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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.

Objects in natural scenes are rarely seen in isolation, but are usually overlapping or partially occluding other objects. To recognize individual objects, the visual system must be able to segregate overlapping objects from one another. Evidence from lesions in humans and monkeys suggest that perceptual segregation of occluded or overlapping objects involves extrastriate visual cortex. In monkeys, area V4 has been shown to play an important role in recognizing occluded or poorly salient shapes. In humans, a retinotopic homologue of ventral V4 (V4v) has been described, but it is not known whether this area is also functionally homologous to area V4 in monkeys. In this study, we tried to localize the visual cortical regions involved in perceptual segregation of overlapping shapes using positron emission tomography (PET). Regional cerebral blood flow (rCBF) was measured in seven subjects while they discriminated the relative areas of simultaneously presented rectangular shapes. In the control condition, the shapes were displayed without overlaps; in a second condition, the shapes overlapped each other partially. In a third condition, the shapes did not overlap but had been reduced in salience by adding random noise to the stimuli. Contrasting the overlapping shape condition with the control condition identified a single region in the left posterior lateral occipital cortex. The rCBF in this region also increased, though more weakly, during discrimination of shapes embedded in noise, relative to the control condition. The region activated by segregation of overlapping shapes was located in the posterior occipital cortex close to the anterior border of area V2, near the average location of human V4v as determined by retinotopic mapping studies. The activation of this region of extrastriate visual cortex by a task that involved segregation of overlapping shapes is consistent with monkey V4 and human V4v being functionally homologous. We conclude that discrimination of overlapping shapes involves in particular a region of extrastriate visual cortex located in the left lateral occipital cortex and that this region may correspond to human V4v.

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. [ABSTRACT FROM AUTHOR]

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2-3. [ABSTRACT FROM AUTHOR]

Abstract Illusory contours provide a striking example of the visual system’s ability to extract a meaningful representation of the surroundings from fragmented visual stimuli. Psychophysical and neurophysiological data suggest that illusory contours are processed in early visual cortical areas, and neuroimaging studies in humans have shown that Kanizsa-type illusory contours activate early retinotopic visual areas that are also activated by real contours. It is not known whether other types of illusory contours are processed by the same mechanisms, nor is it clear to what extent attentional effects may have influenced these results, as no attempt was made to match the salience of real and illusory stimuli in previous imaging studies. It therefore remains an open question whether there are any brain regions specifically involved in the perception of illusory contours. To address these questions, we have used 15O-butanol positron emission tomography (PET) and a novel kind of illusory contour stimulus that is induced only by aligned line ends. By employing a form discrimination task that was matched for attention and stimulus salience across conditions we were able to directly contrast perception of real and illusory contours. We found that the regions activated by illusory contour perception were the same as those activated by real contours. Only one region, located in the right fusiform gyrus, was significantly more strongly activated by perception of illusory contours than by real contours. In addition, a principal component analysis suggested that illusory contour perception is associated with a change in the correlation between V1 and V2. We conclude that different kinds of illusory contours are processed by the same cortical regions and that these regions overlap extensively with those involved in processing of real contours. At the regional level, perception of illusory contours thus appears to differ from perception of real contours by the degree of involvement of higher visual areas as well as by the nature of interaction between early visual areas. [ABSTRACT FROM AUTHOR]