among the three cell types. Statistical significance was assessed by using a Wilcoxon test (for response time course, receptive-field size, spatial linearity, and rebound index), and a K-means cluster analysis followed by a chi-square test (for n-dimensional analysis).
Cross-correlation analysis
Correlograms were calculated with a time window of 10 ms (bin width of 0.1 ms) to search for cell pairs that fired in precise ±1-ms synchrony. The correlograms were band-pass filtered between 75 and 700 Hz and a level of significance was set at a probability of 1.2%, assuming a normal distribution in the baseline amplitudes after filtering. Tight correlations that passed this level of significance were taken as an indication that a cell pair shared a common retinal input (Alonso et al. 1996; Usrey et al. 1998). The correlation strength was calculated from the unfiltered correlograms (1 ms around maximum) after subtracting the baseline. The baseline was defined as the average value of the correlogram at both sides of the central peak (within 2–3 ms from zero).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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). For each experiment, the angle of the multielectrode was adjusted precisely to match the retinotopic map of the LGN [Fig. 1A, left, adapted from Sanderson (1971)] and record from several cells with overlapping receptive fields (Fig. 1A, right). Throughout the entire study YC cells are shown in green, YA cells in orange, and XA cells in blue (Fig. 1A, right). Figure 1B shows the receptive-field centers and response time courses of 4 cells that were simultaneously recorded across the entire depth of the LGN in a quadruple recording. The receptive fields are shown as contour plots (Fig. 1B, left) and the response time courses as biphasic impulse responses. Because these 4 cells were all ON-center, they all had positive first phases followed by negative phases (Fig. 1B, right; see METHODS for details). The 20% contour line was chosen to determine the position of the receptive-field centers, the receptive-field sizes, and receptive-field overlap (Fig. 1C, left; see METHODS). The response time course was measured by calculating several point values within the impulse response (Fig. 1C, middle and right). Differences between YC and YA cells
Simultaneous recordings from YC and YA cells with overlapping receptive fields allowed us to precisely compare their response properties. Figure 2A shows a scatter plot of all YCYA cell pairs represented as a function of the peak time of their impulse responses (each circle represents a YCYA cell pair). Most circles are below the diagonal indicating that the YC cells had faster peak times than the YA cells. We calculated the magnitude of the peak–time difference by subtracting the YA peak time from the YC peak time for each cell pair and then averaging the results for all pairs. The peak–time difference was equal to –2.53 ms, indicating that the peak of the impulse response was on average 2.53 ms faster for YC than for YA cells. This difference was highly significant (P < 0.001, Wilcoxon test). The right side of the Fig. 2A shows examples of cell pairs obtained from three different regions in the scatter plot. In most of the cell pairs (72%) the peak time of the impulse response was faster for the YC cell than for the YA cell.
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YC and YA cells also differed in their receptive-field sizes. In most cell pairs recorded, the receptive field was larger for the YC cell than for the YA cell, as shown in the scatter plot of Fig. 2B (percentages are shown on the right of the figure). We measured the magnitude of the difference in receptive-field size by calculating a ratio for each cell pair (receptive-field size of YC/receptive-field size of YA) and then averaging the results obtained for all pairs. The YC/YA ratio was 1.84, indicating that the receptive-field size was almost twice as large for the YC cell than for the YA cell. Once more this difference was highly significant (P < 0.001, Wilcoxon test).
In addition to the peak time and receptive-field size, YC and YA cells significantly differed in three other additional temporal parameters: zero crossing (Fig. 3A), rebound time (Fig. 3B), and half-duration of the impulse response (Fig. 3C). We calculated the magnitude of these differences by using the same method described above for peak time. The average differences of YC–YA were as follows: zero crossing = –3.86 ms, rebound time = –4.48 ms, half-duration = –1.94 ms. We also compared the linearity of spatial summation by calculating the ratio (F2/F1 of YC)/(F2/F1 of YA). This ratio was 3.9, indicating that F2/F1 was about 4 times higher for YC cells than for YA cells (Table 1).
