On Computational Modeling of Sleep-Wake Cycle
arxiv(2024)
摘要
Why do mammals need to sleep? Neuroscience treats sleep and wake as default
and perturbation modes of the brain. It is hypothesized that the brain
self-organizes neural activities without environmental inputs. This paper
presents a new computational model of the sleep-wake cycle (SWC) for learning
and memory. During the sleep mode, the memory consolidation by the
thalamocortical system is abstracted by a disentangling operator that maps
context-dependent representations (CDR) to context-independent representations
(CIR) for generalization. Such a disentangling operator can be mathematically
formalized by an integral transform that integrates the context variable from
CDR. During the wake mode, the memory formation by the hippocampal-neocortical
system is abstracted by an entangling operator from CIR to CDR where the
context is introduced by physical motion. When designed as inductive bias,
entangled CDR linearizes the problem of unsupervised learning for sensory
memory by direct-fit. The concatenation of disentangling and entangling
operators forms a disentangling-entangling cycle (DEC) as the building block
for sensorimotor learning. We also discuss the relationship of DEC and SWC to
the perception-action cycle (PAC) for internal model learning and perceptual
control theory for the ecological origin of natural languages.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要