Back

Training Session Intervals Shape Functional Connectivity In Spatial Learning: A Brain-Wide Analysis

Gosetti di Sturmeck, T.; Bergamo, S.; Mastrorilli, V.; Patrizi, A.; Nuzzi, D.; Pezzulo, G.; Del Ferraro, G.; Del Ferraro, G.; Rinaldi, A.; Mele, A.

2026-02-13 neuroscience
10.64898/2026.02.12.705541 bioRxiv
Show abstract

A substantial body of research indicates that spaced training, characterized by longer inter-trial intervals between training epochs, consistently outperforms massed training in promoting durable memory. To investigate the neural mechanisms underlying this difference, we quantified c-Fos expression across 126 brain regions and mapped network activity following both spatial and cue-based learning under massed and spaced training protocols. While both training regimens (spaced and massed) and memory types (spatial and cue-based) produced small-world networks with similar overall topology, they differed in the functional organization of specific circuits. Massed spatial training preferentially activated hippocampal-thalamic and claustrum-basal ganglia-thalamic pathways. In contrast, spaced spatial training promoted stronger cortico-thalamic interactions and enhanced communication between the hippocampus and basal ganglia, indicating a shift toward a more integrated, cortically mediated network. These findings suggest that temporal spacing of training reorganizes memory-related brain networks, enhancing cortical-thalamic dynamics to support more efficient spatial memory. Finally, spaced networks were more sensitive to targeted disruptions of key connector hubs--identified through betweenness centrality analysis--than massed networks, pointing to a potential systems-level trade-off.

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.