Medial Prefrontal Cortex Predicts Intertemporal Choice

People often make shortsighted decisions to receive small benefits in the present rather than large benefits in the future, that is, to favor their current selves over their future selves. In two studies using fMRI, we demonstrated that people make such decisions in part because they fail to engage in the same degree of self-referential processing when thinking about their future selves. When participants predicted how much they would enjoy an event in the future, they showed less activity in brain regions associated with introspective self-reference—such as the ventromedial pFC (vMPFC)—than when they predicted how much they would enjoy events in the present. Moreover, the magnitude of vMPFC reduction predicted the extent to which participants made shortsighted monetary decisions several weeks later. In light of recent findings that the vMPFC contributes to the ability to simulate future events from a first-person perspective, these data suggest that shortsighted decisions result in part from a failure to fully imagine the subjective experience of one's future self.Psycholog

Modulating the neural bases of persuasion: why/how, gain/loss, and users/non-users

Designing persuasive content is challenging, in part because people can be poor predictors of their actions. Medial prefrontal cortex (MPFC) activation during message exposure reliably predicts downstream behavior, but past work has been largely atheoretical. We replicated past results on this relationship and tested two additional framing effects known to alter message receptivity. First, we examined gain- vs. loss-framed reasons for a health behavior (sunscreen use). Consistent with predictions from prospect theory, we observed greater MPFC activity to gain- vs. loss-framed messages, and this activity was associated with behavior. This relationship was stronger for those who were not previously sunscreen users. Second, building on theories of action planning, we compared neural activity during messages regarding how vs. why to enact the behavior. We observed rostral inferior parietal lobule and posterior inferior frontal gyrus activity during action planning (“how” messages), and this activity was associated with behavior; this is in contrast to the relationship between MPFC activity during the “why” (i.e., gain and loss) messages and behavior. These results reinforce that persuasion occurs in part via self-value integration—seeing value and incorporating persuasive messages into one\u27s self-concept—and extend this work to demonstrate how message framing and action planning may influence this process

A Functional Near Infrared Spectroscopy (fNIRS) Replication of the Sunscreen Persuasion Paradigm

Activity in medial prefrontal cortex (mPFC) during persuasive messages predicts future message-consistent behavior change, but there are significant limitations to the types of persuasion processes that can be invoked inside an MRI scanner. For instance, real world persuasion often involves multiple people in conversation. Functional near infrared spectroscopy (fNIRS) allows us to move out of the scanner and into more ecologically valid contexts. As a first step, the current study used fNIRS to replicate an existing fMRI persuasion paradigm (i.e. the sunscreen paradigm) to determine if mPFC shows similar predictive value with this technology. Consistent with prior fMRI work, activity in mPFC was significantly associated with message-consistent behavior change, above and beyond self-reported intentions. There was also a difference in this association between previous users and non-users of sunscreen. Activity differences based on messages characteristics were not observed. Finally, activity in a region of right dorsolateral PFC (dlPFC), which has been observed with counterarguing against persuasive messages, correlated negatively with future behavior. The current results suggest it is reasonable to use fNIRS to examine persuasion paradigms that go beyond what is possible in the MRI scanner environment

Quantitative Methods for Comparing Different Polyline Stream Network Models

Abstract Two techniques for exploring relative horizontal accuracy of complex linear spatial features are described and sample source code (pseudo code) is presented for this purpose. The first technique, relative sinuosity, is presented as a measure of the complexity or detail of a polyline network in comparison to a reference network. We term the second technique longitudinal root mean squared error (LRMSE) and present it as a means for quantitatively assessing the horizontal variance between two polyline data sets representing digitize

Combining data from multiple sources using the CUAHSI Hydrologic Information System (Invited)

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) has developed a Hydrologic Information System (HIS) to provide better access to data by enabling the publication, cataloging, discovery, retrieval, and analysis of hydrologic data using web services. The CUAHSI HIS is an Internet based system comprised of hydrologic databases and servers connected through web services as well as software for data publication, discovery and access. The HIS metadata catalog lists close to 100 web services registered to provide data through this system, ranging from large federal agency data sets to experimental watersheds managed by University investigators. The system\u27s flexibility in storing and enabling public access to similarly formatted data and metadata has created a community data resource from governmental and academic data that might otherwise remain private or analyzed only in isolation. Comprehensive understanding of hydrology requires integration of this information from multiple sources. HydroDesktop is the client application developed as part of HIS to support data discovery and access through this system. HydroDesktop is founded on an open source GIS client and has a plug-in architecture that has enabled the integration of modeling and analysis capability with the functionality for data discovery and access. Model integration is possible through a plug-in built on the OpenMI standard and data visualization and analysis is supported by an R plug-in. This presentation will demonstrate HydroDesktop, showing how it provides an analysis environment within which data from multiple sources can be discovered, accessed and integrated

The CUAHSI Community Hydrologic Information System (Invited)

Hydrologic information is collected by many individuals and organizations in government and academia for many purposes, including general monitoring of the condition of the water environment and specific investigations of hydrologic processes. Comprehensive understanding of hydrology requires integration of this information from multiple sources. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) has developed a Hydrologic Information System (HIS) to provide better access to data by enabling the publication, cataloging, discovery and retrieval of hydrologic data using web services. This paper describes HIS capability developed to promote data sharing and interoperability in the Hydrologic Sciences with the purpose of enabling hydrologic analyses that integrate data from multiple sources. The CUAHSI HIS is an Internet based system comprised of hydrologic databases and servers connected through web services as well as software for data publication, discovery and access. The system that has been developed provides new opportunities for the water research community to approach the management, publication, and analysis of their data systematically. The system\u27s flexibility in storing and enabling public access to similarly formatted data and metadata has created a community data resource from public and academic data that might otherwise have been confined to the private files of agencies or individual investigators. Additionally, HIS provides an analysis environment within which data from multiple sources can be discovered, accessed and integrated. The CUAHSI HIS serves as a prototype for the infrastructure to support a network of large scale environmental observatories or research watersheds, and indeed, components of the CUAHSI HIS have now been adopted or modified for use within the Critical Zone Observatory (CZO) network. Software and further information may be obtained from http://his.cuahsi.org

Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth

Acute myeloid leukemia (AML) is a heterogeneous disease caused by different mutations. Previously, we showed that each mutational subtype develops its specific gene regulatory network (GRN) with transcription factors interacting within multiple gene modules, many of which are transcription factor genes themselves. Here, we hypothesize that highly connected nodes within such networks comprise crucial regulators of AML maintenance. We test this hypothesis using FLT3-ITD-mutated AML as a model and conduct an shRNA drop-out screen informed by this analysis. We show that AML-specific GRNs predict crucial regulatory modules required for AML growth. Furthermore, our work shows that all modules are highly connected and regulate each other. The careful multi-omic analysis of the role of one (RUNX1) module by shRNA and chemical inhibition shows that this transcription factor and its target genes stabilize the GRN of FLT3-ITD+ AML and that its removal leads to GRN collapse and cell death.</p

Acarbose, 17‐α‐estradiol, and nordihydroguaiaretic acid extend mouse lifespan preferentially in males

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106661/1/acel12170.pd

Toward Open and Reproducible Environmental Modeling by Integrating Online Data Repositories, Computational Environments, and Model Application Programming Interfaces

Cyberinfrastructure needs to be advanced to enable open and reproducible environmental modeling research. Recent efforts toward this goal have focused on advancing online repositories for data and model sharing, online computational environments along with containerization technology and notebooks for capturing reproducible computational studies, and Application Programming Interfaces (APIs) for simulation models to foster intuitive programmatic control. The objective of this research is to show how these efforts can be integrated to support reproducible environmental modeling. We present first the high-level concept and general approach for integrating these three components. We then present one possible implementation that integrates HydroShare (an online repository), CUAHSI JupyterHub and CyberGIS-Jupyter for Water (computational environments), and pySUMMA (a model API) to support open and reproducible hydrologic modeling. We apply the example implementation for a hydrologic modeling use case to demonstrate how the approach can advance reproducible environmental modeling through the seamless integration of cyberinfrastructure services