Long-Term Potentiation and Memory

One of the most significant challenges in neuroscience is to identify the cellular and molecular processes that underlie learning and memory formation. The past decade has seen remarkable progress in understanding changes that accompany certain forms of acquisition and recall, particularly those forms which require activation of afferent pathways in the hippocampus. This progress can be attributed to a number of factors including well-characterized animal models, well-defined probes for analysis of cell signaling events and changes in gene transcription, and technology which has allowed gene knockout and overexpression in cells and animals. Of the several animal models used in identifying the changes which accompany plasticity in synaptic connections, long-term potentiation (LTP) has received most attention, and although it is not yet clear whether the changes that underlie maintenance of LTP also underlie memory consolidation, significant advances have been made in understanding cell signaling events that contribute to this form of synaptic plasticity. In this review, emphasis is focused on analysis of changes that occur after learning, especially spatial learning, and LTP and the value of assessing these changes in parallel is discussed. The effect of different stressors on spatial learning/memory and LTP is emphasized, and the review concludes with a brief analysis of the contribution of studies, in which transgenic animals were used, to the literature on memory/learning and LTP

Constructing and Implementing a Summer Wellness Curriculum: Bridging the Gaps at YES

Introduction: Youth experiencing homelessness lack learning experiences during the summer months, potentially leading to delinquent activities and hazardous situations. The project created and implemented a summer wellness curriculum at Youth Emergency Service (YES) that aimed to identify gaps in and educate the youth on various health and wellness topics. Daily exercise actively promoted physical wellbeing. Methods: The curriculum aimed at a mixed group of adolescents facing homelessness integrated various educational and/or physical activities with wellness activities by YES staff and Title I programming. Activity description, cost, location, time and date, and number of attendees were recorded in a logbook. Qualitative analysis described reception of the activities and was compared to cost and number of attendees. Title I programming, YES wellness activities, field trips, and activities after 7/26 were not included in analysis. Results: The most attended activities with greatest apparent interest cost money (Power of Words, Tie-Dye, and Skyzone) or supplied a monetary incentive (Haven House). 16 youth learned about HIV and participated in HIV testing. The most successful inclusive free activities were yoga, cooking, and water balloon games, as both males and females participated and were consistently engaged throughout; males predominated attendance of other physical activities. Creating the Heart Smart poster and vision boards were the least popular. Conclusion: Youth at YES tended to be motivated by special activities or monetary incentives; more of these activities should be incorporated into future programming. Individualized input from female youth should be utilized to elicit greater participation during physical activities next year

GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs

This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian Processes (GP), and to states represented as a weighted sum of Gaussians. The key attribute of GP-SUM is that it does not rely on linearizations of the dynamic or observation models, or on unimodal Gaussian approximations of the belief, hence enables tracking complex state distributions. The algorithm can be seen as a combination of a sampling-based filter with a probabilistic Bayes filter. On the one hand, GP-SUM operates by sampling the state distribution and propagating each sample through the dynamic system and observation models. On the other hand, it achieves effective sampling and accurate probabilistic propagation by relying on the GP form of the system, and the sum-of-Gaussian form of the belief. We show that GP-SUM outperforms several GP-Bayes and Particle Filters on a standard benchmark. We also demonstrate its use in a pushing task, predicting with experimental accuracy the naturally occurring non-Gaussian distributions.Comment: WAFR 2018, 16 pages, 7 figure

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology

Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels.We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in originﾗdegree distribution, clustering coefficient, and motifsﾗ within the E. coli CRN. Our model captures the tightly coupled genomeﾖ interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs

Automatically Detecting Confusion and Conflict During Collaborative Learning Using Linguistic, Prosodic, and Facial Cues

