It is well known that formation of new episodic memories depends on hippocampus, but in real-life settings (e.g., conversation), hippocampal amnesics can utilize information from several minutes earlier. What neural systems outside hippocampus might support this minutes-long retention? In this study, subjects viewed an audiovisual movie continuously for 25 min; another group viewed the movie in 2 parts separated by a 1-day delay. Understanding Part 2 depended on retrieving information from Part 1, and thus hippocampus was required in the day-delay condition. But is hippocampus equally recruited to access the same information from minutes earlier? We show that accessing memories from a few minutes prior elicited less interaction between hippocampus and default mode network (DMN) cortical regions than accessing day-old memories of identical events, suggesting that recent information was available with less reliance on hippocampal retrieval. Moreover, the 2 groups evinced
reliable but distinct DMN activity timecourses, reflecting differences in information carried in these regions when Part 1 was recent versus distant. The timecourses converged after 4 min, suggesting a time frame over which the continuous-viewing group may have relied less on hippocampal retrieval. We propose that cortical default mode regions can intrinsically retain real-life episodic information for several minutes.
Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
Abstract:
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.
This dataset contains all the data, model and MATLAB codes used to generate the figures and data reported in the article (DOI: 10.1002/2014JD022278). The data was generated during September 2013 and February 2014 using the Ocean-Land-Atmosphere Model also provided with this package. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
This three-year project, performed by Princeton University in partnership with the University of Minnesota and Brookhaven National Laboratory, examined geologic carbon sequestration in regard to CO2 leakage and potential subsurface liabilities. The research resulted in basin-scale analyses of CO2 and brine leakage in light of uncertainties in the characteristics of leakage processes, and generated frameworks to monetize the risks of leakage interference with competing subsurface resources. The geographic focus was the Michigan sedimentary basin, for which a 3D topographical model was constructed to represent the hydrostratigraphy. Specifically for Ottawa County, a statistical analysis of the hydraulic properties of underlying sedimentary formations was conducted. For plausible scenarios of injection into the Mt. Simon sandstone, leakage rates were estimated and fluxes into shallow drinking-water aquifers were found to be less than natural analogs of CO2 fluxes. We developed the Leakage Impact Valuation (LIV) model in which we identified stakeholders and estimated costs associated with leakage events. It was found that costs could be incurred even in the absence of legal action or other subsurface interference because there are substantial costs of finding and fixing the leak and from injection interruption. We developed a model framework called RISCS, which can be used to predict monetized risk of interference with subsurface resources by combining basin-scale leakage predictions with the LIV method. The project has also developed a cost calculator called the Economic and Policy Drivers Module (EPDM), which comprehensively calculates the costs of carbon sequestration and leakage, and can be used to examine major drivers for subsurface leakage liabilities in relation to specific injection scenarios and leakage events. Finally, we examined the competitiveness of CCS in the energy market. This analysis, though qualitative, shows that financial incentives, such as a carbon tax, are needed for coal combustion with CCS to gain market share. In another part of the project we studied the role of geochemical reactions in affecting the probability of CO2 leakage. A basin-scale simulation tool was modified to account for changes in leakage rates due to permeability alterations, based on simplified mathematical rules for the important geochemical reactions between acidified brines and caprock minerals. In studies of reactive flows in fractured caprocks, we examined the potential for permeability increases, and the extent to which existing reactive transport models would or would not be able to predict it. Using caprock specimens from the Eau Claire and Amherstburg, we found that substantial increases in permeability are possible for caprocks that have significant carbonate content, but minimal alteration is expected otherwise. We also found that while the permeability increase may be substantial, it is much less than what would be predicted from hydrodynamic models based on mechanical aperture alone because the roughness that is generated tends to inhibit flow.
Complete dataset of pore water chemical parameters measured at the Marsh Resource Meadowlands Mitigation Bank, a tidal marsh within the New Jersey Meadowlands, from March 2011 to April 2012. Analytes measured include dissolved methane, sulfate, dissolved organic carbon, temperature, salinity, and pH. Measurements were conducted using porewater dialysis samplers, and water was sampled from the surface to a depth of 60 cm.
