Brian S. Blais

Converging evidence for a simplified biophysical model of synaptic plasticity

Abstract. Different mechanisms that could form the molecular basis for bi-directional synaptic plasticity have been identified experimentally and corresponding biophysical models can be constructed. However, such models are complex and therefore it is hard to deduce their consequences to compare them to existing abstract models of synaptic plasticity. In this paper we examine two such models: a phenomenological one inspired by the phenomena of AMPA receptor insertion, and a more complex biophysical model based on the phenomena of AMPA receptor phosphorylation. We show that under certain approximations both these models can be mapped on to an equivalent, calcium-dependent, differential equation. Intracellular calcium concentration varies locally in each postsynaptic compartment, thus the plasticity rule we extract is a single-synapse rule. We convert this single synapse plasticity equation to a multi-synapse rule by incorporating a model of the NMDA receptor. Finally we suggest a mathematical embodiment of metaplasticity, which is consistent with observations on NMDA receptor properties and dependence on cellular activity. These results, in combination with some of our previous results, produce converging evidence for the calcium control hypothesis including a dependence of synaptic plasticity on the level of intercellular calcium as well as on the temporal pattern of calcium transients.

Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning Rules

We study several statistically and biologically motivated learning rules using the same visual environment: one made up of natural scenes and the same single-cell neuronal architecture. This allows us to concentrate on the feature extraction and neuronal coding properties of these rules. Included in these rules are kurtosis and skewness maximization, the quadratic form of the Bienenstock-Cooper-Munro (BCM) learning rule, and single-cell independent component analysis. Using a structure removal method, we demonstrate that receptive fields developed using these rules depend on a small portion of the distribution. We find that the quadratic form of the BCM rule behaves in a manner similar to a kurtosis maximization rule when the distribution contains kurtotic directions, although the BCM modification equations are computationally simpler.

Recovery From Monocular Deprivation Using Binocular Deprivation

Ocular dominance (OD) plasticity is a robust paradigm for examining the functional consequences of synaptic plasticity. Previous experimental and theoretical results have shown that OD plasticity can be accounted for by known synaptic plasticity mechanisms, using the assumption that deprivation by lid suture eliminates spatial structure in the deprived channel. Here we show that in the mouse, recovery from monocular lid suture can be obtained by subsequent binocular lid suture but not by dark rearing. This poses a significant challenge to previous theoretical results. We therefore performed simulations with a natural input environment appropriate for mouse visual cortex. In contrast to previous work, we assume that lid suture causes degradation but not elimination of spatial structure, whereas dark rearing produces elimination of spatial structure. We present experimental evidence that supports this assumption, measuring responses through sutured lids in the mouse. The change in assumptions about the input environment is sufficient to account for new experimental observations, while still accounting for previous experimental results.

Formation of Direction Selectivity in Natural Scene Environments

Most simple and complex cells in the cat striate cortex are both orientation and direction selective. In this article we use single-cell learning rules to develop both orientation and direction selectivity in a natural scene environment. We show that a simple principal component analysis rule is inadequate for developing direction selectivity, but that the BCM rule as well as similar higher-order rules can. We also demonstrate that the convergence of lagged and nonlagged cells depends on the velocity of motion in the environment, and that strobe rearing disrupts this convergence, resulting in a loss of direction selectivity.

Modeling the infectiousness of Twitter hashtags

This study applies dynamical and statistical modeling techniques to quantify the proliferation and popularity of trending hashtags on Twitter. Using time-series data reflecting actual tweets in New York City and San Francisco, we present estimates for the dynamics (i.e., rates of infection and recovery) of several hundred trending hashtags using an epidemic modeling framework coupled with Bayesian Markov Chain Monte Carlo (MCMC) methods. This methodological strategy is an extension of techniques traditionally used to model the spread of infectious disease. Using SIR-type models, we demonstrate that most hashtags are marginally infectious, while very few emerge as “trending”. In doing so we illustrate that hashtags can be grouped by infectiousness, possibly providing a method for quantifying the trendiness of a topic.

Calcium as the associative signal for a model of Hebbian plasticity: Application to multi-input environments

Abstract The sign and magnitude of bi-directional synaptic plasticity have been shown to depend on: the rate of presynaptic stimulation, the level of postsynaptic depolarization, and the precise relative timing between pre- and postsynaptic spikes. It has been proposed that these different induction paradigms can coexist, and be accounted for by a single learning rule that depends on the dynamics of intracellular calcium concentration. We extend this rule to a multi-synaptic environment, where collective properties such as cooperativity, competition and selectivity can be investigated.

The Relationship between Economic Growth and Environmental Degradation: Exploring Models and Questioning the Existence of an Environmental Kuznets Curve

In this paper, we explore a variety of models attempting to explain the pollution-income relationship (PIR). There has been much literature addressing the notion of an environmental Kuznets curve (EKC). Many researchers find an EKC relationship for certain pollutants, while others do not find evidence of an EKC relationship. There is also literature formally critiquing the EKC. We employ cross-sectional, panel, and time-series analysis to add insight into the relationship between economic growth and environmental degradation, a research area that is far from consensual and that has practical implications. We ultimately find that the clearest case of an EKC effect in our study arises in the analysis of organic water pollution, while there is modest evidence suggesting an EKC effect with regard to CO2, NO, and methane. We also present ample evidence suggesting an anti-EKC effect for PM10. Our analysis causes us to question the existence of an EKC effect throughout the environment in general.

Thermally and optically stimulated exoelectron emission from an electron‐beam irradiated glass–ceramic material

The exposure of insulating materials to an electron beam results in the trapping of excess charge on the surface. We have studied the thermally and optically stimulated emission of this excess charge in an electron‐bombarded, fluorophlogopite mica glass–ceramic material (Macor). The total electron emission from the surface is measured either as a function of the sample temperature during heating or the photon wavelength. The emission as a function of temperature has four characteristic peaks whose relative intensity depends on the beam dose, energy, initial sample temperature, and history (accumulation of beam‐induced defects). One peak occurs immediately upon heating and is related to the total surface charge. Two peaks occur at fixed temperatures of 280 and 325 °C and are associated with the discrete energy trap states. The highest temperature peak is only observed after prolonged beam exposure and is due to the annihilation of defects. Illumination in the ultraviolet is required to produce photoemissio...

A Programmable

This article describes the construction of a safe, programmable, automatic thermal cycler for PCR that can be easily constructed by persons with basic soldering and mechanical skills for under

25 Thermal Cycler for PCR

25 in parts and a modest computer such as IBM 486, all of which are readily available. The cycler relies on the heating provided by an incandescent light bulb and cooling by simple convection.