Modelling non-local neural information processing in the brain
biorxiv(2022)
Abstract
The representation of the surrounding world emerges through integration of sensory information and actions. We present a novel neural model which implements non-local, parallel information processing on a neocolumnar architecture with lateral interconnections. Information is integrated into a holographic wave interference pattern. We compare the simulated in silico pattern with observed in vivo invasive and non-invasive electrophysiological data in human and non-human primates. Our model replicates the modulation of neural high-frequency activity during visual perception showing that phase-locked low and high-frequency oscillations self-organize efficiently and carry high information content. The simulation further models how criticality (high content) of information processing emerges given a sufficiently high number of correlated neurons. Non-local information processing, forming one holographic wave pattern, suggests a platform for emergence of conscious perception.
One sentence summary Simulated non-local information processing on a neocolumnar architecture models well multiple electrophysiological observations of brain activity, including high-frequency activity during visual perception in primates.
### Competing Interest Statement
The authors have declared no competing interest.
MoreTranslated text
Key words
brain,information processing,modelling,non-local
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined