Neuronal Mechanisms of Visual Movement Perception and Some Psychophysical and Behavioral Correlations

Spatio-temporal requirements for direction selectivity in area 18 and PMLS complex cells

The spatio-temporal requirements for direction selectivity were studied in two extrastriate motion processing areas in the cat, area 18 and the posteromedial lateral suprasylvian cortex (PMLS). Direction, velocity and pixel size of random pixel arrays (RPA) were adjusted for each neuron and direction selectivity was measured as a function of step size and delay for a given optimal velocity. A subset of direction selective complex cells in area 18 was tuned to intermediate step size and delay combinations rather than the smoothest motion (band-pass cells). Other area 18 complex cells responded best to the smallest value of step size and delay (low-pass cells). Tuning varied with the pixel size of the RPA. Cells with tuning for smaller pixels favoured a preference for non-smooth motion. Area 18 cells with lower spatial resolution showed larger optimal and maximal step sizes. For a subset of the cells in area 18, we measured direction selectivity for extensive step-delay combinations, covering multiple velocities. Results showed that most cells were tuned to narrow range of step-delay combinations, and that the optimal step size was independent of temporal delay. Direction selective complex cells in PMLS were tuned to larger pixel sizes than those in area 18, although the distributions did overlap. In contrast to area 18, PMLS cells preferred the smoothest motion, irrespective of RPA pixel size.

Neuronal mechanisms for detection of motion in the field of view

The visual system cannot rely only upon information from the retina to perceive object motion because identical retinal stimulations can be evoked by the movement of objects in the field of view as well as by the movements of retinal images self-evoked by eye movements. We clearly distinguish the two situations, perceiving object motion in the first case and stationarity in the second. The present work deals with the neuronal mechanisms that are likely involved in the detection of real motion. In monkeys, cells that are able to distinguish real from self-induced motion (real-motion cells) are distributed in several cortical areas of the dorsal visual stream. We suggest that the activity of these cells is responsible for motion perception, and hypothesize that these cells are the elements of a cortical network representing an internal map of a stable visual world. Supporting this view are the facts that: (i) the same cortical regions in humans are activated in brain imaging studies during perception of object motion; and (ii) lesions of these same regions produce selective impairments in motion detection, so that patients interpret any retinal image motion as object motion, even when they result from her/his eye movements. Among the areas of the dorsal visual stream rich in real-motion cells, V3A and V6, likely involved in the fast form and motion analyses needed for visual guidance of action, could use real-motion signals to orient the animal's attention towards moving objects, and/or to help grasping them. Areas MT/V5, MST and 7a, known to be involved in the control of pursuit eye movements and in the analysis of visual signals evoked by slow ocular movements, could use real-motion signals to give a proper evaluation of motion during pursuits.

Visual motion detection in man is governed by non-retinal mechanisms

It is generally assumed that there is no sizable proportion of motion detectors in the primate retina. To test this specifically for humans, visual evoked potentials (VEPs) and electroretinograms (ERGs) were recorded simultaneously to visual motion onset (9.3 degrees /s) of an expanding or contracting 'dartboard'. The degree of motion-specific responses in cortex and retina was assessed by testing the direction specificity of motion adaptation with three conditions in a fully balanced paradigm: motion-onset potentials were measured after adaptation to: (1) a stationary pattern; (2) motion in the same direction as the test stimulus; and (3) motion in the opposite direction. Motion-onset responses in the VEP were dominated by the typical N2 at 150 ms, in the ERG by a positivity at 70 ms. Onset of contraction or expansion evoked virtually identical VEP and ERG responses (P>0.5). Motion adaptation produced strong direction-specific effects in the VEP (P<0.05), but not in the ERG (P=0.58): In the adapting and non-adapting direction the VEP (N2) was reduced by 75 and 50% (P<0.001), the ERG by 32 and 26% (P<0.01 and 0.05), respectively. The striking difference of the direction-specificity of motion adaptation between cortex and retina suggests that in humans the vast majority of motion-specific processing occurs beyond the retinal ganglion cells.

