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Inhibition, Spike Threshold, and Stimulus Selectivity in Primary Visual Cortex

2008; Cell Press; Volume: 57; Issue: 4 Linguagem: Inglês

10.1016/j.neuron.2008.02.005

1097-4199

Nicholas J. Priebe, David Ferster,

Neurobiology and Insect Physiology Research

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition. Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition. Since Hartline described inhibition between adjacent photoreceptors in the limulus retina (Hartline, 1949Hartline H.K. Inhibition of activity of visual receptors by illuminating nearby retinal areas in the Limulus eye.Fed. Proc. 1949; 8: 69Google Scholar), the principle of lateral inhibition has become deeply embedded in neuroscience. In Hartline's original experiments, lateral inhibition operated purely in the spatial domain, heightening the difference between adjacent photoreceptors' responses to a spatially localized stimulus. The modern concept of lateral inhibition has expanded to incorporate distance along almost any axis in sensory space, in virtually every sensory modality. Lateral inhibition is thought to occur between whiskers in the somatosensory system (Moore and Nelson, 1998Moore C.I. Nelson S.B. Spatio-temporal subthreshold receptive fields in the vibrissa representation of rat primary somatosensory cortex.J. Neurophysiol. 1998; 80: 2882-2892PubMed Google Scholar, Zhu and Connors, 1999Zhu J.J. Connors B.W. Intrinsic firing patterns and whisker-evoked synaptic responses of neurons in the rat barrel cortex.J. Neurophysiol. 1999; 81: 1171-1183PubMed Google Scholar), between odors in the olfactory system (Wilson and Mainen, 2006Wilson R.I. Mainen Z.F. Early events in olfactory processing.Annu. Rev. Neurosci. 2006; 29: 163-201Crossref PubMed Scopus (179) Google Scholar), between sounds of different frequency (Brosch and Schreiner, 1997Brosch M. Schreiner C.E. Time course of forward masking tuning curves in cat primary auditory cortex.J. Neurophysiol. 1997; 77: 923-943PubMed Google Scholar, Calford and Semple, 1995Calford M.B. Semple M.N. Monaural inhibition in cat auditory cortex.J. Neurophysiol. 1995; 73: 1876-1891PubMed Google Scholar), between different phonemes (Crutch and Warrington, 2001Crutch S.J. Warrington E.K. Refractory dyslexia: evidence of multiple task-specific phonological output stores.Brain. 2001; 124: 1533-1543Crossref PubMed Google Scholar, Mirman et al., 2005Mirman D. McClelland J.L. Holt L.L. Computational and behavioral investigations of lexically induced delays in phoneme recognition.J. Mem. Lang. 2005; 52: 424-433Crossref Scopus (8) Google Scholar), and between different tastes in the gustatory system (Vandenbeuch et al., 2004Vandenbeuch A. Pillias A.M. Faurion A. Modulation of taste peripheral signal through interpapillar inhibition in hamsters.Neurosci. Lett. 2004; 358: 137-141Crossref PubMed Scopus (13) Google Scholar). An underlying assumption in each case is that the excitatory afferents from the earlier stages of processing provide a weak bias toward a preferred stimulus and establish only a rough outline of a cell's tuning. Lateral inhibition then sharpens sensory tuning to its final state by vetoing any residual excitation evoked by nonpreferred stimuli. In this way, lateral inhibition could provide considerable computational power to neuronal circuits. In the primary visual cortex (V1), lateral inhibition has been proposed to refine neuronal selectivity in a number of domains, sharpening orientation and direction tuning, making tuning independent of stimulus strength, and generating suppressive interactions between different stimuli (Crook et al., 1998Crook J.M. Kisvarday Z.F. Eysel U.T. Evidence for a contribution of lateral inhibition to orientation tuning and direction selectivity in cat visual cortex: reversible inactivation of functionally characterized sites combined with neuroanatomical tracing techniques.Eur. J. Neurosci. 1998; 10: 2056-2075Crossref PubMed Scopus (91) Google Scholar, Eysel et al., 1990Eysel U.T. Crook J.M. Machemer H.F. GABA-induced remote inactivation reveals cross-orientation inhibition in the cat striate cortex.Exp. Brain Res. 1990; 80: 626-630Crossref PubMed Scopus (55) Google Scholar, Sompolinsky and Shapley, 1997Sompolinsky H. Shapley R. New perspectives on the mechanisms for orientation selectivity.Curr. Opin. Neurobiol. 1997; 7: 514-522Crossref PubMed Scopus (198) Google Scholar, Worgotter and Eysel, 1991Worgotter F. Eysel U.T. Topographical aspects of intracortical excitation and enhibition contributing to orientation specificity in area 17 of the cat visual cortex.Eur. J. Neurosci. 