2021/09/24 by Jing Shuang Li, Li, Jing Shuang · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Neuroscience · #EEG and Brain-Computer Interfaces #FOS: Biological sciences #FOS: Electrical engineering #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering #q-bio.NC
paper · pdf · doi:10.48550/arxiv.2109.11757
To appear in 2022 ACC; Companion paper to arXiv:2110.05029, arXiv:2109.11752; Version updates: author change (J. C. D. has been consulted), additional material + figures
openalex publication_date 2021/09/24 · arxiv created 2022/04/05 · arxiv updated 2022/04/07 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
The presence of internal feedback pathways (IFPs) is a prevalent yet unexplained phenomenon in the brain. Motivated by experimental observations on 1) motor-related signals in visual areas, and 2) massively distributed processing in the brain, we approach this problem from a sensorimotor standpoint and make use of distributed optimal controllers to explain IFPs. We use the System Level Synthesis (SLS) controller to model neural phenomena such as signaling delay, local processing, and local reaction. Based on the SLS controller, we make qualitative predictions about IFPs that strongly align with existing experimental observations. We introduce a `mesocircuit' for optimal performance with distributed and local processing, and local disturbance rejection; this mesocircuit requires extreme amounts of IFPs and memory for proper function. This is the first theory that replicates the massive amounts of IFPs in the brain purely from a priori principles, providing a new theoretical basis upon which we can build to better understand the inner workings of the brain.