From elements to perception: local and global processing in visual neurons

Gestalt psychologists in the early part of the century challenged psychophysical notions that perceptual phenomena can be understood from a punctate (atomistic) analysis of the elements present in the stimulus. Their ideas slowed later attempts to explain vision in terms of single-cell recordings from individual neurons. A rapprochement between Gestalt phenomenology and neurophysiology seemed unlikely when the first ECVP was held in Marburg, Germany, in 1978. Since that time, response properties of neurons have been discovered that invite an interpretation of visual phenomena (including illusions) in terms of neuronal processing by long-range interactions, as first proposed by Mach and Hering in the last century. This article traces a personal journey into the early days of neurophysiological vision research to illustrate the progress that has taken place from the first attempts to correlate single-cell responses with visual perceptions. Whereas initially the receptive-field properties of individual classes of cells--e.g., contrast, wavelength, orientation, motion, disparity, and spatial-frequency detectors--were used to account for relatively simple visual phenomena, nowadays complex perceptions are interpreted in terms of long-range interactions, involving many neurons. This change in paradigm from local to global processing was made possible by recent findings, in the cortex, on horizontal interactions and backward propagation (feedback loops) in addition to classical feedforward processing. These mechanisms are exemplified by studies of the tilt effect and tilt aftereffect, direction-specific motion adaptation, illusory contours, filling-in and fading, figure--ground segregation by orientation and motion contrast, and pop-out in dynamic visual-noise patterns. Major questions for future research and a discussion of their epistemological implications conclude the article.

Recognition of direction of uniform and accelerated visual motion and EEG alpha wave phases

The perception of visual motion in seven subjects was studied comparing motion towards or away from the fixation point in the left or right hemifield. The light target was moved either at a constant velocity or positively or negatively accelerated to compensate for the magnification factor of the visual cortex. We compared probability and latency of motion recognition when it was asynchronous or synchronized to different phases of the alpha wave of the EEG recorded over the occipital cortex. If the motion accelerated away from the fixation point and was synchronized with the alpha wave it was more likely to be perceived whereas if it was towards the fixation point it was less likely to be detected. However, perception of the constant velocity motion was not changed by locking it to the alpha wave phase. These results support the hypothesis that the scanning waves of excitation spread over the visual cortex periodically and that they are locked to the alpha component of the EEG.

The processing of object and self-motion in the tectofugal and accessory optic pathways of birds

This paper reviews electrophysiological studies of motion processing in the tectofugal and accessory optic systems (AOS), and suggests these are specialized respectively for the analysis of object motion and self motion. Evidence is presented which shows that directionally specific neurons in the tectofugal system process local motion and are inhibited by wholefield motion. These cells respond to kinematograms and moving occlusion edges and may therefore also be involved in figure-ground segregation and depth perception. In contrast, cells in the nucleus of the basal optic root (nBOR), a component of the AOS, respond best to large slowly moving patterns. These cells are directionally selective preferring either upward, downward or backward directions. In the posterior region of the nBOR some cells have been found which are binocular and prefer either the same or opposite directions of motion in the two eyes. Thus, these cells are tuned to respond optimally to either translational or rotational components of wholefield motion and it is suggested these may be involved in the control of posture and locomotion.

