Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: Computational study

Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP.     

A computational view of short-term plasticity and its implications for E-I balance

Short-term plasticity (STP) and excitatory-inhibitory balance (EI balance) are both ubiquitous building blocks of brain circuits across the animal kingdom. The synapses involved in EI are also subject to short-term plasticity, and several experimental studies have shown that their effects overlap. Recent computational and theoretical work has begun to highlight the functional implications of the intersection of these motifs. The findings are nuanced: while there are general computational themes, such as pattern tuning, normalization, and gating, much of the richness of these interactions comes from region- and modality specific tuning of STP properties. Together these findings point towards the STP-EI balance combination as being a versatile and highly efficient neural building block for a wide range of pattern-specific responses.     

The role of short-term synaptic dynamics in motor control

During the past few years, much attention has been given to the role of short-term synaptic plasticity, in particular depression and facilitation, in sculpting network activity. A recent study shows that synaptic depression in rhythmic motor networks could switch the control of network frequency from intrinsic neuronal properties to the synaptic dynamics. Short-term synaptic plasticity is also involved in the stabilization and reconfiguration of motor circuits and in the initiation, maintenance and modulation of motor programs.     

Some implications of the short-term synaptic plasticity for neuronal computation: a model study

Spikes arriving at the synaptic connection produce short-term plastic changes of the synaptic efficacy. Model experiments have shown that paired-pulse facilitation attaining its maximum after a specific interval between a pair of arriving spikes might turn a “weak” plastic synapse attached to an integrate-and-fire neuron to a frequency-tuned device. Resulting computational capabilities create biologically plausible mechanisms of information processing relating to: (i) real-time identification of temporal patterns in a stream of random spiking activity (a recognition problem); and (ii) codetermination of the specific activity routing among neurons (an addressing problem) resulting in definite spatio-temporal patterns of the output activity (an input-output pattern problem).     

A modeling study of anaerobic biofilm systems: II. Reactor modeling

A rigorous steady-state model of anaerobic biofilm reactors taking into account acid-base and gas-phase equilibria in the reactor in conjunction with detailed chemical equilibria and mass transfer in acetate-utilizing methanogenic biofilms is presented. The performances of ideal completely stirred tank reactors (CSTRs) and plug-flow reactors, as well as reactors with nonideal hydraulic conditions, are simulated. Decreasing the surface loading rate increases the acetate removal efficiency, while decreasing the influent pH and increasing the buffering capacity improves the removal efficiency only if the bulk pH of the reactor shifts toward more optimal values between 6.8 to 7.0. The reactor can have negative or positive removal efficiencies depending on the start-up conditions. The respiration coefficient plays a critical role in determining the minimum influent pH required for reactor recovery after failure. Having multiple CSTRs-in-series generally increases the overall removal efficiency for the influent conditions investigated. Monitoring of the influent feed quality is critical for plug-flow reactors, becasue failure of the initial sections of the reactor may cause a cascading effect that may lead to a rapid reactor failure. (c) 1995 John Wiley & Sons, Inc.     

Emergence of resonances in neural systems: the interplay between adaptive threshold and short-term synaptic plasticity

In this work we study the detection of weak stimuli by spiking (integrate-and-fire) neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between adaptive neuron threshold and activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our main results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic stochastic synaptic models and realistic signals such as poissonian spike trains.     

Detection and classification of neurotoxins using a novel short-term plasticity quantification method

