Despite the lack of direct evidence, it is generally believed that top-down signals are mediated by the abundant feedback connections from higher-to lower-order sensory areas. Here we provide direct evidence for a top-down mechanism. We stained the visual cortex of the ferret with a voltage-sensitive dye and presented a short-duration contrast square. This elicited an initial feedforward and lateral spreading depolarization at the square representation in areas 17 and 18. After a delay, a broad feedback wave (FBW) of neuron peak depolarization traveled from areas 21 and 19 toward areas 18 and 17. In areas 18 and 17, the FBW contributed the peak depolarization of dendrites of the neurons representing the square, after which the neurons decreased their depolarization and firing. Thereafter, the peak depolarization surrounded the figure representation over most of areas 17 and 18 representing the background. Thus, the FBW is an example of a well behaved long-range communication from higher-order visual areas to areas 18 and 17, collectively addressing very large populations of neurons representing the visual scene. Through local interaction with feedforward and lateral spreading depolarization, the FBW differentially activates neurons representing the object and neurons representing the background.T he current view of perception and cognition is that they rely on three main brain mechanisms, each supported by the existence of particular anatomical connections: bottom up, i.e., processing by early sensory areas, which is conveyed to higherorder areas; lateral processing through horizontal connections within an area; and top-down modulatory influences exerted by the rather extensive anatomical connections from higher-order sensory areas to the cortex in early sensory areas. Despite the fact that these top-down connections have been known for Ͼ25 years (1), and despite an overwhelming number of reports in which one could interpret the observations as presumed effects of top-down modulations, there is still no direct physiological evidence revealing the mechanism(s) by which higher-order sensory areas alter the computations of neurons in early sensory areas (2). That is, there is no evidence how, when, and where the top-down inputs alter the computation of neurons in early sensory areas. Further, the relative importance and timing of local lateral computations and top-down effects in previous studies of object perception are not obvious (3-5).Here, we define top-down modulation as a mechanism by which higher-order sensory areas through their connections influence computations of neurons in early sensory areas. These connections typically target neurons in upper (supragranular) layers or in lower (infragranular) layers within these early areas. Theoretically, it has been proposed that lateral interactions and the eventual feedback from higher-order visual areas would be finely timed to engage a large population of supragranular neurons in areas 17 and 18 in a cooperative computation of the visual stimulus and its surrou...
Motion can be perceived when static images are successively presented with a spatial shift. This type of motion is an illusion and is termed apparent motion (AM). Here we show, with a voltage sensitive dye applied to the visual cortex of the ferret, that presentation of a sequence of stationary, short duration, stimuli which are perceived to produce AM are, initially, mapped in areas 17 and 18 as separate stationary representations. But time locked to the offset of the 1st stimulus, a sequence of signals are elicited. First, an activation traverses cortical areas 19 and 21 in the direction of AM. Simultaneously, a motion dependent feedback signal from these areas activates neurons between areas 19/21 and areas 17/18. Finally, an activation is recorded, traveling always from the representation of the 1st to the representation of the next or succeeding stimuli. This activation elicits spikes from neurons situated between these stimulus representations in areas 17/18. This sequence forms a physiological mechanism of motion computation which could bind populations of neurons in the visual areas to interpret motion out of stationary stimuli.
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