1991; 3: 1232-1244Crossref PubMed Google Scholar). And yet, inhibition measured in intracellular recordings from primary sensory areas often lacks the necessary properties to support lateral inhibition: inhibitory inputs are most often tuned to the same stimuli as the excitatory inputs, and inhibition evoked by nonpreferred stimuli is generally weak (Anderson et al., 2000aAnderson J.S. Carandini M. Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex.J. Neurophysiol. 2000; 84: 909-926PubMed Google Scholar, Tan et al., 2004Tan A.Y. Zhang L.I. Merzenich M.M. Schreiner C.E. Tone-evoked excitatory and inhibitory synaptic conductances of primary auditory cortex neurons.J. Neurophysiol. 2004; 92: 630-643Crossref PubMed Scopus (176) Google Scholar, Wehr and Zador, 2003Wehr M. Zador A.M. Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex.Nature. 2003; 426: 442-446Crossref PubMed Scopus (583) Google Scholar). In addition, inactivation of the cortical circuit (including both excitatory and inhibitory components) does not degrade the selectivity derived from the remaining feed-forward synaptic inputs (Chung and Ferster, 1998Chung S. Ferster D. Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression.Neuron. 1998; 20: 1177-1189Abstract Full Text Full Text PDF PubMed Scopus (171) Google Scholar, Ferster et al., 1996Ferster D. Chung S. Wheat H. Orientation selectivity of thalamic input to simple cells of cat visual cortex.Nature. 1996; 380: 249-252Crossref PubMed Scopus (349) Google Scholar). For orientation selectivity in particular, the contradiction between these two lines of evidence—the apparent need for lateral inhibition to explain response properties, and the apparent lack of lateral inhibition observed in many experiments—has driven considerable controversy. Here, we discuss these two divergent views and outline a possible resolution. We find that a simple feed-forward model—without the inclusion of lateral inhibition—can replicate the receptive field properties of cortical neurons in considerable detail. That is, the complex aspects of cortical responses that have most often been attributed to lateral inhibition can be explained parsimoniously from simple, well-characterized, nonlinear features of the feed-forward excitatory pathways, such as spike threshold, contrast saturation, and spike rectification. One goal of systems neuroscience lies in understanding the mechanisms underlying high-level processing, such as object recognition, language, and decision making. We are, however, just at the early stages of defining the computations that are performed in accomplishing these tasks, let alone understanding the circuitry that performs them. In contrast, the computations performed by V1—extracting orientation and direction of motion from the visual image, for example—are simple enough to define and measure with great precision and yet complex enough to be interesting, making the visual cortex an ideal area in which to study neural computation in detail. Because of the relative homogeneity of the cortical circuitry from area to area, most students of primary visual cortex subscribe to the view that what we learn about the principles of cortical processing there will apply to higher levels (Creutzfeldt, 1977Creutzfeldt O.D. Generality of the functional structure of the neocortex.Naturwissenschaften. 1977; 64: 507-517Crossref PubMed Scopus (95) Google Scholar). If this belief is correct, then the question of whether lateral inhibition is a critical component of processing in primary visual cortex has implications throughout cortex. When Hubel and Wiesel, 1962Hubel D.H. Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.J. Physiol. 1962; 160: 106-154Crossref PubMed Scopus (4977) Google Scholar first described cortical orientation selectivity, they proposed an elegantly simple model for its origin that still serves as a central reference point. According to the model, simple cells in V1, the primary thalamo-recipient cells, become orientation selective by virtue of convergent input from thalamic neurons whose receptive fields are arranged in rows. A stimulus of the preferred orientation therefore activates all of the relay cells in a row simultaneously (Figure 1A), whereas the orthogonal (null) orientation activates only a few relay cells at a time. By virtue of the simple cell's spike threshold, only the large-amplitude response to the preferred stimulus evokes action potentials (Figure 1B). There is compelling evidence that the spatial organization of the feed-forward input generates the ON-OFF spatial organization of simple cells' receptive fields and a consequent bias for orientation. (1) Simple cells are located in layers 4 and 6, the layers in which geniculate relay cell axons terminate (Hirsch and Martinez, 2006Hirsch J.A. Martinez L.M. Circuits that build visual cortical receptive fields.Trends Neurosci. 