The Journal of Physiology arnH Jepson H. Lauren 2 1 Greschner Martin types primate cell in ganglion major among firing Correlated Physiol J C ytm erbooyLbrtr,Sl nttt o ilgclSuis aJla A USA CA, Jolla, La Studies, Biological for Institute Salk Laboratory, Neurobiology Systems at rzIsiuefrPril hsc,Uiest fClfri,SnaCu,C,USA CA, Cruz, Santa California, of University Physics, Particle for Institute Cruz Santa 00TeAtos ora compilation Journal Authors. The 2010 8. 21)p 75–86 pp (2011) 589.1 rn coscl ye ntepiaertn,adcntanso h neligmechanisms. underlying the on constraints ON and correlated receive retina, of primate which overview the an cells, in provide midget types results cell these and Collectively, across cones. parasol firing M ON ON and receive L with which from synchronously cells, primarily fired input is bistratified of cones, photoreceptors small Most from S Surprisingly, noise types. from firing. shared cell input correlated that ganglion of hypothesis retinal cause the other dominant two with the consistent in are observed at observations also scotopic similar were these at was present results were types Similar correlations cell levels. slow across additional the light firing although to correlated levels, proportion light of in scotopic pattern and type, The photopic cell overlap. each field for receptive distance of with degree systematically declined strength The firing correlated. polarity negatively correlated response were higher of light polarity same opposite the to the with with cells cells input nearby correlated; the of positively Pairs were the in types. cell across firing of and course within Correlated time polarity 75% strength, recordings. and characteristic midget, exhibited multi-electrode roughly illumination OFF uniform large-scale and spatially constitute constant, using of ON presence together studied parasol, was which OFF areas, and cells, visual ON cell bistratified among ganglion major firing small the Correlated among and brain. retina. firing the correlated primate to of in structure the and types from degree that transmitted the suggest describes signal correlations study visual This These the chance. shape by significantly expected interactions those network from different rates at synchronously Abstract ganglion be that would known which correlations signals. than in creating cell model circuitry, been ganglion a retinal frequently among with common consistent through are propagates has activity less photoreceptors of cone patterns in the it or noise part, different most between the years more For correlations retina types. distance-dependent primate cell systematic, the simultaneously ganglion many reveal in we activity Here fire correlated For unclear. of been patterns to have retina. particular the However, tendency chance. the by a predicted in exhibit types cells cell ganglion summary Non-technical Rcie 5My21;acpe fe eiin2 etme 00 rtpbihdoln coe 2010) October 4 online published first 2010; September author 28 Corresponding revision after accepted 2010; May 25 (Received Abbreviations [email protected] Email: USA. CA, Downloaded fromJPhysiol ( 1 1 lxne Sher Alexander , oahnShlens Jonathon , eia aginclsehbtsbtnilcreae rn:atnec ofienearly fire to tendency a firing: correlated substantial exhibit cells ganglion Retinal C,coscreainfnto;RC,rtnlgnlo cells. ganglion retinal RGCs, function; cross-correlation CCF, C .Gecnr ytm erbooyLbrtr,Sl nttt o ilgclSuis aJolla, La Studies, Biological for Institute Salk Laboratory, Neurobiology Systems Greschner: M. 00TePyilgclSociety Physiological The 2010 jp.physoc.org 2 ,AlanM.Litke 1 hsppreaie h orltdfiigaogmultiple among firing correlated the examines paper This osatn Bakolitsa Constantina , ) atUNIV OFCALIFORNIA-SAN DIEGO onJanuary10, 2011 2 n .J Chichilnisky J. E. and 1 rgD Field D. Greg , 1 1 efe .Gauthier L. Jeffrey , O:10.1113/jphysiol.2010.193888 DOI: 1 , 75 76 M. Greschner and others J Physiol 589.1

