scholarly journals Infant sensitivity to radial optic flow fields during the first months of life

10.1167/8.4.5 ◽  
2008 ◽  
Vol 8 (4) ◽  
pp. 5 ◽  
Author(s):  
Odile Brosseau-Lachaine ◽  
Christian Casanova ◽  
Jocelyn Faubert
Keyword(s):  
Optic Flow ◽  
Flow Fields

scholarly journals Binocular Contributions to Optic Flow Processing in the Fly Visual System

2001 ◽  
Vol 85 (2) ◽  
pp. 724-734 ◽  
Author(s):  
Holger G. Krapp ◽  
Roland Hengstenberg ◽  
Martin Egelhaaf
Keyword(s):  
Optic Flow ◽  
Functional Role ◽  
Optic Lobe ◽  
Receptive Fields ◽  
Flow Fields ◽  
Wide Field ◽  
Motion Information ◽  
Local Motion ◽  
Response Field

Integrating binocular motion information tunes wide-field direction-selective neurons in the fly optic lobe to respond preferentially to specific optic flow fields. This is shown by measuring the local preferred directions (LPDs) and local motion sensitivities (LMSs) at many positions within the receptive fields of three types of anatomically identifiable lobula plate tangential neurons: the three horizontal system (HS) neurons, the two centrifugal horizontal (CH) neurons, and three heterolateral connecting elements. The latter impart to two of the HS and to both CH neurons a sensitivity to motion from the contralateral visual field. Thus in two HS neurons and both CH neurons, the response field comprises part of the ipsi- and contralateral visual hemispheres. The distributions of LPDs within the binocular response fields of each neuron show marked similarities to the optic flow fields created by particular types of self-movements of the fly. Based on the characteristic distributions of local preferred directions and motion sensitivities within the response fields, the functional role of the respective neurons in the context of behaviorally relevant processing of visual wide-field motion is discussed.

Optokinetic Eye Movements Elicited by Radial Optic Flow in the Macaque Monkey

1998 ◽  
Vol 79 (3) ◽  
pp. 1461-1480 ◽  
Author(s):  
Markus Lappe ◽  
Martin Pekel ◽  
Klaus-Peter Hoffmann
Keyword(s):  
Eye Movements ◽  
Flow Field ◽  
Eye Movement ◽  
Optic Flow ◽  
Macaque Monkey ◽  
Flow Fields ◽  
Movement Direction ◽  
Slow Phase ◽  
Eye Position ◽  
Self Motion

Lappe, Markus, Martin Pekel, and Klaus-Peter Hoffmann. Optokinetic eye movements elicited by radial optic flow in the macaque monkey. J. Neurophysiol. 79: 1461–1480, 1998. We recorded spontaneous eye movements elicited by radial optic flow in three macaque monkeys using the scleral search coil technique. Computer-generated stimuli simulated forward or backward motion of the monkey with respect to a number of small illuminated dots arranged on a virtual ground plane. We wanted to see whether optokinetic eye movements are induced by radial optic flow stimuli that simulate self-movement, quantify their parameters, and consider their effects on the processing of optic flow. A regular pattern of interchanging fast and slow eye movements with a frequency of 2 Hz was observed. When we shifted the horizontal position of the focus of expansion (FOE) during simulated forward motion (expansional optic flow), median horizontal eye position also shifted in the same direction but only by a smaller amount; for simulated backward motion (contractional optic flow), median eye position shifted in the opposite direction. We relate this to a change in Schlagfeld typically observed in optokinetic nystagmus. Direction and speed of slow phase eye movements were compared with the local flow field motion in gaze direction (the foveal flow). Eye movement direction matched well the foveal motion. Small systematic deviations could be attributed to an integration of the global motion pattern. Eye speed on average did not match foveal stimulus speed, as the median gain was only ∼0.5–0.6. The gain was always lower for expanding than for contracting stimuli. We analyzed the time course of the eye movement immediately after each saccade. We found remarkable differences in the initial development of gain and directional following for expansion and contraction. For expansion, directional following and gain were initially poor and strongly influenced by the ongoing eye movement before the saccade. This was not the case for contraction. These differences also can be linked to properties of the optokinetic system. We conclude that optokinetic eye movements can be elicited by radial optic flow fields simulating self-motion. These eye movements are linked to the parafoveal flow field, i.e., the motion in the direction of gaze. In the retinal projection of the optic flow, such eye movements superimpose retinal slip. This results in complex retinal motion patterns, especially because the gain of the eye movement is small and variable. This observation has special relevance for mechanisms that determine self-motion from retinal flow fields. It is necessary to consider the influence of eye movements in optic flow analysis, but our results suggest that direction and speed of an eye movement should be treated differently.

