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Kv4.1, a key ion channel for low frequency firing of dentate granule cells, is crucial for pattern separation.
Year of publication 2020
Title of paper Kv4.1, a key ion channel for low frequency firing of dentate granule cells, is crucial for pattern separation.
Author Kim KR, Yeon Lee S, Ho Yoon S, Kim Y, Jeong HJ, Lee S, Ho Suh Y, Kang JS, Cho H, Lee SH, Kim MH, Ho WK.
Publication in journal Journal of Neuroscience
Status of publication accepted
Vol 40(11)
Link https://www.jneurosci.org/content/40/11/2200.long 248회 연결

The dentate gyrus (DG) in the hippocampus may play key roles in remembering distinct episodes through pattern separation, which may be subserved by the sparse firing properties of granule cells (GCs) in the DG. Low intrinsic excitability is characteristic of mature GCs, but ion channel mechanisms are not fully understood. Here, we investigated ionic channel mechanisms for firing frequency regulation in hippocampal GCs using male and female mice, and identified Kv4.1 as a key player. Immunofluorescence analysis showed that Kv4.1 was preferentially expressed in the DG, and its expression level determined by Western blot analysis was higher at 8-week than 3-week-old mice, suggesting a developmental regulation of Kv4.1 expression. With respect to firing frequency, GCs are categorized into two distinctive groups: low-frequency (LF) and high-frequency (HF) firing GCs. Input resistance (R in) of most LF-GCs is lower than 200 MΩ, suggesting that LF-GCs are fully mature GCs. Kv4.1 channel inhibition by intracellular perfusion of Kv4.1 antibody increased firing rates and gain of the input-output relationship selectively in LF-GCs with no significant effect on resting membrane potential and R in, but had no effect in HF-GCs. Importantly, mature GCs from mice depleted of Kv4.1 transcripts in the DG showed increased firing frequency, and these mice showed an impairment in contextual discrimination task. Our findings suggest that Kv4.1 expression occurring at late stage of GC maturation is essential for low excitability of DG networks and thereby contributes to pattern separation.