Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
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.
Petsev, Nikolai D.; Stillinger, Frank H.; Debenedetti, Pablo G.
Source code for our energy-conserving reformulation of the 4-site molecular model for chiral phenomena originally introduced by Latinwo et al. [F. Latinwo, F. H. Stillinger, and P. G. Debenedetti, Molecular Model for Chirality Phenomena, J. Chem. Phys. 145, 154503 (2016)]. The reformulation includes an additional 8-body force that arises from an explicit configuration-dependent term in the potential energy function, resulting in a coarse-grained energy-conserving force field for molecular dynamics simulations of chirality phenomena. In this model, the coarse-grained interaction energy between two tetramers depends on their respective chiralities, and is controlled by a parameter λ, where favors local configurations involving tetramers of opposite chirality, and gives energetic preference to configurations involving tetramers of the same chirality. The source code is for use with the LAMMPS simulation package.
Physical and biogeochemical variables from the NOAA-GFDL Earth System Model 2M experiments (pre-processed), previously published observation-based datasets, and code to reproduce figures from these datasets, used for the study 'Hydrological cycle amplification reshapes warming-driven oxygen loss in Atlantic Ocean'.
Microscopy images are part of a paper entitled "Structured foraging of soil predators unveils functional responses to bacterial defenses" by Fernando Rossine, Gabriel Vercelli, Corina Tarnita, and Thomas Gregor. For detailed acquisition methods see the paper. Experiments were performed between 2019 and 2020 at Princeton University. Two types of images are provided, macroscopic and microscopic widefiled Images. Macroscopic images all show Petri dishes covered in fluorescent bacteria being consumed by amoebae. Images are shown for D. discoideum, P. violaceum, and A. castellanii. Images depicting drug treatments (Nystatin and Fluorouracil) were obtained using D. discoideum. Images used for the creation of a profile were all taken within 30 minutes of each other. Within each directory numbered images are independent replicates. The raw video directory contains time series for dishes under drug treatments. Each numbered folder is a sequence of photos (taken 30 minutes apart of each other) of a single dish. Microscopic images all show amoebae consuming bacteria on a petri dish. The 45 minute videos show either edge cells (located at the edge of amoebae colonies), or inner cells (located 2.5 millimeters towards the center of the colony, from the edge). Videos are confocal stacks, with bacteria showing in green and amoebae appearing as black holes within the bacterial lawn. As was for the macroscopic images, images are shown for D. discoideum, P. violaceum, and A. castellanii. Images depicting drug treatments (Nystatin and Fluorouracil) were obtained using D. discoideum.
Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
More than 20% Amazon rainforest has been cleared in the past three decades triggering important hydroclimatic changes. Small-scale (~few kilometers) deforestation in the 1980s has caused thermally-triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared to the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing a negligible role of large-scale climate variability. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry season hydroclimate. Our study illustrates the strong scale-sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally- to a dynamically-driven hydroclimatic regime.
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.
Petsev, Nikolai D.; Nikoubashman, Arash; Latinwo, Folarin
Source code for our genetic algorithm optimization investigation of conglomerate and racemic chiral crystals. In this work, we address challenges in determining the stable structures formed by chiral molecules by applying the framework of genetic algorithms to predict the ground state crystal lattices formed by a chiral tetramer model. Using this code, we explore the relative stability and structures of the model’s conglomerate and racemic crystals, and extract a structural phase diagram for the stable Bravais crystal types in the zero-temperature limit.
The materials include codes and example input / output files for Monte Carlo simulations of lattice chains in the grand canonical ensemble, for determining phase behavior, critical points, and formation of aggregates.
Bourrianne, Philippe; Chidzik, Stanley; Cohen, Daniel; Elmer, Peter; Hallowell, Thomas; Kilbaugh, Todd J.; Lange, David; Leifer, Andrew M.; Marlow, Daniel R.; Meyers, Peter D.; Normand, Edna; Nunes, Janine; Oh, Myungchul; Page, Lyman; Periera, Talmo; Pivarski, Jim; Schreiner, Henry; Stone, Howard A.; Tank, David W.; Thiberge, Stephan; Tully, Christopher
The detailed information on the design and construction of the Princeton Open Ventilation Monitor device and software are contained in this data repository. This information consists of the electrical design files, mechanical design files, bill of materials, human subject recording and analysis code, and a copy of the code repository for operating the patient monitors and central station.
Amazonian deforestation causes systematic changes in regional dry season precipitation. Some of these changes at contemporary large scales (a few hundreds of kilometers) of deforestation have been associated with a ‘dynamical mesoscale circulation’, induced by the replacement of rough forest with smooth pasture. In terms of decadal averages, this dynamical mechanism yields increased precipitation in downwind regions and decreased precipitation in upwind regions of deforested areas. Daily, seasonal, and interannual variations in this phenomenon may exist, but have not yet been identified or explained. This study uses observations and numerical simulations to develop relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions across a range of time scales. It is found that the strength of the dynamical mechanism is primarily controlled by the regional-scale thermal and dynamical conditions of the boundary layer, and not by the continental- and global-scale atmospheric state. Lifting condensation level and wind speed within the boundary layer have large and positive correlations with the strength of the dynamical mechanism. The strength of these relationships depends on time scale and is strongest over the seasonal cycle. Overall, the dynamical mechanism is found to be strongest during times when the atmosphere is relatively stable. Hence, for contemporary large scales of deforestation this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially during the dry-to-wet transition), significantly affecting the hydroclimate during this period.
This is the supplemental material for the manuscript "Verification, validation, and results of an approximate model for the stress of a Tokamak toroidal field coil at the inboard midplane" submitted to Fusion Engineering and Design. This material includes PDF writeups of the derivations of the axisymmetric extended plane strain model, the elastic properties smearing model, and 20+ MATLAB scripts and functions which implement the model and generate the figures in the paper.
In the attention schema theory, the brain constructs a model of attention, the attention schema, to aid in the endogenous control of attention. Growing behavioral evidence appears to support this proposal. However, a central question remains: does a controller of attention actually benefit by having access to an attention schema? We constructed an artificial, deep Q-learning, neural network agent that was trained to control a simple form of visuospatial attention, tracking a stimulus with its attention spotlight in order to solve a catch task. The agent was tested with and without access to an attention schema. In both conditions, the agent received sufficient information such that it should, theoretically, be able to learn the task. We found that with an attention schema present, the agent learned to control its attention spotlight and learned the catch task to a high degree of performance. Once the agent learned, if the attention schema was disabled, the agent could no longer perform effectively. If the attention schema was removed before learning began, the agent was drastically impaired at learning. The results show how the presence of even a simple attention schema provides a profound benefit to a controller of attention. We interpret these results as supporting the central argument of AST: the brain evolved an attention schema because of its practical benefit in the endogenous control of attention.