Back

Collective Learning in Living Neural Networks Facilitated by Contextual Background Photostimulation

De Zoysa, D.; Gates, S. J.; Emenheiser, A. M.; O'Neill, K. M.; Losert, W.

2025-03-10 neuroscience
10.1101/2025.03.03.641104 bioRxiv
Show abstract

This study explores collective learning in living neural networks, focusing on group-to-group Hebbian learning, i.e., strengthening and weakening of links dependent on the precise timing of their activities. While neuronal plasticity is now well understood for single pairs of neurons, recent research has demonstrated that groups of tens of neurons are required to encode information in mammalian brains. Thus, it is critical to understand how mechanisms of plasticity, in particular spike-timing-dependent plasticity (STDP) operate at the group scale. We find that neuronal groups can reach significant plasticity after only 45 stimuli when a proper tradeoff between pulse duration and photostimulation effectiveness is chosen. Background stimulation, which enhances the reliability of response for the targeted neuronal groups, is necessary for rapid network-level Hebbian learning. By demonstrating enhanced learning in the presence of background activity, this study underscores the highly cooperative character of neurons and the importance of investigating learning, information flow, and memory formation at the network scale.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.