How Brain Rhythms Influence Neural Communication Pathways

Recent research has shed light on the dynamic ways the brain manages its communication channels when processing information. When recalling familiar memories or exploring new environments, the brain does not rely on a single, fixed route. Instead, it adjusts its pathways by modulating the balance between two key inhibitory circuits that govern neural rhythms.

An international team led by Claudio Mirasso from the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) and Santiago Canals from the Institute for Neurosciences (IN) has demonstrated how the brain's flexibility in routing information depends on this inhibitory balance. Their study, published in PLoS Computational Biology, reveals that the interaction between slow (theta) and fast (gamma) brain rhythms can switch modes based on the regulatory influence of these circuits.

This modulation allows the brain to prioritize different sources of information: in familiar situations, it favors direct pathways that facilitate memory reactivation, whereas in novel scenarios, it activates modes that integrate new sensory inputs with existing memories, supporting learning and adaptation.

The team combined computational modeling with experimental recordings from the hippocampus, a critical brain region for memory and navigation. They discovered that the transition between modes of operation is continuous and driven by the strength of specific synaptic connections. This flexibility enables the brain to efficiently adapt its processing strategies to meet varying cognitive demands.

Beyond memory, this mechanism could influence other cognitive functions like attention, providing a broader understanding of how different brain rhythms interact to optimize information processing. The findings suggest that the balance between inhibitory circuits is a fundamental principle in neural communication, influencing how the brain responds to external stimuli and internal representations.

Looking ahead, researchers aim to extend their models to different brain regions and neuronal types, especially to understand how these dynamics are altered in neurological conditions such as epilepsy, addiction, or Alzheimer's disease. Understanding these mechanisms at a detailed level could pave the way for new therapeutic strategies.