A tissue-based biosensor is described for screening chemical compounds that rapidly affect the nervous system. The proposed sensor is an extension of a previous work on cultured hippocampal slices [Biosens. Bioelectron. 16 (2001) 491]. The detection of the chemical compounds is based on a novel quantification method of short-term plasticity (STP) of the CA1 system in acute hippocampal slices, using random electrical impulse sequences as inputs and population spike (PS) amplitudes as outputs. STP is quantified by the first and the second order kernels using a variant of the Volterra modeling approach. This approach is more specific and time-efficient than the conventional paired pulse and fixed frequency train methods [J. Neurosci. Methods 2 (2002) 111]. Describing the functional state of the biosensor, the kernels changed accordingly as chemical compounds were added. The second order kernel was decomposed into nine Laguerre functions. The corresponding Laguerre coefficients along with the first order kernel were used as features for classification purposes. The biosensor was tested using picrotoxin (100 μM), trimethylopropane phosphate (10 μM), tetraethylammonium (4 mM), valproate (5 mM), carbachol (5 mM), DAP5 (25 μM), CNQX (3 μM), and DNQX (0.15, 1.5, 3, 5 and 10 μM). Each chemical compound gave a different feature profile corresponding to its pharmacological class. The first order kernel and the Laguerre coefficients formed the input to an artificial neural network (ANN) comprised of a single layer of perceptrons. The ANN was able to classify each tested compound into its respective class.     

A modeling study of anaerobic biofilm systems: I. Detailed biofilm modeling

A detailed model acetate-utilizing methanogenic biofilms accounting for the diffusion of neutral and ionic species, chemical equilibrium, electroneutrality, gas production within the biofilm, pH-dependent Monod kinetics, and the presence of a concentration boundary layer is presented. The model qualitatively fits the pH profiles that are reported for acetate-utilizing methanogenic aggregates. A sensitivity analysis on the biological parameters showed that the flux of acetate is sensitive to the maximum utilization rate, half-saturation constant, and biofilm density for the bulk conditions investigated. Criteria when traditional biofilm models can be used to predict the flux of acetate into the biofilm are established. If the maximum pH change predicted using a hypothetical system is within +/-0.05, the traditional model predicts the flux to within +/-5% of the value calculated with the model developed in this study. (c) 1995 John Wiley & Sons, Inc.     

The biochemical basis of synaptic plasticity and neurocomputation: a new theory.

The recent finding that dendritic spines (on which 90% of all excitatory synapses on pyramidal cells are formed) are not permanent structures but are continually being formed and adsorbed has implications for the present theoretical basis of neurocomputation, which is largely based on the concept of fixed nerve nets. This evidence would tend to support the recent theories of Edelman, Freeman, Globus, Pribram and others that neuronal networks in the brain operate mainly as nonlinear dynamic, chaotic systems. This paper presents a hypothesis of a possible neurochemical mechanism underlying this synaptic plasticity based on reactive oxygen species and toxic 0-semiquinones derived from catecholamines (i) by the enzyme prostaglandin H synthetase induced by glutamatergic NMDA receptor activation and (ii) by reactive nitrogen species derived from nitric oxide in a low ascorbate environment. A key factor in this neuromodulation may be the fact that catecholamines are potent antioxidants and free radical scavengers and are thus able to affect the redox mediated balance at the glutamate receptors between synapse formation and synapse removal that may be a key factor in neurocomputational plasticity. But catecholamines are also easily oxidized to neurotoxic 0-semiquinones and this may be relevant to the pathology of several diseases including schizophrenia. The relationship between dopamine release and positive reinforcement is relevant to this hypothesis.     

Use of brain slices to study long-term potentiation and depression as examples of synaptic plasticity.

Brain slices have been responsible for the majority of advances in our understanding of the cellular aspects of altered synaptic strength underlying memory, long-term potentiation (LTP) and long-term depression (LTD), and increases and decreases, respectively, in synaptic strength at glutamatergic synapses. Our current understanding of LTP and LTD has come largely from studies in hippocampal slices. We consider the strengths and limitations of brain slice technology applied to this subject and conclude that they will continue to have an important role in future studies into the cellular machinery underlying changes in synaptic strength.     

Modulation of ion currents and regulation of transmitter release in short-term synaptic plasticity: The rise and fall of the action potential

Up and down-regulation of calcium and potassium conductances are associated with several forms of short-term synaptic modulation. Detailed investigation of synaptic plasticity in the marine gastropodAplysia, and in other mollusks, indicates that synaptic transmission can be influenced in a number of ways by modulatory neurotransmitters acting through several second-messenger cascades. Modulation at the synapse itself occurs by means of the regulation of calcium current as well as through effects on processes directly involved in transmitter mobilization and exocytosis. Modulation of potassium current plays a major role in controlling neuronal excitability and may contribute to a lesser extent to the regulation of transmitter release through actions on the resting potential and on action potential configuration.     

