Theoretical studies suggest that primary visual cortex (area V1) uses a sparse code to efficiently represent natural scenes. This issue was investigated by recording from V1 neurons in awake behaving macaques during both free viewing of natural scenes and conditions simulating natural vision. Stimulation of the nonclassical receptive field increases the selectivity and sparseness of individual V1 neurons, increases the sparseness of the population response distribution, and strongly decorrelates the responses of neuron pairs. These effects are due to both excitatory and suppressive modulation of the classical receptive field by the nonclassical receptive field and do not depend critically on the spatiotemporal structure of the stimuli. During natural vision, the classical and nonclassical receptive fields function together to form a sparse representation of the visual world. This sparse code may be computationally efficient for both early vision and higher visual processing.

We present a generalized reverse correlation technique that can be used to estimate the spatio-temporal receptive fields (STRFs) of sensory neurons from their responses to arbitrary stimuli such as auditory vocalizations or natural visual scenes. The general solution for STRF estimation requires normalization of the stimulus-response cross-correlation by the stimulus autocorrelation matrix. When the second-order stimulus statistics are stationary, normalization involves only the diagonal elements of the Fourier-transformed auto-correlation matrix (the power spectrum). In the non-stationary case normalization requires the entire auto-correlation matrix. We present modelling studies that demonstrate the feasibility and accuracy of this method as well as neurophysiological data comparing STRFs estimated using natural versus synthetic stimulus ensembles. For both auditory and visual neurons, STRFs obtained with these different stimuli are similar, but exhibit systematic differences that may be functionally significant. This method should be useful for determining what aspects of natural signals are represented by sensory neurons and may reveal novel response properties of these neurons.

Studies of the primary visual cortex (V1) have produced models that account for neuronal responses to synthetic stimuli such as sinusoidal gratings. Little is known about how these models generalize to activity during natural vision. We recorded neural responses in area V1 of awake macaques to a stimulus with natural spatiotemporal statistics and to a dynamic grating sequence stimulus. We fit nonlinear receptive field models using each of these data sets and compared how well they predicted time-varying responses to a novel natural visual stimulus. On average, the model fit using the natural stimulus predicted natural visual responses more than twice as accurately as the model fit to the synthetic stimulus. The natural vision model produced better predictions in Ͼ75% of the neurons studied. This large difference in predictive power suggests that natural spatiotemporal stimulus statistics activate nonlinear response properties in a different manner than the grating stimulus. To characterize this modulation, we compared the temporal and spatial response properties of the model fits. During natural stimulation, temporal responses often showed a stronger late inhibitory component, indicating an effect of nonlinear temporal summation during natural vision. In addition, spatial tuning underwent complex shifts, primarily in the inhibitory, rather than excitatory, elements of the response profile. These differences in late and spatially tuned inhibition accounted fully for the difference in predictive power between the two models. Both the spatial and temporal statistics of the natural stimulus contributed to the modulatory effects.

Spatial frequency (SF) and orientation tuning are intrinsic properties of neurons in primary visual cortex (area V1). To investigate the neural mechanisms mediating selectivity in the awake animal, we measured the temporal dynamics of SF and orientation tuning. We adapted a high-speed reverse-correlation method previously used to characterize orientation tuning dynamics in anesthetized animals to estimate efficiently the complete spatiotemporal receptive fields in area V1 of behaving macaques. We found that SF and orientation tuning are largely separable over time in single neurons. However, spatiotemporal receptive fields also contain a small nonseparable component that reflects a significant difference in response latency for low and high SF stimuli. The observed relationship between stimulus SF and latency represents a dynamic shift in SF tuning, and suggests that single V1 neurons might receive convergent input from the magno-and parvocellular processing streams. Although previous studies with anesthetized animals suggested that orientation tuning could change dramatically over time, we find no substantial evidence of dynamic changes in orientation tuning.reverse correlation ͉ striate cortex S patial frequency (SF) and orientation tuning are two of the most prominent features of neuronal selectivity in primary visual cortex (area V1) (1). The dynamics of SF and orientation tuning and their interactions are of particular interest to neurophysiologists because they can reveal important information about the specific circuits and mechanisms of neuronal selectivity (2). Dynamic tuning properties may also be critical for understanding natural vision, where eye movements can introduce complex temporal stimulus dynamics (3, 4).We simultaneously measured the temporal dynamics of both SF and orientation tuning in single V1 neurons in the awake primate. Conventional methods for estimating selectivity in V1 use stationary or drifting gratings of constant SF and orientation. Stimuli are presented for relatively long periods (0.3-1 s), and responses are quantified by mean firing rate. Often one stimulus parameter is varied at a time (e.g., orientation tuning is measured at the best SF). Although this approach can yield accurate orientation and SF tuning estimates, it fails to capture both stimulus interactions and temporal response dynamics that can be obscured by nonspecific onset transients. In addition, methods based on static stimuli can be time-consuming. Efficient characterization methods are particularly important when working with behaving animals, where time is almost always at a premium.One efficient way to characterize tuning that also captures temporal response dynamics is to estimate spatiotemporal receptive fields (STRFs) by using reverse correlation. The STRF describes the probability that a particular spatial stimulus will elicit a spike at a particular latency. In effect, the STRF provides a linear model of a neuron's spatiotemporal filtering characteristics (5, 6).In the visual system, STRFs are traditi...

We have investigated how the nonclassical receptive field (nCRF) affects information transmission by V1 neurons during simulated natural vision in awake, behaving macaques. Stimuli were centered over the classical receptive field (CRF) and stimulus size was varied from one to four times the diameter of the CRF. Stimulus movies reproduced the spatial and temporal stimulus dynamics of natural vision while maintaining constant CRF stimulation across all sizes. In individual neurons, stimulation of the nCRF significantly increases the information rate, the information per spike, and the efficiency of information transmission. Furthermore, the population averages of these quantities also increase significantly with nCRF stimulation. These data demonstrate that the nCRF increases the sparseness of the stimulus representation in V1, suggesting that the nCRF tunes V1 neurons to match the highly informative components of the natural world.

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We describe two related experiments that measured the anisotropy in the cosmic microwave background (CMB). QMAP was a balloon-borne telescope that flew twice in 1996, collecting data on degree angular scales with an array of six high electron mobility transistor-based amplifiers (HEMTs). QMAP was the first experiment to use an interlocking scan strategy to directly produce high signal-to-noise CMB maps. The QMAP gondola was then refit for ground based work as the MAT/TOCO experiment. Observations were made from 5200 m on Cerro Toco in Northern Chile in 1997 and 1998 using time-domain beam synthesis. MAT/TOCO was the first experiment to see both the rise and fall of the CMB angular spectrum, thereby localizing the position of the first peak to l peak = 216 ± 14. In addition to describing the instruments, we discuss the data selection methods, checks for systematic errors, and we compare the MAT/TOCO results to those from recent experiments. We also correct the data to account for an updated calibration and a small contribution from foreground emission. We find the amplitude of the first peak for 160 < l < 240 to be δT peak = 80.9 ± 3.4 ± 5.1 µK, where the first error is statistical and the second is from calibration.

Neural models that simulate single spike trains can help us understand the basic principles of neural coding in vision. Keat et al. (2001) develop a hybrid model that combines spatiotemporal filtering with nonlinear spike generation. The model does a good job of predicting the responses of single retinal ganglion cells and thalamic relay neurons.