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Responsiveness of cerebral cortex to hippocampal inputs depends on brain region and brain state

Created on 19 Aug 2026

Authors

Rezaig, F., Gagliano, W., Lazcano, G., Fuentealba, P., Destexhe, A.

Abstract

Gamma oscillations (30-90 Hz) are a prominent signature of cortical network state, but whether they facilitate or hinder inter-areal communication remains unresolved. The communication-through-coherence hypothesis posits that gamma enhances transmission between areas, whereas recent computational work suggests that high-amplitude gamma oscillations may instead filter incoming inputs and reduce their impact. To distinguish between these accounts, we used a well-defined physiological input - sharp-wave ripple (SWR) complexes - to probe cortical responsiveness via two parallel monosynaptic pathways: from ventral CA1 to prefrontal cortex (PFC), and from dorsal CA1 to retrosplenial cortex (RSC). By classifying the cortical state immediately preceding each ripple as low- or high-amplitude gamma, we found that PFC responses to ripples were significantly larger during low-amplitude gamma states, an effect carried by the ventral CA1-PFC pathway and driven primarily by ripples during quiet wakefulness. RSC showed no such state-dependent modulation. A mean-field model of PFC reproduced the enhanced responsiveness during low-amplitude gamma and revealed that this modulation depends on the excitatory-inhibitory balance of the afferent input and on the level of recurrent excitation, providing a mechanistic explanation for the distinct behaviors of PFC and RSC, which differ in their local recurrent connectivity. Extending the model to a chain of cortical areas predicted that low-amplitude gamma supports robust propagation of activity across regions, whereas high-amplitude gamma confines it locally. Together, these results argue that low-amplitude gamma, rather than strong gamma synchronization, constitutes a favorable substrate for communication between brain areas.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 19 Aug 2026.

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