Integrating Computational and Neural Findings in Visual Object Perception

• Main Author: Hans P. Op de Beeck (auth)
• Other Authors: Judith C. Peters (auth), Rainer Goebel (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: Frontiers Media SA 2016
• Series: Frontiers Research Topics
• Subjects: Neurosciences; object recognition; fMRI; multimodal data integration; neural networks; invariance; computational neuroscience; Computer Vision; Feature representation; Neurophysiology; ventral visual pathway
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.