Spatial characteristics of movement detection mechanisms in human vision

Visual detection of targets moving against structured background fields has been studied with near-monochromatic stimuli, selected so as to isolate the different increment threshold spectral response mechanisms. It is shown that for foveal vision, the red-and green-sensitive mechanisms (₅ and ₄ respectively) yield IMG functions (Barbur and Ruddock, 1980), similar to those found with white light. In contrast, the blue-sensitive (₁) mechanism yields a low-frequency IMG response quite unlike that found for the other mechanisms. There is also considerable variation between subjects in this case. Measurements taken 30° off-axis with low (1.4 log trolands) background illumination level, yield a low frequency response IMG function for both rod and cone spectral mechanisms, similar to those found with white light stimuli. At high illumination levels (>2.2 log trolands), the IMG function for the ₅-mechanism is shifted to higher spatial frequencies, as is also observed with white light stimuli. A wavelength-selective binocular interaction effect, manifested in the detection of moving targets, is also described, and it is suggested that this may be of value in the study of defective colour vision.     

Fractal rotation isolates mechanisms for form-dependent motion in human vision

Here, we describe a motion stimulus in which the quality of rotation is fractal. This makes its motion unavailable to the translation-based motion analysis known to underlie much of our motion perception. In contrast, normal rotation can be extracted through the aggregation of the outputs of translational mechanisms. Neural adaptation of these translation-based motion mechanisms is thought to drive the motion after-effect, a phenomenon in which prolonged viewing of motion in one direction leads to a percept of motion in the opposite direction. We measured the motion after-effects induced in static and moving stimuli by fractal rotation. The after-effects found were an order of magnitude smaller than those elicited by normal rotation. Our findings suggest that the analysis of fractal rotation involves different neural processes than those for standard translational motion. Given that the percept of motion elicited by fractal rotation is a clear example of motion derived from form analysis, we propose that the extraction of fractal rotation may reflect the operation of a general mechanism for inferring motion from changes in form.     

Adaptive filter model of the cerebellum

The Marr-Albus model of the cerebellum has been reformulated with linear system analysis. This adaptive linear filter model of the cerebellum performs a filtering action of a phase lead-lag compensator with learning capability, and will give an account for the phenomena which have been termed cerebellar compensation. It is postulated that a Golgi cell may act as a phase lag element; for example, as a leaky integrator with time constant about several seconds. Under this assumption, a mossy fiber-granule cell-Golgi cell input network functions as a phase lead-lag compensator. Output signals from Golgi-granule cell systems, namely, parallel fiber signals, are gathered together through variable synaptic connections to form a Purkinje cell output. From a general theory of adaptive linear filters, learning principles for these modifiable connections are derived. By these learning principles, a Purkinje cell output converges to the desired response to minimize the mean square error of the performance. In a more general sense, a Purkinje cell acquires a filtering function on the basis of multiple pairs of input signals and corresponding desired output signals. The mode of convergence of the output signal is described when the input signal is sinusoidal.     

Adaptive usage of the Butterworth digital filter

The Butterworth lowpass filter is a conventional tool that has been commonly used in gait analysis applications. Its operation mainly depends on the selection of the cut-off frequency, which must be done based on the condition of the raw signal assuming that it is stationary. This tool is unable to deal with nonstationary signals especially if impact is involved. In this paper, a modified version of the Butterworth filter that can handle nonstationary signals is presented. The new filter has a variable cut-off frequency distribution defined for each data point, which is determined by local signal characteristics. Because of its adaptive nature, it is possible for the filter to accommodate changes in the frequency content of the signal.     

