Dario L. Ringach

Contrast's effect on spatial summation by macaque V1 neurons

Stimulation outside the receptive field of a primary visual cortical (V1) neuron reveals intracortical neural interactions. However, previous investigators implicitly or explicitly considered the extent of cortical spatial summation and, therefore, the size of the classical receptive field to be fixed and independent of stimulus characteristics or of surrounding context. On the contrary, we found that the extent of spatial summation in macaque V1 neurons depended on contrast, and was on average 2.3-fold greater at low contrast. This adaptive increase in spatial summation at low contrast was seen in cells throughout V1 and was independent of surround inhibition.

Orientation selectivity in macaque V1: diversity and laminar dependence.

We studied the steady-state orientation selectivity of single neurons in macaque primary visual cortex (V1). To analyze the data, two measures of orientation tuning selectivity, circular variance and orientation bandwidth, were computed from the tuning curves. Circular variance is a global measure of the shape of the tuning curve, whereas orientation bandwidth is a local measure of the sharpness of the tuning curve around its peak. Circular variance in V1 was distributed broadly, indicating a great diversity of orientation selectivity. This diversity was also reflected in the individual cortical layers. However, there was a tendency for neurons with high circular variance, meaning low selectivity for orientation, to be concentrated in layers 4C, 3B, and 5. The relative variation of orientation bandwidth across the cortical layers was less than for circular variance, but it showed a similar laminar dependence. Neurons with large orientation bandwidth were found predominantly in layers 4C and 3B. There was a weak correlation between orientation selectivity and the level of spontaneous activity of the neurons. We also assigned a response modulation ratio for each cell, which is a measure of the linearity of spatial summation. Cells with low modulation ratios tended to have higher circular variance and bandwidth than those with high modulation ratios. These findings suggest a revision to the classical view that nonoriented receptive fields are principally found in layer 4C and the cytochrome oxidase-rich blobs in layer 2/3. Instead, a broad distribution of tuning selectivity is found in all cortical layers, and neurons that are weakly tuned for orientation are ubiquitous in V1 cortex.

Local Origin of Field Potentials in Visual Cortex

The local field potential (LFP) is increasingly used to measure the combined activity of neurons within a region of tissue. Yet, available estimates of the size of this region are highly disparate, ranging from several hundred microns to a few millimeters. To measure the size of this region directly, we used a combination of multielectrode recordings and optical imaging. We determined the orientation selectivity of stimulus-evoked LFP signals in primary visual cortex and were able to predict it on the basis of the surrounding map of orientation preference. The results show that > 95% of the LFP signal originates within 250 microm of the recording electrode. This quantitative estimate indicates that LFPs are more local than often recognized and provides a guide to the interpretation of the increasing number of studies that rest on LFP recordings.

Stimulus contrast modulates functional connectivity in visual cortex

Neurons in visual cortex are linked by an extensive network of lateral connections. To study the effect of these connections on neural responses, we recorded spikes and local field potentials (LFPs) from multi-electrode arrays that were implanted in monkey and cat primary visual cortex. Spikes at each location generated outward traveling LFP waves. When the visual stimulus was absent or had low contrast, these LFP waves had large amplitudes and traveled over long distances. Their effect was strong: LFP traces at any site could be predicted by the superposition of waves that were evoked by spiking in a ∼1.5-mm radius. As stimulus contrast increased, both the magnitude and the distance traveled by the waves progressively decreased. We conclude that the relative weight of feedforward and lateral inputs in visual cortex is not fixed, but rather depends on stimulus contrast. Lateral connections dominate at low contrast, when spatial integration of signals is perhaps most beneficial.

Dynamics of Orientation Selectivity in the Primary Visual Cortex and the Importance of Cortical Inhibition

To test theories of orientation selectivity in primary visual cortex (V1), we have done experiments to measure the dynamics of orientation tuning of single neurons in the V1 cortex of macaque monkeys. Based on our dynamics results, we propose that a V1 cells orientation selectivity is generated mainly by both tuned enhancement and global suppression. Enhancement near the preferred orientation is probably caused by feed-forward input from LGN (plus amplification by cortical-cortical interaction). Global suppression could be supplied by cortical inhibition. Additionally, in about 1/3 of V1 neurons (usually the most sharply tuned) there is tuned suppression, centered near the cells preferred orientation but broader than tuned enhancement. These mechanisms also can explain important features of steady-state selectivity in the V1 neuron population. Furthermore, similar neuronal mechanisms may be used generally throughout the cerebral cortex.

