Abstract Recent analyses have found waves of neural activity traveling across entire visual cortical areas in awake animals. These traveling waves modulate the excitability of local networks and perceptual sensitivity. The general computational role of these spatiotemporal patterns in the visual system, however, remains unclear. Here, we hypothesize that traveling waves endow the visual system with the capacity to predict complex and naturalistic inputs. We present a network model whose connections can be rapidly and efficiently trained to predict individual natural movies. After training, a few input frames from a movie trigger complex wave patterns that drive accurate predictions many frames into the future solely from the network’s connections. When the recurrent connections that drive waves are randomly shuffled, both traveling waves and the ability to predict are eliminated. These results suggest traveling waves may play an essential computational role in the visual system by embedding continuous spatiotemporal structures over spatial maps.
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What computations can be done with traveling waves in visual cortex?
Abstract Recent analyses have found waves of neural activity traveling across entire visual cortical areas in awake animals. These traveling waves modulate excitability of local networks and perceptual sensitivity. The general computational role for these spatiotemporal patterns in the visual system, however, remains unclear. Here, we hypothesize that traveling waves endow the brain with the capacity to predict complex and naturalistic visual inputs. We present a new network model whose connections can be rapidly and efficiently trained to predict natural movies. After training, a few input frames from a movie trigger complex wave patterns that drive accurate predictions many frames into the future, solely from the network’s connections. When the recurrent connections that drive waves are randomly shuffled, both traveling waves and the ability to predict are eliminated. These results show traveling waves could play an essential computational role in the visual system by embedding continuous spatiotemporal structures over spatial maps.
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- Award ID(s):
- 2015276
- PAR ID:
- 10529738
- Publisher / Repository:
- Research Square
- Date Published:
- Format(s):
- Medium: X
- Institution:
- Research Square
- Sponsoring Org:
- National Science Foundation
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