» Articles » PMID: 39994473

Three Systems of Circuit Formation: Assembly, Updating and Tuning

Overview
Specialty Neurology
Date 2025 Feb 24
PMID 39994473
Authors
Affiliations
Soon will be listed here.
Abstract

Understanding the relationship between genotype and neuronal circuit phenotype necessitates an integrated view of genetics, development, plasticity and learning. Challenging the prevailing notion that emphasizes learning and plasticity as primary drivers of circuit assembly, in this Perspective, we delineate a tripartite framework to clarify the respective roles that learning and plasticity might have in this process. In the first part of the framework, which we term System One, neural circuits are established purely through genetically driven algorithms, in which spike timing-dependent plasticity serves no instructive role. We propose that these circuits equip the animal with sufficient skill and knowledge to successfully engage the world. Next, System Two is governed by rare but critical 'single-shot learning' events, which occur in response to survival situations and prompt rapid synaptic reconfiguration. Such events serve as crucial updates to the existing hardwired knowledge base of an organism. Finally, System Three is characterized by a perpetual state of synaptic recalibration, involving continual plasticity for circuit stabilization and fine-tuning. By outlining the definitions and roles of these three core systems, our framework aims to resolve existing ambiguities related to and enrich our understanding of neural circuit formation.

References
1.
Zador A . A critique of pure learning and what artificial neural networks can learn from animal brains. Nat Commun. 2019; 10(1):3770. PMC: 6704116. DOI: 10.1038/s41467-019-11786-6. View

2.
LeCun Y, Bengio Y, Hinton G . Deep learning. Nature. 2015; 521(7553):436-44. DOI: 10.1038/nature14539. View

3.
Martini F, Guillamon-Vivancos T, Moreno-Juan V, Valdeolmillos M, Lopez-Bendito G . Spontaneous activity in developing thalamic and cortical sensory networks. Neuron. 2021; 109(16):2519-2534. PMC: 7611560. DOI: 10.1016/j.neuron.2021.06.026. View

4.
Wu M, Kourdougli N, Portera-Cailliau C . Network state transitions during cortical development. Nat Rev Neurosci. 2024; 25(8):535-552. PMC: 11825063. DOI: 10.1038/s41583-024-00824-y. View

5.
Kuwahara H, Gao X . Stochastic effects as a force to increase the complexity of signaling networks. Sci Rep. 2013; 3:2297. PMC: 3725509. DOI: 10.1038/srep02297. View