South Dakota Farmland Market Trends: 1991-1999

Agricultural land values and cash rental rates in South Dakota, by region and by state, are the primary topics of this report, which is written for farmers and ranchers, landowners, agricultural professionals (lenders, rural appraisers, professional farm managers, Extension agents, and educators), and policy makers interested in agricultural land market trends. This report contains the results of the 1999 SDSU South Dakota Farm Real Estate Market Survey, the ninth annual SDSU survey developed to estimate agricultural land values and cash rental rates by land use in different regions of South Dakota

Improving the signal detection accuracy of functional Magnetic Resonance Imaging

Available online 12 April 2018A major drawback of functional Magnetic Resonance Imaging (fMRI) concerns the lack of detection accuracy of the measured signal. Although this limitation stems in part from the neuro-vascular nature of the fMRI signal, it also reflects particular methodological decisions in the fMRI data analysis pathway. Here we show that the signal detection accuracy of fMRI is affected by the specific way in which whole-brain volumes are created from individually acquired brain slices, and by the method of statistically extracting signals from the sampled data. To address these limitations, we propose a new framework for fMRI data analysis. The new framework creates whole-brain volumes from individual brain slices that are all acquired at the same point in time relative to a presented stimulus. These whole-brain volumes contain minimal temporal distortions, and are available at a high temporal resolution. In addition, statistical signal extraction occurred on the basis of a non-standard time point-by-time point approach. We evaluated the detection accuracy of the extracted signal in the standard and new framework with simulated and real-world fMRI data. The new slice-based data-analytic framework yields greatly improved signal detection accuracy of fMRI signals.See https://github.com/iamnielsjanssen/slice-based for a full analysis script using the Slice-Based method. This work was supported by The Spanish Ministry of Economy and Competitiveness (RYC2011-08433 and PSI2013-46334 to NJ)

Hungry or Stressed? Relationship between Stress and Attention for Food-related Words

Obesity is a major health problem in western society and caused by different factors. Stress-induced eating is widely thought to increase the risk for obesity. The purpose of this study was to investigate the influence of stress on attention for food. We hypothesized that stress creates an attentional bias for high-caloric food, which can be assessed by an adapted Stroop task. This is measured by comparing reaction times for food-related words and non-food related words before and after stress. Against our expectations, we found that stress had no significantly different effect on the food word list compared to the neutral word list. Stressed and non-stressed participants turned out to be significantly slower on the food-word list than on the neutral-word list and participants were generally faster on both lists after stress. Taken together, our results show that the attentional bias for high-caloric food is not influenced by stress

Functional connectivity of the hippocampus and its subfields in resting-state networks

First published: 30 March 2021Many neuroimaging studies have shown that the hippocampus participates in a resting-state network called the default mode network. However, how the hippocampus connects to the default mode network, whether the hippocampus connects to other resting-state networks and how the different hippocampal subfields take part in resting-state networks remains poorly understood. Here, we examined these issues using the high spatial-resolution 7T resting-state fMRI dataset from the Human Connectome Project. We used data-driven techniques that relied on spatially-restricted Independent Component Analysis, Dual Regression and linear mixed-effect group-analyses based on participant-specific brain morphology. The results revealed two main activity hotspots inside the hippocampus. The first hotspot was located in an anterior location and was correlated with the somatomotor network. This network was subserved by co-activity in the CA1, CA3, CA4 and Dentate Gyrus fields. In addition, there was an activity hotspot that extended from middle to posterior locations along the hippocampal long-axis and correlated with the default mode network. This network reflected activity in the Subiculum, CA4 and Dentate Gyrus fields. These results show how different sections of the hippocampus participate in two known resting-state networks and how these two resting-state networks depend on different configurations of hippocampal subfield co-activity.Agencia Canaria de Investigación, Innovación y Sociedad de la Información; Ministerio de Ciencia, Innovación y Universidades, Grant/Award Number: PSI2017-84933- P, PSI2017-91955- EXP and TEC2016-80063- C3- 2- R; NIH Blueprint for Neuroscience Research, Grant/Award Number: 1U54MH091657; McDonnell Center for Systems Neuroscience; European Social Fund (ESF

Scattering features and variability of the Crab pulsar

We report on Westerbork Synthesis Radio Telescope observations of the Crab pulsar at 350 MHz from 2012 November 24 until 2015 June 21. During this period we consistently observe variations in the pulse profile of the Crab. Both variations in the scattering width of the pulse profile as well as delayed copies, also known as echoes, are seen regularly. These observations support the classification of two types of echoes: those that follow the truncated exponential shape expected for the thin-screen scattering approximation, and echoes that show a smoother, more Gaussian shape. During a sequence of high-cadence observations in 2015, we find that these non-exponential echoes evolve in time by approaching the main pulse and interpulse in phase, overlapping the main pulse and interpulse, and later receding. We find a pulse scatter-broadening time scale, $\tau$, scaling with frequency as $\nu^{\alpha}$, with $\alpha=-3.9\pm0.5$, which is consistent with expected values for thin-screen scattering modelsComment: 10 pages, 7 figure