Analog VLSI-based, neuromorphic sensorimotor systems: modeling the primate oculomotor system

Using neuromorphic analog VLSI techniques for modeling large neural systems has several advantages over software techniques. By designing massively-parallel analog circuit arrays which are ubiquitous in neural systems, analog VLSI models are extremely fast, particularly when local interactions are important in the computation. While analog VLSI circuits are not as flexible as software methods, the constraints posed by this approach are often very similar to the constraints faced by biological systems. As a result, these constraints can offer many insights into the solutions found by evolution. This dissertation describes a hardware modeling effort to mimic the primate oculomotor system which requires both fast sensory processing and fast motor control. A one-dimensional hardware model of the primate eye has been built which simulates the physical dynamics of the biological system. It is driven by analog VLSI circuits mimicking brainstem and cortical circuits that control eye movements. In this framework, a visually-triggered saccadic system is demonstrated which generates averaging saccades. In addition, an auditory localization system, based on the neural circuits of the barn owl, is used to trigger saccades to acoustic targets in parallel with visual targets. Two different types of learning are also demonstrated on the saccadic system using floating-gate technology allowing the non-volatile storage of analog parameters directly on the chip. Finally, a model of visual attention is used to select and track moving targets against textured backgrounds, driving both saccadic and smooth pursuit eye movements to maintain the image of the target in the center of the field of view. This system represents one of the few efforts in this field to integrate both neuromorphic sensory processing and motor control in a closed-loop fashion.

Expanding the repertoire of DNA-mediated signaling in DNA repair

DNA damage is extremely detrimental to the cell and must be repaired to protect the genome. DNA is capable of conducting charge through the overlapping π-orbitals of stacked bases; this phenomenon is extremely sensitive to the integrity of the π-stack, as perturbations attenuate DNA charge transport (CT). Based on the E. coli base excision repair (BER) proteins EndoIII and MutY, it has recently been proposed that redox-active proteins containing metal clusters can utilize DNA CT to signal one another to locate sites of DNA damage.

To expand our repertoire of proteins that utilize DNA-mediated signaling, we measured the DNA-bound redox potential of the nucleotide excision repair (NER) helicase XPD from Sulfolobus acidocaldarius. A midpoint potential of 82 mV versus NHE was observed, resembling that of the previously reported BER proteins. The redox signal increases in intensity with ATP hydrolysis in only the WT protein and mutants that maintain ATPase activity and not for ATPase-deficient mutants. The signal increase correlates directly with ATP activity, suggesting that DNA-mediated signaling may play a general role in protein signaling. Several mutations in human XPD that lead to XP-related diseases have been identified; using SaXPD, we explored how these mutations, which are conserved in the thermophile, affect protein electrochemistry.

To further understand the electrochemical signaling of XPD, we studied the yeast S. cerevisiae Rad3 protein. ScRad3 mutants were incubated on a DNA-modified electrode and exhibited a similar redox potential to SaXPD. We developed a haploid strain of S. cerevisiae that allowed for easy manipulation of Rad3. In a survival assay, the ATPase- and helicase-deficient mutants show little survival, while the two disease-related mutants exhibit survival similar to WT. When both a WT and G47R (ATPase/helicase deficient) strain were challenged with different DNA damaging agents, both exhibited comparable survival in the presence of hydroxyurea, while with methyl methanesulfonate and camptothecin, the G47R strain exhibits a significant change in growth, suggesting that Rad3 is involved in repairing damage beyond traditional NER substrates. Together, these data expand our understanding of redox-active proteins at the interface of DNA repair.

Demographic studies of extrasolar planets

Uncovering the demographics of extrasolar planets is crucial to understanding the processes of their formation and evolution. In this thesis, we present four studies that contribute to this end, three of which relate to NASA's Kepler mission, which has revolutionized the field of exoplanets in the last few years.

In the pre-Kepler study, we investigate a sample of exoplanet spin-orbit measurements---measurements of the inclination of a planet's orbit relative to the spin axis of its host star---to determine whether a dominant planet migration channel can be identified, and at what confidence. Applying methods of Bayesian model comparison to distinguish between the predictions of several different migration models, we find that the data strongly favor a two-mode migration scenario combining planet-planet scattering and disk migration over a single-mode Kozai migration scenario. While we test only the predictions of particular Kozai and scattering migration models in this work, these methods may be used to test the predictions of any other spin-orbit misaligning mechanism.

We then present two studies addressing astrophysical false positives in Kepler data. The Kepler mission has identified thousands of transiting planet candidates, and only relatively few have yet been dynamically confirmed as bona fide planets, with only a handful more even conceivably amenable to future dynamical confirmation. As a result, the ability to draw detailed conclusions about the diversity of exoplanet systems from Kepler detections relies critically on understanding the probability that any individual candidate might be a false positive. We show that a typical a priori false positive probability for a well-vetted Kepler candidate is only about 5-10%, enabling confidence in demographic studies that treat candidates as true planets. We also present a detailed procedure that can be used to securely and efficiently validate any individual transit candidate using detailed information of the signal's shape as well as follow-up observations, if available.

Finally, we calculate an empirical, non-parametric estimate of the shape of the radius distribution of small planets with periods less than 90 days orbiting cool (less than 4000K) dwarf stars in the Kepler catalog. This effort reveals several notable features of the distribution, in particular a maximum in the radius function around 1-1.25 Earth radii and a steep drop-off in the distribution larger than 2 Earth radii. Even more importantly, the methods presented in this work can be applied to a broader subsample of Kepler targets to understand how the radius function of planets changes across different types of host stars.

Neural network design for switching network control

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

Binding Site Structure and Stoichiometry in Serotonin Type 3 Receptors

This dissertation primarily describes studies of serotonin type 3 (5-HT₃) receptors of the Cys-loop super-family of ligand gated ion channels. The first chapter provides a general introduction to these important proteins and the methods used to interrogate their structure and function. The second chapter details the delineation of a structural unit of the ligand binding site of homomeric 5-HT₃A receptors on which the ligands serotonin (5-HT) and m-chlorophenyl biguanide (mCPBG) are reliant for effective receptor activation. Unnatural amino acid mutagenesis results show that the details of each ligand’s interaction with this organizing feature of the binding site differ, providing insights into general principles of receptor activation.

The third chapter describes a study in which florescent protein fusions of the A and B subunits of the heteromeric 5-HT₃AB receptor are employed to determine the subunit stoichiometry and order within functional receptors. Strong evidence is found for an A₃B₂ stoichiometry with A-A-B-A-B order. The fourth chapter investigates the potential for ligand binding across heteromeric binding sites in the 5-HT₃AB receptor. Unlike serotonin, mCPBG is found to bind the receptor at heteromeric binding sites. Further mCPBG is capable of allosterically modulating the response of serotonin on the 5-HT₃AB receptor from these heteromeric sites.

Finally, the fifth chapter describes progress towards the application of unnatural amino acid mutagenesis to an important new class of proteins, transcription factors. Experiments optimizing novel methods for the detection of function are described, using RARα of the nuclear receptor family of transcription factors.

Computationally Guided Monomerization of Red Fluorescent Proteins of the Class Anthozoa

Red fluorescent proteins (RFPs) have attracted significant engineering focus because of the promise of near infrared fluorescent proteins, whose light penetrates biological tissue, and which would allow imaging inside of vertebrate animals. The RFP landscape, which numbers ~200 members, is mostly populated by engineered variants of four native RFPs, leaving the vast majority of native RFP biodiversity untouched. This is largely due to the fact that native RFPs are obligate tetramers, limiting their usefulness as fusion proteins. Monomerization has imposed critical costs on these evolved tetramers, however, as it has invariably led to loss of brightness, and often to many other adverse effects on the fluorescent properties of the derived monomeric variants. Here we have attempted to understand why monomerization has taken such a large toll on Anthozoa class RFPs, and to outline a clear strategy for their monomerization. We begin with a structural study of the far-red fluorescence of AQ143, one of the furthest red emitting RFPs. We then try to separate the problem of stable and bright fluorescence from the design of a soluble monomeric β-barrel surface by engineering a hybrid protein (DsRmCh) with an oligomeric parent that had been previously monomerized, DsRed, and a pre-stabilized monomeric core from mCherry. This allows us to use computational design to successfully design a stable, soluble, fluorescent monomer. Next we took HcRed, which is a previously unmonomerized RFP that has far-red fluorescence (λemission = 633 nm) and attempted to monomerize it making use of lessons learned from DsRmCh. We engineered two monomeric proteins by pre-stabilizing HcRed’s core, then monomerizing in stages, making use of computational design and directed evolution techniques such as error-prone mutagenesis and DNA shuffling. We call these proteins mGinger0.1 (λem = 637 nm / Φ = 0.02) and mGinger0.2 (λem = 631 nm Φ = 0.04). They are the furthest red first generation monomeric RFPs ever developed, are significantly thermostabilized, and add diversity to a small field of far-red monomeric FPs. We anticipate that the techniques we describe will be facilitate future RFP monomerization, and that further core optimization of the mGingers may allow significant improvements in brightness.

Optomechanical Inertial Sensors and Feedback Cooling

The optomechanical interaction is an extremely powerful tool with which to measure mechanical motion. The displacement resolution of chip-scale optomechanical systems has been measured on the order of 1⁄10th of a proton radius. So strong is this optomechanical interaction that it has recently been used to remove almost all thermal noise from a mechanical resonator and observe its quantum ground-state of motion starting from cryogenic temperatures.

In this work, chapter 1 describes the basic physics of the canonical optomechanical system, optical measurement techniques, and how the optomechanical interaction affects the coupled mechanical resonator. In chapter 2, we describe our techniques for realizing this canonical optomechanical system in a chip-scale form factor.

In chapter 3, we describe an experiment where we used radiation pressure feedback to cool a mesoscopic mechanical resonator near its quantum ground-state from room-temperature. We cooled the resonator from a room temperature phonon occupation of <n> = 6.5 million to an occupation of <n> = 66, which means the resonator is in its ground state approximately 2% of the time, while being coupled to a room-temperature thermal environment. At the time of this work, this is the closest a mesoscopic mechanical resonator has been to its ground-state of motion at room temperature, and this work begins to open the door to room-temperature quantum control of mechanical objects.

Chapter 4 begins with the realization that the displacement resolutions achieved by optomechanical systems can surpass those of conventional MEMS sensors by an order of magnitude or more. This provides the motivation to develop and calibrate an optomechanical accelerometer with a resolution of approximately 10 micro-g/rt-Hz over a bandwidth of approximately 30 kHz. In chapter 5, we improve upon the performance and practicality of this sensor by greatly increasing the test mass size, investigating and reducing low-frequency noise, and incorporating more robust optical coupling techniques and capacitive wavelength tuning. Finally, in chapter 6 we present our progress towards developing another optomechanical inertial sensor - a gyroscope.

Rydberg states of diatomic and polyatomic molecules using model potentials

A simple model potential is used to calculate Rydberg series for the molecules: nitrogen, oxygen, nitric oxide, carbon monoxide, carbon dioxide, nitrogen dioxide, nitrous oxide, acetylene, formaldehyde, formic acid, diazomethane, ketene, ethylene, allene, acetaldehyde, propyne, acrolein, dimethyl ether, 1, 3-butadiene, 2-butene, and benzene. The model potential for a molecule is taken as the sum of atomic potentials, which are calibrated to atomic data and contain no further parameters. Our results agree with experimentally measured values to within 5-10% in all cases. The results of these calculations are applied to many unresolved problems connected with the above molecules. Some of the more notable of these problems are the reassignment of states in carbon monoxide, the first ionization potential of nitrogen dioxide, the interpretation of the V state in ethylene, and the mystery bands in substituted ethylenes, the identification of the R and R’ series in benzene and the determination of the orbital scheme in benzene from electron impact data.