Introduction This study provides a quantitative description of spontaneous correlated firing within and across the five A fundamental aspect of population coding in the nervous numerically dominant RGC types in macaque retina, as system is correlated firing: a tendency for two or more well as two other cell types, at photopic and scotopic light neurons to fire nearly simultaneously more or less levels. The pattern of correlated firing varied systematically frequently than would be expected by chance. Correlated with cell type, and was mostly consistent with an origin firing has been observed in many neural circuits, provides in shared noise from photoreceptors. The results provide clues about their structure, and may have a fundamental the basis for quantitative models of correlated firing in impact on the neural code (see Rieke et al. 1997; Shlens the retina as well as information about the underlying et al. 2008). mechanisms. In the retina, correlated firing is an important aspect of the visual signal transmitted to the brain. Correlated firing is prevalent in retinal ganglion cells (RGCs) of many Methods species (e.g. cat, goldfish, salamander, rabbit, guinea pig and macaque) (Rodieck, 1967; Arnett, 1978; Mastronarde, Recording 1983a;Meisteret al. 1995; DeVries, 1999; Schnitzer & were obtained and recorded as described Meister, 2003; Shlens et al. 2006), reflecting a combination previously (Litke et al. 2004; Field et al. 2007). Briefly, of shared inputs and reciprocal coupling (Mastronarde, were enucleated from terminally anaesthetized macaque 1983a; Brivanlou et al. 1998; DeVries, 1999; Hu & monkeys (Macaca mulatta and Macaca fascicularis) used Bloomfield, 2003; Hidaka et al. 2004; Trong & Rieke, in the course of other experiments, in accordance with Salk 2008). Correlated spikes in RGCs have been proposed Institute IACUC guidelines for the care and use of animals. to represent a distinct mode of visual signalling (Meister Data were obtained in 12 recordings from the retinas of et al. 1995; Schnitzer & Meister, 2003; Schneidman et al. 10 macaques. Immediately after enucleation, the anterior 2006), conveying information not available in the spikes portion of the eye and vitreous were removed in room of individual cells (Meister, 1996) and driving post- light. Following a dark-adaptation period of >40 min, synaptic responses with high efficacy (Usrey et al. 1998). segments of peripheral retina (7–13 mm, 30–60 deg; More generally, correlated firing between RGCs influences Drasdo & Fowler, 1974; Perry & Cowey, 1985) that were the statistics of population responses in RGCs. Because well attached to the pigment epithelium were isolated correlations can originate in shared circuitry and/or shared and placed flat, RGC layer down, on a planar array of visual stimulation, their structure and organization may extracellular microelectrodes. In some cases the pigment affect our understanding of how the brain can most epithelium was left attached to the retina during recording. effectively read out retinal signals (Puchalla et al. 2005; No differences in spike rate were observed between iso- Pillow et al. 2008; but see Nirenberg et al. 2001). lated and attached recordings other than those attributable Relatively little is known about the properties of to temperature (n = 2). During recording, the retina was correlated firing within and across the diverse types of perfused with Ames’ solution (33–36◦C) bubbled with RGCs in macaque monkey retina. The macaque retina 95% O2 and 5% CO2, pH 7.4. and closely resemble their human counter- Recordings were analysed offline to isolate the spikes of parts, and are the basis for much of our understanding of different cells, as described previously (Field et al. 2007). . Each RGC type – which is characterized Briefly, candidate spikes were detected using a threshold by distinctive morphology, light responses, connectivity on each electrode, and the voltage waveforms on the to retinal interneurons, and projection patterns in the electrode and nearby electrodes around the time of the brain – is thought to convey a full representation of the spike were extracted. Clusters of similar spike waveforms visual scene, forming an elementary parallel pathway for were identified as arising from a single neuron if they vision (see Rodieck, 1998). Five numerically dominant exhibited a refractory period. RGC types – ON and OFF midget, ON and OFF parasol, and small bistratified cells – collectively constitute ∼75% Visual stimulation of the retinal representation (Dacey, 2004). To date, correlated firing has been studied only in parasol cells, Visual stimulation techniques were described previously at photopic light levels (Shlens et al. 2006, 2008; Trong (Field et al. 2007). Briefly, the optically reduced image & Rieke, 2008). However, previous studies in cat retina of a linearized cathode ray tube computer display (Sony (Mastronarde, 1983a) and rabbit retina (DeVries, 1999) Multiscan E100) refreshing at 120 Hz was focused on indicate that the extent and properties of correlated firing the photoreceptor outer segments. In most experiments vary significantly between different RGC types and with the image was delivered from the photoreceptor side. light level, potentially providing insight into mechanism. In experiments in which the pigment epithelium was These findings suggest the need for a more comprehensive left attached, the image was delivered through the understanding of correlated firing in primate retina. mostly transparent electrode array. The display was

