Prediction of orientation selectivity from receptive field architecture in simple cells of cat visual cortex

The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation

The responses of simple cells in primary visual cortex to sinusoidal gratings can primarily be predicted from their spatial receptive fields, as mapped using spots or bars. Although this quasilinearity is well documented, it is not clear whether it holds for complex natural stimuli. We recorded from simple cells in the primary visual cortex of anesthetized ferrets while stimulating with flashed digitized photographs of natural scenes. We applied standard reverse-correlation methods to quantify the average natural stimulus that invokes a neuronal response. Although these maps cannot be the receptive fields, we find that they still predict the preferred orientation of grating for each cell very well (r = 0.91); they do not predict the spatial-frequency tuning. Using a novel application of the linear reconstruction method called regularized pseudoinverse, we were able to recover high-resolution receptive-field maps from the responses to a relatively small number of natural scenes. These receptive-field maps not only predict the optimum orientation of each cell (r = 0.96) but also the spatial-frequency optimum (r = 0.89); the maps also predict the tuning bandwidths of many cells. Therefore, our first conclusion is that the tuning preferences of the cells are primarily linear and constant across stimulus type. However, when we used these maps to predict the actual responses of the cells to natural scenes, we did find evidence of expansive output nonlinearity and nonlinear influences from outside the classical receptive fields, orientation tuning, and spatial-frequency tuning.

Emergent properties of layer 2/3 neurons reflect the collinear arrangement of horizontal connections in tree shrew visual cortex

The superficial layers of primary visual cortex, unlike layer 4, have an extensive network of long-range horizontal connections linking sites of similar orientation preference. To identify possible functional consequences of this distinct anatomy, we compared the receptive field properties of layers 2/3 and 4 neurons in tree shrew primary visual cortex with electrophysiological recordings. We found that elongated receptive fields, strong orientation tuning, and length summation (properties predicted by the anatomy of the horizontal connections) are present in layer 2/3 neurons, but not in layer 4 neurons. We further characterized the summation fields of layer 2/3 neurons and found axis and orientation-specific facilitation that matched the distribution of horizontal connections. The functional signature of horizontal connections was also evident in the population response of layer 2/3 neurons; the intrinsic signal activation pattern elicited by an array of collinear Gabor elements was significantly stronger than that elicited by a noncollinear array. Furthermore, our results showed that this enhancement of population response was achieved without compromising spatial resolution along the collinear axis, providing stimulus-specific facilitation without filling in between stimuli. Taken together, these results suggest that horizontal connections play a significant role in shaping the visual responses of layer 2/3 neurons.

A cooperation and competition based simple cell receptive field model and study of feed-forward linear and nonlinear contributions to orientation selectivity

We present a model for development of orientation selectivity in layer IV simple cells. Receptive field (RF) development in the model, is determined by diffusive cooperation and resource limited competition guided axonal growth and retraction in geniculocortical pathway. The simulated cortical RFs resemble experimental RFs. The receptive field model is incorporated in a three-layer visual pathway model consisting of retina, LGN and cortex. We have studied the effect of activity dependent synaptic scaling on orientation tuning of cortical cells. The mean value of hwhh (half width at half the height of maximum response) in simulated cortical cells is 58 degrees when we consider only the linear excitatory contribution from LGN. We observe a mean improvement of 22.8 degrees in tuning response due to the non-linear spiking mechanisms that include effects of threshold voltage and synaptic scaling factor.

Receptive fields and response properties of neurons in layer 4 of ferret visual cortex

The ferret has become a model animal for studies exploring the development of the visual system. However, little is known about the receptive-field structure and response properties of neurons in the adult visual cortex of the ferret. We performed single-unit recordings from neurons in layer 4 of adult ferret primary visual cortex to determine the receptive-field structure and visual-response properties of individual neurons. In particular, we asked what is the spatiotemporal structure of receptive fields of layer 4 neurons and what is the orientation selectivity of layer 4 neurons? Receptive fields of layer 4 neurons were mapped using a white-noise stimulus; orientation selectivity was determined using drifting, sine-wave gratings. Our results show that most neurons (84%) within layer 4 are simple cells with elongated, spatially segregated, ON and OFF subregions. These neurons are also selective for stimulus orientation; peaks in orientation-tuning curves have, on average, a half-width at half-maximum response of 21.5 +/- 1.2 degrees (mean +/- SD). The remaining neurons in layer 4 (16%) lack orientation selectivity and have center/surround receptive fields. Although the organization of geniculate inputs to layer 4 differs substantially between ferret and cat, our results demonstrate that, like in the cat, most neurons in ferret layer 4 are orientation-selective simple cells.