Adaptive mechanisms of spinal locomotion in cats

This paper reviews some aspects of locomotor plasticity afterspinalisation and after peripheral nerve lesions. Adult catscan recover spontaneous hindlimb locomotion on a treadmill severaldays or weeks after a complete section of the spinal cord atT13. The kinematics as well as the electromyographic activityare compared in the same animal before and after the spinalsection to highlight the resemblance of locomotor characteristicsin the two conditions. To study further the mechanisms of spinalplasticity potentially underlying such locomotor recovery, wealso summarize the locomotor adaptation of cats submitted tovarious types of peripheral nerve section of either ankle flexoror extensor muscles or after denervation of the hindpaws' cutaneousinputs. It is argued that, even in the spinal state, cats havethe ability to compensate for such lesions of the peripheralnervous system suggesting that the spinal cord has a significantpotential for adaptive plasticity that could be used in rehabilitationstrategies to restore locomotion after spinal cord injury.     

Matched filters in human vision

The technique of subthreshold addition of sinusoidal gratings was used to analyse the visual system of man during the perception of edges, lines, and bars. The experimentally obtained sensitivity function varies in close relationship to the test pattern, and can be factorized into the conjugate complex spectrum of the test pattern at threshold and a pattern-invariant function of spatial frequency. Interpreting the sensitivity function as transfer function, which is possible under certain conditions, we can describe the visual system as a matched filter which extracts an input signal contaminated with noise of specified spectral energy density. Questions discussed refer to the spatial operations occurring in matched filters, the relationship between the modulation transfer function for sine-wave gratings and the pattern-invariant transfer component, the exact determination of elements within the theoretical concept, and the realization of matched filters by the nervous system.These investigations were supported as a project of the Sonderforschungsbereich 50 Kybernetik, München.     

Fly vision: neural mechanisms of motion computation

A wide range of novel approaches are being used to dissect the visual system of the fly, both the neural networks of motion detection and the performance of these networks under complex natural stimulus conditions.     

The molecular basis of mechanisms underlying polarization vision

The underlying mechanisms of polarization sensitivity (PS) have long remained elusive. For rhabdomeric photoreceptors, questions remain over the high levels of PS measured experimentally. In ciliary photoreceptors, and specifically cones, little direct evidence supports any type of mechanism. In order to promote a greater interest in these fundamental aspects of polarization vision, we examined a varied collection of studies linking membrane biochemistry, protein-protein interactions, molecular ordering and membrane phase behaviour. While initially these studies may seem unrelated to polarization vision, a common narrative emerges. A surprising amount of evidence exists demonstrating the importance of protein-protein interactions in both rhabdomeric and ciliary photoreceptors, indicating the possible long-range ordering of the opsin protein for increased PS. Moreover, we extend this direction by considering how such protein paracrystalline organization arises in all cell types from controlled membrane phase behaviour and propose a universal pathway for PS to occur in both rhabdomeric and cone photoreceptors.     

Feature-based image segmentation in human vision

Experiments are described which indicate that the integration of high-precision shape information along a bright line is blocked by the presence of certain image features. All the features involved have three properties: (1) they are points where contours are not smooth (i.e. not twice differentiable) within the limits set by the finite space constants of visual processes; (2) they are all points that are emphasized in the responses of certain classes of circularly symmetric bandpass spatial filter; and (3) they are all significant for three-dimensional shape analysis. The results are interpreted as implying an inflexible segmentation of the contour image before detailed shape analysis.     