C 2010 The Authors. Journal compilation C 2010 The Physiological Society Downloaded from J Physiol (jp.physoc.org) at UNIV OF CALIFORNIA-SAN DIEGO on January 10, 2011 J Physiol 589.1 Correlated firing among major ganglion cell types in primate retina 77 calibrated using a PR-701 spectroradiometer (Photo- with a model consisting of the product of a spatial profile, Research, Chatsworth, CA, USA) and a photodiode (UDT which was used for further analysis, and a temporal profile Instruments, San Diego, CA, USA). The light intensity was (see Field et al. 2007). For midget and parasol cells, at controlled by neutral density filters in the light path. The photopic light levels, the spatial profile was a difference light level was 830 (840, 440) P∗ (L (M, S) cone)−1 s−1 of Gaussian functions, with a centre–surround diameter if not noted differently. The photopic photon absorption ratiofixedbytheaverageoffitsacrosscellsofthattype rates were computed assuming a 0.37 μm2 collecting area in the same preparation. This surround radius was always for primate cones (Schnapf et al. 1990). ∼2–3 times that of the centre. For small bistratified cells, A white noise stimulus, composed of a lattice of square a single Gaussian function was fitted to the blue display pixels updating randomly and independently over time, primary component of the STA. At scotopic light levels, was used to characterize the receptive field properties no surrounds were observed and the spatial component of of recorded RGCs (Chichilnisky, 2001). The intensity of the fit was a single Gaussian function for all cell types. The each display primary at each pixel location was chosen outlines in Fig. 1 represent the elliptical 1 S.D. boundary independently from a binary distribution at each refresh. of the centre components of Gaussian fits. The distance The time-averaged contrast of each primary (difference between cells (abscissa in Figs 2B and 3B) was normalized between the maximum and minimum intensities divided by the mean S.D. of their Gaussian fits measured along the by the sum of intensities) was 96%. A stimulus pixel line connecting the centres of the fits. Adjacent neurons in size of ∼60 (∼90) μm on a side was used at photo- each mosaic were identified using a Voronoi tessellation pic (scotopic) light levels. Measurements of correlated (Shlens et al. 2009). Misidentified adjacencies in a mosaic spontaneous firing were obtained in the presence of a apparently attributable to unrecorded cells were excluded. spatially uniform, full-field display with intensity equal Cross-correlation functions (CCFs, e.g. Fig. 2A)were to the mean intensity of the white noise stimulus used obtained by binning spikes into 1 ms time bins and for receptive field characterization. No entrainment to the computing the correlation coefficient between the refresh rate of the stimulus display was detected in the resulting spike count vectors, with a temporal offset. spike autocorrelation function of the recorded cells or its CCFs were summarized by averaging across pairs with Fourier transform. For the measurements of correlated the highest overlap of a given cell type combination. Cells firing in response to light stimulation, a low-pass-filtered with noisy STAs, unstable spike rate, or autocorrelation white noise pattern was presented. A fine-grained white functions or electrical images (Litke et al. 2004) indicative noise pattern (frame rate 120 Hz, pixel size ∼12 μm) was of imperfect spike sorting were excluded from analysis. convolved with an exponential temporal filter with a time CCFs that exhibited spike sorting artifacts due to wave- constant of 50 ms, and with a Gaussian spatial filter of form overlap were excluded (see below). The zero time standard deviation ∼22–176 μm. Unfiltered white noise bin in each CCF plot was omitted. The shuffled CCF (or stimuli produced similar results (not shown). shift predictor) was calculated over identical repeats of the stimulus (Perkel et al. 1967). For a given pair of cells, the spikes from the first cell in one repeat, and the spikes from Data analysis the second cell in another repeat, were used to calculate a Distinct RGC types were identified using their functional CCF, and the average CCF was obtained across all possible properties, e.g. response time course, receptive field size combinations of repeats. and autocorrelation function (Chichilnisky & Kalmar, To summarize the peak cross-correlation (e.g. Fig. 2B), 2002; Field et al. 2007; Petrusca et al. 2007). In a space spikes were accumulated in 10 ms bins (Shlens et al. 2006) defined by these parameters, well-defined clusters were and the correlation coefficient at zero offset was computed. taken to represent distinct functional cell classes. The The dependence of this value on distance (e.g. Fig. 2B) correspondence of these cell classes to cell types known was fitted with a function based on receptive field over- from anatomical work was confirmed by the uniform lap, calculated as follows. For each cell type, the mean tiling of visual space by the receptive fields of each class fitted receptive field diameter for all cells of that type (Devries & Baylor, 1997). Cell types were determined by was calculated. The diameter was defined as that of a density and light response properties as described pre- circle occupying the same area as the 1 S.D. contour of viously (Chichilnisky & Kalmar, 2002; Field et al. 2007; the Gaussian fit. The receptive field overlap at a given Petrusca et al. 2007). The receptive fields of the wide-field distance was then computed using circularly symmetric ON cell class tile visual space, and these cells exhibit a Gaussian functions at that distance with 1 S.D. diameters density similar to that of OFF upsilon cells (Petrusca et al. equal to the mean diameters for the cell types. The over- 2007). lap was defined as the inner product of the two Gaussian Receptive fields were estimated by computing the functions expressed as vectors, normalized by the square spike triggered average (STA) of a white-noise stimulus root of the product of their vector lengths. The amplitude (Chichilnisky, 2001) and summarized by fitting the STA of the curves was fitted independently to the data from

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Table 1. Average correlation strength within and across cell types

ON parasol OFF parasol ON midget OFF midget Small bistratified

Photopic ON parasol 0.18 ± 0.05 −0.04 ± 0.01 0.12 ± 0.03 −0.01 ± 00.03 ± 0.02 OFF parasol 0.07 ± 0.05 −0.03 ± 0.01 0.08 ± 0.04 — ON midget 0.03 ± 0 −0.02 ± 0.01 0.02 ± 0.01 OFF midget 0.01 ± 0— Small bistratified 0.03 ± 0

