Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.

The Perception of the Visual World. By James J. Gibson. U.S.A.: Houghton Mifflin Company, 1950 (George Allen & Unwin, Ltd., London). Price 35s.

A tutorial review of both linear and quadratic representations is given. The linear representations discussed are the short-time Fourier transform and the wavelet transform. The discussion of quadratic representations concentrates on the Wigner distribution, the ambiguity function, smoothed versions of the Wigner distribution, and various classes of quadratic time-frequency representations. Examples of the application of these representations to typical problems encountered in time-varying signal processing are provided. >

Linear and quadratic time-frequency signal representations

The computational brain: Patricia S. Churchland and Terrence J. Sejnowski (MIT Press, Cambridge, MA, 1992); xi, 544 pages, $39.95

Simple cells in the primary visual cortex often appear to compute a weighted sum of the light intensity distribution of the visual stimuli that fall on their receptive fields. A linear model of these cells has the advantage of simplicity and captures a number of basic aspects of cell function. It, however, fails to account for important response nonlinearities, such as the decrease in response gain and latency observed at high contrasts and the effects of masking by stimuli that fail to elicit responses when presented alone. To account for these nonlinearities we have proposed a normalization model, which extends the linear model to include mutual shunting inhibition among a large number of cortical cells. Shunting inhibition is divisive, and its effect in the model is to normalize the linear responses by a measure of stimulus energy. To test this model we performed extracellular recordings of simple cells in the primary visual cortex of anesthetized macaques. We presented large stimulus sets consisting of (1) drifting gratings of various orientations and spatiotemporal frequencies; (2) plaids composed of two drifting gratings; and (3) gratings masked by full-screen spatiotemporal white noise. We derived expressions for the model predictions and fitted them to the physiological data. Our results support the normalization model, which accounts for both the linear and the nonlinear properties of the cells. An alternative model, in which the linear responses are subject to a compressive nonlinearity, did not perform nearly as well.

/pdf/linearity-and-normalization-in-simple-cells-of-the-macaque-55rc1ohksj.pdf

Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex

Using functional magnetic resonance imaging (fMRI) and cortical unfolding techniques, we analyzed the retinotopy, motion sensitivity, and functional organization of human area V3A. These data were compared with data from additional human cortical visual areas, including V1, V2, V3/VP, V4v, and MT (V5). Human V3A has a retinotopy that is similar to that reported previously in macaque: (1) it has a distinctive, continuous map of the contralateral hemifield immediately anterior to area V3, including a unique retinotopic representation of the upper visual field in superior occipital cortex; (2) in some cases the V3A foveal representation is displaced from and superior to the confluent foveal representations of V1, V2, V3, and VP; and (3) inferred receptive fields are significantly larger in human V3A, compared with those in more posterior areas such as V1. However, in other aspects human V3A appears quite different from its macaque counterpart: human V3A is relatively motion-selective, whereas human V3 is less so. In macaque, the situation is qualitatively reversed: V3 is reported to be prominently motion-selective, whereas V3A is less so. As in human and macaque MT, the contrast sensitivity appears quite high in human areas V3 and V3A.

https://www.cogsci.ucsd.edu/~sereno/papers/V3AHuman97.pdf

Functional Analysis of V3A and Related Areas in Human Visual Cortex

Joint spatial/spatial-frequency representation

We advance in this paper the spatiotemporal-frequency (STF) approach for computing the optical flow of a time-varying image. STF flow derivation provides an attractive alternative to earlier approaches based on (1) feature correspondence, (2) spatiotemporal gradients, and (3) Fourier-phase changes. After briefly surveying these three earlier approaches to flow computation, we provide an historical overview of the development of the STF approach. Then an improved STF method for flow derivation that has recently been developed by the authors is presented along with experimental results that demonstrate its use. The STF yields a dense time and spatially varying 2D optical flow field for each image frame. We conclude by showing that STF derivation (a) promises substantially improved performance over the flow computation methods, and (b) provides a partial explanation of motion coherence as observed in human vision.

Derivation of optical flow using a spatiotemporal-frequency approach

Interneuronal interaction between members of quadrature phase and anti-phase pairs in the cat's visual cortex.

White noise stimuli were used to estimate second-order kernels for complex cells in cortical area VI of the macaque monkey, and drifting grating stimuli were presented to the same sample of neurons to obtain orientation and spatial-frequency tuning curves. Using these data, we quantified how well second-order kernels predict the normalized tuning of the average response of complex cells to drifting gratings.The estimated second-order kernel of each complex cell was transformed into an interaction function defined over all spatial and temporal lags without regard to absolute position or delay. The Fourier transform of each interaction function was then computed to obtain an interaction spectrum. For a cell that is well modeled by a second-order system, the cell’s interaction spectrum is proportional to the tuning of its average spike rate to drifting gratings. This result was used to obtain spatial-frequency and orientation tuning predictions for each cell based on its second-order kernel. From the spatial-frequency and orientation tuning curves, we computed peaks and bandwidths, and an index for directional selectivity.We found that the predictions derived from second-order kernels provide an accurate description of the change in the average spike rate of complex cells to single drifting sine–wave gratings. These findings are consistent with a model for complex cells that has a quadratic spectral energy operator at its core but are inconsistent with a spectral amplitude model.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0952523800003102

Lowell D. Jacobson

Papers

Joint spatial/spatial-frequency representation

Derivation of optical flow using a spatiotemporal-frequency approach

Interneuronal interaction between members of quadrature phase and anti-phase pairs in the cat's visual cortex.

Space-time spectra of complex cell filters in the macaque monkey: a comparison of results obtained with pseudowhite noise and grating stimuli.

Spatial and temporal frequency selectivity of neurons in visual cortical area V3A of the macaque monkey.