Motion detection in the presence and absence of background motion in an Anolis lizard

Anolis lizards respond to a moving object viewed in the periphery of their visual field by turning their eye to fixate the object with their central fovea. This paper describes the relative effectiveness of different patterns of motion of a small black lure in eliciting these eye movements and the way motion of a backdrop of vegetation affects the response. The stimulus was positioned 45 degrees from the animal's line of gaze and oscillated in the vertical axis at different frequencies between 0.5 and 10 Hz. At each frequency, the amplitude of the oscillation was increased until the lizard flicked its eye towards the stimulus. The minimum amplitude needed for response (0.22 degrees of visual angle) was independent of frequency and waveform. The probability of any response occurring was, however, lower at higher frequencies (7 and 10 Hz) and a 1.5 Hz square wave evoked the greatest proportion of responses. Sinusoidal oscillation of a background of vegetation at 1.6 Hz during or before motion of the stimulus lure reduced the probability of an eye flick but did not raise the minimum amplitude needed for a response. The suppressive effect was greatest when the lure was oscillated at frequencies close to that of the background. It is concluded that Anolis, which rely upon motion to detect objects in the periphery of the visual field, filter out irrelevant motion such as that of windblown vegetation by responding preferentially to particular patterns of motion and short term habituation to commonly present patterns of motion.

The antidromic activation of tectal neurons by electrical stimuli applied to the caudal medulla oblongata in the toad, Bufo bufo L

In order to specify the tectal projection to the bulbar/spinal regions, the antidromic responses of the physiologically identified tectal neurons as well as the gross antidromic field responses in the optic tectum to electrical stimuli applied to the caudal medulla were examined in the paralyzed common toad, Bufo bufo. The antidromic field potential was recorded in the optic tectum in response to electrical stimuli applied to the ventral paramedian portion of the contralateral caudal medulla (where the crossed tecto-spinal pathway of Rubinson (1968) and Lázár (1969) runs), but generally not when they were applied to various parts of the ipsilateral caudal medulla. The antidromic field potential was largest at the superficial part of Layer 6 or at the border between Layers 6 and 7 of the optic tectum, indicating that neurons in these layers project to the contralateral caudal medulla. Mapping experiments of the antidromic field potential over the optic tectum showed that the antidromic field potential was recorded mainly in the lateral part of it, indicating that this part of the optic tectum is the main source of projection neurons to the contralateral caudal medulla. Various classes of tectal neurons as well as retinal ganglion neurons were identified from the characteristics of the response properties to moving visual stimuli and the properties of the receptive fields. Of these, the Class T1, T2, T3, T4, T5(1), T5(2), T5(3), and T5(4) tectal neurons were activated antidromically by stimuli applied to the contralateral caudal medulla. Only a limited proportion of the Class T5(1) neurons was activated antidromically by stimuli applied to the ipsilateral caudal medulla. On the other hand, the Class T7 and T8 neurons, as well as the Class R2, R3, and R4 retinal neurons, were not activated antidromically by stimuli applied to the caudal medulla of either side. These results suggest a possibility that these tectal neurons which project to the medullary regions form the substrate of the sensorimotor interfacing and contribute to the initiation or coordination of the visually guided behavior, such as prey-catching.

Separate motion aftereffects from each eye and from both eyes

Monocular and binocular motion aftereffects (MAEs) are described, which were contingent upon which eye(s) was (were) exposed to the adapting motion. Subjects viewed clockwise rotation of a patterned disc with their left eye, alternating every 5 sec with anticlockwise rotation seen with their right eye, for a 10-min adapting period.

RESULT

they saw an anticlockwise motion aftereffect with their left eye, and a clockwise MAE with their right eye. These monocular MAEs lasted for only 2-20 sec, but could be elicited repeatedly over a 2-6 min period, and could still be re-elicited two hours later. In a second experiment, subjects adapted for 10 min to the following cycle of 5-sec rotations: left eye, clockwise: right eye, clockwise: and both eyes together, anticlockwise.

RESULT

they saw an anticlockwise MAE with their left eye only or with their right eye only, and a clockwise MAE when both eyes were open. A model of monocular and binocular inputs to motion sensitive neural channels is proposed.

Visual motion detection models: features and frequency filters

Two kinds of models have been proposed for taking into account the sensory processes at work in the detection of visual motion: the feature model and the frequency-filter model. The problem of the complementarity of these models is raised. On the basis of empirical data, it is proposed that they are consistent.