The Packet Switching Brain

By Daniel J. Graham, D. Rockmore. 2011

54 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neuroscience

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Citations in the corpus

What can the brain teach us about building artificial intelligence? (2016, background): “We should consider that one of the missing components in deep learning models of cognition— and of most large-scale models of brain and cognitive function—is understanding of how signals are selectively routed to different destinations in brains (Graham and Rockmore, 2011; Graham 2014).”
Closures and Cavities in the Human Connectome (2016, background): “Such structure facilitates more traditional conceptual models of parallel processing, wherein data is copied or divided into multiple pieces in order to rapidly perform distinct computations, and then recombined [29].”
Linking Structure and Function in Macroscale Brain Networks. (2020, unknown): “Communication models emerging from network science and telecommunication engineering conceptualize functional interactions as the superposition of elementary signaling events on the underlying anatomical network [43,55] (Figure 2).”
Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks (2014, background): “A physiologically plausible alternative would be a packet-switched architecture, wherein a message is broken up into packets, which individually take the most efficient path to the destination, where they are re-assembled [45].”
Cliques and cavities in the human connectome (2016, background): “Such structure facilitates more traditional conceptual models of parallel processing, wherein data is copied or divided into multiple pieces in order to rapidly perform distinct computations, and then recombined (Graham and Rockmore 2011).”
Communication dynamics in complex brain networks (2017, background): “A corollary is that the load of information flow on edges that comprise the shortest paths is disproportionately large, resulting in non-resilient communication that is prone to bottlenecks 53 and vulnerable to delays, loss of information and failure owing to damage 54,55 .”
Routing in the brain (2014, background): “But while single neuron dynamics are reasonably well understood, and while researchers have begun to elucidate key aspects of network topology in brains, very little work has been devoted to possible routing schemes in the brain (Graham and Rockmore, 2011). Indeed, brain networks must possess a syst”