2006; 29: 30-39Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar, Martinez et al., 2005Martinez L.M. Wang Q. Reid R.C. Pillai C. Alonso J.M. Sommer F.T. Hirsch J.A. Receptive field structure varies with layer in the primary visual cortex.Nat. Neurosci. 2005; 8: 372-379Crossref PubMed Scopus (110) Google Scholar). (2) The aggregate preferred orientation of the relay cells that innervate a cortical orientation column matches the preferred orientation of the cells in the column (Chapman et al., 1991Chapman B. Zahs K.R. Stryker M.P. Relation of cortical cell orientation selectivity to alignment of receptive fields of the geniculocortical afferents that arborize within a single orientation column in ferret visual cortex.J. Neurosci. 1991; 11: 1347-1358PubMed Google Scholar). A similar match occurs in the connection between layer 4 to layer 2/3, where orientation selectivity emerges in the tree shrew (Mooser et al., 2004Mooser F. Bosking W.H. Fitzpatrick D. A morphological basis for orientation tuning in primary visual cortex.Nat. Neurosci. 2004; 7: 872-879Crossref PubMed Scopus (46) Google Scholar). (3) The majority of simple cells receive monosynaptic input from geniculate relay cells (Ferster et al., 1996Ferster D. Chung S. Wheat H. Orientation selectivity of thalamic input to simple cells of cat visual cortex.Nature. 1996; 380: 249-252Crossref PubMed Scopus (349) Google Scholar, Ferster and Lindström, 1983Ferster D. Lindström S. An intracellular analysis of geniculocortical connectivity in area 17 of the cat.J. Physiol. 1983; 342: 181-215Crossref PubMed Google Scholar). (4) Any relay cell that connects to a simple cell has the matching polarity (ON- or OFF-center) to the simple cell subfield with which its receptive field overlaps (Reid and Alonso, 1995Reid R.C. Alonso J.M. Specificity of monosynaptic connections from thalamus to visual cortex.Nature. 1995; 378: 281-284Crossref PubMed Google Scholar, Jin et al., 2008Jin J.Z. Weng C. Yeh C.I. Gordon J.A. Ruthazer E.S. Stryker M.P. Swadlow H.A. Alonso J.M. On and off domains of geniculate afferents in cat primary visual cortex.Nat. Neurosci. 2008; 11: 88-94Crossref PubMed Scopus (65) Google Scholar, Tanaka, 1983Tanaka K. Cross-correlation analysis of geniculostriate neuronal relationships in cats.J. Neurophysiol. 1983; 49: 1303-1318PubMed Google Scholar). While purely feed-forward models have been able to account for the foundation of cortical orientation tuning, up to now they have been largely unable to account for a number of critical features of simple cell behavior. These include (1) the sharpness of orientation tuning, which is far narrower than predicted by the spatial organization of the feed-forward input; (2) crossorientation suppression, in which a stimulus of the nonpreferred orientation suppresses the response to a stimulus of the preferred orientation; (3) contrast invariance of orientation tuning, in which simple cells fail to respond to nonpreferred stimuli of any strength (contrast), and the width of orientation tuning varies little with changes in the contrast; and (4) dynamics of orientation tuning, in which tuning width narrows over the time course of a response. These apparent failures of feed-forward models have long been considered to be classical cases in which lateral inhibition—in the form of crossorientation inhibition—is required to shape neuronal selectivity. We will examine each of these features in turn and show that each can, in fact, be accounted for by excitatory relay cell input to simple cells, without lateral inhibition. Here, we focus almost exclusively on the visual cortex of the cat, where many of the relevant experiments have been performed. In the primate visual cortex, an additional set of orientation unselective cells in layer 4C is likely interposed between the thalamic relay cells and orientation selective simple cells (Hubel and Wiesel, 1968Hubel D.H. Wiesel T.N. Receptive fields and functional architecture of monkey striate cortex.J. Physiol. 