Flexible serial processing in networks of spiking neurons From access consciousness to flexible behaviour
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2020-08-01
Language
en
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Abstract
The ability to
exibly route information between otherwise separate brain regions is
crucial to perform newly instructed tasks in which each step takes as input the result
of the preceding step. How the brain implements that in parallel substrate is not well
understood. Psychological studies suggest that consciousness plays a key role, as single
steps can be performed when the input stimulus is subliminal, but not multiple ones. This
is in line with the global neuronal workspace theory which suggests that information is
consciously perceived when granted access to a broad fronto-parietal network and can be
broadcast to virtually any processor in the brain.
In this project, I propose the rst spiking neural model based on this theory to
perform serial tasks composed of multiple steps. The Neural Engineering Framework
and the Semantic Pointer Architecture are used to construct the model consisting of
parallel processing networks, a global workspace, working memory components and gating
networks. The resulting neural network is consistent with global neuronal workspace
theory at both cognitive and biological levels, as it accounts for conscious competition,
the associated ignition indexed by P3 waves, and selective broadcast. Interestingly, it
also addresses the unsolved issue of diachronic and synchronic integration in the process
of forming coalitions for conscious access. Simulations suggest that the model is capable
of performing many steps in a robust manner. Most importantly, it reproduces the same
patterns of response time as humans. Hence, the model provides a good framework for
explaining the role of consciousness in serial processing.
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Faculteit der Sociale Wetenschappen