Possible mechanism of flicking-induced short-term plasticity in retinal cone-LHC synapse: a computational study

In retinal cone-HC synapse, it has been found that repetitive stimulation could induce postsynaptic short-term responsiveness enhancement. However, the detailed mechanism underlying this short-term plasticity in the retinal graded neurons remains unclear. In this study, based on an ion-channel model described using Hodgkin--Huxley equations, the possible mechanism of repetitive-stimulation-induced short-term plasticity in the synapse between retinal cones and horizontal cells was investigated. The computational simulation results, together with evidence from experimental observations, suggest that the short-term modification of signal transmission between the retinal graded neurons is likely to be attributed to the regulatory effects that calcium-dependent process exerts on the single-channel properties of the postsynaptic AMPA receptors.     

Kinetic modeling of cellulosic biomass to ethanol via simultaneous saccharification and fermentation: Part II. Experimental validation using waste paper sludge and anticipation of CFD analysis

A kinetic model of cellulosic biomass conversion to ethanol via simultaneous saccharification and fermentation (SSF) developed previously was validated experimentally using paper sludge as the substrate. Adsorption parameters were evaluated based on the data obtained at various values for fractional cellulose conversion. The adsorption model was then combined with batch SSF data to evaluate the cellulose hydrolysis parameters. With the parameters evaluated for the specific substrate, the discrete model was able to predict SSF successfully both with discrete addition of cellulase only and with discrete feeding of substrate, cellulase, and media. The model tested in this study extends the capability of previous SSF models to semi-continuous feeding configurations, and invites a mechanistic interpretation of the recently observed trend of increasing conversion with decreasing feeding frequency [Fan et al. (2007a) Bioprocess Biosyst Eng 30(1):27-34]. Our results also support the feasibility and utility of determining adsorption parameters based on data obtained at several conversions, particularly when the model is to be applied to extended reaction times rather than only initial hydrolysis rates. The revised model is considerably more computationally efficient than earlier models, and appears for many conditions to be within the capability of simulation using computational fluid dynamics.     

Kinetic modeling of light limitation and sulfur deprivation effects in the induction of hydrogen production with Chlamydomonas reinhardtii. Part II: Definition of model‐based protocols and experimental validation

Photosynthetic hydrogen production under light by the green microalga Chlamydomonas reinhardtii was investigated in a torus‐shaped PBR in sulfur‐deprived conditions. Culture conditions, represented by the dry biomass concentration of the inoculum, sulfate concentration, and incident photon flux density (PFD), were optimized based on a previously published model (Fouchard et al., 2009. Biotechnol Bioeng 102:232–245). This allowed a strictly autotrophic production, whereas the sulfur‐deprived protocol is usually applied in photoheterotrophic conditions. Experimental results combined with additional information from kinetic simulations emphasize effects of sulfur deprivation and light attenuation in the PBR in inducing anoxia and hydrogen production. A broad range of PFD was tested (up to 500 µmol photons m⁻² s⁻¹). Maximum hydrogen productivities were 1.0 ± 0.2 mL H₂/h/L (or 25 ± 5 mL H₂/m² h) and 3.1 mL ± 0.4 H₂/h L (or 77.5 ± 10 mL H₂/m² h), at 110 and 500 µmol photons m⁻² s⁻¹, respectively. These values approached a maximum specific productivity of approximately 1.9 mL ± 0.4 H₂/h/g of biomass dry weight, clearly indicative of a limitation in cell capacity to produce hydrogen. The efficiency of the process and further optimizations are discussed. Biotechnol. Bioeng. 2011;108: 2288–2299. © 2011 Wiley Periodicals, Inc.     