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Differences between Y and X cells
These results demonstrate that YC and YA cells significantly differ in several temporal and spatial response properties. How do these differences compare with the differences between YA and XA cells? The answer to this question is important because Y and X cells are generally accepted as separate cell types (Boycott and Wässle 1974; Bullier and Norton 1979; Cleland et al. 1971; Enroth-Cugell and Robson 1966; Guillery 1966; Hoffmann et al. 1972; LeVay and Ferster 1977; So and Shapley 1979). Similarly to YCYA cell pairs, YA and XA cells differed in the peak time (YA – XA = –3.90 ms, P < 0.001, Fig. 4A) and receptive-field size (YA/XA = 1.62, P < 0.001, Fig. 4B). The percentage of YC cells with faster impulse responses than those of YA cells (72%) was similar to the percentage of YA cells with faster impulse responses than those of XA cells (76%) and such similarity in percentages was also found for receptive-field size (62% of YC > YA and 64% of YA > XA). In spite of this striking parallel in percentages, the magnitude of the differences in most of the parameters tested was larger between YA and XA cells than between YC and YA cells. In fact, the largest differences were found in YCXA cell pairs (YC – XA in peak time = –5.26 ms, P < 0.001; YC/XA in receptive-field size = 2.62, P < 0.001; Fig. 4, D and E). The impulse responses of Y and X cells differed not only in the peak time but also in zero crossing, rebound time, and half-duration. In addition X and Y cells are known to differ in their linearity of spatial summation and their morphology (see Lennie 1980; Sherman 1985; Stone 1979 for reviews). Therefore although the differences between YC and YA cells are pronounced, they are still relatively modest compared with the differences between Y and X cells (Table 1).
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Differences between YC, YA, and XA cells measured in triple simultaneous recordings
Differences between YC, YA, and XA cells could be compared more precisely in simultaneous recordings from triplets of cells with overlapping receptive fields (n = 34). Figure 5 (top) shows the receptive-field centers and impulse responses of three simultaneously recorded YC, YA, and XA cells (cell triplet). In this example, the YC cell had the largest receptive field and fastest impulse response and the XA cell the smallest receptive field and slowest impulse response. In the analysis of all the cell triplets, again we found that YC cells had larger receptive fields, faster peak times, and stronger nonlinearities than those of YA cells (receptive-field size: YC > YA in 85% of triplets, YC/YA = 1.81, P < 0.001; peak time: YC < YA in 82% of triplets, YC – YA = –3.46 ms, P < 0.001; F2/F1: YC > YA in 65% of the triplets, YC/YA = 4.3, P < 0.03). Interestingly, in the analysis of cell triplets, the differences in peak time and receptive-field size between YC and YA cells were definitely not smaller than the differences between YA and XA cells (receptive-field size: YA/XA = 1.32, P < 0.05; peak time: YA – XA = –1.28 ms, P < 0.06). The histograms in Fig. 5 (bottom) illustrate these differences [the absolute value was chosen as the best representation of the magnitude differences; a nearly identical histogram was obtained by using (YC – YA)/(YA – XA)].
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It is generally assumed that Y-receptive fields are 3 times larger than X-receptive fields both at the level of the retina and within the LGN (So and Shapley 1979; see also Shapley and Lennie 1985 for review). This notion derives from careful measurements of the spatial frequency tuning of X and Y cells recorded in layer A with a single electrode (So and Shapley 1979). As shown here, measurements of receptive-field size with white noise leads to a slightly different conclusion. Whereas the YC:XA receptive-field ratio approaches 3:1, the YA:XA ratio is smaller than 2:1. Similarly, the differences in response latency are larger between YC–XA than between YA– XA. It seems as if YA cells had found a compromise between the high spatial resolution of the XA pathway and the fast temporal resolution of the YC pathway. This "intermediate status" of YA cells is further supported by cluster analysis. Figure 6 shows multiple YC, YA, and XA cells plotted in a 3D space determined by the receptive-field size, peak time, and half-duration of the impulse responses (Fig. 6A: all cells, Fig. 6B: YC–YA– XA triplets obtained in simultaneous recordings). At the top of the 3D plot, a copy of the same data points is shown only for YC and XA cells. The top plot illustrates the clean separation of YC and XA cells. The bottom plot illustrates the "intermediate" status of the YA cells. As shown in this figure, YC and XA cells can be reliably separated into two different clusters (K-means cluster analysis and chi-square test, P < 0.01 for YC, P < 0.001 for XA), whereas YA cells lie in between.