1968; 195: 215-243Crossref PubMed Scopus (2628) Google Scholar). Although they remain to be tested, many of the same arguments that we make here for the cat visual cortex might apply to the primate visual cortex. If orientation tuning were derived solely from the spatial organization of relay cell input, an important prediction would follow: it should be possible, using a simple linear model, to derive the orientation tuning curve of any simple cell from a detailed map of its receptive field. In cells with short, wide subregions (Figure 2A, bottom), a bar stimulus can be rotated far away from the preferred orientation and still overlap with a large portion of the ON region, giving rise to broad orientation tuning. In contrast, long, narrow receptive field subregions (Figure 2A, top) should make a cell extremely sensitive to small changes in orientation and give rise to a narrow orientation tuning curve. While this general trend is often observed, the predicted quantitative relationship between receptive field maps and orientation tuning width is not. When based on the firing rate responses of neurons, the measured orientation tuning is up to three times narrower than linear predictions (Figure 2B) (Gardner et al., 1999Gardner J.L. Anzai A. Ohzawa I. Freeman R.D. Linear and nonlinear contributions to orientation tuning of simple cells in the cat's striate cortex.Vis. Neurosci. 1999; 16: 1115-1121Crossref PubMed Scopus (70) Google Scholar, Jones and Palmer, 1987Jones J.P. Palmer L.A. The two-dimensional spatial structure of simple receptive fields in cat striate cortex.J. Neurophysiol. 1987; 58: 1187-1211PubMed Google Scholar). This mismatch has often been interpreted as evidence for lateral inhibition between neurons of different orientation preferences, also called crossorientation inhibition (Figure 2C, red curve). Such inhibition could suppress the effect of feed-forward excitation at nonpreferred orientations (green curve), thereby narrowing the tuning of the net changes in membrane potential (black curve). In the figure, inhibition peaks at orientations away from the preferred orientation. Lateral inhibition could also peak at the preferred orientation and be more broadly tuned than excitation or be largely untuned for orientation (Ben-Yishai et al., 1995Ben-Yishai R. Bar-Or R.L. Sompolinsky H. Theory of orientation tuning in visual cortex.Proc. Natl. Acad. Sci. USA. 1995; 92: 3844-3848Crossref PubMed Google Scholar, Hirsch et al., 2003Hirsch J.A. Martinez L.M. Pillai C. Alonso J.M. Wang Q. Sommer F.T. Functionally distinct inhibitory neurons at the first stage of visual cortical processing.Nat. Neurosci. 2003; 6: 1300-1308Crossref PubMed Scopus (118) Google Scholar, Somers et al., 1995Somers D.C. Nelson S.B. Sur M. An emergent model of orientation selectivity in cat visual cortical simple cells.J. Neurosci. 1995; 15: 5448-5465PubMed Google Scholar, Sompolinsky et al., 1990Sompolinsky H. Golomb D. Kleinfeld D. Global processing of visual stimuli in a neural network of coupled oscillators.Proc. Natl. Acad. Sci. USA. 1990; 87: 7200-7204Crossref PubMed Google Scholar, Sompolinsky and Shapley, 1997Sompolinsky H. Shapley R. New perspectives on the mechanisms for orientation selectivity.Curr. Opin. Neurobiol. 1997; 7: 514-522Crossref PubMed Scopus (198) Google Scholar, Troyer et al., 2002Troyer T.W. Krukowski A.E. Miller K.D. LGN input to simple cells and contrast-invariant orientation tuning: an analysis.J. Neurophysiol. 2002; 87: 2741-2752PubMed Google Scholar). In either case, inhibition evoked by stimuli far from the preferred orientation would suppress the excitatory input and effectively narrow the orientation tuning of the spike output. The most direct way to test for the presence of synaptic inhibition is through intracellular recording. Inhibition could reveal itself as a frank hyperpolarization. Simultaneous excitation and inhibition, however, might antagonize one another and generate no net change in membrane potential, making it necessary to measure changes in inhibitory conductance, either using voltage-clamp in vivo (Borg-Graham et al., 1998Borg-Graham L.J. Monier C. Fregnac Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons.Nature. 1998; 393: 369-373Crossref PubMed Scopus (425) Google Scholar), or current-clamp with different levels of injected current (Anderson et al., 2000aAnderson J.S. Carandini M. Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex.J. Neurophysiol. 2000; 84: 909-926PubMed Google Scholar, Douglas et al., 1991Douglas R.J. Martin K.A.C. Whitteridge D. An intracellular analysis of the visual responses of neurones in cat visual cortex.J. Physiol. 1991; 440: 659-696Crossref PubMed Google Scholar, Ferster, 1986Ferster D. Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex.J. Neurosci. 