Manipulation and removal of defects in spontaneous optical patterns

Defects play an important role in a number of fields dealing with ordered structures. They are often described in terms of their topology, mutual interaction and their statistical characteristics. We demonstrate theoretically and experimentally the possibility of an active manipulation and removal of defects. We focus on the spontaneous formation of two-dimensional spatial structures in a nonlinear optical system, a liquid crystal light valve under single optical feedback. With increasing distance from threshold, the spontaneously formed hexagonal pattern becomes disordered and contains several defects. A scheme based on Fourier filtering allows us to remove defects and to restore spatial order. Starting without control, the controlled area is progressively expanded, such that defects are swept out of the active area.Comment: 4 pages, 4 figure

Enhanced Odor Discrimination and Impaired Olfactory Memory by Spatially Controlled Switch of AMPA Receptors

Genetic perturbations of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptors (AMPARs) are widely used to dissect molecular mechanisms of sensory coding, learning, and memory. In this study, we investigated the role of Ca(2+)-permeable AMPARs in olfactory behavior. AMPAR modification was obtained by depletion of the GluR-B subunit or expression of unedited GluR-B(Q), both leading to increased Ca(2+) permeability of AMPARs. Mice with this functional AMPAR switch, specifically in forebrain, showed enhanced olfactory discrimination and more rapid learning in a go/no-go operant conditioning task. Olfactory memory, however, was dramatically impaired. GluR-B depletion in forebrain was ectopically variable (“mosaic”) among individuals and strongly correlated with decreased olfactory memory in hippocampus and cortex. Accordingly, memory was rescued by transgenic GluR-B expression restricted to piriform cortex and hippocampus, while enhanced odor discrimination was independent of both GluR-B variability and transgenic GluR-B expression. Thus, correlated differences in behavior and levels of GluR-B expression allowed a mechanistic and spatial dissection of olfactory learning, discrimination, and memory capabilities

Effects of lipid composition on membrane permeation

© 2018 The Royal Society of Chemistry. Passive permeation through lipid membranes is an essential process in biology. In vivo membranes typically consist of mixtures of lamellar and nonlamellar lipids. Lamellar lipids are characterized by their tendency to form lamellar sheet-like structures, which are predominant in nature. Nonlamellar lipids, when isolated, instead form more geometrically complex nonlamellar phases. While mixed lamellar/nonlamellar lipid membranes tend to adopt the ubiquitous lamellar bilayer structure, the presence of nonlamellar lipids is known to have profound effects on key membrane properties, such as internal distributions of stress and elastic properties, which in turn may alter related biological processes. This work focuses on one such process, i.e., permeation, by utilising atomistic molecular dynamics simulations in order to obtain transfer free energy profiles, diffusion profiles and permeation coefficients for a series of thirteen small molecules and drugs. Each permeant is tested on two bilayer membranes of different lipid composition, i.e., purely lamellar and mixed lamellar/nonlamellar. Our results indicate that the presence of nonlamellar lipids reduces permeation for smaller molecules (molecular weight 100). This work represents an advancement towards the development of more realistic in silico permeability assays, which may have a substantial future impact in the area of rational drug design

Partners No More: Relational Transformation and the Turn to Litigation in Two Conservationist Organizations

The rise in litigation against administrative bodies by environmental and other political interest groups worldwide has been explained predominantly through the liberalization of standing doctrines. Under this explanation, termed here the floodgate model, restrictive standing rules have dammed the flow of suits that groups were otherwise ready and eager to pursue. I examine this hypothesis by analyzing processes of institutional transformation in two conservationist organizations: the Sierra Club in the United States and the Society for the Protection of Nature in Israel (SPNI). Rather than an eagerness to embrace newly available litigation opportunities, as the floodgate model would predict, the groups\u27 history reveals a gradual process of transformation marked by internal, largely intergenerational divisions between those who abhorred conflict with state institutions and those who saw such conflict as not only appropriate but necessary to the mission of the group. Furthermore, in contrast to the pluralist interactions that the floodgate model imagines, both groups\u27 relations with pertinent agencies in earlier eras better accorded with the partnership-based corporatist paradigm. Sociolegal research has long indicated the importance of relational distance to the transformation of interpersonal disputes. I argue that, at the group level as well, the presence or absence of a (national) partnership-centered relationship determines propensities to bring political issues to court. As such, well beyond change in groups\u27 legal capacity and resources, current increases in levels of political litigation suggest more fundamental transformations in the structure and meaning of relations between citizen groups and the state

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)