Scotopic ON parasol 0.18 ± 0.01 −0.06 ± 0.02 0.20 ± 0.02 −0.03 ± 00.10 ± 0.04 OFF parasol 0.08 ± 0.02 −0.05 ± 0.02 0.10 ± 0.03 −0.03 ± 0.01 ON midget 0.09 ± 0.04 −0.04 ± 00.06 ± 0.01 OFF midget 0.03 ± 0.01 −0.01 ± 0 Small bistratified 0.02 ± 0 Values are estimated from fits indicated by curves in Figs 2B and 3B. For cell pairs composed of different cell types, correlation strength is given at zero distance. For cell pairs composed of the same cell type, correlation strength is given at the normalized nearest neighbour distance (arrowhead on the abscissa). These estimates represent the amplitude of the strongest correlations typically observed between cells of the given types. The extrapolated theoretical correlation between cells of the same type at a distance of zero is approximately 2.7-fold higher that the value at a distance of 2 S.D.s, which is approximately the normalized nearest neighbour distance. Unreliable estimates were excluded (blank entries in table). Light levels: photopic, 830 (840, 440) P∗ (L (M, S) cone)−1 s−1; scotopic, 0.5–1.3 P∗ rod−1 s−1.Overall54± 27% of the variance in correlation strength with distance was explained by the degree of receptive field overlap, with a range from 87% (ON parasol–ON parasol) to 27% (OFF midget–OFF midget). each cell type combination. For pairs of cells of the same 12 (8) cell pairs. Table 1 shows the average across 4–6 cell type, the amplitude was fitted to neighbouring cell (3–4) recordings for the photopic (scotopic) stimulus pairs(blackdotsinFigs2B and 3B). For pairs of cells of conditions; cell type combinations with insufficient data different types, the amplitude was fitted to pairs separated for a given recording were excluded. In Fig. 4 data from by <1 S.D. one preparation and 18 (10) ON parasol (ON midget) When the waveforms of spikes produced by different cell pairs are presented. The recording duration ranged neurons overlapped in time, the recorded voltage wave- from 1200 to 1800 s (mean: ∼1600 s), and the spike rate formdifferedfromthewaveformproducedbyeithercell was 8 ± 2Hz(5± 2 Hz) for ON parasol (ON midget) alone, in some cases causing precisely synchronized spikes cells. In Fig. 5 data from one preparation and 19 (24) ON from both cells to be missed in the spike identification parasol–ON parasol (ON parasol–OFF parasol) cell pairs procedure. To control for this effect, CCFs of all cell are presented. The spike rate was 17 ± 5Hz(11± 6Hz) pairs were inspected, and cell pairs that exhibited obvious, for ON parasol (OFF parasol) cells. Ten identical repeats sharp gaps in the CCF at zero time offset were excluded. of a 60 s stimulus sequence were used for the computation To estimate the influence of imperfect spike sorting, of the shift-corrected CCFs. As a control for stability, the cross-correlation was computed with all cell pairs recordings of 1500 s in the presence of a constant stimulus included. On average across all recordings, the correlation were interleaved after each recording with a stimulus. decreased by 8 ± 11% for cell type combinations with positive correlations, and increased by 3 ± 2% for combinations with negative correlations. The greatest Results impact occurred for combinations of ON parasol cells and ON midget cells (31 ± 12%), and OFF parasol and ON To probe the properties of correlated firing, extracellular midget cells (5 ± 8%), respectively. Overall, 1.7 ± 1.2% of recordings were obtained simultaneously from several cell pairs were excluded. hundred RGCs of identified types in segments of For Figs 2 and 3 and Table 1 the recording duration peripheral macaque monkey retina, using a custom ranged from 1200 to 3600 s (mean: ∼2100 s), and the 512-electrode array and recording system (Litke et al. spike rate was 9 ± 4(7± 4, 7 ± 3, 5 ± 3, 10 ± 7) Hz for 2004). To identify the cell type and response properties ON parasol (OFF parasol, ON midget, OFF midget, small of recorded RGCs, spatio-temporal receptive fields were bistratified) cells. In Fig. 2A (Fig. 3A)theaverageover4–25 measured using reverse correlation with white noise (3–18) cell pairs is presented with a mean number of stimuli (see Chichilnisky, 2001). The five numerically

