A05 Dependece of network and cognitive function on Kv7/M and HCN/h-mediated intrinsic neural properties in medial entorhinal cortex

Dependece of network and cognitive function on Kv7/M and HCN/h-mediated intrinsic neural properties in medial entorhinal cortex

The medial entorhinal cortex (MEC) is the gateway between cortex and hippocampus (HPC) and is vital for certain memory functions. Learning depends on state-dependent oscillatory patterns in the entorhinal-hippocampal circuitry, which are thought to structure information transfer during memory consolidation. In MEC principal neurons, Kv7/M and HCN/h currents, which are affected in human neonatal or infantile epileptic encephalopathy, respectively, shape neuronal excitability and subthreshold intrinsic resonance properties. Due to robust inhibition within the MEC, the presence of the HCN/h-current leads to rebound potentials and rebound spiking, which can also be controlled by Kv7/M channels. Intrinsic M and h currents shape neuronal activity –via resonance and rebound spiking– at frequencies overlapping with entorhinal-hippocampal network patterns. It has been hypothesized that these properties, and their interplay with network oscillations, facilitate communication throughout the entorhinal–hippocampal network and contribute to grid cell formation. To reversibly alter intrinsic properties of MEC layer II/III principal neurons, we generated mouse lines to control the activity of Kv7/M or HCN/h channels through transgenic expression of dominant-negative Kv7 or HCN channel subunits. Our approach goes beyond lesion or functional inactivation studies because it allows for complete and reversible modification of two ion channel families whose dysfunction is linked to cognitive impairment in human diseases. This project is designed to assess local field potentials (LFP) in MEC and HPC during different brain states and behavioral tasks to elucidate the link between altered intrinsic neuronal properties and entorhinal–hippocampal network patterns and their importance to learning and memory processes.