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...

In the inferior temporal (IT) cortex of monkeys, which has been shown to play a critical role in colour discrimination, there are neurons sensitive to a narrow range of hues and saturation. By contrast, neurons in the retina and the parvocellular layer of the lateral geniculate nucleus (pLGN) encode colours in a way that does not provide explicit representation of hue or saturation, and the process by which hue- and saturation-selectivity is elaborated remains unknown. We therefore tested the colour-selectivity of neurons in the primary visual cortex (V1) and compared it with those of pLGN and IT neurons. Quantitative analysis was performed using a standard set of colours, systematically distributed within the CIE (Commission Internationale de l'Eclairage)-xy chromaticity diagram. Selectivity for hue and saturation was characterized by analysing response contours reflecting the overall distribution of responses across the chromaticity diagram. We found that the response contours of almost all pLGN neurons were linear and broadly tuned for hue. Many V1 neurons behaved similarly; nonetheless, a considerable number of V1 neurons had clearly curved response contours and were selective for a narrow range of hues or saturation. The relative frequencies of neurons exhibiting various selectivities for hue and saturation were remarkably similar in the V1 and IT cortex, but were clearly different in the pLGN. Thus, V1 apparently plays a very important role in the conversion of colour signals necessary for generating the elaborate colour selectivity observed in the IT cortex.

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.

We determined the spatio-temporal dynamics of cortical gamma-oscillations modulated during eye movement tasks, using simultaneous eye tracking and intracranial electrocorticography (ECoG) recording. Patients with focal epilepsy were instructed to follow a target moving intermittently and unpredictably from one place to another either in an instantaneous or smooth fashion during extraoperative ECoG recording. Target motion elicited augmentation of gamma-oscillations in the lateral, inferior and polar occipital regions in addition to portions of parietal and frontal regions; subsequent voluntary eye movements elicited gamma-augmentation in the medial occipital region. Such occipital gamma-augmentations could not be explained by contaminations of ocular or myogenic artifacts. The degree of gamma-augmentation was generally larger during saccade compared to pursuit trials, while a portion of the polar occipital region showed pursuit-preferential gamma-augmentations. In addition to the aforementioned eye movement task, patients were asked to read a single word popping up on the screen. Gamma-augmentation was elicited in widespread occipital regions following word presentation, while gamma-augmentation in the anterior portion of the medial occipital region was elicited by an involuntary saccade following word presentation rather than word presentation itself. Gamma-augmentation in the lateral, inferior and polar occipital regions can be explained by increased attention to a moving target, whereas gamma-augmentation in the anterior-medial occipital region may be elicited by images in the peripheral field realigned following saccades. In functional studies comparing brain activation between two tasks, eye movement patterns during tasks may need to be considered as confounding factors.

The texture of an object provides important cues for its recognition; however, little is known about the neural representation of texture. To investigate the representation of texture in the visual cortex, we recorded single-cell activities in area V4 of macaque monkeys. To distinguish the sensitivity of the cells to texture parameters such as density and element size from that to spatial frequency, we used texture stimuli mimicking shaded granular surfaces. We varied the size and density of the texture elements and the direction of elemental luminance gradients (apparent shadings) as stimulus parameters. Most macaque V4 cells (151 of 170; 89%) exhibited sensitivity to the texture parameters. Interestingly, 21of these cells were tuned to single shading directions (unidirectional tuning). This unidirectional tuning cannot be explained by complex-cell-like tuning for spectral power of spatial frequency, because texture stimuli with a shading direction and its opposite have almost the same spectral power. Unidirectional tunings of these cells were invariant for the position of the texture elements. Thus, this tuning cannot be explained by simple-cell-like phase-dependent spatial frequency tuning or selectivity to a particular arrangement of the elements. Moreover, the unidirectional tuning had a bias toward vertical directions, consistent with an anisotropy in the perception of three-dimensional shape from shading. This novel spatial property suggests that V4 cells are involved in extracting texture features from objects, including their three-dimensionality.