C 2010 The Authors. Journal compilation C 2010 The Physiological Society Downloaded from J Physiol (jp.physoc.org) at UNIV OF CALIFORNIA-SAN DIEGO on January 10, 2011 J Physiol 589.1 Correlated firing among major ganglion cell types in primate retina 79 dominant RGC types could be identified based on their to fire synchronously (Shlens et al. 2006; Trong & Rieke, density and receptive field properties: ON and OFF mid- 2008). Pairs composed of one ON and one OFF parasol get, ON and OFF parasol, and small bistratified cells cell exhibited negative correlation: the probability of firing (Rodieck, 1998; Dacey, 2004; Field et al. 2007). In some of one cell was reduced when the second cell fired (e.g. A experiments, two other cell types were also identified: and a). At larger distances, correlations were similar but OFF upsilon cells (Petrusca et al. 2007) and a wide-field weaker (e.g. A and C, A and c, a and c). ON cell type of similar density. The receptive fields of To examine the temporal structure of correlated firing, each identified cell type formed a regular mosaic covering CCFs were summarized for each cell type combination. the region of retina recorded (Devries & Baylor, 1997; Figure 2A shows such a summary, for ON and OFF Gauthier et al. 2009a). An example is shown for ON and parasol, ON and OFF midget, small bistratified, OFF OFF parasol cells in Fig. 1A. upsilon and unidentified wide-field ON cells. Average To examine correlated activity generated in the retinal CCFsareshownforpairsofnearbycellsofeachavailable circuitry independently of a specified time-varying cell type combination. The particular cell pairs that stimulus, spontaneous activity was recorded with the comprised these averages were selected to highlight strong retina exposed to steady, spatially uniform illumination correlations and to exclude spike-sorting artifacts (see at a photopic light level. Correlations in the firing of pairs Methods). Some cell type combinations are not shown of cells were examined by inspecting the cross-correlation because insufficient data were available. For pairs of cells of function (CCF) of the spontaneous activity (Fig. 1B). The two different types, the CCFs were selected from cells with CCF shows the correlation coefficient between spike trains, highly overlapping receptive fields. For pairs of the same expressed as a function of a time shift imposed on one spike type, the mosaic organization of receptive fields (Fig. 1) train with respect to the other. Statistically independent implied that cells were never closer together than roughly spike trains would exhibit a CCF of zero at all time offsets. two receptive field radii (see Devries & Baylor, 1997; Instead, for pairs of adjacent ON parasol cells (e.g. A and Gauthier et al. 2009b), and CCFs were selected from cells B), or pairs of adjacent OFF parasol cells (e.g. a and b), that were immediate neighbours in the mosaic. In both the CCF exhibited a substantial peak centred at the origin cases, this selection approach represented the strongest with a width of roughly ±5 ms, consistent with a tendency correlated firing observed between cells of the given types.

Figure 1. Correlated firing among ON and OFF parasol cells A, receptive field outlines of complete ON and OFF mosaics, simultaneously recorded. Outlines are drawn at the 1 S.D. contour of Gaussian fits (see Methods). Rectangle indicates the outline of the electrode array. B, cross-correlation of the spontaneous activity between cells labelled in A; cell pairs are given in insets. Note the positive correlation in the ON–ON and OFF–OFF pairs, the negative correlation in ON–OFF pairs, and the decline in correlation with distance. Bin size: 1 ms.

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Several major trends emerged in the patterns of types. Similar behaviour was observed for OFF cells. Note correlated firing within and across cell types. First, pairs of that in several cases the central peak in the CCF was flanked cells of the same type always exhibited positive correlation, by dips below zero, and some CCFs between different cell though the magnitude of correlation was different in types were asymmetric (see Discussion). different cell types. Second, ON cells exhibited positive To characterize the spatial organization of correlated correlation with ON cells of other types, while ON cells firing, the correlation coefficient at zero time offset was exhibited negative correlations with OFF cells of other examined as a function of distance between the receptive

Photopic ABON parasol OFF parasol ON midget OFF midget small bistratified 0.2 0.02 0.1 0.01 0 0 Correlation ON parasol ON parasol

0.2 0.02 0.1 0.01 0 0 Correlation OFF parasol OFF parasol

0.2 0.02 0.1 0.01 0 0 ON midget Correlation ON midget

0.2 0.02 0.1 0.01 0 0 Correlation OFF midget OFF midget

0.2 0.02 0.1 0.01 0 0 Correlation small bistratified 0246810 small bistratified Distance (sd) 0.02 0.01 0 OFF upsilon

0.02 0.01 0 Correlation Correlation Correlation Correlation Correlation Correlation Correlation ON widefield -50 0 50 -50 0 50 -50 0 50 -50 0 50 -50 0 50

ON parasol OFF parasol ON midget OFF midget small bistratified

Figure 2. Spatial organization of spontaneous correlated firing within and across RGC types at a photo- pic light level. Bin size: 10 ms. Light level: 830 (840, 440) P∗ (L (M, S) cone)−1 s−1) A, average CCF of nearby cell pairs of each cell type combination. Data from ON and OFF parasol, ON and OFF midget, and small bistratified cells were obtained in a single recording; data from OFF upsilon cells and unidentified wide-field ON cells were obtained in separate recordings (bin size: 1 ms; zero bin omitted; grey shaded region represents 1 S.D. across cell pairs). B, correlation coefficient at time zero as a function of distance between cells. Curves show the dependence of the average receptive field overlap on distance (see Methods). In panels that represent correlations between cells of the same type, neighbouring pairs of cells in the mosaic are indicated with black points, other cell pairs are represented with grey points. The normalized nearest neighbour distance is marked with a arrowhead on the abscissa. Bin size: 10 ms.

