Integrated data analytics to understand visual processes in the cortex
DOI:
https://doi.org/10.34024/rnc.2023.v31.15237Keywords:
visual perception, visual cortex, times series, ROC curve, network modelsAbstract
Understanding the mechanisms of visual processing is essential for studying visual perception. In this article, the cortical areas involved in visual processing were discussed, such as the primary visual cortex (V1) and the secondary and associative visual areas. These areas play distinct roles in analyzing visual features such as shape, color, and motion. Furthermore, the importance of different approaches to analyze neural activity data and responses to visual stimuli was highlighted. It is concluded that the integration of different analysis techniques, such as time series, ROC curve, and network models, can expand the scope of investigation into visual perception processes. These approaches provide valuable insights into the organization and functioning of the visual cortex at different processing levels. The application of these techniques in studies of visual perception can contribute to a deeper understanding of the mechanisms involved in visual experience formation.
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