The nucleus isthmi and dual modulation of the receptive field of tectal neurons in non-mammals

The nucleus isthmi in the dorsolateral tegmentum had been one of the most obscure structures in the nonmammalian midbrain for eight decades. Recent studies have shown that this nucleus and its mammalian homologue, the parabigeminal nucleus, are all visual centers, which receive information from the ipsilateral tectum and project back either ipsilaterally or bilaterally depending on species, but not an auditory center as suggested before. On the other hand, the isthmotectal pathways exert dual, both excitatory and inhibitory, actions on tectal cells in amphibians and reptiles. In birds, the magnocellular and parvocellular subdivisions of this nucleus produce excitatory and inhibitory effects on tectal cells, respectively. The excitatory pathway is mediated by glutamatergic synapses with AMPA and NMDA receptors and/or cholinergic synapses with muscarinic receptors, whereas the inhibitory pathway is mediated by GABAergic synapses via GABA(A) receptors. Further studies have shown that the magnocellular and parvocellular subdivisions can differentially modulate the excitatory and inhibitory regions of the receptive field of tectal neurons, respectively. Both the positive and the negative feedback pathways may work together in a winner-take-all manner, so that the animal could attend to only one of several competing visual targets simultaneously present in the visual field. Some behavioral tests seem to be consistent with this hypothesis. The present review indicates that the tecto-isthmic system in birds is an excellent model for further studying tectal modulation and possibly winner-take-all mechanisms.

Synaptic integration by V1 neurons depends on location within the orientation map

Neurons in the primary visual cortex (V1) are organized into an orientation map consisting of orientation domains arranged radially around "pinwheel centers" at which the representations of all orientations converge. We have combined optical imaging of intrinsic signals with intracellular recordings to estimate the subthreshold inputs and spike outputs of neurons located near pinwheel centers or in orientation domains. We find that neurons near pinwheel centers have subthreshold responses to all stimulus orientations but spike responses to only a narrow range of orientations. Across the map, the selectivity of inputs covaries with the selectivity of orientations in the local cortical network, while the selectivity of spike outputs does not. Thus, the input-output transformation performed by V1 neurons is powerfully influenced by the local structure of the orientation map.

A synaptic explanation of suppression in visual cortex

The responses of neurons in the primary visual cortex (V1) are suppressed by mask stimuli that do not elicit responses if presented alone. This suppression is widely believed to be mediated by intracortical inhibition. As an alternative, we propose that it can be explained by thalamocortical synaptic depression. This explanation correctly predicts that suppression is monocular, immune to cortical adaptation, and occurs for mask stimuli that elicit responses in the thalamus but not in the cortex. Depression also explains other phenomena previously ascribed to intracortical inhibition. It explains why responses saturate at high stimulus contrast, whereas selectivity for orientation and spatial frequency is invariant with contrast. It explains why transient responses to flashed stimuli are nonlinear, whereas spatial summation is primarily linear. These results suggest that the very first synapses into the cortex, and not the cortical network, may account for important response properties of V1 neurons.

LGN input to simple cells and contrast-invariant orientation tuning: an analysis

We develop a new analysis of the lateral geniculate nucleus (LGN) input to a cortical simple cell, demonstrating that this input is the sum of two terms, a linear term and a nonlinear term. In response to a drifting grating, the linear term represents the temporal modulation of input, and the nonlinear term represents the mean input. The nonlinear term, which grows with stimulus contrast, has been neglected in many previous models of simple cell response. We then analyze two scenarios by which contrast-invariance of orientation tuning may arise. In the first scenario, at larger contrasts, the nonlinear part of the LGN input, in combination with strong push-pull inhibition, counteracts the nonlinear effects of cortical spike threshold, giving the result that orientation tuning scales with contrast. In the second scenario, at low contrasts, the nonlinear component of LGN input is negligible, and noise smooths the nonlinearity of spike threshold so that the input-output function approximates a power-law function. These scenarios can be combined to yield contrast-invariant tuning over the full range of stimulus contrast. The model clarifies the contribution of LGN nonlinearities to the orientation tuning of simple cells and demonstrates how these nonlinearities may impact different models of contrast-invariant tuning.

Anatomical evidence of subcortical contributions to the orientation selectivity and columns of the cat's primary visual cortex

Physiological studies have demonstrated a subcortical origin for orientation selectivity and the orientation columns of the primary visual cortex. However, there are no anatomical data showing how subcortical cells contribute to this important property. Optical imaging, combined with 1,1'-dioctadecyl-3,3,3,3'-tetramethylin-docarbocyanine perchlolate (DiI) and biocytin retrograde tracing, reveals that relay cells projecting to a single orientation column representing the horizontal meridian were clustered within 300 microm in the dorsal lateral geniculate nucleus (LGN). Interestingly, some labeled cells were located on a line parallel to an iso-elevation line in the LGN. Thus, according to the quantitative projection of the visual field to the LGN (J. Comp. Neurol. 143 (1971) 101), their receptive fields must distribute horizontally in alignment in the visual field providing the first anatomical evidence for Hubel and Wiesel's model of simple cell receptive fields (J. Physiol. 160 (1962) 106).

On the classification of simple and complex cells

In their pioneering studies of primary visual cortex, Hubel and Wiesel described the existence of two classes of cells, which they termed "simple" and "complex". The original classification scheme was based on a number of partly subjective tests of linear spatial summation. Later, investigators adopted an objective classification method based on the ratio between the amplitude of the first harmonic of the response and the mean spike rate (or the F(1)/F(0) ratio) when the neuron is stimulated with drifting sinusoidal gratings. This measure is bimodally distributed over the population and divides neurons into two classes that correspond closely to the classical definition by Hubel and Wiesel. Here we show that a simple rectification model can predict the observed bimodal distribution of F(1)/F(0) in primary visual cortex when the distributions of the intracellular response modulation and mean are unimodal. Thus, contrary to common belief, the bimodality of F(1)/F(0) does not necessarily imply the existence of two discrete cell classes. Furthermore, in reviewing the literature, we find no independent support for a simple/complex dichotomy. These results suggest that the existence of two distinct neural populations in primary visual cortex, and the associated hierarchical model of receptive field organization, need to be re-evaluated.

Neural mechanisms of object recognition

Single-unit recordings from behaving monkeys and human functional magnetic resonance imaging studies have continued to provide a host of experimental data on the properties and mechanisms of object recognition in cortex. Recent advances in object recognition, spanning issues regarding invariance, selectivity, representation and levels of recognition have allowed us to propose a putative model of object recognition in cortex.

Laminar processing of stimulus orientation in cat visual cortex

One of the most salient features to emerge in visual cortex is sensitivity to stimulus orientation. Here we asked if orientation selectivity, once established, is altered by successive stages of cortical processing. We measured patterns of orientation selectivity at all depths of the cat's visual cortex by making whole-cell recordings with dye-filled electrodes. Our results show that the synaptic representation of orientation indeed changes with position in the microcircuit, as information passes from layer 4 to layer 2+3 to layer 5. At the earliest cortical stage, for simple cells in layer 4, orientation tuning curves for excitation (depolarization) and inhibition (hyperpolarization) had similar peaks (within 0-7 deg, n = 11) and bandwidths. Further, the sharpness of orientation selectivity covaried with receptive field geometry (r = 0.74) - the more elongated the strongest subregion, the shaper the tuning. Tuning curves for complex cells in layer 2+3 also had similar peaks (within 0-4 deg, n = 7) and bandwidths. By contrast, at a later station, layer 5, the preferred orientation for excitation and inhibition diverged such that the peaks of the tuning curves could be as far as 90 deg apart (average separation, 54 deg; n = 6). Our results support the growing consensus that orientation selectivity is generated at the earliest cortical level and structured similarly for excitation and inhibition. Moreover, our novel finding that the relative tuning of excitation and inhibition changes with laminar position helps resolve prior controversy about orientation selectivity at later phases of processing and gives a mechanistic view of how the cortical circuitry recodes orientation.

Neural noise can explain expansive, power-law nonlinearities in neural response functions

Many phenomenological models of the responses of simple cells in primary visual cortex have concluded that a cell's firing rate should be given by its input raised to a power greater than one. This is known as an expansive power-law nonlinearity. However, intracellular recordings have shown that a different nonlinearity, a linear-threshold function, appears to give a good prediction of firing rate from a cell's low-pass-filtered voltage response. Using a model based on a linear-threshold function, Anderson et al. showed that voltage noise was critical to converting voltage responses with contrast-invariant orientation tuning into spiking responses with contrast-invariant tuning. We present two separate results clarifying the connection between noise-smoothed linear-threshold functions and power-law nonlinearities. First, we prove analytically that a power-law nonlinearity is the only input-output function that converts contrast-invariant input tuning into contrast-invariant spike tuning. Second, we examine simulations of a simple model that assumes instantaneous spike rate is given by a linear-threshold function of voltage and voltage responses include significant noise. We show that the resulting average spike rate is well described by an expansive power law of the average voltage (averaged over multiple trials), provided that average voltage remains less than about 1.5 SDs of the noise above threshold. Finally, we use this model to show that the noise levels recorded by Anderson et al. are consistent with the degree to which the orientation tuning of spiking responses is more sharply tuned relative to the orientation tuning of voltage responses. Thus neuronal noise can robustly generate power-law input-output functions of the form frequently postulated for simple cells.