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fields of the cells, for the five major cell types (Fig. 2B). To characterize the transition of correlations from In all cases, the magnitude of correlated firing declined scotopic to photopic light levels, spontaneous activity smoothly from a peak for the most closely spaced pairs was measured as a function of light level. Figure 4 shows to near zero at distances of 1–2 receptive field diameters, CCFs for pairs of ON parasol cells and for pairs of suggesting that correlations are mediated by local circuitry. ON midget cells. At the lowest light level (0.05 photo- For any given distance, the degree of correlated firing isomerizations per rod per second (P∗ rod−1 s−1)), light varied little across cells, suggesting highly stereotyped responses are driven exclusively by the high-sensitivity circuitry. rod pathway mediated by AII amacrine cells (Murphy & The spatial localization of correlations, and the Rieke, 2006; Field et al. 2009). At the highest light level correlations between cell types (e.g. midget and parasol) (4500 P∗ rod−1 s−1, and 1550, 1570 and 740 P∗ cone−1 s−1 that share little circuitry beyond the photoreceptors, for L, M and S cones, respectively), rods are saturated suggest that a significant contribution to correlated (Field et al. 2009). The threshold for cone vision is firing may be shared noise in cone photoreceptors (see ∼100 P∗ rod−1 s−1 (Rodieck, 1998; Sharpe & Stockman, Discussion). If this were true, the degree of correlated 1999). The disappearance of the broad correlation from firing as a function of distance should be predictable from scotopic to photopic light levels was graded with light level. receptive field overlap. The curves in Fig. 2B show the The strength of the narrow correlation remained roughly overlap between spatial receptive fields as a function of constant as a function of light level. the distance between them. The amplitudes of the curves If a significant source of spontaneous correlated firing is were fitted independently to the data from each cell type shared noise in cone photoreceptors (see Discussion), then combination (see Methods). These curves provided an these correlations might be expected to add to correlations adequate account of correlated firing. Table 1 provides a induced by visual stimuli. A test of this possibility is quantitative summary of the amplitudes of the curves. shown in Fig. 5 for stimuli with spatial correlations Note that the analysis was performed between small of increasing extent. The fast correlations present in bistratified cells and other cell types, despite the fact that constant illumination (Fig. 5, left panel) are superim- small bistratified cells receive dominant input from S cones posed on a broader peak that grows with the spatial while the other cell types receive dominant input from L extent of correlations in the stimulus (raw CCF). CCFs and M cones (see Discussion). between different repeats of the identical stimulus reveal To probe correlated firing in conditions in which visual the correlations induced by the stimulus alone (shuffled signals are driven by rods, spontaneous activity was CCF, or shift predictor, see Methods). The difference recorded at a scotopic light level. Figure 3A shows CCFs between the raw CCF and the shuffled CCF reveals for the same cell types under these conditions. Three main stimulus-independent correlations, under the assumption trends emerge. First, prominent peaks and troughs similar of additivity (corrected CCF). The corrected CCF is to those visible in the CCFs at the photopic light level similar to the CCF of the spontaneous activity, though the (Fig. 2A) were largely preserved, with similar dynamics, at magnitude of the former is lower, perhaps due to firing the scotopic light level. Second, these peaks and troughs rate saturation. The mean corrected correlation strength were superimposed on much broader peaks and troughs for distant cell pairs falls to zero, as do the spontaneous not observed at photopic light level. Third, the overall correlations (data not shown). pattern of positive and negative correlations within and across cell types was similar to the results at the photo- pic light level. The pattern of correlated firing over space Discussion wasalsolargelypreserved.ThecurvesinFig.3B show the correlation at zero time offset as a function of distance This study surveyed correlated firing among seven RGC between cells. The trend is broadly similar to the results types in macaque retina. The findings are broadly obtained at the photopic light level. consistent with previous findings in non-primate species, ThebroaderCCFsatscotopiclightlevels,andthe but also provide clarifications and raise questions about patterns across different ON and OFF cell types, suggest mechanism. a significant contribution to correlated firing from shared Many of the present findings mirror seminal findings in noise or quantal events in rod photoreceptors (see the cat retina (Mastronarde, 1983a,b,c) including: rapid Discussion). The curves in Fig. 3B show the predictions correlated firing within several cell types at photopic light of the receptive field overlap model used in Fig. 2B,but levels, positive correlations between cells of the same light with receptive fields measured at the scotopic light level. response polarity, negative correlations between ON and Again, these curves largely capture the dependence of OFF cells of several types, variation in correlation strength correlated firing on distance, consistent with an origin in in different cell types, systematic decline in correlation photoreceptor noise. A quantitative summary is given in with distance, and slow correlations at scotopic light levels. Table 1. Previous findings in rabbit retina also highlighted the

C 2010 The Authors. Journal compilation C 2010 The Physiological Society Downloaded from J Physiol (jp.physoc.org) at UNIV OF CALIFORNIA-SAN DIEGO on January 10, 2011 82 M. Greschner and others J Physiol 589.1 diversity of correlated firing between different cell types 1999), but the large number of cell pairs obtained in (DeVries, 1999). the present work provide a more complete picture. This A striking feature of the present results is the stereotyped regularity would be difficult to observe if distinct cell types degree of correlated firing in a given pair of cell types at a were not considered separately. given distance, i.e. the small vertical scatter in each panel The present findings are largely consistent with the idea of Figs 2B and 3B (see Shlens et al. 2006). This precision that shared photoreceptor noise contributes significantly is reminiscent of the exquisite precision of the mosaic to correlated firing in RGCs. First, correlations between organization of RGC receptive fields (Devries & Baylor, midget and parasol cells suggest an origin in photo- 1997; Gauthier et al. 2009a), suggesting that correlations receptors, because midget and parasol cells are known to are mediated by stereotyped local circuitry and perhaps receive input from different types of bipolar cells (Boycott even the same circuitry that forms the receptive fields. A & Wassle, 1991). Second, at both scotopic and photo- hint of this precision was visible in previous work in cat pic light levels, the dependence of correlated firing on retina (Mastronarde, 1983a) and rabbit retina (DeVries, distance was roughly proportional to receptive field over-

