A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all organisms

Students’ Misconceptions in Chemical Equilibria and Suggestions for Improved Instruction

An investigation was conducted into the common misconceptions in chemical equilibria, adopted by a sample of UK secondary school students. These included the characteristics of a dynamic equilibrium, the nature of the reactants and products at equilibrium, as well as the effect of conditions and catalyst on equilibrium. Suggestions for improved teaching were obtained from the students. These included ensuring a clear and comprehensive delivery of basic principles, more or better use of practical demonstrations where appropriate, and use of practice questions. Further research around these suggestions could investigate the value of consulting students’ views and ideas in addressing their misconceptions, to ultimately improve overall conceptual understanding in instruction

Wave theory modeling of three-dimensional seismo-acoustic reverberation in ocean waveguides

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1995.Includes bibliographical references (leaves 175-182).by Henry Fan.Ph.D

A Brief History of Simulation Neuroscience

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of brain organization and the need to integrate these data to trace the causal chain of interactions within and across all these levels. Simulation neuroscience is currently the only methodology for systematically approaching the multiscale brain. In this review, we attempt to reconstruct the deep historical paths leading to simulation neuroscience, from the first observations of the nerve cell to modern efforts to digitally reconstruct and simulate the brain. Neuroscience began with the identification of the neuron as the fundamental unit of brain structure and function and has evolved towards understanding the role of each cell type in the brain, how brain cells are connected to each other, and how the seemingly infinite networks they form give rise to the vast diversity of brain functions. Neuronal mapping is evolving from subjective descriptions of cell types towards objective classes, subclasses and types. Connectivity mapping is evolving from loose topographic maps between brain regions towards dense anatomical and physiological maps of connections between individual genetically distinct neurons. Functional mapping is evolving from psychological and behavioral stereotypes towards a map of behaviors emerging from structural and functional connectomes. We show how industrialization of neuroscience and the resulting large disconnected datasets are generating demand for integrative neuroscience, how the scale of neuronal and connectivity maps is driving digital atlasing and digital reconstruction to piece together the multiple levels of brain organization, and how the complexity of the interactions between molecules, neurons, microcircuits and brain regions is driving brain simulation to understand the interactions in the multiscale brain

Mathematics preservice teachers’ argumentation

ABSTARCT: This research deals with the preservice teachers’ dialogic argumentationswhen presenting geometry tasks to their colleagues, during discussion sessions previous to teaching to children. An argumentation analysis tool is used that complement Toulmin’s analysis proposal and that includes features related to mathematicallogic, rhetoric and dialectic features.We propose both a representation for the dialogic argumentation and a way to identify its structural qualitie

Motivational State and Reward Content Determine Choice Behavior under Risk in Mice

Risk is a ubiquitous feature of the environment for most organisms, who must often choose between a small and certain reward and a larger but less certain reward. To study choice behavior under risk in a genetically well characterized species, we trained mice (C57BL/6) on a discrete trial, concurrent-choice task in which they must choose between two levers. Pressing one lever (safe choice) is always followed by a small reward. Pressing the other lever (risky choice) is followed by a larger reward, but only on some of the trials. The overall payoff is the same on both levers. When mice were not food deprived, they were indifferent to risk, choosing both levers with equal probability regardless of the level of risk. In contrast, following food or water deprivation, mice earning 10% sucrose solution were risk-averse, though the addition of alcohol to the sucrose solution dose-dependently reduced risk aversion, even before the mice became intoxicated. Our results falsify the budget rule in optimal foraging theory often used to explain behavior under risk. Instead, they suggest that the overall demand or desired amount for a particular reward determines risk preference. Changes in motivational state or reward identity affect risk preference by changing demand. Any manipulation that increases the demand for a reward also increases risk aversion, by selectively increasing the frequency of safe choices without affecting frequency of risky choices