The Flow of Axonal Information Among Hippocampal Subregions: 1. Feed-Forward and Feedback Network Spatial Dynamics Underpinning Emergent Information Processing - Vakilna, Yash S.; Tang, William C.; Wheeler, Bruce C.; Brewer, Gregory J. (Frontiers in Neural Circuits, 2021)
The trisynaptic pathway in the mammalian hippocampus enables cognitive learning and memory. Despite decades of reports on the anatomy and physiology, the functional architecture of the hippocampal network remains poorly understood in terms of the dynamics of axonal information transfer between subregions. Information largely flows from the entorhinal cortical (EC) inputs into the dentate gyrus (DG) and further processing in the CA3 and CA1 before returning to the EC. Here we reconstructed elements of the rat hippocampus in a novel device over an electrode array that allowed monitoring the directionality of individual axons between the subregions. The direction of spike propagation was determined by the transmission delay of the axons recorded between two electrodes in the microfluidic tunnels. The majority of axons from the EC to DG operated in the feedforward direction, with other regions developing unexpectedly large proportions of feedback axons to balance excitation. Spike timing in axons between each region followed single exponential log-log distributions over two orders of magnitude from 0.01 to 1 s indicating that conventional descriptors of mean firing rates are misleading assumptions. Most of the spiking occurred in bursts that required two exponentials to fit the distribution of interburst intervals. This suggested the presence of up states and down states in every region, with the least up states in the DG to CA3 feedforward axons and the CA3 subregion. The peaks of the lognormal distributions of intraburst spike rates were similar in axons between regions with modes around 95 Hz distributed over an order of magnitude. Burst durations were also lognormally distributed around a peak of 88 ms over two orders of magnitude. Despite the diversity of these spike distributions, spike rates from individual axons were often linearly correlated to subregions. These linear relationships enabled generation of structural connectivity graphs not previously possible without the directional flow of axonal information. The rich axonal spike dynamics between subregions of the hippocampus reveal both constraints and broad emergent dynamics of hippocampal architecture. Knowledge of this network architecture may enable more efficient computational AI networks, neuromorphic hardware as well as stimulation and decoding from cognitive implants.