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Dario L Ringach

Publications and source records attributed to Dario L Ringach.

16 recordsLinked to original sources
PubMed2005

Effect of stimulus size on the dynamics of orientation selectivity in Macaque V1.

Previous research has established that orientation selectivity depends to a great extent on suppressive mechanisms in the visual cortex. In this study, we investigated the spatial organization and the time-course of these mechanisms. Stimuli were presented in circular windows of "optimal" and "large" radii. The two stimulus sizes were chosen based on an area-response function measured with drifting gratings at high contrast. The "optimal" size was defined as the smallest radius that elicited the peak response (average value of 0.45 degrees ), whereas "large" was defined as two to five times the optimal size. We found that the peak amplitude of tuned enhancement and untuned suppression varied <10% on average with stimulus radius, indicating that they are mainly concentrated in the classical receptive field. However, tuned suppression--in those cells that showed it--was significantly stronger with large stimuli, indicating that this component has a contribution from beyond the classical receptive field. These results imply that spatial context (in large stimuli) enhances orientation selectivity by increasing tuned suppression. We also characterized the time evolution of enhancement, of untuned suppression, and of tuned suppression. The time-course of tuned suppression was markedly slower in time-to-peak and longer in its persistence than untuned suppression. Therefore tuned suppression is likely to be generated by long-range recurrent connections or cortico-cortical feedback, whereas untuned suppression is mainly generated locally in V1.

Animals↗
PubMed2004

Spatial overlap of ON and OFF subregions and its relation to response modulation ratio in macaque primary visual cortex.

We studied the spatial overlap of on and off subregions in macaque primary visual cortex and its relation to the response modulation ratio (the F1/F0 ratio). Spatial maps of on and off subregions were obtained by reverse correlation with a dynamic noise pattern of bright and dark spots. Two spatial maps, on and off, were produced by cross-correlating the spike train with the location of bright and dark spots in the stimulus respectively. Several measures were used to assess the degree of overlap between subregions. In a subset of neurons, we also computed the F1/F0 ratio in response to drifting sinusoidal gratings. Significant correlations were found among all the overlap measures and the F1/F0 ratio. Most overlap indices considered, and the F1/F0 measure, had bimodal distributions. In contrast, the distance between on and off subregions normalized by their size was unimodal. Surprisingly, a simple model that additively combines on and off subregions with spatial separations drawn from a unimodal distribution, can readily explain the data. These analyses clarify the relationship between subregion overlap and the F1/F0 ratio in macaque primary visual cortex, and a simple model provides a parsimonious explanation for the co-existence of bimodal distributions of overlap indices and a unimodal distribution of the normalized distance.

Action Potentials↗
PubMed2004

Mapping receptive fields in primary visual cortex.

Nearly 40 years ago, in the pages of this journal, Hubel and Wiesel provided the first description of receptive fields in the primary visual cortex of higher mammals. They defined two classes of cortical cells, "simple" and "complex", based on neural responses to simple visual stimuli. The notion of a hierarchy of receptive fields, where increasingly intricate receptive fields are constructed from more elementary ones, was introduced. Since those early days we have witnessed the birth of quantitative methods to map receptive fields and mathematical descriptions of simple and complex cell function. Insights gained from these models, along with new theoretical concepts, are refining our understanding of receptive field structure and the underlying cortical circuitry. Here, I provide a brief historical account of the evolution of receptive field mapping in visual cortex along with the associated conceptual advancements, and speculate on the shape novel theories of the cortex may take as a result these measurements.

Animals↗
PubMed2004

Correlation of local and global orientation and spatial frequency tuning in macaque V1.

Visual cortical neurones display a variety of visual properties. Among those that emerge in the primary visual cortex V1 are sharpening of selectivity for spatial frequency and for orientation. The selectivity for these stimulus attributes can be measured around the peak of the tuning function, usually as bandwidth. Other selectivity measures take into account the response across a broader range of stimulus values. An example of such a global measure is the circular variance of orientation tuning. Here we introduce a similar measure in the spatial frequency domain that takes into account the shape of the tuning curve at frequencies lower than the peak, called the low-spatial frequency variance. Our recent studies with dynamic stimuli suggest that the selectivity for spatial frequency and orientation is strongly correlated with the degree of suppression at low spatial frequencies and off-axis orientations. Here we extend the study of the global tuning to stimulus conditions that measure the response of cells to the presentation of drifting sinusoidal grating stimuli for periods of a few seconds. We find that under such steady-state stimulus conditions there is a strong correlation between the global selectivity measures, orientation circular variance and low spatial frequency variance. Consistent with previous studies, there is a weaker correlation between the local tuning measures, orientation and spatial frequency bandwidth. These results support the idea that there are multiple factors that contribute to tuning and that suppression observed in dynamic experiments is also likely to contribute to the global selectivity for steady-state stimuli.

Animals↗
PubMed2004

Haphazard wiring of simple receptive fields and orientation columns in visual cortex.

The receptive fields of simple cells in visual cortex are composed of elongated on and off subregions. This spatial arrangement is widely thought to be responsible for the generation of orientation selectivity. Neurons with similar orientation preferences cluster in "columns" that tile the cortical surface and form a map of orientation selectivity. It has been proposed that simple cell receptive fields are constructed by the selective pooling of geniculate receptive fields aligned in space. A recent analysis of monosynaptic connections between geniculate and cortical neurons appears to reveal the existence of "wiring rules" that are in accordance with the classical model. The precise origin of the orientation map is unknown, but both genetic and activity-dependent processes are thought to contribute. Here, we put forward the hypothesis that statistical sampling from the retinal ganglion cell mosaic may contribute to the generation of simple cells and provide a blueprint for orientation columns. Results from computer simulations show that the "haphazard wiring" model is consistent with data on the probability of monosynaptic connections and generates orientation columns and maps resembling those found in the cortex. The haphazard wiring hypothesis could be tested by measuring the correlation between the orientation map and the structure of the retinal ganglion cell mosaic of the contralateral eye.