A subspace reverse-correlation technique for the study of visual neurons.

A new discrete-time reverse-correlation scheme for the study of visual neurons is proposed. The visual stimulus is generated by drawing with uniform probability, at each refresh time, an image from a finite set S of orthonormal images. We show that if the neuron can be modeled as a spatiotemporal linear filter followed by a static nonlinearity, the cross-correlation between the input image sequence and the cells spike train output gives the projection of the receptive field onto the subspace spanned by S. The technique has been applied to the analysis of simple cells in the primary visual cortex of cats and macaque monkeys. Experimental results are presented where S spans a subspace of spatially low-pass signals. Advantages of the proposed scheme over standard white-noise techniques include improved signal to noise ratios, increased spatial resolution, and the possibility to restrict the study to particular subspaces of interest.

Receptive field structure of neurons in monkey primary visual cortex revealed by stimulation with natural image sequences

Probing the visual system with the ensemble of signals that occur in the natural environment may reveal aspects of processing that are not evident in the neural responses to artificial stimulus sets, such as conventional bars and sinusoidal gratings. However, unsolved is the question of how to use complex natural stimulation, many aspects of which the experimenter cannot completely specify, to study neural processing. Here a method is presented to investigate the structure of a neurons receptive field based on its response to movie clips and other stimulus ensembles. As a particular case, the technique provides an estimate of the conventional first-order receptive field of a neuron, similar to what can be obtained with other reverse-correlation schemes. This is demonstrated experimentally and with computer simulations. Our analysis also revealed that the receptive fields of both simple and complex cells had regions where image boundaries, independent of their contrast sign, would enhance or suppress the cells response. In some cases, these signals were tuned for the orientation of the boundary. This demonstrates for the first time that it might be feasible to investigate the receptive field structure of visual neurons from their responses to natural image sequences.

Predictions of a recurrent model of orientation selectivity

Recurrent models of orientation selectivity in the visual cortex postulate that an initially broad tuning given by the pattern of geniculate afferents is substantially sharpened by intracortical feedback. We show that these models can be tested on the basis of their predicted responses to certain visual stimuli, without the need for pharmacological or physiological manipulations. First, we consider a detailed recurrent model proposed by Somers, Nelson and Sur [(1995) Journal of Neuroscience, 15, 5448-5465] and show that it can be simplified to a single equation: a center-surround feedback filter in the orientation domain. Then, we explore the responses of the simplified model to stimuli containing two or more orientations. We find that the model exhibits peculiar responses to stimuli containing two orientations, such as plaids or crosses: if the component orientations differ by less than 45 deg the model cannot distinguish between them; if the orientations differ by more than 45 deg the model overestimates their angle by as much as 30 deg. Moreover, the model cannot signal the presence of three orientations separated by 60 deg (it responds as if there were only two orientations), and the addition of two-dimensional visual noise to an oriented stimulus results in strong spurious responses at the orthogonal orientation. We argue that the effects of attraction and repulsion between orientations and the emergence of responses at off-optimal orientations are common to a wide class of feedback models of orientation selectivity. These models could thus be tested by measuring the visual responses of cortical neurons to stimuli containing multiple orientations.

Topological analysis of population activity in visual cortex.

Information in the cortex is thought to be represented by the joint activity of neurons. Here we describe how fundamental questions about neural representation can be cast in terms of the topological structure of population activity. A new method, based on the concept of persistent homology, is introduced and applied to the study of population activity in primary visual cortex (V1). We found that the topological structure of activity patterns when the cortex is spontaneously active is similar to those evoked by natural image stimulation and consistent with the topology of a two sphere. We discuss how this structure could emerge from the functional organization of orientation and spatial frequency maps and their mutual relationship. Our findings extend prior results on the relationship between spontaneous and evoked activity in V1 and illustrates how computational topology can help tackle elementary questions about the representation of information in the nervous system.

Reverse correlation in neurophysiology

Abstract This article presents a review of reverse correlation in neurophysiology. We discuss the basis of reverse correlation in linear transducers and in spiking neurons. The application of reverse correlation to measure the receptive fields of visual neurons using white noise and m-sequences, and classical findings about spatial and color processing in the cortex resulting from such measurements, are emphasized. Finally, we describe new developments in reverse correlation, including “sub-space” and categorical reverse-correlation. Recent results obtained by applying such methods in the orientation, spatial-frequency and Fourier domains have revealed the importance of cortical inhibition in the establishment of sharp tuning selectivity in single neurons.