Funds from this grant support a pair of projects aimed at understanding the role that attention and inattention play in consumer behavior and decision-making. In the first, economist Nick Netzer of the University of Zurich will develop the beginnings of a theoretical framework that treats attention as a relatively-fixed resource that decision-makers allocate as they move through the world and make decisions. Netzer will work to incorporate insights from psychology and neuroscience into standard economic decision-making models, allowing a more nuanced, psychologically realistic account of how humans make decisions, one that has the potential to more gracefully explain common behavioral phenomena, like why decisions made in a rush or while multi-tasking tend to be non-optimal. In the second phase of the project, Netzer will partner with behavioral neuroscientist Phil Tobler to test his framework. Tobler has designed a series of experiments that aim to quantify how increases in subjects’ attentional resources, occasioned by the administration of low-dose attention-enhancing drugs, affect their performance on decision-making tasks. The experiments will be able to demonstrate whether increased attentional resources improve decision-making in the ways predicted by Netzer’s models.

The interior of a cell is a chaotic, turbulent place dominated by random, thermally driven collisions.  Inside this tempest, the internal structures of a cell must do their delicate work.  The creation of a single strand of mRNA, essential for creating the proteins that make cells run, requires the meticulous assembly of long sequences of adenine, cytosine, guanine, and uracil.  Yet despite the ever present internal squall and the exacting nature of the work, these cellular processes have surprisingly low error rates.  The chance of a transcription error inside e. coli bacteria, for example, has been observed to be about 1 in 10,000.      Explaining how such high accuracy is achieved under such adverse conditions is an enduring challenge for biology.  This grant funds a series of experiments designed by Rockefeller University’s Gregory Alushin, Amy Shyer, and Shixin Liu that explore one promising explanation: mechanical force. Alushin, Shyer, and Liu will use grant funds to field two research projects that use emerging technologies, such as high-resolution imaging and tools that apply and measure nanoscale forces, to explore the role played by mechanical force in two areas of biology. In the first, Alushin, Shyer, and Liu will work at the nanoscale to test the hypothesis that force influences the fidelity of the molecular machine that executes the primary step in gene expression, the copying of genetic information from DNA to RNA (transcription). This multiprotein machine is called RNA polymerase (RNAP) and the project team hypothesizes that force can cause RNAP to adopt structures that favor error correction during transcription. To test this, the team will exert forces on RNAP and measure the resulting error rates and structures. In the second project, the team will examine the role of force in morphogenesis, the development of heterogeneity in an initially uniform collection of cells (e.g., tissue) that underlies organ development. The team will use force manipulation and imaging to directly probe how force propagates across tissue-scale lengths while also mapping how force drives the molecular-scale rearrangements that launch gene expression. Here the principal investigators hypothesize that force propagates at a speed that exceeds what’s possible in models of chemical-signal propagation.

Established in 2014, the Institute for Research on Innovation and Science (IRIS) at the University of Michigan systematically collects, cleans, compiles, and curates administrative data from universities about their grant spending, including financial and HR records. IRIS then links these datasets with patenting, publishing, and other important information sources, notably confidential Census files. Using state-of-the-art privacy protection techniques, IRIS makes aggregate statistics available to the university community, while also making detailed microdata available to qualified researchers for further exploration. For example, IRIS researchers have traced how a particular grant supported a particular lab that hired a particular student who went on to publish papers, file patents, and start a company in the same particular field. Assembling this kind of information in bulk for statistical study has been the dream of generations of scholars concerned with innovation and of policymakers and administrators interested in evaluating the return on investments in research. Funds from this grant provide two years of operational support for IRIS, with a particular emphasis on projects to collect and analyze data that will advance our understanding of the effects of the COVID-19 pandemic on research activities within universities. Additional funds will support outreach activities aimed at helping IRIS expand its roster of partner universities and grow the number of affiliated scholars working to analyze the data collected.