Animals↗
PubMed2003

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 cell's 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 cell's 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.

Animals↗
PubMed2003

Dynamics of orientation tuning in macaque V1: the role of global and tuned suppression.

The temporal development of neural selectivity to physical attributes of a visual stimulus, such as its orientation and spatial frequency, can provide important clues about mechanisms of cortical tuning. We measured the dynamics of orientation tuning in macaque primary visual cortex (V1) and found several dynamical features in the data: changes in global enhancement and suppression, narrowing of orientation bandwidth, small but significant shifts in preferred orientation, and "Mexican-hat" tuning curves. The dynamics data were analyzed with a model that sums two fixed, tuned components (enhancement and suppression) and one global (untuned) component. The analysis suggests that there is early global enhancement followed by global and tuned suppression. Tuned suppression accounts for the dynamical reduction of orientation bandwidth and for the generation of Mexican-hat tuning profiles. Our findings imply that global and tuned suppression are important factors that determine the selectivity and dynamics of V1 responses to orientation.

Animals↗
PubMed2003

Estimating membrane voltage correlations from extracellular spike trains.

The cross-correlation coefficient between neural spike trains is a commonly used tool in the study of neural interactions. Two well-known complications that arise in its interpretation are 1) modulations in the correlation coefficient may result solely from changes in the mean firing rate of the cells and 2) the mean firing rates of the neurons impose upper and lower bounds on the correlation coefficient whose absolute values differ by an order of magnitude or more. Here, we propose a model-based approach to the interpretation of spike train correlations that circumvents these problems. The basic idea of our proposal is to estimate the cross-correlation coefficient between the membrane voltages of two cells from their extracellular spike trains and use the resulting value as the degree of correlation (or association) of neural activity. This is done in the context of a model that assumes the membrane voltages of the cells have a joint normal distribution and spikes are generated by a simple thresholding operation. We show that, under these assumptions, the estimation of the correlation coefficient between the membrane voltages reduces to the calculation of a tetrachoric correlation coefficient (a measure of association in nominal data introduced by Karl Pearson) on a contingency table calculated from the spike data. Simulations of conductance-based leaky integrate-and-fire neurons indicate that, despite its simplicity, the technique yields very good estimates of the intracellular membrane voltage correlation from the extracellular spike trains in biologically realistic models.

Action Potentials↗
PubMed2002

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.

Action Potentials↗
PubMed2002

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.

Electrophysiology↗
PubMed2002

Suppression of neural responses to nonoptimal stimuli correlates with tuning selectivity in macaque V1.

Neural responses in primary visual cortex (area V1) are selective for the orientation and spatial frequency of luminance-modulated sinusoidal gratings. Selectivity could arise from enhancement of the cell's response by preferred stimuli, suppression by nonoptimal stimuli, or both. Here, we report that the majority of V1 neurons do not only elevate their activity in response to preferred stimuli, but their firing rates are also suppressed by nonoptimal stimuli. The magnitude of suppression is similar to that of enhancement. There is a tendency for net response suppression to peak at orientations near orthogonal to the optimal for the cell, but cases where suppression peaks at oblique orientations are observed as well. Interestingly, selectivity and suppression correlate in V1: orientation and spatial frequency selectivity are higher for neurons that are suppressed by nonoptimal stimuli than for cells that are not. This finding is consistent with the idea that suppression plays an important role in the generation of sharp cortical selectivity. We show that nonlinear suppression is required to account for the data. However, the precise structure of the neural circuitry generating the suppressive signal remains unresolved. Our results are consistent with both feedback and (nonlinear) feed-forward inhibition.

Animals↗
PubMed2002

Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex.

I present measurements of the spatial structure of simple-cell receptive fields in macaque primary visual cortex (area V1). Similar to previous findings in cat area 17, the spatial profile of simple-cell receptive fields in the macaque is well described by two-dimensional Gabor functions. A population analysis reveals that the distribution of spatial profiles in primary visual cortex lies approximately on a one-parameter family of filter shapes. Surprisingly, the receptive fields cluster into even- and odd-symmetry classes with a tendency for neurons that are well tuned in orientation and spatial frequency to have odd-symmetric receptive fields. The filter shapes predicted by two recent theories of simple-cell receptive field function, independent component analysis and sparse coding, are compared with the data. Both theories predict receptive fields with a larger number of subfields than observed in the experimental data. In addition, these theories do not generate receptive fields that are broadly tuned in orientation and low-pass in spatial frequency, which are commonly seen in monkey V1. The implications of these results for our understanding of image coding and representation in primary visual cortex are discussed.

Animals↗
PubMed2002

Full identification of a linear-nonlinear system via cross-correlation analysis.

A statistical model used extensively in vision research consists of a cascade of a linear operator followed by a static (memoryless) nonlinearity. Common applications include the measurement of simple-cell receptive fields in primary visual cortex and the modeling of human performance in various psychophysical tasks. It is well known that the front-end linear filter of the model can readily be recovered, up to a multiplicative constant, using reverse-correlation techniques. However, a full identification of the model also requires an estimation of the output nonlinearity. Here, we show that for a large class of static nonlinearities, one can obtain analytical expressions for the estimates. The technique works with both Gaussian and binary noise stimuli. The applicability of the method in physiology and psychophysics is demonstrated. Finally, the proposed technique is shown to converge much faster than the currently used linear-reconstruction method.

Humans↗
PubMed2002

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 neuron's 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 cell's 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.

Animals↗