Revealing and reshaping attractor dynamics in large networks of cortical neurons

PLoS Comput Biol. 2024 Jan 19;20(1):e1011784. doi: 10.1371/journal.pcbi.1011784. eCollection 2024 Jan.

Abstract

Attractors play a key role in a wide range of processes including learning and memory. Due to recent innovations in recording methods, there is increasing evidence for the existence of attractor dynamics in the brain. Yet, our understanding of how these attractors emerge or disappear in a biological system is lacking. By following the spontaneous network bursts of cultured cortical networks, we are able to define a vocabulary of spatiotemporal patterns and show that they function as discrete attractors in the network dynamics. We show that electrically stimulating specific attractors eliminates them from the spontaneous vocabulary, while they are still robustly evoked by the electrical stimulation. This seemingly paradoxical finding can be explained by a Hebbian-like strengthening of specific pathways into the attractors, at the expense of weakening non-evoked pathways into the same attractors. We verify this hypothesis and provide a mechanistic explanation for the underlying changes supporting this effect.

MeSH terms

  • Brain
  • Learning* / physiology
  • Neurons* / physiology

Grants and funding

OB is supported by the Israeli Science Foundation (grant 1442/21) and an HFSP research grant (RGP0017/2021). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.