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Overall, these results indicate that YC, YA, and XA cells significantly differ in several temporal and spatial parameters. YC cells have the largest receptive fields and generate the fastest, most transient, and least linear responses to visual stimuli. XA cells have the smallest receptive-fields and generate the slowest, least transient, and most linear responses. The response properties of YA cells fall in between YC and XA cells.
Correlated firing between YC and YA cells
The finding that YC and YA cells have different properties is puzzling because the anatomy indicates that almost every Y retinal afferent from the contralateral eye projects to both layers A and C (Bowling and Michael 1980, 1984; Sur et al. 1982b, 1987; Tamamaki et al. 1995). This puzzle can be addressed in part by measuring the correlated firing between YC and YA cells. It was previously shown that cells sharing a common retinal afferent within layer A fire in a tight 1-ms synchrony (Alonso et al. 1996; Usrey et al. 1998). If YC and YA cells share a retinal afferent they should also generate tight correlated firing. Figure 7A shows an example of a pair of YC and YA cells with overlapping receptive fields that were simultaneously recorded. The YC cell had a larger receptive field and faster impulse response than those of the YA cell. Importantly, the receptive fields were of the same sign (OFF-center) and the receptive-field overlap was almost total. The bottom of Fig. 7A shows a correlogram with a very narrow peak centered at zero, indicating that the two cells were likely to share a retinal afferent.
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The great majority of YCYA cell pairs (n = 9/11) with receptive fields overlapped more than 80%, and of the same sign, showed tight correlated firing. However, the average strength of the YCYA tight correlations (7.5%) was almost half the value reported for tight correlations within layer A (13%; Alonso et al. 1996). This finding seems to indicate that most YCYA cells with overlapping receptive fields of the same sign share common retinal afferents. However, the shared afferents are weaker across layers than within the same layer.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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; Orban 1984; Payne and Peters 2002; Pettigrew et al. 1986; Rodieck 1973; Sherman and Guillery 2001; Steriade et al. 1990; Stone 1983). However, the total number of channels is likely to be much higher. Berson and his colleagues identified more than 12 morphologically different types of retinal ganglion cells (Berson et al. 1998, 1999; Isayama et al. 2000; O'Brien et al. 2002; see also Dacey et al. 2003 and Masland 2001), and Cleland et al. identified 8 different functional types (Cleland et al. 1971, 1974a,b). Moreover, each of the parallel pathways originating in the retina is likely to diverge into more specialized channels as the information progress in the visual pathway. The anatomy of the Y pathway in the cat is very suggestive of this channel divergence/specialization. Y retinal afferents from the contralateral eye diverge to innervate two different layers within the LGN (layers C and A) and, as suggested here, this anatomical divergence could translate into two different types of Y receptive fields.
Are YC and YA two different cell types?
