Planarity of para Hexaphenyl

URL:http://link.aps.org/doi/10.1103/PhysRevLett.82.3625 DOI:10.1103/PhysRevLett.82.3625We present experimental and theoretical findings on the geometry of polycrystalline para hexaphenyl via Raman scattering. The planarity of the molecule is affected by hydrostatic pressure and temperature. Our studies indicate that the potential energy curve which governs the torsional motion between neighboring phenyl rings is “W” shaped. We determine the activation energy to promote the molecule from a nonplanar to a planar state to be 0.04 eV, in good agreement with our quantum chemical calculations. From the relative intensities of the 1280cm-1 to the 1220cm-1 Raman modes we show that high pressure planarizes the molecules, modifying the “W”-shaped potential energy curve to a “U”-shaped one.We acknowledge the financial support from U.S. Army Grant No. DAAL03-92-0381, University of Missouri Research Board and Österreichische Nationalbank (Project No. 6608)

High pressure effects on the photoluminescence intensity of sexithiophene single crystals

We report on the influence of interchain interactions on the light emission properties of a sexithiophene single crystal. The strength of the intermolecular interactions is controlled by applying hydrostatic pressure. The combined use of both steady-state and time-resolved photoluminescence techniques permits to show that the pressure-induced quenching of the photoluminescence is caused by a reduction of the radiative recombination rate

Geometry-Dependent Electronic Properties of Highly Fluorescent Conjugated Molecules

URL:http://link.aps.org/doi/10.1103/PhysRevLett.85.2388 DOI:10.1103/PhysRevLett.85.2388We present a combined experimental/theoretical study of the electronic properties of conjugated para- phenylene type molecules under high pressure up to 80 kbar. Pressure is used as a tool to vary the molecular geometry and intermolecular interaction. The influence of the latter two on singlet and triplet excitons as well as polarons is monitored via optical spectroscopy. We have performed band structure calculations for the planar poly(para-phenylene) and calculated the dielectric function. By varying the intermolecular distances and the length of the polymer repeat unit the observed pressure effects can be explained.Supported by the University of Missouri Research Board, OeNB Project No. 6608, the vector-computer facilities at the University of Graz

Conjugation-Length Dependence of Spin-Dependent Exciton Formation Rates in Pi-Conjugated Oligomers and Polymers

We have measured the ratio, r = $\sigma_S/\sigma_T$ of the formation cross section, $\sigma$ of singlet ($\sigma_S$) and triplet ($\sigma_T$) excitons from oppositely charged polarons in a large variety of $\pi$-conjugated oligomer and polymer films, using the photoinduced absorption and optically detected magnetic resonance spectroscopies. The ratio r is directly related to the singlet exciton yield, which in turn determines the maximum electroluminescence quantum efficiency in organic light emitting diodes (OLED). We discovered that r increases with the conjugation length, CL; in fact a universal dependence exists in which $r^{-1}$ depends linearly on $CL^{-1}$, irrespective of the chain backbone structure. These results indicate that $\pi$-conjugated polymers have a clear advantage over small molecules in OLED applications.Comment: 5 pages, 4 figure

State based model of long-term potentiation and synaptic tagging and capture

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.We thank Michael Hines for helping with synapse model implementation in NEURON; Mariana Vargas-Caballero for sharing NMDAR data; Veronica Egger for sharing in vitro data and for clarifications on the analysis methods; Jesper Sjöström for sharing in vitro data, helpful discussions, and feedback on the manuscript; Ralf Schneggenburger for helpful discussions and clarifications on the NMDAR calcium current model; Fabien Delalondre for helpful discussions; Francesco Casalegno and Taylor Newton for helpful discussion on model fitting; Daniel Keller for helpful discussions on the biophysics of synaptic plasticity; Natali Barros-Zulaica for helpful discussions on MVR modeling and generalization; Srikanth Ramaswamy, Michael Reimann and Max Nolte for feedback on the manuscript; Wulfram Gerstner and Guillaume Bellec for helpful discussions on synaptic plasticity modeling. This study was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne, from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology. E.B.M. received additional support from the CHU Sainte-Justine Research Center (CHUSJRC), the Institute for Data Valorization (IVADO), Fonds de Recherche du Québec–Santé (FRQS), the Canada CIFAR AI Chairs Program, the Quebec Institute for Artificial Intelligence (Mila), and Google. R.B.P. and J.DF. received support from the Spanish “Ministerio de Ciencia e Innovación” (grant PGC2018-094307-B-I00). M.D. and I.S. were supported by a grant from the ETH domain for the Blue Brain Project, the Gatsby Charitable Foundation, and the Drahi Family Foundation

