Developing Tools for Neurobiology: The Retina as a Neuropharmacology Testbed & Electrode Pooling to Boost Extracellular Array Recording

Citation

Ni, Yu-Li (2023) Developing Tools for Neurobiology: The Retina as a Neuropharmacology Testbed & Electrode Pooling to Boost Extracellular Array Recording. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/jeh6-w316. https://resolver.caltech.edu/CaltechTHESIS:10112022-213905012

Abstract

This thesis presents two tool development projects for neurobiology and one explorative project to find organizing principles for autism.

The first project (Chap 2, Retina as Probe) was conceived to tackle the problem that there hasn’t been a reliable model system for system-level neuropharmacology. We introduce a testbed for this: the mammalian retina. The retina involves many of the known neurotransmitters and modulators. Yet its synaptic wiring is well understood, and quantitative models exist to explain its input-output functions. One can connect the systems-level effects to the underlying cellular and molecular causes. To demonstrate the retina’s use, we explored the effects of a range of general anesthetics on the light responses of the mouse retina. At sub-anesthetic doses, we found that certain anesthetics exert a paradoxical effect: they increase the light response of some retinal neurons and suppress the response of others. Notably, this occurred for alcohols and ketamine but not for isoflurane. We traced these effects to transmitter release at a specific synapse and, in one case, to a specific presynaptic ion channel. All the anesthetics silenced the output of the retina completely at concentrations similar to their effective dose for anesthesia in humans. Sedatives reduced retinal sensitivity but did not silence it. Finally, we used specific drugs that target hypothesized molecular mechanisms to probe how much they each contribute to anesthesia of the retina.

The second project which attempted to probe the principles of autism (Chap 3) was conceptually a direct extension of the retina as a testbed. Similar to the situation in seeking for what the mechanism of general anesthesia is, the field of autism research also lacks a good testbed but for systemically comparing gene mutation - circuit defect - behavior outcomes. Similarly, we utilized the retina as a platform to identify circuit defects in four different autism model mice and followed through the different mouse line’s behavior readouts using our lab’s maze navigation paradigm. We discovered that the different autism mouse lines varied in the retinal circuits and varied in their navigation preferences. Nevertheless, unlike the anesthetic project, there wasn’t a simple mechanism to explain why or how these differences are coupled together.

The last project, Electrode Pooling, (Chap 4) aimed to boost the yield of extracellular recording electrode arrays with a novel method we named electrode pooling. The per-implant yield of extracellular recording leaped significantly from the order of tens to the order of hundreds when engineers built multiple electrode arrays based on silicon technology to replace tetrode wires. Unfortunately, this yield-per-site is already maxed out with modern silicon technology. The constraint of the yield is mainly biological, as explained in the chapter, and thus could not be further advanced by improving the manufacturing processes of semiconductors. Our solution utilized an approach that multiplexed the array recording sites (not the bottleneck) onto the readout wires with accompanying filters (the actual bottleneck). Specifically, the method proposes intelligently choosing many recording sites that carry signals and connecting them to a single wire via manipulating the switches and later un-mixed with a spike-sorting algorithm. We demonstrated the first proof-of-principle study that shows that one could get more single-neuron recordings per implant site with electrode pooling, and made recommendations on the hardware design that could facilitate the advancement of probes that use pooling algorithms.

Thesis Files