Discrepancy between antennal and behavioral responses for enantiomers of a-Pinene : electrophysiology and behavior of helicoverpa armigera (Lepidoptera)

The ability of adult cotton bollworm, Helicoverpa armigera (Hübner), to distinguish and respond to enantiomers of α-pinene was investigated with electrophysiological and behavioral methods. Electroantennogram recordings using mixtures of the enantiomers at saturating dose levels, and single unit electrophysiology, indicated that the two forms were detected by the same receptor neurons. The relative size of the electroantennogram response was higher for the (−) compared to the (+) form, indicating greater affinity for the (−) form at the level of the dendrites. Behavioral assays investigated the ability of moths to discriminate between, and respond to the (+) and (−) forms of α-pinene. Moths with no odor conditioning showed an innate preference for (+)-α-pinene. This preference displayed by naïve moths was not significantly different from the preferences of moths conditioned on (+)-α-pinene. However, we found a significant difference in preference between moths conditioned on the (−) enantiomer compared to naïve moths and moths conditioned on (+)-α-pinene, showing that learning plays an important role in the behavioral response. Moths are less able to distinguish between enantiomers of α-pinene than different odors (e.g., phenylacetaldehyde versus (−)-α-pinene) in learning experiments. The relevance of receptor discrimination of enantiomers and learning ability of the moths in host plant choice is discussed.

Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology

Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

Discrepancy Between Antennal and Behavioral Responses for Enantiomers of a-Pinene: Electrophysiology and Behavior of Helicoverpa Armigera (Lepidoptera)

The ability of adult cotton bollworm, Helicoverpa armigera (Hubner), to distinguish and respond to enantiomers of α-pinene was investigated with electrophysiological and behavioral methods. Electroantennogram recordings using mixtures of the enantiomers at saturating dose levels, and single unit electrophysiology, indicated that the two forms were detected by the same receptor neurons. The relative size of the electroantennogram response was higher for the (−) compared to the (+) form, indicating greater affinity for the (−) form at the level of the dendrites. Behavioral assays investigated the ability of moths to discriminate between, and respond to the (+) and (−) forms of α pinene. Moths with no odor conditioning showed an innate preference for (+)-α-pinene. This preference displayed by naıve moths was not significantly different from the preferences of moths conditioned on (+)-α-pinene. However, we found a significant difference in preference between moths conditioned on the (−) enantiomer compared to naıve moths and moths conditioned on (+)-α-pinene, showing that learning plays an important role in the behavioral response. Moths are less able to distinguish between enantiomers of α-pinene than different odors (e.g., phenylacetaldehyde versus (−)-α-pinene) in learning experiments. The relevance of receptor discrimination of enantiomers and learning ability of the moths in host plant choice is discussed.

Sampling Methods for Exploring Between Subject Variability in Cardiac Electrophysiology Experiments

Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.

On the order of the fractional Laplacian in determining the spatio-temporal evolution of a space-fractional model of cardiac electrophysiology

Space-fractional operators have been used with success in a variety of practical applications to describe transport processes in media characterised by spatial connectivity properties and high structural heterogeneity altering the classical laws of diffusion. This study provides a systematic investigation of the spatio-temporal effects of a space-fractional model in cardiac electrophysiology. We consider a simplified model of electrical pulse propagation through cardiac tissue, namely the monodomain formulation of the Beeler-Reuter cell model on insulated tissue fibres, and obtain a space-fractional modification of the model by using the spectral definition of the one-dimensional continuous fractional Laplacian. The spectral decomposition of the fractional operator allows us to develop an efficient numerical method for the space-fractional problem. Particular attention is paid to the role played by the fractional operator in determining the solution behaviour and to the identification of crucial differences between the non-fractional and the fractional cases. We find a positive linear dependence of the depolarization peak height and a power law decay of notch and dome peak amplitudes for decreasing orders of the fractional operator. Furthermore, we establish a quadratic relationship in conduction velocity, and quantify the increasingly wider action potential foot and more pronounced dispersion of action potential duration, as the fractional order is decreased. A discussion of the physiological interpretation of the presented findings is made.

Dissecting neural circuits for vision in nonhuman primates using fMRI-guided electrophysiology and optogenetics

The visual system is a remarkable platform that evolved to solve difficult computational problems such as detection, recognition, and classification of objects. Of great interest is the face-processing network, a sub-system buried deep in the temporal lobe, dedicated for analyzing specific type of objects (faces). In this thesis, I focus on the problem of face detection by the face-processing network. Insights obtained from years of developing computer-vision algorithms to solve this task have suggested that it may be efficiently and effectively solved by detection and integration of local contrast features. Does the brain use a similar strategy? To answer this question, I embark on a journey that takes me through the development and optimization of dedicated tools for targeting and perturbing deep brain structures. Data collected using MR-guided electrophysiology in early face-processing regions was found to have strong selectivity for contrast features, similar to ones used by artificial systems. While individual cells were tuned for only a small subset of features, the population as a whole encoded the full spectrum of features that are predictive to the presence of a face in an image. Together with additional evidence, my results suggest a possible computational mechanism for face detection in early face processing regions. To move from correlation to causation, I focus on adopting an emergent technology for perturbing brain activity using light: optogenetics. While this technique has the potential to overcome problems associated with the de-facto way of brain stimulation (electrical microstimulation), many open questions remain about its applicability and effectiveness for perturbing the non-human primate (NHP) brain. In a set of experiments, I use viral vectors to deliver genetically encoded optogenetic constructs to the frontal eye field and faceselective regions in NHP and examine their effects side-by-side with electrical microstimulation to assess their effectiveness in perturbing neural activity as well as behavior. Results suggest that cells are robustly and strongly modulated upon light delivery and that such perturbation can modulate and even initiate motor behavior, thus, paving the way for future explorations that may apply these tools to study connectivity and information flow in the face processing network.