1986; 6: 1284-1301PubMed Google Scholar, Hirsch et al., 1998Hirsch J.A. Alonso J.M. Reid R.C. Martinez L.M. Synaptic integration in striate cortical simple cells.J. Neurosci. 1998; 18: 9517-9528PubMed Google Scholar, Martinez et al., 2002Martinez L.M. Alonso J.M. Reid R.C. Hirsch J.A. Laminar processing of stimulus orientation in cat visual cortex.J. Physiol. 2002; 540: 321-333Crossref PubMed Scopus (72) Google Scholar). In these latter studies, synaptic inhibition in layer 4 cells was tuned to the same orientation as synaptic excitation and firing rate responses. The preferred stimulus increases the conductance of a cell by 100% or more (Anderson et al., 2000aAnderson J.S. Carandini M. Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex.J. Neurophysiol. 2000; 84: 909-926PubMed Google Scholar, Borg-Graham et al., 1998Borg-Graham L.J. Monier C. Fregnac Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons.Nature. 1998; 393: 369-373Crossref PubMed Scopus (425) Google Scholar, Douglas et al., 1991Douglas R.J. Martin K.A.C. Whitteridge D. An intracellular analysis of the visual responses of neurones in cat visual cortex.J. Physiol. 1991; 440: 659-696Crossref PubMed Google Scholar, Ferster, 1986Ferster D. Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex.J. Neurosci. 1986; 6: 1284-1301PubMed Google Scholar, Martinez et al., 2002Martinez L.M. Alonso J.M. Reid R.C. Hirsch J.A. Laminar processing of stimulus orientation in cat visual cortex.J. Physiol. 2002; 540: 321-333Crossref PubMed Scopus (72) Google Scholar). Null-oriented stimuli, by comparison, rarely increase the conductance of a neuron by more than 25%, and most often by far less (Anderson et al., 2000aAnderson J.S. Carandini M. Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex.J. Neurophysiol. 2000; 84: 909-926PubMed Google Scholar, Priebe and Ferster, 2006Priebe N.J. Ferster D. Mechanisms underlying cross-orientation suppression in cat visual cortex.Nat. Neurosci. 2006; 9: 552-561Crossref PubMed Scopus (92) Google Scholar), which may be too small to make a significant contribution to orientation selectivity. A second method to determine whether intracortical inhibition shapes orientation tuning is to measure orientation tuning while inactivating inhibition. The removal of inhibition by extracellular application of bicuculline does indeed alter receptive field structure (Sillito, 1975Sillito A.M. The contribution of inhibitory mechanisms to the receptive field properties of neurones in the striate cortex of the cat.J. Physiol. 1975; 250: 305-329Crossref PubMed Scopus (419) Google Scholar) and broaden orientation tuning (Sillito et al., 1980Sillito A.M. Kemp J.A. Milson J.A. Berardi N. A re-evaluation of the mechanisms underlying simple cell orientation selectivity.Brain Res. 1980; 194: 517-520Crossref PubMed Scopus (148) Google Scholar). There is some question, however, as to whether widespread inactivation of inhibition may render the cortical network unstable and thereby broaden the orientation tuning of intracortical excitation. To avoid this potential problem, inhibitory input was selectively inactivated in single cortical neurons by intracellular application of DIDS or picrotoxin (Nelson et al., 1994Nelson S. Toth L. Sheth B. Sur M. Orientation selectivity of cortical neurons during intracellular blockade of inhibition.Science. 1994; 265: 774-777Crossref PubMed Google Scholar), with little effect on orientation tuning. As an alternative to pharmacological inactivation, intracortical inhibition and excitation were inactivated simultaneously by local cooling (Ferster et al., 1996Ferster D. Chung S. Wheat H. Orientation selectivity of thalamic input to simple cells of cat visual cortex.Nature. 1996; 380: 249-252Crossref PubMed Scopus (349) Google Scholar) or electrical stimulation (Chung and Ferster, 1998Chung S. Ferster D. Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression.Neuron. 1998; 20: 1177-1189Abstract Full Text Full Text PDF PubMed Scopus (171) Google Scholar). In both cases, the remaining synaptic inputs, which predominately arise from the thalamic feed-forward pathway, had similar orientation tuning to the intact cell, suggesting that inhibition is not significantly narrowing orientation tuning. If not lateral inhibition, what makes the width of orientation tuning narrower than that predicted by the map of a simple cell's receptive field? Both Gardner et al., 1999Gardner J.L. Anzai A. Ohzawa I. Freeman R.D. Linear and nonlinear contributions to orientation tuning of simple cells in the cat's striate cortex.Vis. Neurosci. 