Characterization of the neural mechanisms supporting the implementation of cognitive control in human decision making

Humans are particularly adept at modifying their behavior in accordance with changing environmental demands. Through various mechanisms of cognitive control, individuals are able to tailor actions to fit complex short- and long-term goals. The research described in this thesis uses functional magnetic resonance imaging to characterize the neural correlates of cognitive control at two levels of complexity: response inhibition and self-control in intertemporal choice. First, we examined changes in neural response associated with increased experience and skill in response inhibition; successful response inhibition was associated with decreased neural response over time in the right ventrolateral prefrontal cortex, a region widely implicated in cognitive control, providing evidence for increased neural efficiency with learned automaticity. We also examined a more abstract form of cognitive control using intertemporal choice. In two experiments, we identified putative neural substrates for individual differences in temporal discounting, or the tendency to prefer immediate to delayed rewards. Using dynamic causal models, we characterized the neural circuit between ventromedial prefrontal cortex, an area involved in valuation, and dorsolateral prefrontal cortex, a region implicated in self-control in intertemporal and dietary choice, and found that connectivity from dorsolateral prefrontal cortex to ventromedial prefrontal cortex increases at the time of choice, particularly when delayed rewards are chosen. Moreover, estimates of the strength of connectivity predicted out-of-sample individual rates of temporal discounting, suggesting a neurocomputational mechanism for variation in the ability to delay gratification. Next, we interrogated the hypothesis that individual differences in temporal discounting are in part explained by the ability to imagine future reward outcomes. Using a novel paradigm, we imaged neural response during the imagining of primary rewards, and identified negative correlations between activity in regions associated the processing of both real and imagined rewards (lateral orbitofrontal cortex and ventromedial prefrontal cortex, respectively) and the individual temporal discounting parameters estimated in the previous experiment. These data suggest that individuals who are better able to represent reward outcomes neurally are less susceptible to temporal discounting. Together, these findings provide further insight into role of the prefrontal cortex in implementing cognitive control, and propose neurobiological substrates for individual variation.

Robot navigation in dense crowds : statistical models and experimental studies of human robot cooperation

This thesis explores the problem of mobile robot navigation in dense human crowds. We begin by considering a fundamental impediment to classical motion planning algorithms called the freezing robot problem: once the environment surpasses a certain level of complexity, the planner decides that all forward paths are unsafe, and the robot freezes in place (or performs unnecessary maneuvers) to avoid collisions. Since a feasible path typically exists, this behavior is suboptimal. Existing approaches have focused on reducing predictive uncertainty by employing higher fidelity individual dynamics models or heuristically limiting the individual predictive covariance to prevent overcautious navigation. We demonstrate that both the individual prediction and the individual predictive uncertainty have little to do with this undesirable navigation behavior. Additionally, we provide evidence that dynamic agents are able to navigate in dense crowds by engaging in joint collision avoidance, cooperatively making room to create feasible trajectories. We accordingly develop interacting Gaussian processes, a prediction density that captures cooperative collision avoidance, and a "multiple goal" extension that models the goal driven nature of human decision making. Navigation naturally emerges as a statistic of this distribution.

Most importantly, we empirically validate our models in the Chandler dining hall at Caltech during peak hours, and in the process, carry out the first extensive quantitative study of robot navigation in dense human crowds (collecting data on 488 runs). The multiple goal interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities nearing 1 person/m², while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as the multiple goal extension, and twice as often as the basic interacting Gaussian process approach. Furthermore, a reactive planner based on the widely used dynamic window approach proves insufficient for crowd densities above 0.55 people/m². We also show that our noncooperative planner or our reactive planner capture the salient characteristics of nearly any dynamic navigation algorithm. For inclusive validation purposes, we show that either our non-interacting planner or our reactive planner captures the salient characteristics of nearly any existing dynamic navigation algorithm. Based on these experimental results and theoretical observations, we conclude that a cooperation model is critical for safe and efficient robot navigation in dense human crowds.

Finally, we produce a large database of ground truth pedestrian crowd data. We make this ground truth database publicly available for further scientific study of crowd prediction models, learning from demonstration algorithms, and human robot interaction models in general.

Models of the Oxygen-Evolving Complex of Photosystem II

In the five chapters that follow, I delineate my efforts over the last five years to synthesize structurally and chemically relevant models of the Oxygen Evolving Complex (OEC) of Photosystem II. The OEC is nature’s only water oxidation catalyst, in that it forms the dioxygen in our atmosphere necessary for oxygenic life. Therefore understanding its structure and function is of deep fundamental interest and could provide design elements for artificial photosynthesis and manmade water oxidation catalysts. Synthetic endeavors towards OEC mimics have been an active area of research since the mid 1970s and have mutually evolved alongside biochemical and spectroscopic studies, affording ever-refined proposals for the structure of the OEC and the mechanism of water oxidation. This research has culminated in the most recent proposal: a low symmetry Mn₄CaO₅ cluster with a distorted Mn₃CaO₄ cubane bridged to a fourth, dangling Mn. To give context for how my graduate work fits into this rich history of OEC research, Chapter 1 provides a historical timeline of proposals for OEC structure, emphasizing the role that synthetic Mn and MnCa clusters have played, and ending with our Mn₃CaO₄ heterometallic cubane complexes.

In Chapter 2, the triarylbenzene ligand framework used throughout my work is introduced, and trinuclear clusters of Mn, Co, and Ni are discussed. The ligand scaffold consistently coordinates three metals in close proximity while leaving coordination sites open for further modification through ancillary ligand binding. The ligands coordinated could be varied, with a range of carboxylates and some less coordinating anions studied. These complexes’ structures, magnetic behavior, and redox properties are discussed.

Chapter 3 explores the redox chemistry of the trimanganese system more thoroughly in the presence of a fourth Mn equivalent, finding a range of oxidation states and oxide incorporation dependent on oxidant, solvent, and Mn salt. Oxidation states from Mn^II₄ to Mn^IIIMn^IV₃ were observed, with 1-4 O^2– ligands incorporated, modeling the photoactivation of the OEC. These complexes were studied by X-ray diffraction, EPR, XAS, magnetometry, and CV.

As Ca²⁺ is a necessary component of the OEC, Chapter 4 discusses synthetic strategies for making highly structurally accurate models of the OEC containing both Mn and Ca in the Mn₃CaO₄ cubane + dangling Mn geometry. Structural and electrochemical characterization of the first Mn₃CaO₄ heterometallic cubane complex— and comparison to an all-Mn Mn₄O₄ analog—suggests a role for Ca²⁺ in the OEC. Modification of the Mn₃CaO₄ system by ligand substitution affords low symmetry Mn₃CaO₄ complexes that are the most accurate models of the OEC to date.

Finally, in Chapter 5 the reactivity of the Mn₃CaO₄ cubane complexes toward O- atom transfer is discussed. The metal M strongly affects the reactivity. The mechanisms of O-atom transfer and water incorporation from and into Mn₄O₄ and Mn₄O₃ clusters, respectively, are studied through computation and ¹⁸O-labeling studies. The μ3-oxos of the Mn₄O₄ system prove fluxional, lending support for proposals of O^2– fluxionality within the OEC.