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      Informed feature regularization in voxelwise modeling for naturalistic fMRI experiments

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      Embargo Lift Date: 2021-04-21
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      Author(s)
      Yılmaz, Özgür
      Çelik, Emin
      Çukur, Tolga
      Date
      2020-04-21
      Source Title
      European Journal of Neuroscience
      Print ISSN
      0953-816X
      Publisher
      Wiley
      Volume
      52
      Issue
      5
      Pages
      3394 - 3410
      Language
      English
      Type
      Article
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      Abstract
      Voxelwise modeling is a powerful framework to predict single‐voxel functional selectivity for the stimulus features that exist in complex natural stimuli. Yet, because VM disregards potential correlations across stimulus features or neighboring voxels, it may yield suboptimal sensitivity in measuring functional selectivity in the presence of high levels of measurement noise. Here, we introduce a novel voxelwise modeling approach that simultaneously utilizes stimulus correlations in model features and response correlations among voxel neighborhoods. The proposed method performs feature and spatial regularization while still generating single‐voxel response predictions. We demonstrated the performance of our approach on a functional magnetic resonance imaging dataset from a natural vision experiment. Compared to VM, the proposed method yields clear improvements in prediction performance, together with increased feature coherence and spatial coherence of voxelwise models. Overall, the proposed method can offer improved sensitivity in modeling of single voxels in naturalistic functional magnetic resonance imaging experiments.
      Keywords
      Computational neuroscience
      Feature regularization
      Modeling
      Stimulus correlation
      Permalink
      http://hdl.handle.net/11693/75450
      Published Version (Please cite this version)
      https://doi.org/10.1111/ejn.14760
      Collections
      • Aysel Sabuncu Brain Research Center (BAM) 213
      • Department of Electrical and Electronics Engineering 3702
      • National Magnetic Resonance Research Center (UMRAM) 218
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