Although the idea of two different Y channels has been in the literature since the 1970s, it has not been systematically tested. The closest attempt was done by Frascella and Lehmkuhle (1984) and Lee et al. (1992). However, both studies had a relatively small sample of cells (19 YC in Frascella and Lehmkuhle (1984); 9 YC in Lee et al. 1992) and precise comparisons were further complicated by the fact that the cells were not simultaneously recorded and were not precisely matched in retinotopy. In spite of these technical limitations, Frascella and Lehmkuhle (1984) recorded from 19 YC cells, all within 15° of the area centralis, and did a detailed quantification of contrast sensitivity (using different temporal and spatial frequencies) and linearity of spatial summation (using different contrasts). By doing so, these authors clearly demonstrated that YC cells have higher contrast sensitivity and stronger nonlinearities than those of YA cells. Our study confirms the result that YC cells have stronger nonlinearities than those of YA cells and, in addition, it reports the following new findings: 1) YC and YA cells significantly differ in their receptive-field sizes and the peak time, zero crossing, rebound time, and half-duration of their impulse responses. 2) The differences in receptive-field size between YC and YA cells are not smaller in magnitude than the differences between YA and XA cells. 3) Cluster analysis based on receptive-field size and response timing can successfully separate XA cells from YC cells, whereas YA cells lie in between the two clusters.
Are these findings enough to propose that YC and YA cells are two different "cell types"? Rodieck and Brening (1983) argued that a "natural cell type" should be defined by simultaneously considering a large number of parameters, both quantitative and qualitative (see also Rowe and Stone 1977). The greater the number of parameters, the sharper and more individualistic the definition of cell type is. Based on this definition, YC and YA cells could be considered as separate "natural cell types" because they differ in several parameters including receptive-field size, response latency, response transience, linearity of spatial summation, and contrast sensitivity. It is important to remember the words of Rodieck and Brening (1983): "The notion that a given cell type is indivisible retains the character of a hypothesis. The inclusion of an additional parameter always has the potential for further subdividing the clusters." On the other hand, it is also important to emphasize that the differences between YC and YA cells are relatively modest compared to the differences between Y and X cells (Table 1), particularly when considering the linearity of spatial summation and the morphology. Therefore YC and YA cells may not be different cell types but the extremes of a continuum.
How may the different response properties of YC and YA cells be generated?
Even if YC and YA cells are the extremes of a continuum, it is still somewhat surprising that they are so different. After all, almost every Y retinal afferent from the contralateral eye projects to both geniculate layers, layer A and layer C. An explanation to this puzzle could be advanced if we make the following assumptions.
, 1984; Sur et al. 1982b, 1987; Tamamaki et al. 1995). Second, cross-correlation analysis indicates that YC and YA cells with overlapping receptive fields of the same sign share common retinal afferents (Yeh et al. 2000). ) and tight correlated firing is weaker between YC and YA cells than between layer A cells (Alonso et al. 1996). These three assumptions are summarized in a cartoon represented in Fig. 7B. The square boxes represent three geniculate cells: two YA cells (in orange) and one YC cell (in green). A single retinal afferent makes a larger number of synapses with the YA cell than with the YC cell (the number of synapses are represented by the size of the black circle). Because the YC cell receives input from another retinal afferent, the YC cell receives more retinal synapses in total than does the YA cell. The correlated firing between the YA cell and the YC cell is relatively weak because there is only one shared retinal afferent that makes a relatively weak connection in layer C. This cartoon illustrates the simplest possible circuit. In a more complicated version, there could be more retinal afferents for each YA cell and even more for each YC cell.
Possible functional significance of two Y-channels
The differences between YC and YA cells would be irrelevant if their projections within the cortex were not segregated. Several previous studies have suggested that this is not the case. First, cells in layers C and A of LGN target different cortical areas—most layer C cells project to area 18, whereas most layer A cells project to area 17 (Boyd et al. 1998; Bullier et al. 1984; Garey and Powell 1967; Geisert 1980; Gilbert and Kelly 1975; Holländer and Vanegas 1977; Humphrey et al. 1985a,b; LeVay and Ferster 1977; Niimi and Sprague 1970). Second, the layer C cells that do project to area 17 are likely to target different cortical layers than the layer A cells (Boyd and Matsubara 1996; Bullier and Henry 1979; Ferster and LeVay 1978; Freund et al. 1985b; Gilbert and Kelly 1975; Humphrey et al. 1985a; LeVay and Gilbert 1976; Mullikin et al. 1984). Third, Y cells projecting to area 18 are significantly faster, have larger soma sizes, and have stronger nonlinearities than Y cells projecting to area 17 (Boyd et al. 1998; Garey et al. 1967, 1977; Gilbert and Kelly 1975; Holländer and Vanegas 1977; Humphrey et al. 1985b; Mitzdorf and Singer 1978; Niimi and Sprague 1970). Fourth, YC cells bifurcate into areas 17 and 18 more frequently than YA cells (Bullier et al. 1984; Geisert 1980; Humphrey et al. 1985b).
