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• W2018444744 abstract "Although orientation columns are less than a millimeter in width, recent neuroimaging studies indicate that viewed orientations can be decoded from cortical activity patterns sampled at relatively coarse resolutions of several millimeters. One proposal is that these differential signals arise from random spatial irregularities in the columnar map. However, direct support for this hypothesis has yet to be obtained. Here, we used high-field, high-resolution functional magnetic resonance imaging (fMRI) and multivariate pattern analysis to determine the spatial scales at which orientation-selective information can be found in the primary visual cortex (V1) of cats and humans. We applied a multiscale pattern analysis approach in which fine- and coarse-scale signals were first removed by ideal spatial lowpass and highpass filters, and the residual activity patterns then analyzed by linear classifiers. Cat visual cortex, imaged at 0.3125 mm resolution, showed a strong orientation signal at the scale of individual columns. Nonetheless, reliable orientation bias could still be found at spatial scales of several millimeters. In the human visual cortex, imaged at 1 mm resolution, a majority of orientation information was found on scales of millimeters, with small contributions from global spatial biases exceeding ∼1 cm. Our high-resolution imaging results demonstrate a reliable millimeters-scale orientation signal, likely emerging from irregular spatial arrangements of orientation columns and their supporting vasculature. fMRI pattern analysis methods are thus likely to be sensitive to signals originating from other irregular columnar structures elsewhere in the brain." @default.
• W2018444744 created "2016-06-24" @default.
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• W2018444744 date "2010-01-06" @default.
• W2018444744 modified "2023-10-17" @default.
• W2018444744 title "Multiscale Pattern Analysis of Orientation-Selective Activity in the Primary Visual Cortex" @default.
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• W2018444744 doi "https://doi.org/10.1523/jneurosci.4811-09.2010" @default.
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