A Stable Brain From Unstable Components: Emerging Concepts and Implications for Neural Computation

Neuroscience. 2017 Aug 15;357:172-184. doi: 10.1016/j.neuroscience.2017.06.005. Epub 2017 Jun 8.

Abstract

Neuroscientists have often described the adult brain in similar terms to an electronic circuit board- dependent on fixed, precise connectivity. However, with the advent of technologies allowing chronic measurements of neural structure and function, the emerging picture is that neural networks undergo significant remodeling over multiple timescales, even in the absence of experimenter-induced learning or sensory perturbation. Here, we attempt to reconcile the parallel observations that critical brain functions are stably maintained, while synapse- and single-cell properties appear to be reformatted regularly throughout adult life. In this review, we discuss experimental evidence at multiple levels ranging from synapses to neuronal ensembles, suggesting that many parameters are maintained in a dynamic equilibrium. We highlight emerging hypotheses that could explain how stable brain functions may be generated from dynamic elements. Furthermore, we discuss the impact of dynamic circuit elements on neural computations, and how they could provide living neural circuits with computational abilities a fixed structure cannot offer. Taken together, recent evidence indicates that continuous dynamics are a fundamental property of neural circuits compatible with macroscopically stable behaviors. In addition, they may be a unique advantage imparting robustness and flexibility throughout life.

Keywords: chronic calcium imaging; computational modeling; dendritic spines; neural stability; synaptic plasticity.

Publication types

  • Review

MeSH terms

  • Animals
  • Brain / physiology*
  • Humans
  • Models, Neurological
  • Neural Networks, Computer
  • Neurons / physiology*