Although it has been repeatedly shown that Y geniculate cells project to area 17 (Alonso et al. 2001; Boyd and Matsubara 1996; Bullier et al. 1979, 1984; Ferster and LeVay 1978; Freund et al. 1985a,b; Garey and Blakemore 1977; Gilbert and Wiesel 1979; Holländer and Vanegas 1977; Humphrey et al. 1985a,b; LeVay et al. 1976, 1977; Leventhal 1979; Tanaka 1983), careful experiments using both intracellular recordings and source density analysis have reached a different conclusion: the Y projection to area 17 is functionally very weak (Ferster 1990a,b). Consistent with this conclusion are the following findings. 1) Geniculate cells projecting to area 17 have slower conduction velocities and higher thresholds to electrical stimulation than geniculate cells projecting to area 18 (Ferster 1990a,b). 2) The linearity of spatial summation is "Y-like" for most area 18 cells and "X-like" for most area 17 cells (Ferster and Jagadeesh 1991; Movshon et al. 1978b; Spitzer and Hochstein 1985). 3) On average, receptive fields are three times larger in area 18 than area 17, exactly the same 3:1 ratio of Y:X retinal ganglion cells (Ferster 1981; Movshon et al. 1978a; Pollen and Ronner 1975; Shapley and Lennie 1985; Troy 1983).
The different opinions about the functional significance of the Y pathway in area 17 could be easily reconciled by accepting the existence of two different Y channels. Because most inputs to area 17 originate in YA cells and X cells, it is not surprising that the bulk of the geniculate input to area 17 has low conduction velocity (Ferster 1990b; Humphrey et al. 1985a; Mitzdorf and Singer 1978; if we assume that receptive-field size and conduction velocity are correlated). It is not surprising either that most area 17 cells have X-like linearity of spatial summation because, at least near the area centralis, area 17 cells are 4 times more likely to receive input from an X cell than from a Y cell (Alonso et al. 2001). Moreover, for those cells receiving mixed YA and XA input (Alonso et al. 1996; Ferster 1990b; Tanaka 1983), the weak nonlinear contribution from the YA cells could be easily washed out by the more abundant X input. Finally, although receptive fields are 3 times larger in Y than in X retinal ganglion cells (see Shapley and Lennie 1985 for review), the ratio is <2 for YA/XA geniculate cells and is only near 3 for YC/XA cells (see RESULTS). [In fact, the ratio of receptive-field sizes between area 17 cells located at the top (Y-recipient) and bottom of layer 4 (X-recipient) is <2 (Tolhurst and Thomson 1981)].
The existence of subcategories within the X and Y pathways is unlikely to be an oddity of the cat visual system. In primates X cells are found in both the parvocellular and magnocellular layers of LGN (Kaplan and Shapley 1982) and their properties may not be the same across layers (e.g., X-parvocellular cells may have smaller receptive fields and slower response time courses than those of X-magnocellular cells). There are data suggesting that different morphological types of X cells may coexist within a single geniculate layer (Friedlander et al. 1981; see also Dacey et al. 2003), and some authors have reported subcategories of lagged and nonlagged cells within the X and Y pathways (Humphrey and Weller 1988; Mastronarde et al. 1987, 1991).
