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Observing a trained demonstrator influences associative appetitive learning in rats
No full textThe ability to acquire information about the environment through social observation or instruction is an essential form of learning in humans and other animals. Here, we assessed the ability of rats to acquire an association between a light stimulus and the presentation of a reward that is either hidden (sucrose solution) or visible (food pellet) via observation of a trained demonstrator. Subsequent training of observers on the light-reward association indicated that while observation alone was not sufficient for observers to acquire the association, contact with the reward location was higher in observers that had had a demonstrator when the light cue predicted a sucrose reward. Additionally, we found that in the visible reward condition, levels of demonstrator orienting and food cup contact during the observation period tended to be positively correlated with the corresponding behavior of their observer. This relationship was only seen during later sessions of observer training. Together, these results suggest that while our models were not sufficient to induce associative learning through observation alone, demonstrator behavior during observation did influence how their paired observer’s behavioral response to the cue evolved over the course of direct individual training
Simulation Output Data
No full textOutput analyzed as part of Persad, G. The Dependence of Aerosols’ Global and Local Precipitation Impacts on Emitting Region.
SLAB OCEAN SIMULATIONS
Structure of filenames:
[Variable].[Simulation_Name].ts.001-100.ANN.nc
All files contain the annual, 100-year timeseries for a single variable. For analysis, the first 40 years are considered to be the model equilibration period. Years 40-100 are used as the equilibrated signal.
Variables:
TREFHT = 2D Surface Air Temperature
PREC = 2D Convective and Largescale Precipitation Rates
E_2000_CAM5_1850aero = Control simulation, year 2000 conditions in all but anthropogenic aerosols, anthropogenic aerosols at year 1850 values.
E_2000_CAM5_1850aero_BRonly_Jan18 = Brazil-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Brazil
E_2000_CAM5_1850aero_CHonly_Jan18 = China-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of China
E_2000_CAM5_1850aero_EAonly_Jan18 = East Africa-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of East Africa
E_2000_CAM5_1850aero_EUonly_Jan18 = Europe-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Western Europe
E_2000_CAM5_1850aero_INonly_Jan18 = India-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of India
E_2000_CAM5_1850aero_NESonly_Jan18 = Indonesia-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Indonesia
E_2000_CAM5_1850aero_USonly_Jan18 = US-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of the United States
E_2000_CAM5_1850aero_SAonly_Jan18 = South Africa-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of South Africa
ATMOSPHERE-ONLY SIMULATIONS
Structure of filenames:
[Variable].[Simulation_Name].ts.001-60.ANN.nc OR
[Variable].[Simulation_Name].mon.001-60.nc
Files contain either the annual, 60-year timeseries ('...ANN.nc') or the monthly, 60-year timeseries ('...mon....nc') for a single variable. For analysis, the first 20 years are considered to be the model equilibration period. Years 20-60 are used as the equilibrated signal.
Variables:
PREC = 2D Convective and Large-scale Precipitation Rates
PRECL = 2D Large-scale Precipitation Rates
PRECC = 2D Convective Precipitation Rates
FLNT = 2D Net longwave flux at top of model
FLNS = 2D Net longwave flux at the surface
FSNT = 2D Net shortwave flux at top of model
FSNS = 2D Net shortwave flux at the surface
F_2000_CAM5_1850aero = Control simulation, year 2000 conditions in all but anthropogenic aerosols, anthropogenic aerosols at year 1850 values.
F_2000_CAM5_1850aero_BRonly_Jan18 = Brazil-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Brazil
F_2000_CAM5_1850aero_CHonly_Jan18 = China-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of China
F_2000_CAM5_1850aero_EAonly_Jan18 = East Africa-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of East Africa
F_2000_CAM5_1850aero_EUonly_Jan18 = Europe-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Western Europe
F_2000_CAM5_1850aero_INonly_Jan18 = India-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of India
F_2000_CAM5_1850aero_NESonly_Jan18 = Indonesia-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of Indonesia
F_2000_CAM5_1850aero_USonly_Jan18 = US-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of the United States
F_2000_CAM5_1850aero_SAonly_Jan18 = South Africa-only perturbation simulation, control simulation conditions, but with fixed aerosol perturbation added within geographic boundaries of South Africa
For full region definitions and specification of the fixed aerosol perturbation, please refer to Persad, G. G., & Caldeira, K. (2018). Divergent global-scale temperature effects from identical aerosols emitted in different regions. Nature Communications, 9(1), 3289. https://doi.org/10.1038/s41467-018-05838-
Quantity Bias Study 1
No full textStudy 1 for Quantity Bias. presented eight shopping situations, manipulating three variables between low and high values for a two by two-by-two presentation total cart cost, potential total savings by going to a second store, and total number of items to be purchased at the second store. Total items in the cart was centered on 20 with a randomized presentation value of {19, 20, 21}. Total cart cost was centered on 100; with a randomized presentation value +/- 50 cents. Potential total savings by going to the second store was centered on 10; with a randomized presentation value +/- 50 cents. Total number of items to purchase at the second store were randomized between two sets: {1,2} and {9,10,11}
Replication Data for: Cross-seeding controls Abeta Fibril Populations and Resulting Function
No full textAmyloid peptides nucleate from monomers to aggregate into fibrils through primary nucleation. Pre-existing fibrils can then act as seeds for additional monomers to fibrillize through secondary nucleation. Both nucleation processes occur simultaneously, yielding a distribution of fibril polymorphs that can generate a spectrum of neurodegenerative effects. Understanding the mechanisms driving polymorph structural distribution during both nucleation processes is important for uncovering fibril structure-function relationships, as well creating polymorph distributions in vitro that better match fibril structures found in vivo. Here, we explore how cross-seeding WT Aβ1-40 with Aβ1-40 mutants E22G (Arctic) and E22Δ (Osaka), as well as with WT Aβ1-42 affects the distribution of fibril structural polymorphs, and how changes in structural distribution impact toxicity. Transmission electron microscopy analysis revealed that fibril seeds derived from mutants of Aβ1-40 imparted their structure to WT Aβ1-40 monomer during secondary nucleation, but WT Aβ1-40 fibril seeds do not affect the structure of fibrils assembled from mutant Aβ1-40 monomers, despite kinetics data indicating accelerated aggregation when cross-seeding of any combination of mutants. Additionally, WT Aβ1-40 fibrils seeded with mutant fibrils produced similar structural distributions to the mutant seeds with similar cytotoxicity profiles. This indicates that mutant fibril seeds not only impart their structure to growing WT Aβ1-40 aggregates, but they also impart cytotoxic properties. Our findings establish a relationship between fibril structure and phenotype on a polymorph population level, and that these properties can be passed on through secondary nucleation to succeeding generations of fibrils
Replication Data for: Mentor-Protégé Similarities Enhance Mentoring Experiences and Persistence for Hispanic STEM Students
No full textData for the study - add mor
Replication Data for: Investigating Detection Probability of Mobile Survey Solutions for Natural Gas Pipeline Leaks under Different Atmospheric Conditions
No full textReplication Data for: Investigating Detection Probability of Mobile Survey Solutions for Natural Gas Pipeline Leaks under Different Atmospheric Condition
Data Collection Instruments
No full textThis data set includes data collection instructions for the article "The offline and online effects of Processing Instruction: An investigation of case marking in L2 German.
Turbulent Pipe flow at Re_tau=180
No full textThe data was extracted from a direct numerical simulation of fully developed turbulent pipe flow. Contact Jie Yao ([email protected]) for questions.
NOTE: before publication, please check here for any updates to the data