Electrophysiology of Oculomotor Delayed Response Tasks: A Model for the Maturation of Visual-Spatial Working Memory Networks

In the literature, persistent neural activity over frontal and parietal areas during the delay period of oculomotor delayed response (ODR) tasks has been interpreted as an active representation of task relevant information and response preparation. Following a recent ERP study (Tekok-Kilic, Tays, & Tkach, 2011 ) that reported task related slow wave differences over frontal and parietal sites during the delay periods of three ODR tasks, the present investigation explored developmental differences in young adults and adolescents during the same ODR tasks using 128-channel dense electrode array methodology and source localization. This exploratory study showed that neural functioning underlying visual-spatial WM differed between age groups in the Match condition. More specifically, this difference is localized anteriorly during the late delay period. Given the protracted maturation of the frontal lobes, the observed variation at the frontal site may indicate that adolescents and young adults may recruit frontal-parietal resources differently.

Relation between neuronal morphology and electrophysiology in the Kainate lesion model of Alzheimer's Disease

This paper describes a computational and statistical study of the influence of morphological changes on the electrophysiological response of neurons from an animal model of Alzheimer's Disease (AD). We combined experimental morphological data from rat hippocampal CA1 pyramidal cells with a well-established model of active membrane properties. Dendritic morphology and the somatic response to simulated current clamp conditions were then compared for cells from the control and the AD group. The computational approach allowed us to single out the influences of neuromorphology on neuronal response by eliminating the effects of active channel variability. The results did not reveal a simple relationship between morphological changes associated with AD and changes in neural response. However, they did suggest the existence of more complex than anticipated relationships between dendritic morphology and single-cell electrophysiology.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.

Mercury toxicity in Amazon gold miners: Visual dysfunction assessed by retinal and cortical electrophysiology

Amazonian gold mining activity results in human exposure to mercury vapor. We evaluated the visual system of two Amazonian gold miners (29 and 37 years old) by recording the transient pattern electroretinogram (tPERG) and transient pattern visual evoked potential (tPVEP). We compared these results with those obtained from a regional group of control subjects. For both tPERG and tPVEP, checkerboards with 0.5 or 2 cycles per degree (cpd) of spatial frequency were presented in a 16 degrees squared area, 100% Michelson contrast, 50cd/m(2) mean luminance, and 1 Hz square-wave pattern-reversal presentation. Two averaged waveforms (n = 240 sweeps, Is each) were monocularly obtained for each subject in each condition. Both eyes were monocularly tested only in gold miners. Normative data were calculated using a final pooled waveforin with 480 sweeps. The first gold miner, LCS, had normal tPERG responses. The second one, RNP, showed low tPERG (P50 component) amplitudes at 0.5cpd for both eyes, outside the normative data, and absence of response at 2 cpd for his right eye. Delayed tPVEP responses (P 100 component) were found at 2 cpd for LCS but the implicit times were inside the normative data. Subject RNP also showed delayed tPVEP responses (all components), but only the implicit time obtained with his right eye was outside the normative data at 2cpd. We conclude that mercury exposure levels found in the Amazon gold miners is high enough to damage the visual system and can be assessed by non-invasive electrophysiological techniques. (C) 2007 Elsevier Inc. All rights reserved.

Neural coding tools, based on Information Theory, applied to discrete time series: from electrophysiology to neuroethology

This work is supported by Brazilian agencies Fapesp, CAPES and CNPq

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Computational Modelling of Cardiac Electrophysiology: from Cell to Bedside

Heart diseases are the leading cause of death worldwide, both for men and women. However, the ionic mechanisms underlying many cardiac arrhythmias and genetic disorders are not completely understood, thus leading to a limited efficacy of the current available therapies and leaving many open questions for cardiac electrophysiologists. On the other hand, experimental data availability is still a great issue in this field: most of the experiments are performed in vitro and/or using animal models (e.g. rabbit, dog and mouse), even when the final aim is to better understand the electrical behaviour of in vivo human heart either in physiological or pathological conditions. Computational modelling constitutes a primary tool in cardiac electrophysiology: in silico simulations, based on the available experimental data, may help to understand the electrical properties of the heart and the ionic mechanisms underlying a specific phenomenon. Once validated, mathematical models can be used for making predictions and testing hypotheses, thus suggesting potential therapeutic targets. This PhD thesis aims to apply computational cardiac modelling of human single cell action potential (AP) to three clinical scenarios, in order to gain new insights into the ionic mechanisms involved in the electrophysiological changes observed in vitro and/or in vivo. The first context is blood electrolyte variations, which may occur in patients due to different pathologies and/or therapies. In particular, we focused on extracellular Ca2+ and its effect on the AP duration (APD). The second context is haemodialysis (HD) therapy: in addition to blood electrolyte variations, patients undergo a lot of other different changes during HD, e.g. heart rate, cell volume, pH, and sympatho-vagal balance. The third context is human hypertrophic cardiomyopathy (HCM), a genetic disorder characterised by an increased arrhythmic risk, and still lacking a specific pharmacological treatment.