Scotopic ABON parasol OFF parasol ON midget OFF midget small bistratified 0.04 0.2 0.02 0.1 0 0 Correlation ON parasol ON parasol

0.04 0.2 0.02 0.1 0 0 Correlation OFF parasol OFF parasol

0.04 0.2 0.02 0.1 0 0 Correlation ON midget ON midget

0.04 0.2 0.02 0.1 0 0 Correlation Correlation Correlation Correlation Correlation OFF midget OFF midget

0.04 0.2 0.02 0.1 0 0 Correlation Correlation small bistratified small bistratified 0246810 0.04 Distance (sd)

0.02

0 Correlation OFF upsilon

0.04

0.02

0 Correlation ON widefield -100 0 100 -100 0 100 -100 0 100 -100 0 100 -100 0 100

ON parasol OFF parasol ON midget OFF midget small bistratified

Figure 3. Spatial organization of spontaneous correlated firing within and across RGC types at a scotopic light level Panels are as in Fig. 2. All data were obtained in a single recording. Light level: 1.2 P∗ rod−1s−1.

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scotopic photopic 0.05 P* rod-1 s-1 1.1 22 225 4500 ON parasol - ON parasol 0.03

0.02

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ON midget - ON midget 0.03

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Figure 4. CCFs across light levels for pairs of ON parasol cells and pairs of ON midget cells The light level increases from left to right. 4500 P∗ rod−1 s−1 corresponds to 1550 (1570, 740) P∗ (L (M, S) cone)−1 s−1.Binsize:1ms. lap, and the overall pattern of correlations across cell types showed that RGC types with little shared circuitry other was preserved. A significant contribution of rod photo- than cones exhibit correlations at photopic light levels, receptor noise at scotopic light levels was indicated by and that the kinetics of cone noise are sufficiently previous work in cat retina relating the kinetics rapid to mediate correlations (Ala-Laurila P & Rieke F, and statistics of correlations to quantal events in unpublished observations). rods (Mastronarde, 1983b). At photopic light levels, Correlationsinheritedfromsharedphotoreceptornoise previous work has argued against a substantial are likely to be modified by the retinal circuitry and contribution of cone photoreceptor noise, based on the intrinsic properties of RGCs. For example, the timing of rapid kinetics of correlations compared to cone light signal transmission in different circuits probably shapes responses (Mastronarde, 1983c; Brivanlou et al. 1998; the kinetics of correlations in different RGC types, DeVries, 1999). However, recent work in primate retina and non-linearities in synaptic transmission and spike

constant background spatially correlated visual stimulation μ ON parasol - ON parasol S.D.: 22 m 44 88 176 0.04

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0.04 raw CCF shuffled CCF 0.02 corrected CCF

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Figure 5. CCFs in the presence of stimuli with correlations of increasing spatial extent, for pairs of ON parasol cells and pairs of one ON and one OFF parasol cell Left: CCFs of activity during constant illumination. Four CCFs are overlaid from recordings interleaved between recordings with visual stimulation. Right: CCFs in the presence of a time-varying stimulus (see text for details). Extent of spatial correlation in the stimulus is expressed as the standard deviation of the low-pass filter used to construct the stimuli. The mean ON parasol receptive field diameter was ∼140 μm. For each condition, the raw CCF, the CCF from shuffled identical stimulus repeats (shift predictor), and the difference between the two (corrected CCF) are shown. Grey shaded region represents 1 S.D. across cell pairs; for clarity this is only shown for the corrected CCF. Bin size: 1 ms.

