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Recurrent Processing Dynamics in Occluded Object Recognition Revealed by Electroencephalography and Deep Neural

Ruiqi Li1, Zhencai Liu1, Shaoting Yan1

  • 1School of Electrical and Information Engineering, Zhengzhou University, Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Institute of Neuroscience, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, P. R. China.

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Recognizing partially hidden objects involves a two-stage recurrent process. Higher occlusion recruits additional processing, crucial for robust visual perception.

Keywords:
DNNsEEGOccluded object recognitionRSAbackward maskingrecurrent processing

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Vision

Background:

  • The human visual system effectively recognizes objects despite occlusion.
  • The precise temporal dynamics of recurrent processing in occluded object recognition are not well understood.

Purpose of the Study:

  • To investigate the temporal dynamics of recurrent processing during occluded object recognition.
  • To differentiate feedforward and recurrent contributions using electroencephalography (EEG) and deep neural networks (DNNs).

Main Methods:

  • Utilized high-temporal-resolution EEG, backward masking, and DNNs in a two-stage paradigm.
  • Applied multivariate pattern analysis (MVPA), temporal generalization analysis (TGA), and representational similarity analysis (RSA).
  • Manipulated occlusion levels and employed early masking to disrupt processing stages.

Main Results:

  • Low occlusion relied on feedforward processing, while higher occlusion engaged additional processing stages.
  • A two-stage recurrent process was identified: an early stage (200-300ms) for low-level features and a late stage (300-500ms) for higher-level representations.
  • Early masking disrupted the coordination of these recurrent stages, underscoring their importance.

Conclusions:

  • Occluded object recognition involves distinct feedforward and recurrent processing stages.
  • Recurrent processing, particularly cross-hierarchical interactions, is essential for robust visual perception of occluded objects.
  • The findings clarify the temporal dynamics of recurrence in visual object recognition.