Wide-field, motion-sensitive neurons and matched filters for optic flow fields

2000 ◽  
Vol 83 (3) ◽  
pp. 185-197 ◽  
Author(s):  
Matthias O. Franz ◽  
Holger G. Krapp
Keyword(s):  
Optic Flow ◽  
Flow Fields ◽  
Wide Field ◽  
Matched Filters

A Neural Network for the Processing of Optic Flow from Ego-Motion in Man and Higher Mammals

1993 ◽  
Vol 5 (3) ◽  
pp. 374-391 ◽  
Author(s):  
Markus Lappe ◽  
Josef P. Rauschecker
Keyword(s):  
Neural Network ◽  
Motion Perception ◽  
Network Model ◽  
Neural Network Model ◽  
Optic Flow ◽  
Cortical Area ◽  
Visual Motion ◽  
Flow Fields ◽  
Subspace Algorithm ◽  
Motion Flow

Interest in the processing of optic flow has increased recently in both the neurophysiological and the psychophysical communities. We have designed a neural network model of the visual motion pathway in higher mammals that detects the direction of heading from optic flow. The model is a neural implementation of the subspace algorithm introduced by Heeger and Jepson (1990). We have tested the network in simulations that are closely related to psychophysical and neurophysiological experiments and show that our results are consistent with recent data from both fields. The network reproduces some key properties of human ego-motion perception. At the same time, it produces neurons that are selective for different components of ego-motion flow fields, such as expansions and rotations. These properties are reminiscent of a subclass of neurons in cortical area MSTd, the triple-component neurons. We propose that the output of such neurons could be used to generate a computational map of heading directions in or beyond MST.

Neuronal responses in extrastriate cortex to objects in optic flow fields

1997 ◽  
Vol 14 (5) ◽  
pp. 879-895 ◽  
Author(s):  
Helen Sherk ◽  
Kathleen Mulligan ◽  
Jong-Nam Kim
Keyword(s):  
Optic Flow ◽  
Cortical Neurons ◽  
Flow Fields ◽  
Target Object ◽  
Direction Selectivity ◽  
Object Motion ◽  
Extrastriate Cortex ◽  
Flow Simulations ◽  
Preferred Direction ◽  
Visual Cortical

AbstractDuring locomotion, observers respond to objects in the environment that may represent obstacles to avoid or landmarks for navigation. Although much is known about how visual cortical neurons respond to stimulus objects moving against a blank background, nothing is known about their responses when objects are embedded in optic flow fields (the patterns of motion seen during locomotion). We recorded from cells in the lateral suprasylvian visual area (LS) of the cat, an area probably analogous to area MT. In our first experiments, optic flow simulations mimicked the view of a cat trotting across a plain covered with small balls; a black bar lying on the balls served as a target object. In subsequent experiments, optic flow simulations were composed of natural elements, with target objects representing bushes, rocks, and variants of these. Cells did not respond to the target bar in the presence of optic flow backgrounds, although they did respond to it in the absence of a background. However, 273/423 cells responded to at least one of the taller, naturalistic objects embedded in optic flow simulations. These responses might represent a form of image segmentation, in that cells detected objects against a complex background. Surprisingly, the responsiveness of cells to objects in optic flow fields was not correlated with preferred direction as measured with a moving bar or whole-field texture. Because the direction of object motion was determined solely by receptive-field location, it often differed considerably from a cell's preferred direction. About a quarter of the cells responded well to objects in optic flow movies but more weakly or not at all to bars moving in the same direction as the object, suggesting that the optic flow background modified or suppressed direction selectivity.

scholarly journals An illusory transformation of optic flow fields without local motion interactions

2004 ◽  
Vol 4 (8) ◽  
pp. 609-609
Author(s):  
J. Duijnhouwer ◽  
J. A. Beintema ◽  
R. J. A. Wezel ◽  
A. V. Berg
Keyword(s):  
Optic Flow ◽  
Flow Fields ◽  
Local Motion

An illusory transformation of optic flow fields

1993 ◽  
Vol 33 (11) ◽  
pp. 1481-1490 ◽  
Author(s):  
Charles J. Duffy ◽  
Robert H. Wurtz
Keyword(s):  
Optic Flow ◽  
Flow Fields

scholarly journals Detection of first-order structure in optic flow fields

1996 ◽  
Vol 36 (2) ◽  
pp. 259-270 ◽  
Author(s):  
Susan F. Te Pas ◽  
Astrid M.L. Kappers ◽  
Jan J. Koenderink
Keyword(s):  
Optic Flow ◽  
Flow Fields ◽  
Order Structure ◽  
First Order
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