C 2010 The Authors. Journal compilation C 2010 The Physiological Society Downloaded from J Physiol (jp.physoc.org) at UNIV OF CALIFORNIA-SAN DIEGO on January 10, 2011 84 M. Greschner and others J Physiol 589.1 generation may further modify correlation structure. Also, than a quarter of the area of the central peak of the CCFs differences in the spike-timing structure of different RGC of ON parasol cells (Trong & Rieke, 2008). types are likely to affect the observed CCFs. These factors Second, small bistratified cells exhibited positive may explain why CCFs are symmetric within a cell type correlations with ON midget and ON parasol cells at but often asymmetric between cell types, and why CCFs photopic light levels. This seems potentially inconsistent involving wide-field cell types show structure offset from with an origin in shared cone noise, because the ON zero. Also, many CCFs exhibited flanking dips that are component of the small bistratified cell light response is qualitatively consistent with a tendency for spikes in each driven by short wavelength-sensitive (S) cones, whereas cell to be separated from one another in time: if the firing the light responses of ON parasol and ON midget cells of two cells is correlated, and the firing of each cell is are dominated by long and middle wavelength-sensitive followed by a reduction in its own firing probability, then (L and M) cones (Sun et al. 2006; Tailby et al. 2008; Field the firing of each cell should be associated with reduced et al. 2010; but see Chatterjee2002, Lee2007). Indeed, L firing in the other cell earlier and later. and M cones provide an OFF input to small bistratified The broader CCFs at scotopic light levels are believed to cells (Dacey & Lee, 1994). One possible explanation is originate from quantal noise events in rod photoreceptors that strong input to small bistratified cells (Mastronarde, 1983b). Surprisingly, fast correlations (Ghosh & Grunert, 1999) contributes to correlations with presentatphotopiclightlevelswerealsopresentatscotopic other cell types. At scotopic light levels, the additional slow light levels, superimposed on the broader correlations correlations between small bistratified and other ON cell arising from rod noise. Many studies have indicated types are more easily explained because small bistratified that the rod signalling pathways are optimized for the cells, like midget and parasol cells, receive strong input transmission of signals representing the absorption of from rods (Crook et al. 2009; Field et al. 2009). individual photons in rods, along with the required mini- In general, correlated activity between RGCs can be mization of noise (see Field et al. 2005). In this context, produced by a combination of two factors: shared noise it is surprising that a substantial component of the fast arising in common circuitry such as shared photo- correlations, which may originate in cone noise, remains receptors, and shared signal arising from stimuli with visible in RGCs, possibly degrading the fidelity of single spatial correlations. It is unclear whether these two sources photon responses. However, the scotopic experiments of correlations combine independently in natural vision, were performed in the presence of a dim background light, or alternatively, whether the noise depends on the signal. a condition in which retinal signalling may not be at its In the present data, shared noise alone produced fast peak sensitivity. Furthermore, fast correlations exhibit a spontaneous correlations in nearby RGCs. The addition frequency structure different from the slow scotopic visual of stimuli with spatial correlations introduced slower signal, and therefore may not present a serious problem. correlations (Meister et al. 1995; DeVries, 1999; Pillow Note that the mixture of fast and slow correlations at et al. 2008), in a roughly additive manner for weak stimuli scotopic light levels also complicates the interpretation (Fig. 5). Thus, measurements of spontaneous activity of the receptive field overlap model fitted to the data in provide an approximate indication of noise correlations Fig. 3B. present in visual signals transmitted to the brain. However, Previous work in other species has provided signal and noise correlations were not additive for strong evidence that mechanisms other than photoreceptor visual stimuli. This failure of additivity may reflect noise contribute to correlations, including gap junction saturation in the spike rate at times of high (or low) coupling and diverging signals from interneurons firing probability, when it is unlikely that an added noise (Mastronarde, 1983a,c; Brivanlou et al. 1998; DeVries, source could increase (or decrease) the firing rate. A 1999). Indeed, two observations in the present work test of this hypothesis would be to examine whether the appear to reflect factors other than shared photoreceptor correlations observed with and without visual stimuli are noise. explained by models of light response in which stimulus First, pairs of ON parasol, but not OFF parasol cells and noise add, but a non-linearity in spike generation exhibited bimodal CCFs at a fine timescale (not shown), produces saturation. This would indicate the degree consistent with previous findings (Trong & Rieke, 2008; to which measurements of spontaneous correlations Shlens et al. 2008). This observation strongly suggests reveal the noise correlations present during natural gap junction coupling, probably through intermediate vision. amacrine cells (Dacey & Brace, 1992; Jacoby et al. 1996). The data presented here are largely consistent with The reciprocal coupling between ON parasol cells may a model in which RGCs that share cone photoreceptor contributetothefactthatreceptivefieldoverlapprovided input also share cone noise that produces correlated firing a slightly less accurate description of correlation as a (Ala-Laurila P & Rieke F, unpublished observations). function of distance than it did for other cell types More distant RGCs that share fewer cones exhibit weaker (Fig. 2B). Reciprocal coupling probably accounts for less correlations. Cone noise is modified by the specific retinal

C 2010 The Authors. Journal compilation C 2010 The Physiological Society Downloaded from J Physiol (jp.physoc.org) at UNIV OF CALIFORNIA-SAN DIEGO on January 10, 2011 J Physiol 589.1 Correlated firing among major ganglion cell types in primate retina 85 circuitry and intrinsic properties of each RGC type, giving Field GD, Gauthier JL, Sher A, Greschner M, Machado T, rise to a distinct form of the CCF for each RGC type pair. Jepson LH, Shlens J, Gunning DE, Mathieson K, Dabrowski Other sources of correlations, such as reciprocal coupling W, Paninski L, Litke AM & Chichilnisky EJ (2010). Mapping and diverging input from interneurons, play a smaller role. a neural circuit: a complete input-output diagram in the At scotopic light levels, slow correlations from quantal primate retina. Nature (in press). Field GD, Greschner M, Gauthier JL, Rangel C, Shlens J, Sher noise in rod photoreceptors add to the fast cone noise A, Marshak DW, Litke AM & Chichilnisky EJ (2009). correlations. 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