Adaptive and Phase Selective Spike Timing Dependent Plasticity in Synaptically Coupled Neuronal Oscillators

We consider and analyze the influence of spike-timing dependent plasticity (STDP) on homeostatic states in synaptically coupled neuronal oscillators. In contrast to conventional models of STDP in which spike-timing affects weights of synaptic connections, we consider a model of STDP in which the time lags between pre- and/or post-synaptic spikes change internal state of pre- and/or post-synaptic neurons respectively. The analysis reveals that STDP processes of this type, modeled by a single ordinary differential equation, may ensure efficient, yet coarse, phase-locking of spikes in the system to a given reference phase. Precision of the phase locking, i.e. the amplitude of relative phase deviations from the reference, depends on the values of natural frequencies of oscillators and, additionally, on parameters of the STDP law. These deviations can be optimized by appropriate tuning of gains (i.e. sensitivity to spike-timing mismatches) of the STDP mechanism. However, as we demonstrate, such deviations can not be made arbitrarily small neither by mere tuning of STDP gains nor by adjusting synaptic weights. Thus if accurate phase-locking in the system is required then an additional tuning mechanism is generally needed. We found that adding a very simple adaptation dynamics in the form of slow fluctuations of the base line in the STDP mechanism enables accurate phase tuning in the system with arbitrary high precision. Adaptation operating at a slow time scale may be associated with extracellular matter such as matrix and glia. Thus the findings may suggest a possible role of the latter in regulating synaptic transmission in neuronal circuits

A theory of Plasma Membrane Calcium Pump stimulation and activity

The ATP-driven Plasma Membrane Calcium pump or Ca(2+)-ATPase (PMCA) is characterized by a high affinity to calcium and a low transport rate compared to other transmembrane calcium transport proteins. It plays a crucial role for calcium extrusion from cells. Calmodulin is an intracellular calcium buffering protein which is capable in its Ca(2+) liganded form of stimulating the PMCA by increasing both the affinity to calcium and the maximum calcium transport rate. We introduce a new model of this stimulation process and derive analytical expressions for experimental observables in order to determine the model parameters on the basis of specific experiments. We furthermore develop a model for the pumping activity. The pumping description resolves the seeming contradiction of the Ca(2+):ATP stoichiometry of 1:1 during a translocation step and the observation that the pump binds two calcium ions at the intracellular site. The combination of the calcium pumping and the stimulation model correctly describes PMCA function. We find that the processes of calmodulin-calcium complex attachment to the pump and of stimulation have to be separated. Other PMCA properties are discussed in the framework of the model. The presented model can serve as a tool for calcium dynamics simulations and provides the possibility to characterize different pump isoforms by different type-specific parameter sets.Comment: 24 pages, 6 figure

Attentional Window Set by Expected Relevance of Environmental Signals

The existence of an attentional window—a limited region in visual space at which attention is directed—has been invoked to explain why sudden visual onsets may or may not capture overt or covert attention. Here, we test the hypothesis that observers voluntarily control the size of this attentional window to regulate whether or not environmental signals can capture attention. We have used a novel approach to test this: participants eye-movements were tracked while they performed a search task that required dynamic gaze-shifts. During the search task, abrupt onsets were presented that cued the target positions at different levels of congruency. The participant knew these levels. We determined oculomotor capture efficiency for onsets that appeared at different viewing eccentricities. From these, we could derive the participant's attentional window size as a function of onset congruency. We find that the window was small during the presentation of low-congruency onsets, but increased monotonically in size with an increase in the expected congruency of the onsets. This indicates that the attentional window is under voluntary control and is set according to the expected relevance of environmental signals for the observer's momentary behavioral goals. Moreover, our approach provides a new and exciting method to directly measure the size of the attentional window

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations