Neural routing circuits for forming invariant representations of visual objects

This thesis presents a biologically plausible model of an attentional mechanism for forming position- and scale-invariant representations of objects in the visual world. The model relies on a set of control neurons to dynamically modify the synaptic strengths of intra-cortical connections so that information from a windowed region of primary visual cortex (Vl) is selectively routed to higher cortical areas. Local spatial relationships (i.e., topography) within the attentional window are preserved as information is routed through the cortex, thus enabling attended objects to be represented in higher cortical areas within an object-centered reference frame that is position and scale invariant. The representation in V1 is modeled as a multiscale stack of sample nodes with progressively lower resolution at higher eccentricities. Large changes in the size of the attentional window are accomplished by switching between different levels of the multiscale stack, while positional shifts and small changes in scale are accomplished by translating and rescaling the window within a single level of the stack. The control signals for setting the position and size of the attentional window are hypothesized to originate from neurons in the pulvinar and in the deep layers of visual cortex. The dynamics of these control neurons are governed by simple differential equations that can be realized by neurobiologically plausible circuits. In pre-attentive mode, the control neurons receive their input from a low-level "saliency map" representing potentially interesting regions of a scene. During the pattern recognition phase, control neurons are driven by the interaction between top-down (memory) and bottom-up (retinal input) sources. The model respects key neurophysiological, neuroanatomical, and psychophysical data relating to attention, and it makes a variety of experimentally testable predictions.

State-dependent modulation of neuronal circuits in C. elegans sleep

C. elegans is a compact system of 302 neurons with identifiable and mapped connections that makes it ideal for systems analysis. This work is a demonstration of what I have been able to learn about the nature of state-specific modulation and reversibility during a state called lethargus, a sleep-like state in the worm. I begin with description about the nervous system of the worm, the nature of sleep in the worm, the questions about behavior and its apparent circuit properties, the tools available and used to manipulate the nervous system, and what I have been able to learn from these studies. I end with clues that the physiology helps to teach us about the dynamics of state specific modulation, what makes sleep so different from other states, and how we can use these measurements to understand which modulators, neurotransmitters, and channels can be used to create different dynamics in a simple model system.

Coupled plasmonic systems and devices : applications in visible metamaterials, nanophotonic circuits, and CMOS imaging

With the size of transistors approaching the sub-nanometer scale and Si-based photonics pinned at the micrometer scale due to the diffraction limit of light, we are unable to easily integrate the high transfer speeds of this comparably bulky technology with the increasingly smaller architecture of state-of-the-art processors. However, we find that we can bridge the gap between these two technologies by directly coupling electrons to photons through the use of dispersive metals in optics. Doing so allows us to access the surface electromagnetic wave excitations that arise at a metal/dielectric interface, a feature which both confines and enhances light in subwavelength dimensions - two promising characteristics for the development of integrated chip technology. This platform is known as plasmonics, and it allows us to design a broad range of complex metal/dielectric systems, all having different nanophotonic responses, but all originating from our ability to engineer the system surface plasmon resonances and interactions. In this thesis, we demonstrate how plasmonics can be used to develop coupled metal-dielectric systems to function as tunable plasmonic hole array color filters for CMOS image sensing, visible metamaterials composed of coupled negative-index plasmonic coaxial waveguides, and programmable plasmonic waveguide network systems to serve as color routers and logic devices at telecommunication wavelengths.

Dissecting neural circuits for vision in nonhuman primates using fMRI-guided electrophysiology and optogenetics

The visual system is a remarkable platform that evolved to solve difficult computational problems such as detection, recognition, and classification of objects. Of great interest is the face-processing network, a sub-system buried deep in the temporal lobe, dedicated for analyzing specific type of objects (faces). In this thesis, I focus on the problem of face detection by the face-processing network. Insights obtained from years of developing computer-vision algorithms to solve this task have suggested that it may be efficiently and effectively solved by detection and integration of local contrast features. Does the brain use a similar strategy? To answer this question, I embark on a journey that takes me through the development and optimization of dedicated tools for targeting and perturbing deep brain structures. Data collected using MR-guided electrophysiology in early face-processing regions was found to have strong selectivity for contrast features, similar to ones used by artificial systems. While individual cells were tuned for only a small subset of features, the population as a whole encoded the full spectrum of features that are predictive to the presence of a face in an image. Together with additional evidence, my results suggest a possible computational mechanism for face detection in early face processing regions. To move from correlation to causation, I focus on adopting an emergent technology for perturbing brain activity using light: optogenetics. While this technique has the potential to overcome problems associated with the de-facto way of brain stimulation (electrical microstimulation), many open questions remain about its applicability and effectiveness for perturbing the non-human primate (NHP) brain. In a set of experiments, I use viral vectors to deliver genetically encoded optogenetic constructs to the frontal eye field and faceselective regions in NHP and examine their effects side-by-side with electrical microstimulation to assess their effectiveness in perturbing neural activity as well as behavior. Results suggest that cells are robustly and strongly modulated upon light delivery and that such perturbation can modulate and even initiate motor behavior, thus, paving the way for future explorations that may apply these tools to study connectivity and information flow in the face processing network.

Nanofabrication for On-Chip Optical Levitation, Atom-Trapping, and Superconducting Quantum Circuits

Researchers have spent decades refining and improving their methods for fabricating smaller, finer-tuned, higher-quality nanoscale optical elements with the goal of making more sensitive and accurate measurements of the world around them using optics. Quantum optics has been a well-established tool of choice in making these increasingly sensitive measurements which have repeatedly pushed the limits on the accuracy of measurement set forth by quantum mechanics. A recent development in quantum optics has been a creative integration of robust, high-quality, and well-established macroscopic experimental systems with highly-engineerable on-chip nanoscale oscillators fabricated in cleanrooms. However, merging large systems with nanoscale oscillators often require them to have extremely high aspect-ratios, which make them extremely delicate and difficult to fabricate with an "experimentally reasonable" repeatability, yield and high quality. In this work we give an overview of our research, which focused on microscopic oscillators which are coupled with macroscopic optical cavities towards the goal of cooling them to their motional ground state in room temperature environments. The quality factor of a mechanical resonator is an important figure of merit for various sensing applications and observing quantum behavior. We demonstrated a technique for pushing the quality factor of a micromechanical resonator beyond conventional material and fabrication limits by using an optical field to stiffen and trap a particular motional mode of a nanoscale oscillator. Optical forces increase the oscillation frequency by storing most of the mechanical energy in a nearly loss-less optical potential, thereby strongly diluting the effects of material dissipation. By placing a 130 nm thick SiO₂ pendulum in an optical standing wave, we achieve an increase in the pendulum center-of-mass frequency from 6.2 to 145 kHz. The corresponding quality factor increases 50-fold from its intrinsic value to a final value of Q_m = 5.8(1.1) x 10⁵, representing more than an order of magnitude improvement over the conventional limits of SiO₂ for a pendulum geometry. Our technique may enable new opportunities for mechanical sensing and facilitate observations of quantum behavior in this class of mechanical systems. We then give a detailed overview of the techniques used to produce high-aspect-ratio nanostructures with applications in a wide range of quantum optics experiments. The ability to fabricate such nanodevices with high precision opens the door to a vast array of experiments which integrate macroscopic optical setups with lithographically engineered nanodevices. Coupled with atom-trapping experiments in the Kimble Lab, we use these techniques to realize a new waveguide chip designed to address ultra-cold atoms along lithographically patterned nanobeams which have large atom-photon coupling and near 4π Steradian optical access for cooling and trapping atoms. We describe a fully integrated and scalable design where cold atoms are spatially overlapped with the nanostring cavities in order to observe a resonant optical depth of d₀ ≈ 0.15. The nanodevice illuminates new possibilities for integrating atoms into photonic circuits and engineering quantum states of atoms and light on a microscopic scale. We then describe our work with superconducting microwave resonators coupled to a phononic cavity towards the goal of building an integrated device for quantum-limited microwave-to-optical wavelength conversion. We give an overview of our characterizations of several types of substrates for fabricating a low-loss high-frequency electromechanical system. We describe our electromechanical system fabricated on a Si₃N₄ membrane which consists of a 12 GHz superconducting LC resonator coupled capacitively to the high frequency localized modes of a phononic nanobeam. Using our suspended membrane geometry we isolate our system from substrates with significant loss tangents, drastically reducing the parasitic capacitance of our superconducting circuit to ≈ 2.5$ fF. This opens up a number of possibilities in making a new class of low-loss high-frequency electromechanics with relatively large electromechanical coupling. We present our substrate studies, fabrication methods, and device characterization.

Expanding the Toolkit for Synthetic Biology: Frameworks for Native-like Non-natural Gene Circuits

Synthetic biology combines biological parts from different sources in order to engineer non-native, functional systems. While there is a lot of potential for synthetic biology to revolutionize processes, such as the production of pharmaceuticals, engineering synthetic systems has been challenging. It is oftentimes necessary to explore a large design space to balance the levels of interacting components in the circuit. There are also times where it is desirable to incorporate enzymes that have non-biological functions into a synthetic circuit. Tuning the levels of different components, however, is often restricted to a fixed operating point, and this makes synthetic systems sensitive to changes in the environment. Natural systems are able to respond dynamically to a changing environment by obtaining information relevant to the function of the circuit. This work addresses these problems by establishing frameworks and mechanisms that allow synthetic circuits to communicate with the environment, maintain fixed ratios between components, and potentially add new parts that are outside the realm of current biological function. These frameworks provide a way for synthetic circuits to behave more like natural circuits by enabling a dynamic response, and provide a systematic and rational way to search design space to an experimentally tractable size where likely solutions exist. We hope that the contributions described below will aid in allowing synthetic biology to realize its potential.

An in vitro biomolecular breadboard for prototyping synthetic biological circuits

Biomolecular circuit engineering is critical for implementing complex functions in vivo, and is a baseline method in the synthetic biology space. However, current methods for conducting biomolecular circuit engineering are time-consuming and tedious. A complete design-build-test cycle typically takes weeks' to months' time due to the lack of an intermediary between design ex vivo and testing in vivo. In this work, we explore the development and application of a "biomolecular breadboard" composed of an in-vitro transcription-translation (TX-TL) lysate to rapidly speed up the engineering design-build-test cycle. We first developed protocols for creating and using lysates for conducting biological circuit design. By doing so we simplified the existing technology to an affordable ($0.03/uL) and easy to use three-tube reagent system. We then developed tools to accelerate circuit design by allowing for linear DNA use in lieu of plasmid DNA, and by utilizing principles of modular assembly. This allowed the design-build-test cycle to be reduced to under a business day. We then characterized protein degradation dynamics in the breadboard to aid to implementing complex circuits. Finally, we demonstrated that the breadboard could be applied to engineer complex synthetic circuits in vitro and in vivo. Specifically, we utilized our understanding of linear DNA prototyping, modular assembly, and protein degradation dynamics to characterize the repressilator oscillator and to prototype novel three- and five-node negative feedback oscillators both in vitro and in vivo. We therefore believe the biomolecular breadboard has wide application for acting as an intermediary for biological circuit engineering.

I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca$^{2+}$ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider \textit{in silico} specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize \textit{in silico} methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.

Biochemical studies of postsynaptic density signaling proteins with a focus on synaptic GTPase activating protein and PDZ domains

Memory storage in the brain involves adjustment of the strength of existing synapses and formation of new neural networks. A key process underlying memory formation is synaptic plasticity, the ability of excitatory synapses to strengthen or weaken their connections in response to patterns of activity between their connected neurons. Synaptic plasticity is governed by the precise pattern of Ca²⁺ influx through postsynaptic N-methyl-D-aspartate-type glutamate receptors (NMDARs), which can lead to the activation of the small GTPases Ras and Rap. Differential activation of Ras and Rap acts to modulate synaptic strength by promoting the insertion or removal of 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl)propanoic acid receptors (AMPARs) from the synapse. Synaptic GTPase activating protein (synGAP) regulates AMPAR levels by catalyzing the inactivation of GTP-bound (active) Ras or Rap. synGAP is positioned in close proximity to the cytoplasmic tail regions of the NMDAR through its association with the PDZ domains of PSD-95. SynGAP’s activity is regulated by the prominent postsynaptic protein kinase, Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) and cyclin-dependent kinase 5 (CDK5), a known binding partner of CaMKII. Modulation of synGAP’s activity by phosphorylation may alter the ratio of active Ras to Rap in spines, thus pushing the spine towards the insertion or removal of AMPARs, subsequently strengthening or weakening the synapse. To date, all biochemical studies of the regulation of synGAP activity by protein kinases have utilized impure preparations of membrane bound synGAP. Here we have clarified the effects of phosphorylation of synGAP on its Ras and Rap GAP activities by preparing and utilizing purified, soluble recombinant synGAP, Ras, Rap, CaMKII, CDK5, PLK2, and CaM. Using mass spectrometry, we have confirmed the presence of previously identified CaMKII and CDK5 sites in synGAP, and have identified novel sites of phosphorylation by CaMKII, CDK5, and PLK2. We have shown that the net effect of phosphorylation of synGAP by CaMKII, CDK5, and PLK2 is an increase in its GAP activity toward HRas and Rap1. In contrast, there is no effect on its GAP activity toward Rap2. Additionally, by assaying the GAP activity of phosphomimetic synGAP mutants, we have been able to hypothesize the effects of CDK5 phosphorylation at specific sites in synGAP. In the course of this work, we also found, unexpectedly, that synGAP is itself a Ca²⁺/CaM binding protein. While Ca²⁺/CaM binding does not directly affect synGAP activity, it causes a conformational change in synGAP that increases the rate of its phosphorylation and exposes additional phosphorylation sites that are inaccessible in the absence of Ca²⁺/CaM.

The postsynaptic density (PSD) is an electron-dense region in excitatory postsynaptic neurons that contains a high concentration of glutamate receptors, cytoskeletal proteins, and associated signaling enzymes. Within the PSD, three major classes of scaffolding molecules function to organize signaling enzymes and glutamate receptors. PDZ domains present in the Shank and PSD-95 scaffolds families serve to physically link AMPARs and NMDARs to signaling molecules in the PSD. Because of the specificity and high affinity of PDZ domains for their ligands, I reasoned that these interacting pairs could provide the core components of an affinity chromatography system, including affinity resins, affinity tags, and elution agents. I show that affinity columns containing the PDZ domains of PSD-95 can be used to purify active PDZ domain-binding proteins to very high purity in a single step. Five heterologously expressed neuronal proteins containing endogenous PDZ domain ligands (NMDAR GluN2B subunit Tail, synGAP, neuronal nitric oxide synthase PDZ domain, cysteine rich interactor of PDZ three and cypin) were purified using PDZ domain resin, with synthetic peptides having the sequences of cognate PDZ domain ligands used as elution agents. I also show that conjugation of PDZ domain-related affinity tags to Proteins Of Interest (POIs) that do not contain endogenous PDZ domains or ligands does not alter protein activity and enables purification of the POIs on PDZ domain-related affinity resins.

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.