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Network analysis of cortical visual pathways mapped with PET

AR McIntosh, CL Grady, LG Ungerleider, JV Haxby, SI Rapoport and B Horwitz
Journal of Neuroscience 1 February 1994, 14 (2) 655-666; DOI: https://doi.org/10.1523/JNEUROSCI.14-02-00655.1994
AR McIntosh
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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CL Grady
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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LG Ungerleider
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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JV Haxby
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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SI Rapoport
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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B Horwitz
Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892.
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Abstract

Brain metabolic mapping techniques, such as positron emission tomography (PET), can provide information about the functional interactions within entire neural systems. With the large quantity of data that can accumulate from a mapping study, a network analysis, which makes sense of the complex interactions among neural elements, is necessary. A network analysis was performed on data obtained from a PET study that examined both the changes in regional cerebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot- location matching) task. Brain areas for the network were selected based on regions showing significant rCBF or interregional correlations between tasks. Anterior temporal and frontal lobe regions were added to the network using a principal components analysis. Interactions among selected regions were quantified with structural equation modeling. In the structural equation models, connections between brain areas were based on known neuroanatomy and the interregional correlations were used to calculate path coefficients representing the magnitude of the influence of each directional path. The combination of the anatomical network and interregional correlations created a functional network for each task. The functional network for the right hemisphere showed that in the object vision task, dominant path influences were among occipitotemporal areas, while in the spatial vision task, occipitoparietal interactions were stronger. The network for the spatial vision task also had a strong feedback path from area 46 to occipital cortex, an effect that was absent in the object vision task. There were strong interactions between dorsal and ventral pathways in both networks. Functional networks for the left hemisphere did not differ between tasks. Networks for the interhemispheric interactions showed that the dominant pathway in the right hemisphere also had stronger effects on homologous left hemisphere areas and are consistent with a hypothesis that intrahemispheric interactions were greater in the right hemisphere in both tasks, and that these influences were transmitted callosally to the left hemisphere.

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The Journal of Neuroscience: 14 (2)
Journal of Neuroscience
Vol. 14, Issue 2
1 Feb 1994
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Network analysis of cortical visual pathways mapped with PET
AR McIntosh, CL Grady, LG Ungerleider, JV Haxby, SI Rapoport, B Horwitz
Journal of Neuroscience 1 February 1994, 14 (2) 655-666; DOI: 10.1523/JNEUROSCI.14-02-00655.1994

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Network analysis of cortical visual pathways mapped with PET
AR McIntosh, CL Grady, LG Ungerleider, JV Haxby, SI Rapoport, B Horwitz
Journal of Neuroscience 1 February 1994, 14 (2) 655-666; DOI: 10.1523/JNEUROSCI.14-02-00655.1994
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