Lateral occipital cortical areas are involved in the perception of objects, but it is not clear how these areas interact with first tier visual areas. Using synthetic images portraying a simple texture-defined figure and an electrophysiological paradigm that allows us to monitor cortical responses to figure and background regions separately, we found distinct neuronal networks responsible for the processing of each region. The figure region of our displays was tagged with one temporal frequency (3.0 Hz) and the background region with another (3.6 Hz). Spectral analysis was used to separate the responses to the two regions during their simultaneous presentation. Distributed source reconstructions were made by using the minimum norm method, and cortical current density was measured in a set of visual areas defined on retinotopic and functional criteria with the use of functional magnetic resonance imaging. The results of the main experiments, combined with a set of control experiments, indicate that the figure region, but not the background, was routed preferentially to lateral cortex. A separate network extending from first tier through more dorsal areas responded preferentially to the background region. The figure-related responses were mostly invariant with respect to the texture types used to define the figure, did not depend on its spatial location or size, and mostly were unaffected by attentional instructions. Because of the emergent nature of a segmented figure in our displays, feedback from higher cortical areas is a likely candidate for the selection mechanism by which the figure region is routed to lateral occipital cortex.Key words: visual cortex; object processing; figure/ground; cue invariance; lateral occipital complex; source imaging IntroductionObject recognition mechanisms must be able to extract shape independently of the surface cues that are present. Local estimates of surface cues such as texture grain or orientation, although necessary as inputs to the recognition process, convey little sense of object shape. Rather it is the pattern of cue similarity across regions and cue discontinuity across borders that must be integrated to recover object shape.The process of cue-invariant shape processing begins at an early stage of visual cortex and extends deep into extrastriate cortex and the temporal lobe. Cue invariance first is seen as early as V2, where some cells have a similar orientation or direction tuning for borders defined by different feature discontinuities (Leventhal et al., 1998;Marcar et al., 2000;Ramsden et al., 2001;Zhan and Baker, 2006). At higher levels of the visual system, such as inferotemporal cortex (Sary et al., 1993) and medial superior temporal area (Geesaman and Andersen, 1996), cells show shape selectivity that is mostly independent of the defining cues and spatial position. Functional magnetic resonance imaging (fMRI) studies in humans have implicated homologous extrastriate regions, in particular the lateral occipital complex (LOC), as sites of category-specific, cue-...

Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. We decomposed the posterior AR in the cortical source space with a 3-way PARAFAC technique, taking into account the spatial, frequency, and temporal aspects of mid-density EEG. We found a multicomponent AR structure in 90% of a group of 29 healthy adults. The typical resting-state structure consisted of a high-frequency occipito-parietal component of the AR (ARC1) and a low-frequency occipito-temporal component (ARC2), characterized by individual dynamics in time. In a few cases, we found a 3-component structure, with two ARC1s and one ARC2. The AR structures were stable in their frequency and spatial features over weeks to months, thus representing individual EEG alpha phenotypes. Cortical topography, individual stability, and similarity to the primate AR organization link ARC1 to the dorsal visual stream and ARC2 to the ventral one. Understanding how many and what kind of posterior AR components contribute to the EEG is essential for clinical neuroscience as an objective basis for AR segmentation and for interpreting AR dynamics under various conditions, both normal and pathological, which can selectively affect individual components.

Symmetry is a highly salient feature of animals, plants, and the constructed environment. Although the perceptual phenomenology of symmetry processing is well understood, little is known about the underlying neural mechanisms. Here we use visual evoked potentials to measure the time course of neural events associated with the extraction of symmetry in random dot fields. We presented sparse random dot patterns that were symmetric about both the vertical and horizontal axes. Symmetric patterns were alternated with random patterns of the same density every 500 msec, using new exemplars of symmetric and random patterns on each image update. Random/random exchanges were used as a control. The response to updates of random patterns was multiphasic, consisting of P65, N90, P110, N140 and P220 peaks. The response to symmetric/random sequences was indistinguishable from that for random/random sequences up to about 220 msec, after which the response to symmetric patterns became relatively more negative. Symmetry in random dot patterns thus appears to be extracted after an initial response phase that is indifferent to configuration. These results are consistent with the hypothesis (Lee, Mumford, Romero, & Lamme, 1998; Tyler & Baseler, 1998) that the symmetry property is extracted by processing in extrastriate cortex.

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Discontinuities in feature maps serve as important cues for the location of object boundaries. Here we used multi-input nonlinear analysis methods and EEG source imaging to assess the role of several different boundary cues in visual scene segmentation. Synthetic figure/ground displays portraying a circular figure region were defined solely by differences in the temporal frequency of the figure and background regions in the limiting case and by the addition of orientation or relative alignment cues in other cases. The use of distinct temporal frequencies made it possible to separately record responses arising from each region and to characterize the nature of nonlinear interactions between the two regions as measured in a set of retinotopically and functionally defined cortical areas. Figure/background interactions were prominent in retinotopic areas, and in an extra-striate region lying dorsal and anterior to area MT+. Figure/background interaction was greatly diminished by the elimination of orientation cues, the introduction of small gaps between the two regions, or by the presence of a constant second-order border between regions. Nonlinear figure/background interactions therefore carry spatially precise, time-locked information about the continuity/discontinuity of oriented texture fields. This information is widely distributed throughout occipital areas, including areas that do not display strong retinotopy.