PT  - JOURNAL ARTICLE
AU  - Sihn, Duho
AU  - Kim, Sung-Phil
TI  - Spatio-temporally efficient coding assigns functions to hierarchical structures of the visual system
AID  - 10.1101/2021.08.13.456321
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.08.13.456321
4099  - http://biorxiv.org/content/early/2021/08/28/2021.08.13.456321.short
4100  - http://biorxiv.org/content/early/2021/08/28/2021.08.13.456321.full
AB  - Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given that visual hierarchical structures contain both bottom-up and top-down pathways, the derived principles should encompass these bidirectional pathways. However, existing principles such as predictive coding do not provide an effective principle for bidirectional pathways. Therefore, we propose a novel computational principle for visual hierarchical structures as spatio-temporally efficient coding underscored by the efficient use of given resources in both neural activity space and processing time. This coding principle optimises bidirectional predictions over hierarchical structures by simultaneously minimising temporally differences in neural responses and maximising entropy in neural representations. Simulations demonstrated that the proposed spatio-temporally efficient coding was able to assign the function of appropriate neural representations of natural visual scenes to visual hierarchical structures. Furthermore, spatio-temporally efficient coding was able to predict well-known phenomena, including deviations in neural responses to unfamiliar inputs and bias in preferred orientations. Our proposed spatio-temporally efficient coding may facilitate deeper mechanistic understanding of the computational processes of hierarchical brain structures.Author Summary The visual system in the brain is composed of a hierarchical structure where neural signals pass in both bottom-up and top-down pathways. To account for how such a hierarchical structure attains a function to represent the external world, previous research has proposed diverse neural computational principles. Predictive coding, one of those principles, has attracted much attention recently that can assign representation functions to hierarchical structures but its computation relies on hypothetical error units. The present study proposes a novel coding principle for hierarchical structures without the notion of such hypothetical entities, via spatio-temporally efficient coding which underscores the efficient use of given resources. Spatio-temporally efficient coding optimises bidirectional predictions in hierarchical structures of the brain and can assign representational functions to visual hierarchical structures, without complex inference systems or hypothetical neuronal entities. We demonstrate that spatio-temporally efficient coding predicts well-known features of neural responses in the visual system such as that deviation in neural responses to unfamiliar inputs and a bias in preferred orientations.Competing Interest StatementThe authors have declared no competing interest.