Back

Unique spatiotemporal synchronization solutions of heterogeneous local Ca2+ dynamics underlie the formation of each impulse that emerges from the cardiac sinoatrial node

Tagirova, S.; Maltsev, A. V.; Baca, G. L.; Bychkov, R.; Maltsev, V. A.; Lakatta, E. G.

2024-12-20 cell biology
10.1101/2024.12.18.629224 bioRxiv
Show abstract

We used both linear and nonlinear analyses to determine how information processing within and among incessant heterogeneous local Ca2+ oscillation (LCO) results in formation of rhythmic impulses in mouse SAN ex vivo. Phase analysis delineated a network of functional pacemaker cell clusters, distinguished by their LCO amplitudes, kinetics, and phases. Cross-talk of LCO dynamics within the network culminated in rhythmic SAN global Ca2+ transients (CaTs), having a mean rate and rhythm identical to that recorded by the reference sharp electrode in the right atria, indicating that CaTs are induced by global SAN electrical impulses. Initial conditions of each impulse and subsequent LCO ensemble evolution during an impulse differed from each other, associated with an apparent stochastic process (carrying a degree of uncertainty) within network. A small pacemaker cluster located near the crista terminalis (CT) exhibited the highest degrees of intrinsic power, earliest rotor-like energy transfer, most frequent point-to-point instability, earliest acrophase, greatest impulse-to-impulse variability within the SAN functional cluster network. Unique, variable small-world network Ca2+ information sharing within and among all clusters during initial and terminal impulse phases, created a unique solution for each impulse, while preserving the identity of each cluster (a highly efficient form of information processing at low wiring and energy costs). Cross-recurrence analysis verified that LCO dynamics within the small cluster near CT were more stochastic and less deterministic than those of the other clusters, indicating that this small cluster took the lead in the initiation of the SAN impulse and that the others followed.

Matching journals

The top 6 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.