Virtual Model of Mouse Cortex Solves Visual Tasks
acid andy writes:
Researchers for the Human Brain Project have trained a large-scale computer model of the mouse primary visual cortex to accurately solve five visual tasks.
[A] study by Human Brain Project (HBP) researchers from the Graz University of Technology (Austria) showed how a large data-based model can reproduce a number of the brain's visual processing capabilities in a versatile and accurate way. The results were published in the journal Science Advances.
With the help of the PCP Pilot Systems at the Julich Supercomputing Centre, developed in a collaboration between the HBP and the software company Nvidia, the team analysed a biologically detailed large-scale model of the mouse primary visual cortex that can solve multiple visual processing tasks. This model provides the largest integration of anatomical detail and neurophysiological data currently available for the visual cortex area V1, which is the first cortical region to receive and process visual information.
The model is built with a different architecture than those of deep neural networks used in current AI, and the researchers found out that it has interesting advantages regarding learning speed and visual processing performance over models that are commonly used for visual processing in AI.
The model was able to solve all five visual tasks presented by the team with high accuracy. For instance, these tasks involved classifying images of hand-written numbers or detecting visual changes in a long sequence of images. Strikingly, the virtual model achieved the same high performance as the brain even when the researchers subjected the model to noise in the images and in the network that it had not encountered during training.
Original Publication:Chen Guozhang, Franz Scherr & Wolfgang Maass (2022). A data-based large-scale model for primary visual cortex enables brain-like robust and versatile visual processing. Science Advances, DOI: 10.1126/sciadv.abq7592
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