Two spatio-temporal filters in human vision

1. We have studied visual detection of a circular target moving across a spatially and/or temporally modulated background. Illumination, I _t , for threshold detection of the target has been measured as a function of background modulation frequency and changes in I _t associated with background modulation provide a means of determining the frequency response characteristics of visual channels. 2. Temporal frequency responses obtained with temporally modulated, spatially uniform backgrounds have pass-band characteristics and the temporal frequency for peak response increases with increase in mean background illumination. These temporal frequency responses resemble those of the de Lange (1954) filter, but the latter incorporates the incremental thresholds for steady backgrounds. 3. The amplitude of this temporal response saturates at low (40%) background modulation, decreases to zero as the target velocity falls to zero, and is maximum for a circular target of diameter 2°. 4. The spatial characteristics of this temporal filter were measured with a background field consisting of alternate steady and flickering bars. The resulting spatial frequency curve peaks at 1 cycle deg^-1 for all background illuminations and is independent of the background grating orientation. This spatial response differs significantly from the IMG spatial functions observed with a background grating (Barbur and Ruddock, 1980). 5. The spatial and temporal responses reviewed above exhibit similar parametric variations and we therefore associate them with a single spatiotemporal filter, ST2. 6. A second temporal response, with low-pass frequency characteristics, was observed with a background field consisting of two matched gratings, presented in spatial and temporal antiphase. This response has parametric properties similar to those of the IMG spatial response described previously by Barbur and Ruddock (1980), thus we associated the two sets of data with a single spatio-temporal filter, ST1. 7. We show that the ST2 responses can be obtained by combining ST1 responses, and we present a network incorporating the two filters. 8. We review other psychophysical studies which imply the activity of two spatio-temporal filters with properties of the kind revealed in our studies. We argue that filter ST1 has properties equivalent to those of X-type and filter ST2 has properties equivalent to those of Y-type electrophysiological mechanisms.     

A programmable VLSI filter architecture for application in real-time vision processing systems

An architecture is proposed for the realization of real-time edge-extraction filtering operation in an Address-Event-Representation (AER) vision system. Furthermore, the approach is valid for any 2D filtering operation as long as the convolutional kernel F(p,q) is decomposable into an x-axis and a y-axis component, i.e. F(p,q)=H(p)V(q), for some rotated coordinate system [p,q]. If it is possible to find a coordinate system [p,q], rotated with respect to the absolute coordinate system a certain angle, for which the above decomposition is possible, then the proposed architecture is able to perform the filtering operation for any angle we would like the kernel to be rotated. This is achieved by taking advantage of the AER and manipulating the addresses in real time. The proposed architecture, however, requires one approximation: the product operation between the horizontal component H(p) and vertical component V(q) should be able to be approximated by a signed minimum operation without significant performance degradation. It is shown that for edge-extraction applications this filter does not produce performance degradation. The proposed architecture is intended to be used in a complete vision system known as the Boundary-Contour-System and Feature-Contour-System Vision Model, proposed by Grossberg and collaborators. The present paper proposes the architecture, provides a circuit implementation using MOS transistors operated in weak inversion, and shows behavioral simulation results at the system level operation and electrical simulation and experimental results at the circuit level operation of some critical subcircuits.     

Two spatio-temporal filters in human vision

We have used the psychophysical methods described in the first paper of this series (Holliday and Ruddock, 1983) to determine selected spatial and temporal response characteristics of the ST1 and ST2 filters for subjects suffering visual defects. Data are given for 19 amblyopes, an albino and a hemianope, and comparison data are also given for a number of subjects with normal vision. The ST1 spatial responses for both the "normal" and "amblyopic" eyes of 12 convergent strabismic amblyopes are displaced to low spatial frequencies compared to the normal curve, which implies that there is a loss of fine spatial tuning. In all but one subject, the curve for the "amblyopic" eye peaks at a spatial frequency lower than that for the "normal" eye, thus the former deviates further from the normal pattern than the latter. The ST1 spatial responses of 6 refractive amblyopes are also displaced to the low frequency side of the normal curve, although on average the shift is smaller than in the case of the strabismic amblyopes. For each subject, the response curve of the "amblyopic" eye peaks at a lower spatial frequency than does that for the "normal" eye. ST1 spatial responses were measured for targets located up to 30 degrees off-axis along the horizontal meridian and sample data are given for one strabismic and one refractive amblyope and for two normal subjects. It is concluded from these data that the changes in the spatial responses associated with amblyopia do not simply reflect eccentric fixation of the target. The ST2 spatial response was measured for the "normal" and "amblyopic" eyes of 9 amblyopes (7 strabismic and 2 refractive). There is no significant difference between the average amblyopic response and that of normal subjects, and only in one case does the response for an "amblyopic" eye peak at a frequency lower than the peak frequency for normal vision. The ST2 temporal response for 9 amblyopes shows no systematic deviations from the normal response. For the albino, both the ST1 and ST2 spatial responses peak at around 0.3 cycles deg-1, and both curves are displaced considerably to the low spatial frequency side of the normal ST2 spatial response. The albino's ST2 temporal response is essentially normal. Measurements for the hemianope's "blind" hemifield under conditions appropriate to the isolation of the ST1 and ST2 spatial responses reveal no tuning curves. The ST2 temporal response for the "blind" hemifield, however, is of large amplitude, with a peak at 2 Hz, well below the normal frequency response peak. It is argued that the loss of fine spatial tuning which occurs in the ST1, but not the ST2, spatial responses of the amblyopes is consistent with the sequential organisation of these two filter classes proposed by Holliday and Ruddock (1983). Further, for the only two subjects whose ST2 spatial response curves are displaced to abnormally low frequencies (the albino and a strabismic amblyope) the ST1 spatial response is shifted to low spatial frequencies compared to the normal ST2 curve...     

Adaptive mechanisms underlying the bat biosonar behavior

For survival, bats of the suborder Microchiropetra emit intense ultrasonic pulses and analyze the weak returning echoes to extract the direction, distance, velocity, size, and shape of the prey. Although these bats and other mammals share the common layout of the auditory pathway and sound coding mechanism, they have highly developed auditory systems to process biologically relevant pulses at the expense of a reduced visual system. During this active biosonar behavior, they progressively shorten the pulse duration, decrease the amplitude and pulse-echo gap as they search, approach and finally intercept the prey. Presumably, these changes in multiple pulse parameters throughout the entire course of hunting enable them to extract maximal information about localized prey from the returning echoes. To hunt successfully, the auditory system of these bats must be less sensitive to intense emitted pulses but highly sensitive to weak returning echoes. They also need to recognize and differentiate the echoes of their emitted pulses from echoes of pulses emitted by other conspecifics. Past studies have shown the following mechanical and neural adaptive mechanisms underlying the successful bat biosonar behavior: (1) Forward orienting and highly mobile pinnae for effective scanning, signal reception, sound pressure transformation and mobile auditory sensitivity; (2) Avoiding and detecting moving targets more successfully than stationary ones; (3) Coordinated activity of highly developed laryngeal and middle ear muscles during pulse emission and reception; (4) Mechanical and neural attenuation of intense emitted pulses to prepare for better reception of weak returning echoes; (5) Increasing pulse repetition rate to improve multiple-parametric selectivity to echoes; (6) Dynamic variation of duration selectivity and recovery cycle of auditory neurons with hunting phase for better echo analysis; (7) Maximal multiple-parametric selectivity to expected echoes returning within a time window after pulse emission; (8) Pulse-echo delaysensitive neurons in higher auditory centers for echo ranging; (9) Corticofugal modulation to improve on-going multiple-parametric signal processing and reorganize signal representation, and (10) A large area of the superior colliculus, pontine nuclei and cerebellum that is sensitive to sound for sensori-motor integration. All these adaptive mechanisms facilitate the bat to effectively extract prey features for successful hunting.     

Ultraviolet polarization vision in fishes: possible mechanisms for coding e-vector

Polarization vision in vertebrates has been marked with significant controversy over recent decades. In the last decade, however, models from two laboratories have indicated that the spatial arrangement of photoreceptors provides the basis for polarization sensitivity Work in my laboratory, in collaboration with I. Novales Flamarique and F. I. Harosi, has shown that polarization sensitivity depends on a well-defined square cone mosaic pattern and that the biophysical properties of the square cone mosaic probably account for polarization vision in the ultraviolet spectrum. The biophysical mechanism appears to be based on the selective reflection of axial-polarized light by the partitioning membrane, formed along the contact zone between the members of the double cones, onto neighbouring ultraviolet-sensitive cones. In this short review, I discuss the historical development of this research problem.