MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex.

ABSTRACT: Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contrast to the deep hierarchical organization of primates, the visual system of the mouse has a shallower arrangement. Since mice and primates are both capable of visually guided behavior, this raises questions about the role of architecture in neural computation. In this work, we introduce a novel framework for building a biologically constrained convolutional neural network model of the mouse visual cortex. The architecture and structural parameters of the network are derived from experimental measurements, specifically the 100-micrometer resolut

SUBMITTER: Shi J 

PROVIDER: S-EPMC9481165 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature