Adapting threat-related memories towards changing environments is a fundamental ability of organisms. One central process of fear reduction is suggested to be extinction learning, experimentally modeled by extinction training that is repeated exposure to a previously conditioned stimulus (CS) without providing the expected negative consequence (unconditioned stimulus, US). Although extinction training is well investigated, evidence regarding process-related changes in neural activation over time is still missing. Using optimized delayed extinction training in a multicentric trial we tested whether: 1) extinction training elicited decreasing CS-specific neural activation and subjective ratings, 2) extinguished conditioned fear would return after presentation of the US (reinstatement), and 3) results are comparable across different assessment sites and repeated measures. We included 100 healthy subjects (measured twice, 13-week-interval) from six sites. 24 h after fear acquisition training, extinction training, including a reinstatement test, was applied during fMRI. Alongside, participants had to rate subjective US-expectancy, arousal and valence. In the course of the extinction training, we found decreasing neural activation in the insula and cingulate cortex as well as decreasing US-expectancy, arousal and negative valence towards CS+. Re-exposure to the US after extinction training was associated with a temporary increase in neural activation in the anterior cingulate cortex (exploratory analysis) and changes in US-expectancy and arousal ratings. While ICCs-values were low, findings from small groups suggest highly consistent effects across time-points and sites. Therefore, this delayed extinction fMRI-paradigm provides a solid basis for the investigation of differences in neural fear-related mechanisms as a function of anxiety-pathology and exposure-based treatment.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118157 | DOI Listing |
Nanoscale
January 2025
AIT Austrian Institute of Technology, Molecular Diagnostics, 1210 Vienna, Austria.
Metal nanoparticles are established tools for biomedical applications due to their unique optical properties, primarily attributed to localized surface plasmon resonances. They show distinct optical characteristics, such as high extinction cross-sections and resonances at specific wavelengths, which are tunable across the wavelength spectrum by modifying the nanoparticle geometry. These attributes make metal nanoparticles highly valuable for sensing and imaging in biology and medicine.
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Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China.
Using microwave remote sensing to invert forest parameters requires clear canopy scattering characteristics, which can be intuitively investigated through scattering measurements. However, there are very few ground-based measurements on forest branches, needles, and canopies. In this study, a quantitative analysis of the canopy branches, needles, and ground contribution of Masson pine scenes in C-, X-, and Ku-bands was conducted based on a microwave anechoic chamber measurement platform.
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Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany.
Illegal wildlife trade is a growing problem internationally. Poaching of animals not only leads to the extinction of populations and species but also has serious consequences for ecosystems and economies. This study introduces a molecular marker system that authorities can use to detect and substantiate wildlife trafficking.
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January 2025
Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9FE, UK.
Fieldwork-based research and education in ecology are under multiple threats and are progressively declining. We call for greater attention to this ongoing loss of direct field experience within the ecology community, as it could have widespread consequences for science and education, ultimately hindering efforts to address the ongoing biodiversity crisis.
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January 2025
KU Leuven, Department of Movement Sciences, B-3000 Leuven, Belgium.
In motor adaptation, learning is thought to rely on a combination of several processes. Two of these are implicit learning (incidental updating of the movement due to sensory prediction error) and explicit learning (intentional adjustment to reduce target error). The explicit component is thought to be fast adapting, while the implicit one is slow.
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