Reactions of small molecules facilitated by metal-acceptor interactions

The role of metal-acceptor interactions arising from M–BR3 and M–PR3 bonding is discussed with respect to reactions between first-row transition metals and N2, H2, and CO. Thermally robust, S = 1/2 (TPB)Co(H2) and (TPB)Co(N2) complexes (TPB = tris(2- (diisopropylphosphino)phenyl)borane) are described and the energetics of N2 and H2 binding are measured. The H2 and N2 ligands are bound more weakly in the (TPB)Co complexes than in related (SiP3)M(L) complexes (SiP3 = tris(2- (diisopropylphosphino)phenyl)silyl). Comparisons within and between these two ligand platforms allow for the factors that affect N2 (and H2) binding and activation to be delineated. The characterization and reactivity of (DPB)Fe complexes (DPB = bis(2- (diisopropylphosphino)phenyl)phenylborane) in the context of N2 functionalization and E–H bond addition (E = H, C, N, Si) are described. This platform allows for the one-pot transformation of free N2 to an Fe hydrazido(-) complex via an Fe aminoimide intermediate. The principles learned from the N2 chemistry using (DPB)Fe are applied to CO reduction on the same system. The preparation of (DPB)Fe(CO)2 is described as well as its reductive functionalization to generate an unprecedented Fe dicarbyne. The bonding in this highly covalent complex is discussed in detail. Initial studies of the reactivity of the Fe dicarbyne reveal that a CO-derived olefin is released upon hydrogenation. Alternative approaches to uncovering unusual reactivity using metal- acceptor interactions are described in Chapters 5 and 6, including initial studies on a new π-accepting tridentate diphosphinosulfinyl ligand and strategies for designing ligands that undergo site-selective metallation to generate heterobimetallic complexes.

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.