Abstract
Abstract
Objective. Decoding memory functions for each hippocampal subregion involves extensive understanding of how each hippocampal subnetwork processes input stimuli. Theta burst stimulation (TBS) recapitulates natural brain stimuli which potentiates synapses in hippocampal circuits. TBS is typically applied to a bundle of axons to measure the immediate response in a downstream subregion like the cornu ammonis 1 (CA1). Yet little is known about network processing in response to stimulation, especially because individual axonal transmission between subregions is not accessible. Approach. To address these limitations, we reverse engineered the hippocampal network on a micro-electrode array partitioned by a MEMS four-chambered device with interconnecting microfluidic tunnels. The micro tunnels allowed monitoring single axon transmission which is inaccessible in slices or in vivo. The four chambers were plated separately with entorhinal cortex (EC), dentate gyrus (DG), CA1, and CA3 neurons. The patterned TBS was delivered to the EC hippocampal gateway. Evoked spike pattern similarity in each subregions was quantified with Jaccard distance metrics of spike timing. Main results. We found that the network subregion produced unique axonal responses to different stimulation patterns. Single site and multisite stimulations caused distinct information routing of axonal spikes in the network. The most spatially similar output at axons from CA3 to CA1 reflected the auto association within CA3 recurrent networks. Moreover, the spike pattern similarities shifted from high levels for axons to and from DG at 0.2 s repeat stimuli to greater similarity in axons to and from CA1 for repetitions at 10 s intervals. This time-dependent response suggested that CA3 encoded temporal information and axons transmitted the information to CA1. Significance. Our design and interrogation approach provide first insights into differences in information transmission between the four subregions of the structured hippocampal network and the dynamic pattern variations in response to stimulation at the subregional level to achieve probabilistic pattern separation and novelty detection.
Subject
Cellular and Molecular Neuroscience,Biomedical Engineering
Cited by
2 articles.
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