During collaborative learning, confusion and conflict emerge naturally. However, persistent confusion or conflict have the potential to generate frustration and significantly impede learners' performance. Early automatic detection of confusion and conflict would allow us to support early interventions which can in turn improve students' experience with and outcomes from collaborative learning. Despite the extensive studies modeling confusion during solo learning, there is a need for further work in collaborative learning. This paper presents a multimodal machine-learning framework that automatically detects confusion and conflict during collaborative learning. We used data from 38 elementary school learners who collaborated on a series of programming tasks in classrooms. We trained deep multimodal learning models to detect confusion and conflict using features that were automatically extracted from learners' collaborative dialogues, including (1) language-derived features including TF-IDF, lexical semantics, and sentiment, (2) audio-derived features including acoustic-prosodic features, and (3) video-derived features including eye gaze, head pose, and facial expressions. Our results show that multimodal models that combine semantics, pitch, and facial expressions detected confusion and conflict with the highest accuracy, outperforming all unimodal models. We also found that prosodic cues are more predictive of conflict, and facial cues are more predictive of confusion. This study contributes to the automated modeling of collaborative learning processes and the development of real-time adaptive support to enhance learners' collaborative learning experience in classroom contexts.Comment: 27 pages, 7 figures, 7 table

3D Visualisation of Additive Occlusion and Tunable Full-Spectrum Fluorescence in Calcite

From biomineralization to synthesis, organic additives provide an effective means of controlling crystallisation processes. There is growing evidence that these additives are often occluded within the crystal lattice, where this promises an elegant means of creating nanocomposites and tuning physical properties. Here, we use the incorporation of sulfonated fluorescent dyes to gain new understanding of additive occlusion in calcite (CaCO3), and to link morphological changes to occlusion mechanisms. We demonstrate that these additives are incorporated within specific zones, as defined by the growth conditions, and show how occlusion can govern changes in crystal shape. Fluorescence spectroscopy and lifetime imaging microscopy also show that the dyes experience unique local environments within different zones. Our strategy was then extended to simultaneously incorporate mixtures of dyes, whose fluorescence cascade creates calcite nanoparticles that fluoresce white. This offers a simple strategy for generating biocompatible and stable fluorescent nanoparticles whose output can be tuned as required

Effect of phase fluctuation and dephasing on the dynamics of entanglement generation in a correlated emission laser

A detailed study of the effects of phase fluctuation and dephasing on the dynamics of the entanglement generated from a coherently pumped correlated emission laser is presented. It is found that the time evolution of the entanglement is significantly reliant on the phase fluctuation and dephasing, particularly, at early stages of the lasing process. In the absence of external driving radiation, the degree of entanglement and intensity turns out to attain a maximum value just before starting to exhibit oscillation which dies at longer time scale. However, in case the driving mechanism is on, the oscillatory nature disappears due to the additional induced coherent superposition and the degree of entanglement would be larger at steady state. Moreover, the degree of entanglement as predicted by the logarithmic negativity and the Duan-Giedke-Cirac-Zoller criteria exhibits a similar nature when there is no driving radiation, although such a trend is eroded with increasing strength of the pumping radiation at longer time scale. The other important aspect of the phase fluctuation and dephasing is the possibility of relaxing the time at which the maximum entanglement is detected.Comment: 10 pages, 10 figure

Probing elastic and inelastic breakup contributions to intermediate-energy two-proton removal reactions

The two-proton removal reaction from 28Mg projectiles has been studied at 93 MeV/u at the NSCL. First coincidence measurements of the heavy 26Ne projectile residues, the removed protons and other light charged particles enabled the relative cross sections from each of the three possible elastic and inelastic proton removal mechanisms to be determined. These more final-state-exclusive measurements are key for further interrogation of these reaction mechanisms and use of the reaction channel for quantitative spectroscopy of very neutron-rich nuclei. The relative and absolute yields of the three contributing mechanisms are compared to reaction model expectations - based on the use of eikonal dynamics and sd-shell-model structure amplitudes.Comment: Accepted for publication in Physical Review C (Rapid Communication