Continuous fixed-bed column study and adsorption modeling: Removal of cadmium (II) and lead (II) ions in aqueous solution by dead calcareous skeletons

The sorption of Cd(II) and Pb(II) ions was conducted in a continuous fixed-bed column by using dead calcareous skeletons (CS). The column performances were evaluated by varying the adsorbent bed height, influent flow rate and metals initial concentration. The breakthrough curve for the bed height indicated that a longer bed column prolonged the life span of the column with a maximum capacity of 26.447 and 38.460 mg/g for the Cd(II) and Pb(II) column, respectively. The increased flow rate and initial concentration caused the column exhaustion time to occur earlier. The experimental column data were also expressed in column adsorption models, namely, the Thomas, Yoon–Nelson and Adam–Bohart models. The Thomas model fitted well with the Cd(II) data with the correlated curve (r² > 0.9). The Yoon–Nelson model was selected to predict the 50% breakthrough time achieved by the column system and provided the estimated breakthrough time for the columns that were not exhausted during the operation. The Adam–Bohart model was applicable for the initial part of adsorption with the saturation concentration data at the equilibrium. The saturation index of aragonite and calcite depicted that dissolution of calcium occurred in the aqueous solution. The experimental and theoretical data were correlated with a significant relationship trend (p < 0.01), which showed that the trend of experimental data fit well with the modeling trend. The trends of both the experimental and theoretical data were strongly and significantly correlated due to involving the column parameters and the components of CS.     

Comparative modeling of the three-dimensional structure of type II antifreeze protein.

Type II antifreeze proteins (AFP), which inhibit the growth of seed ice crystals in the blood of certain fishes (sea raven, herring, and smelt), are the largest known fish AFPs and the only class for which detailed structural information is not yet available. However, a sequence homology has been recognized between these proteins and the carbohydrate recognition domain of C-type lectins. The structure of this domain from rat mannose-binding protein (MBP-A) has been solved by X-ray crystallography (Weis WI, Drickamer K, Hendrickson WA, 1992, Nature 360:127-134) and provided the coordinates for constructing the three-dimensional model of the 129-amino acid Type II AFP from sea raven, to which it shows 19% sequence identity. Multiple sequence alignments between Type II AFPs, pancreatic stone protein, MBP-A, and as many as 50 carbohydrate-recognition domain sequences from various lectins were performed to determine reliably aligned sequence regions. Successive molecular dynamics and energy minimization calculations were used to relax bond lengths and angles and to identify flexible regions. The derived structure contains two alpha-helices, two beta-sheets, and a high proportion of amino acids in loops and turns. The model is in good agreement with preliminary NMR spectroscopic analyses. It explains the observed differences in calcium binding between sea raven Type II AFP and MBP-A. Furthermore, the model proposes the formation of five disulfide bridges between Cys 7 and Cys 18, Cys 35 and Cys 125, Cys 69 and Cys 100, Cys 89 and Cys 111, and Cys 101 and Cys 117.(ABSTRACT TRUNCATED AT 250 WORDS)     

Modeling the influence of cyclodextrins on oral absorption of low solubility drugs: II. Experimental validation

A model was developed for predicting the influence of cyclodextrins (CDs) delivered as a physical mixture with drug on oral absorption. CDs are cyclic oligosaccharides which form inclusion complexes with many drugs and are often used as solubilizing agents. The purpose of this work is to compare the simulation predictions with in vitro as well as in vivo experimental results to test the model's ability to capture the influence of CD on key processes in the gastrointestinal (GI) tract environment. Dissolution and absorption kinetics of low solubility drugs (Naproxen and Nifedipine) were tested in the presence and absence of CD in a simulated gastrointestinal environment. Model predictions were also compared with in vivo experimental results (Glibenclamide and Carbamazepine) from the literature to demonstrate the model's ability to predict oral bioavailability. Comparisons of simulation and experimental results indicate that a model incorporating the influence of CD (delivered as a physical mixture) on dissolution kinetics and binding of neutral drug can predict trends in the influence of CD on bioavailability. Overall, a minimal effect of CD dosed as a physical mixture was observed and predicted. Modeling may aid in enabling rational design of CD containing formulations. Biotechnol. Bioeng. 2010; 105: 421–430. © 2009 Wiley Periodicals, Inc.