Flicker defined form (FDF) is a temporally-dependent illusion created by the counterphase flicker of randomly positioned element dots, that preferentially stimulates the magnocellular system. Previous studies have found improvement with peripheral presentation, a resistance to blur and a dependence on high temporal frequencies. (Quaid & Flanagan, 2005a; Quaid & Flanagan, 2005b). Although it is seemingly very different from most luminance defined, static stimuli, it is still unknown in what ways it differs. The current study aimed to determine how FDF varies or is similar to static, luminance defined stimuli. Current results showed that FDF could be matched to particular spatial frequencies, and improved with increasing background structure and area. Shapes could be discriminated from each other and recognized. These results suggest that although FDF is dependent on motion pathways for temporal dynamic perception, it could also benefit from the input of form perception pathways, depending on the cues present in the stimulus (e.g. background structure, area). Results also showed that FDF does not benefit from Gestalt rules of contour closure, unlike some static stimuli, although related studies have shown that FDF could still be detected in spite of blur. These studies suggest that FDF appears to rely on motion perception pathways, areas such as MT, but is easier to perceive at times due to overlap in function with shape perception pathways, areas such as IT. As such FDF shares many characteristics with other motion-defined-form stimuli, but uniquely shares aspects of form vision.

Flicker defined form (FDF) is a temporally-dependent illusion created by the counterphase flicker of randomly positioned element dots, that preferentially stimulates the magnocellular system. Previous studies have found improvement with peripheral presentation, a resistance to blur and a dependence on high temporal frequencies. (Quaid & Flanagan, 2005a; Quaid & Flanagan, 2005b). Although it is seemingly very different from most luminance defined, static stimuli, it is still unknown in what ways it differs. The current study aimed to determine how FDF varies or is similar to static, luminance defined stimuli. Current results showed that FDF could be matched to particular spatial frequencies, and improved with increasing background structure and area. Shapes could be discriminated from each other and recognized. These results suggest that although FDF is dependent on motion pathways for temporal dynamic perception, it could also benefit from the input of form perception pathways, depending on the cues present in the stimulus (e.g. background structure, area). Results also showed that FDF does not benefit from Gestalt rules of contour closure, unlike some static stimuli, although related studies have shown that FDF could still be detected in spite of blur. These studies suggest that FDF appears to rely on motion perception pathways, areas such as MT, but is easier to perceive at times due to overlap in function with shape perception pathways, areas such as IT. As such FDF shares many characteristics with other motion-defined-form stimuli, but uniquely shares aspects of form vision.

<p>Pictorial cues, together with motion and stereoscopic depth fields, can be used for perception and constitute ‘three kinds’ of vision. Edges in images are important features and can be created in either of these attributes. Are local edge and global shape detection processes attribute-specific? Three visual phenomena, believed to be due to low-level visual processes, were used as probes to address these issues. (1) Tilt illusions (misperceived orientation of a bar caused by an inducing grating) were used to investigate possible binding of edges across attributes. Double dissociation of tilt repulsion illusions (obtained with small orientation differences between inducer and bar) and attraction illusions (obtained with large orientation differences) suggest different mechanisms for their origins. Repulsion effects are believed to be due to processes in striate cortex and attraction because of higher level processing. The double dissociation was reproduced irrespective of the attributes used to create the inducing grating and the test-bar, suggesting that the detection and binding of edges across attributes take place in striate cortex. (2) Luminance-based illusory contour perception is another phenomenon believed to be mediated by processes in early visual cortical areas. Illusory contours can be cued by other attributes as well. Detection facilitation of a near-threshold luminous line occurred when it was superimposed on illusory contours irrespective of the attributes used as inducers. The result suggests attribute-independent activation of edge detectors, responding to real as well as illusory contours. (3) The performance in detecting snake-like shapes composed of aligned oriented elements embedded in randomly oriented noise elements was similar irrespective of the attributes used to create the elements. Performance when the attributes alternated along the path was superior to that predicted with an independent channel model. These results are discussed in terms of binding across attributes by feed-forward activation of orientation selective attribute-invariant cells (conjunction cells) in early stages of processing and contextual modulation and binding across visual space mediated by lateral and/or feedback signals from higher areas (dynamic binding).</p>

Pictorial cues, together with motion and stereoscopic depth fields, can be used for perception and constitute ‘three kinds’ of vision. Edges in images are important features and can be created in either of these attributes. Are local edge and global shape detection processes attribute-specific? Three visual phenomena, believed to be due to low-level visual processes, were used as probes to address these issues. (1) Tilt illusions (misperceived orientation of a bar caused by an inducing grating) were used to investigate possible binding of edges across attributes. Double dissociation of tilt repulsion illusions (obtained with small orientation differences between inducer and bar) and attraction illusions (obtained with large orientation differences) suggest different mechanisms for their origins. Repulsion effects are believed to be due to processes in striate cortex and attraction because of higher level processing. The double dissociation was reproduced irrespective of the attributes used to create the inducing grating and the test-bar, suggesting that the detection and binding of edges across attributes take place in striate cortex. (2) Luminance-based illusory contour perception is another phenomenon believed to be mediated by processes in early visual cortical areas. Illusory contours can be cued by other attributes as well. Detection facilitation of a near-threshold luminous line occurred when it was superimposed on illusory contours irrespective of the attributes used as inducers. The result suggests attribute-independent activation of edge detectors, responding to real as well as illusory contours. (3) The performance in detecting snake-like shapes composed of aligned oriented elements embedded in randomly oriented noise elements was similar irrespective of the attributes used to create the elements. Performance when the attributes alternated along the path was superior to that predicted with an independent channel model. These results are discussed in terms of binding across attributes by feed-forward activation of orientation selective attribute-invariant cells (conjunction cells) in early stages of processing and contextual modulation and binding across visual space mediated by lateral and/or feedback signals from higher areas (dynamic binding).