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Integrating Computational and Neural Findings in Visual Object Perception

Integrating Computational and Neural Findings in Visual Object Perception

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The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.

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Keywords

  • Biology, Life Sciences
  • Computational neuroscience
  • Computer vision
  • Feature representation
  • fMRI
  • invariance
  • Life sciences: general issues
  • Mathematics & science
  • multimodal data integration
  • neural networks
  • Neurophysiology
  • Neurosciences
  • object recognition
  • ventral visual pathway

Links

DOI: 10.3389/978-2-88919-873-3

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