The Y visual pathway was probably designed to detect rapid changes in the environment (Paternak and Maunsell 1992; Tolhurst 1973); however, change is important for both motion and shape processing. Therefore two specialized Y channels may be needed for vision in the cat. In the motion channel, the fast YC cells with their large receptive fields could provide excellent temporal resolution for the rapid detection of a visual stimulus. In the shape channel, the slower YA inputs with their smaller receptive fields could provide a fair compromise between the temporal and spatial resolution needed for the rapid identification of the stimulus shape. The idea of 2 separate Y channels can be traced back to the work of Mitzdorf and Singer (1978). Future studies will probably reveal an increasingly larger number of channels that originate at different levels within the visual pathway (Yabuta et al. 2001).
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DISCLOSURES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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Present address of J. M. Alonso and C. I. Yeh: Department of Biological Sciences, State University of New York, Optometry, 33 West 42nd Street, New York, NY 10036.
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FOOTNOTES |
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Address for reprint requests and other correspondence: J.-M. Alonso, Department of Biological Sciences, SUNY, Optometry, 33 West 42nd Street, New York, NY 10036 (E-mail: jalonso{at}mail.sunyopt.edu).
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REFERENCES |
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Alonso JM, Usrey WM, and Reid RC. Rules of connectivity between geniculate cells and simple cells in cat primary visual cortex. J Neurosci 21: 4002–4015, 2001.
Berson DM, Isayama T, and Pu M. The Eta ganglion cell type of cat retina. J Comp Neurol 408: 204–219, 1999.[ISI][Medline]
Berson DM, Pu M, and Famiglietti EV. The zeta cell: a new ganglion cell type in cat retina. J Comp Neurol 399: 269–288, 1998.[ISI][Medline]
Bowling DB and Michael CR. Projection patterns of single physiologically characterized optic tract fibres in cat. Nature 286: 899–902, 1980.[Medline]
Bowling DB and Michael CR. Terminal patterns of single, physiologically characterized optic tract fibers in the cat's lateral geniculate nucleus. J Neurosci 4: 198–216, 1984.[Abstract]
Boycott BB and Wässle H. The morphological types of ganglion cells of the domestic cat's retina. J Physiol 240: 397–419, 1974.
Boyd JD, Casegrande VA, and Bonds AB. How distinct are the lateral geniculate nucleus (LGN) inputs to area 17 and 18 in the cat? Soc Neurosci Abstr 24: 354.1, 1998.
Boyd JD and Matsubara JA. Laminar and columnar patterns of geniculocortical projections in the cat: relationship to cytochrome oxidase. J Comp Neurol 365: 659–682, 1996.[ISI][Medline]
Bullier J and Henry GH. Laminar distribution of first-order neurons and afferent terminals in cat striate cortex. J Neurophysiol 42: 1271–1281, 1979.
Bullier J, Kennedy H, and Salinger W. Bifurcation of subcortical afferents to visual areas 17, 18, and 19 in the cat cortex. J Comp Neurol 228: 309–328, 1984.[ISI][Medline]
Bullier J and Norton TT. X and Y relay cells in cat lateral geniculate nucleus: quantitative analysis of receptive-field properties and classification. J Neurophysiol 42: 244–273, 1979.
Cai D, DeAngelis GC, and Freeman RD. Spatiotemporal receptive field organization in the lateral geniculate nucleus of cats and kittens. J Neurophysiol 78: 1045–1061, 1997.
Cleland BG, Dubin MW, and Levick WR. Sustained and transient neurons in the cat's retina and lateral geniculate nucleus. J Physiol 217: 473–496, 1971.
Cleland BG and Levick WR. Brisk and sluggish concentrically organized ganglion cells in the cat's retina. J Physiol 240: 421–456, 1974a.
Cleland BG and Levick WR. Properties of rarely encountered types of ganglion cells in the cat's retina and an overall classification. J Physiol 240: 457–492, 1974b.
