ABSTRACTHippocampal damage results in profound retrograde, but no anterograde amnesia in contextual fear conditioning (CFC). Although the content learned in the latter have been discussed, the compensating regions were seldom proposed and never empirically addressed. Here, we employed network analysis of pCREB expression quantified from brain slices of rats with dorsal hippocampal lesion (dHPC) after undergoing CFC session. Using inter-regional correlations of pCREB-positive nuclei between brain regions, we modelled functional networks using different thresholds. The dHPC network showed small-world topology, equivalent to SHAM (control) network. However, diverging hubs were identified in each network. In a direct comparison, hubs in both networks showed consistently higher centrality values compared to the other network. Further, the distribution of correlation coefficients was different between the groups, with most significantly stronger correlation coefficients belonging to the SHAM network. These results suggest that dHPC network engaged in CFC learning is partially different, and engage alternative hubs. We next tested if pre-training lesions of dHPC and one of the new dHPC network hubs (perirhinal, Per; or disgranular retrosplenial, RSC, cortices) would impair CFC. Only dHPC-RSC, but not dHPC-Per, impaired CFC. Interestingly, only RSC showed a consistently higher centrality in the dHPC network, suggesting that the increased centrality reflects an increased functional dependence on RSC. Our results provide evidence that, without hippocampus, the RSC, an anatomically central region in the medial temporal lobe memory system might support CFC learning and memory.AUTHOR SUMMARYWhen determined cognitive performances are not affected by brain lesions of regions generally involved in that performance, the interpretation is that the remaining regions can compensate the damaged one. In contextual fear conditioning, a memory model largely used in laboratory rodents, hippocampal lesions produce amnesia for events occurred before, but not after the lesion, although the hippocampus is known to be important for new learning. Addressing compensation in animal models has always been challenging as it requires large-scale brain mapping. Here, we quantified 30 brain regions and used mathematical tools to model how a brain network can compensate hippocampal loss and learn contextual fear. We described that the damaged network preserved general interactivity characteristics, although different brain regions were identified as highly important for the network (e.g. highly connected). Further, we empirically validated our network model by performing double lesions of the hippocampus and the alternative hubs observed in the network models. We verified that double lesion of the hippocampus and retrosplenial cortex, one of the hubs, impaired contextual fear learning. We provide evidence that without hippocampus, the remaining network relies on alternative important regions from the memory system to coordinate contextual fear learning.
Network supporting contextual fear learning after dorsal hippocampal damage has increased dependence on retrosplenial cortex