We live in a world that is dominated by vision more than any other sense. Interpreting the structure of the world, for example constructing its third dimension (which must be inferred based on 2-D retinal projections), is an active and poorly understood task of the brain. For example, negotiating the 3-D world entails more than simply assigning distances to objects. Depth analysis involves interpreting shadows, gradients, relative motion, occlusion, and stereoscopic disparity, to understand objects, their spatial relationships, and our own relationship to them. Such analysis is important for all animals that need to ask: Which object is in front and what is behind? What is the shape of an object that is about to be manipulated? Where should a hand or hoof next be placed? The starting point is always a dynamic flat image, or at best a pair. Our 3-D impression of the world is a product of the brain. This principle is perhaps most strikingly demonstrated by visual illusions in which the same sensory stimulus can be interpreted by the brain in multiple different ways. In some cases, the brain can even decide to completely suppress the perception of a visual image.? ? This description of vision as """"""""active and interpretive"""""""" does not fit neatly with the experimental toolbox of the sensory physiologist, who is primarily concerned with stimuli and the responses they elicit. What should one make of stimuli that do not have a unique perceptual solution? It is interesting that such stimuli, which are inherently ambiguous, or sometimes inherently conflicting, often have a property of bistability. Bistable patterns, when viewed continuously, produce an alternating sequence of perceptual changes. As in the case of the famous faces vs. vase illusion, the two competing perceptual solutions alternate in the mind's eye, and unsurprisingly this alternation is most often in depth. For the physiologist, such spontaneous perceptual reversals pose a fascinating question: where in the brain do neural responses correspond to the structural components of a stimulus, and where do they instead correspond to a perceptual interpretation?? ? In the past year, we have made good progress toward our goal of understanding the neural mechanisms that underlie a fundamental aspect of visual perception: namely, what makes a stimulus visible? We have approached this problem by performing neurophysiological and imaging experiments in monkeys who were trained to report to us, by making manual responses, when a stimulus was perceived as being visible, and when it subjectively disappeared. To achieve this, we exploited a visual illusion we developed several years ago to induce the prolonged disappearance of a bright, central stimulus upon the presentation of surrounding field of moving stimuli in the periphery. We asked, ? can be induced to abruptly disappear when a surrounding pattern is flashed to the periphery. We asked, when a high contrast image on the retina, which is normally visible and salient, is perceptually suppressed, does this image continue to activate neurons the primary visual cortex? We focused on this question since it is very important for interpreting a broad range of studies that have found it surprisingly difficult to converge on an answer.? ? Recently, we have published our findings on this topic, which examine the basis of a previously identified discrepancy in the literature. Briefly, human fMRI studies have found that perceptual suppression was associated with a profound decrease in the BOLD (blood oxygenation level-dependent) response in the primary visual cortex, while electrophysiological studies in monkeys found that neurons in the same area did not show any percept-related changes. To examine possible reasons for this discrepancy, we combined microelectrode recordings and fMRI experiments in monkeys trained to report their perception. Using a paradigm we developed called generalized flash suppression (GFS), we found that in the very same monkey subjects, the two techniques (fMRI and single-unit recordings) yielded very different results. Surprisingly, we found that by monitoring the fMRI signal of a monkey's primary visual cortex, it is possible to determine whether a stimulus is visible or invisible, while it is impossible to do so by measuring the responses of individual neurons in the same area. In a control condition, the functional changes in the single unit and fMRI data were in perfect agreement. Thus the story has wider implications: while the neural and fMRI signals were in good agreement in one set of stimulus conditions, they diverged entirely in a different set of conditions. It is interesting that it is precisely during the condition of perceptual suppression (when the stimulus was physically present but invisible) that this uncoupling between the physiological signals took place.? ? Subsequent findings (manuscripts in preparation) studied the role of the visual thalamus in perceptual suppression. Single-unit studies showed that neurons the pulvinar nucleus, a large secondary thalamic nucleus heavily connected with the cortex, are closely associated with stimulus visibility. Unlike the primary visual cortex, neurons in this area showed strong changes in activity when the monkey reported that the stimulus had become invisible. In contrast, neurons in the neighboring lateral geniculate nucleus, whose main role is to pass visual information to the cortex respond only based on the sensory stimulus, and not what is perceived. Thus it appears that information about the perceptual state contributes to the pulvinar's responses to a stimulus. Additional studies are presently investigating the effects of inactivating this structure, whose responses may have less to do with """"""""sensory analysis"""""""" and more to do with the organization of stimulus-based attention and actions.? ? Finally, several studies, including our most recent one, indicates that there is a widespread modulation of local field potential (LFP) in the primary visual cortex during perceptual suppression. Using a technique called current source density analysis, we have found that the synaptic currents giving rise to this signal appear to be located not in V1, where the LFP modulations have been measured. Instead they appear to be originating elsewhere in the brain. These findings raise questions about how to think about the site of visual perception, particularly in light of the different tools used to study it. They also underscore the importance of studying and understanding the relationship between the neural responses in the brain and the corresponding fMRI responses, which are sometimes in clear disagreement.

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Müller, K-M; Wilke, M; Leopold, D A (2009) Visual adaptation to convexity in macaque area V4. Neuroscience 161:655-62
Shmuel, Amir; Leopold, David A (2008) Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest. Hum Brain Mapp 29:751-61
Maier, Alexander; Logothetis, Nikos K; Leopold, David A (2007) Context-dependent perceptual modulation of single neurons in primate visual cortex. Proc Natl Acad Sci U S A 104:5620-5
Wang, Zhisong; Maier, Alexander; Leopold, David A et al. (2007) Single-trial evoked potential estimation using wavelets. Comput Biol Med 37:463-73
Wang, Zhisong; Maier, Alexander; Leopold, David A et al. (2006) Relaxation-based multichannel signal combination (RELAX-MUSIC) for ROC analysis of percept-related neuronal activity. IEEE Trans Biomed Eng 53:2615-8
Leopold, David A; Bondar, Igor V; Giese, Martin A (2006) Norm-based face encoding by single neurons in the monkey inferotemporal cortex. Nature 442:572-5
Fukunaga, Masaki; Horovitz, Silvina G; van Gelderen, Peter et al. (2006) Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages. Magn Reson Imaging 24:979-92
Leopold, David A; Maier, Alexander (2006) Neuroimaging: perception at the brain's core. Curr Biol 16:R95-8
Wilke, Melanie; Logothetis, Nikos K; Leopold, David A (2006) Local field potential reflects perceptual suppression in monkey visual cortex. Proc Natl Acad Sci U S A 103:17507-12
Leopold, David A; Rhodes, Gillian; Muller, Kai-Markus et al. (2005) The dynamics of visual adaptation to faces. Proc Biol Sci 272:897-904

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