1999; 16: 1115-1121Crossref PubMed Scopus (70) Google Scholar and Jones and Palmer, 1987Jones J.P. Palmer L.A. The two-dimensional spatial structure of simple receptive fields in cat striate cortex.J. Neurophysiol. 1987; 58: 1187-1211PubMed Google Scholar hypothesized that orientation tuning could be narrowed by spike threshold. In this scenario, only the largest membrane potential deflections, those evoked by orientations close to the preferred orientation, evoke spikes (Figure 2D), a phenomenon referred to as the “iceberg effect” (Rose and Blakemore, 1974Rose D. Blakemore C. Effects of bicuculline on functions of inhibition in visual cortex.Nature. 1974; 249: 375-377Crossref PubMed Google Scholar). This hypothesis makes two critical predictions. First, the orientation tuning for spike rate should be significantly narrower than the tuning for membrane potential. This predicted narrowing is shown for a single cell in Figure 2E, and for a population of cells in Figure 2F. The average narrowing (about 3-fold; Figure 2B) is very similar to the average mismatch between tuning width predicted from receptive field maps and tuning width measured from spike rate (Carandini and Ferster, 2000Carandini M. Ferster D. Membrane potential and firing rate in cat primary visual cortex.J. Neurosci. 2000; 20: 470-484PubMed Google Scholar, Volgushev et al., 2000Volgushev M. Pernberg J. Eysel U.T. Comparison of the selectivity of postsynaptic potentials and spike responses in cat visual cortex.Eur. J. Neurosci. 2000; 12: 257-263Crossref PubMed Scopus (47) Google Scholar). The second prediction of the iceberg effect is that a simple cell's receptive field map should accurately predict the width of orientation tuning as measured not from spike rate responses (Figure 2B), but from membrane potential responses (Lampl et al., 2001Lampl L. Anderson J.S. Gillespie D. Ferster D. Prediction of orientation selectivity from receptive field architecture in simple cells of cat visual cortex.Neuron. 2001; 30: 263-274Abstract Full Text Full Text PDF PubMed Scopus (58) Google Scholar). Receptive field maps for two cells, one with long narrow subfields and one with short, broad subfields are shown in Figure 2G, together with predicted and measured orientation tuning curves of membrane potential responses (Figure 2H). For these cells, and for the population (Figure 2I), measurement and prediction match well. The sharpness of orientation tuning, then, can be accounted for quantitatively by feed-forward geniculo-cortical input to simple cells, as long as the nonlinear effects of threshold are taken into account. The most compelling evidence for lateral inhibition has come from the strong functional interactions between stimuli of different orientation, called crossorientation suppression. In psychophysical experiments, it has been shown that the detectability of one oriented stimulus is lowered by superimposing a second stimulus of the orthogonal orientation (Campbell and Kulikowski, 1966Campbell F.W. Kulikowski J.J. Orientational selectivity of the human visual system.J. Physiol. 1966; 187: 437-445Crossref PubMed Scopus (340) Google Scholar). At the single-cell level, the spike responses of a cortical neuron to a stimulus of the preferred orientation are reduced by superimposing an orthogonal stimulus (Bishop et al., 1973Bishop P.O. Coombs J.S. Henry G.H. Receptive fields of simple cells in the cat striate cortex.J. Physiol. 1973; 231: 31-60Crossref PubMed Scopus (150) Google Scholar). The responses to high-contrast preferred stimuli can be suppressed by as much as 50%; the responses to low-contrast preferred stimuli can be suppressed almost entirely. It has long been thought that this suppression arises from inhibition between cells with orthogonal preferred orientations. In support of this interpretation, antagonists of GABAA-mediated inhibition reduce crossorientation suppression in visual evoked potentials (Morrone et al., 1987Morrone M.C. Burr D.C. Speed H.D. Cross-orientation inhibition in cat is GABA mediated.Exp. Brain Res. 1987; 67: 635-644Crossref PubMed Scopus (56) Google Scholar). Note, however, that more recently bicuculline has been shown to have nonspecific excitatory effects on neurons through its block of Ca2+-activated K+ (SK) channels (Khawaled et al., 1999Khawaled R. Bruening-Wright A. Adelman J.P. Maylie J. Bicuculline block of small-conductance calcium-activated potassium channels.Eur. J. Phys. 1999; 438: 314-321Crossref Scopus (107) Google Scholar). Nor are all the visual response properties of cortical cells consistent with inhibition being the mechanism underlying crossorientation suppression. F