/pdf/feeling-and-thinking-preferences-need-no-inferences-q4mw2hj8rx.pdf

Feeling and thinking : Preferences need no inferences

A theory of edge detection is presented. The analysis proceeds in two parts. (1) Intensity changes, which occur in a natural image over a wide range of scales, are detected separately at different scales. An appropriate filter for this purpose at a given scale is found to be the second derivative of a Gaussian, and it is shown that, provided some simple conditions are satisfied, these primary filters need not be orientation-dependent. Thus, intensity changes at a given scale are best detected by finding the zero values of delta 2G(x,y)*I(x,y) for image I, where G(x,y) is a two-dimensional Gaussian distribution and delta 2 is the Laplacian. The intensity changes thus discovered in each of the channels are then represented by oriented primitives called zero-crossing segments, and evidence is given that this representation is complete. (2) Intensity changes in images arise from surface discontinuities or from reflectance or illumination boundaries, and these all have the property that they are spatially. Because of this, the zero-crossing segments from the different channels are not independent, and rules are deduced for combining them into a description of the image. This description is called the raw primal sketch. The theory explains several basic psychophysical findings, and the operation of forming oriented zero-crossing segments from the output of centre-surround delta 2G filters acting on the image forms the basis for a physiological model of simple cells (see Marr & Ullman 1979).

http://www.hms.harvard.edu/bss/neuro/bornlab/qmbc/beta/day4/marr-hildreth-edge-prsl1980.pdf

Theory of Edge Detection

The study of decision making spans such varied fields as neuroscience, psychology, economics, statistics, political science, and computer science. Despite this diversity of applications, most decisions share common elements including deliberation and commitment. Here we evaluate recent progress in understanding how these basic elements of decision formation are implemented in the brain. We focus on simple decisions that can be studied in the laboratory but emphasize general principles likely to extend to other settings.

/pdf/the-neural-basis-of-decision-making-2p5agsty56.pdf

The Neural Basis of Decision Making

A motion sequence may be represented as a single pattern in x–y–t space; a velocity of motion corresponds to a three-dimensional orientation in this space. Motion sinformation can be extracted by a system that responds to the oriented spatiotemporal energy. We discuss a class of models for human motion mechanisms in which the first stage consists of linear filters that are oriented in space-time and tuned in spatial frequency. The outputs of quadrature pairs of such filters are squared and summed to give a measure of motion energy. These responses are then fed into an opponent stage. Energy models can be built from elements that are consistent with known physiology and psychophysics, and they permit a qualitative understanding of a variety of motion phenomena.

/pdf/spatiotemporal-energy-models-for-the-perception-of-motion-43mzze32mc.pdf

Spatiotemporal energy models for the perception of motion

An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.

https://link.springer.com/content/pdf/10.3758/BF03202828.pdf

QUEST: a Bayesian adaptive psychometric method.

Summation and discrimination of gratings moving in opposite directions.

Contrast sensitivity for square-wave gratings of spatial frequencies between 0.44 and 33.2 cycles/deg was determined for exposure durations between 11 and 500 msec. The space-average luminance of the targets was kept constant at 10 mL, regardless of contrast, and equal to that of the pre- and post-exposure fields, which contained a cross-hair reticle to help maintain accommodation and fixation. At the longest exposure duration (500 msec) the contrast sensitivity function exhibited both the high- and the low-frequency declines described by previous investigators. At the briefest exposure duration tested (11 msec), the low-frequency decline of contrast sensitivity was virtually absent. Log contrast sensitivity improves with increasing exposure duration, but more for high-frequency than for low-frequency gratings. These results are compatible with the assumption that there is a time delay in the occurrence of inhibitory interactions in the retina.

Effect of Exposure Duration on Visual Contrast Sensitivity with Square-Wave Gratings*†

Subjects were presented with two gratings with different spatial frequencies and they were asked to discriminate one from the other. Their ability to discriminate between the gratings was found to depend primarily on the ratio of their spatial frequencies over a wide range of absolute frequency. At high spatial frequencies, discrimination deteriorates when differences of subjective contrast are eliminated.

Spatial-Frequency Discrimination in Human Vision

A rating-scale psychophysical method was employed to obtain receiver operating characteristics for detection and for discrimination of luminance increments. These curves were used to estimate the parameters of a normal probability-density function which was assumed to describe the relevant internal effects of the test flash. The over-all results strongly indicate that the mean of this distribution is a positively accelerated function of luminance of the test flash, and suggest that the standard deviation is a non-monotonic function of luminance. It is argued that quantum fluctuations and criterion fluctuations cannot account for these findings, whereas channel uncertainty may be at the root of some of them.

Visual Detection and Discrimination of Luminance Increments

Discrimination of simple and complex gratings.

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