Biomedical subjects

E P Simoncelli

Publications and source records attributed to E P Simoncelli.

5 recordsLinked to original sources

PubMed2000

Mechanisms of visual motion detection.

Visual motion is processed by neurons in primary visual cortex that are sensitive to spatial orientation and speed. Many models of local velocity computation are based on a second stage that pools the outputs of first-stage neurons selective for different orientations, but the nature of this pooling remains controversial. In a human psychophysical detection experiment, we found near-perfect summation of image energy when it was distributed uniformly across all orientations, but poor summation when it was concentrated in specific orientation bands. The data are consistent with a model that integrates uniformly over all orientations, even when this strategy is sub-optimal.

Adaptation, Physiological↗

PubMed1998

A model of neuronal responses in visual area MT.

Electrophysiological studies indicate that neurons in the middle temporal (MT) area of the primate brain are selective for the velocity of visual stimuli. This paper describes a computational model of MT physiology, in which local image velocities are represented via the distribution of MT neuronal responses. The computation is performed in two stages, corresponding to neurons in cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by rectification and divisive normalization. V1 receptive field weights are designed for orientation and direction selectivity. MT receptive field weights are designed for velocity (both speed and direction) selectivity. The paper includes computational simulations accounting for a wide range of physiological data, and describes experiments that could be used to further test and refine the model.

Brain Mapping↗

PubMed1998

Local velocity representation: evidence from motion adaptation.

Adaptation to a moving visual pattern induces shifts in the perceived motion of subsequently viewed moving patterns. Explanations of such effects are typically based on adaptation-induced sensitivity changes in spatio-temporal frequency tuned mechanisms (STFMs). An alternative hypothesis is that adaptation occurs in mechanisms that independently encode direction and speed (DSMs). Yet a third possibility is that adaptation occurs in mechanisms that encode 2D pattern velocity (VMs). We performed a series of psychophysical experiments to examine predictions made by each of the three hypotheses. The results indicate that: (1) adaptation-induced shifts are relatively independent of spatial pattern of both adapting and test stimuli; (2) the shift in perceived direction of motion of a plaid stimulus after adaptation to a grating indicates a shift in the motion of the plaid pattern, and not a shift in the motion of the plaid components; and (3) the 2D pattern of shift in perceived velocity radiates away from the adaptation velocity, and is inseparable in speed and direction of motion. Taken together, these results are most consistent with the VM adaptation hypothesis.

Adaptation, Ocular↗

PubMed1998

Range estimation by optical differentiation.

We describe a novel formulation of the range recovery problem based on computation of the differential variation in image intensities with respect to changes in camera position. This method uses a single stationary camera and a pair of calibrated optical masks to measure this differential quantity directly. We also describe a variant based on changes in aperture size. The subsequent computation of the range image involves simple arithmetic operations and is suitable for real-time implementation. We present the theory of this technique and show results from a prototype camera that we have constructed.

Humans↗

PubMed1996

Computational models of cortical visual processing.

The visual responses of neurons in the cerebral cortex were first adequately characterized in the 1960s by D. H. Hubel and T. N. Wiesel [(1962) J. Physiol. (London) 160, 106-154; (1968) J. Physiol. (London) 195, 215-243] using qualitative analyses based on simple geometric visual targets. Over the past 30 years, it has become common to consider the properties of these neurons by attempting to make formal descriptions of these transformations they execute on the visual image. Most such models have their roots in linear-systems approaches pioneered in the retina by C. Enroth-Cugell and J. R. Robson [(1966) J. Physiol. (London) 187, 517-552], but it is clear that purely linear models of cortical neurons are inadequate. We present two related models: one designed to account for the responses of simple cells in primary visual cortex (V1) and one designed to account for the responses of pattern direction selective cells in MT (or V5), an extrastriate visual area thought to be involved in the analysis of visual motion. These models share a common structure that operates in the same way on different kinds of input, and instantiate the widely held view that computational strategies are similar throughout the cerebral cortex. Implementations of these models for Macintosh microcomputers are available and can be used to explore the models' properties.

Computer Simulation↗