Back

HCN channel currents underlie distinct neurophysiology of mediodorsal thalamus subnuclei

Ordemann, G. J.; Heckler, G. J.; Springer, K.; Driver, F.; Jackson, A. C.; Brumback, A. C.

2025-10-06 neuroscience
10.1101/2025.10.05.680564 bioRxiv
Show abstract

The mediodorsal thalamus (MD) is a hub coordinating cortical and subcortical brain regions to support executive and social/emotional functioning. MD can be subdivided into medial (M), central (C), and lateral (L) based on synaptic coupling, molecular identity, and physiology. Recently, we identified differential intrinsic properties between thalamocortical M and L neurons projecting to the medial prefrontal cortex (mPFC). L neurons projecting to mPFC showed increased hyperpolarization activated cyclic nucleotide gated (HCN) channel activity compared with M neurons, which caused L neurons to have lower cellular resistance and shorter time windows for integration of inputs. In addition to their role in synaptic integration, HCN channels are critical for thalamic rhythm generation. In this study, we used a combination of patch clamp electrophysiology and in situ hybridization to investigate how differences in HCN impact intrinsic oscillatory dynamics in M, C, and L neurons. We found that HCN current differed across MD subnuclei with C > L >> M. Clustering neurons based on HCN properties was sufficient to classify subnuclei with >95% accuracy, highlighting the differences in HCN function between subnuclei. Greater HCN activity in MD neurons was associated with decreased input resistance, decreased action potential firing, and higher resonant frequency. These findings provide an ionic basis for differences in cellular resonance across MD subnuclei, with implications for thalamic rhythm generation and information processing.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.