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  • Title: Spatiotemporal dynamics of human object recognition processing: an integrated high-density electrical mapping and functional imaging study of "closure" processes.
    Author: Sehatpour P, Molholm S, Javitt DC, Foxe JJ.
    Journal: Neuroimage; 2006 Jan 15; 29(2):605-18. PubMed ID: 16168676.
    Abstract:
    Humans are capable of recognizing objects, often despite highly adverse viewing conditions (e.g., occlusion). The term "perceptual closure" has been used to refer to the neural processes responsible for "filling-in" missing information in the visual image under such conditions. Closure phenomena have been linked to a group of object recognition areas, the so-called lateral-occipital complex (LOC). Here, we investigated the spatiotemporal dynamics of perceptual closure processes by coregistering data from high-density electrical recordings (ERPs) and functional magnetic resonance imaging (fMRI) while subjects participated in a perceptual closure task. Subjects were presented with highly fragmented images and control scrambled images. Fragmented images were calibrated to be 'just' recognizable as objects (that is, perceptual closure was necessary), whereas the scrambled images were unrecognizable. Comparison of responses to these two stimulus classes revealed the neural processes underlying perceptual closure. fMRI revealed an object recognition system that mediates these closure processes, the core of which consists of the LOC regions. ERP recordings resulted in the well-characterized N(CL) component (for negativity associated with closure), a robust relative negativity over bilateral occipito-temporal scalp that occurs in the 230-400 ms timeframe. Our investigations further revealed an extended network of dorsal and frontal regions, also involved in perceptual closure processes. Inverse source analysis showed that the major generators of N(CL) localized to the identical regions within LOC revealed by the fMRI recordings and detailed the temporal dynamics across these LOC regions including interactions between LOC and these other nodes of the object recognition circuit.
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