Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Changes in plant metabolism induced by dioxygenase inhibitors and their effect on the epiphytic microbial community and fire blight (Erwinia amylovora) control

Fire blight, caused by the gram negative bacterium Erwinia amylovora, is one of the most destructive bacterial diseases of Pomaceous plants. Therefore, the development of reliable methods to control this disease is desperately needed. This research investigated the possibility to interfere, by altering plant metabolism, on the interactions occurring between Erwinia amylovora, the host plant and the epiphytic microbial community in order to obtain a more effective control of fire blight. Prohexadione-calcium and trinexapac-ethyl, two dioxygenase inhibitors, were chosen as a chemical tool to influence plant metabolism. These compounds inhibit the 2-oxoglutarate-dependent dioxygenases and, therefore, they greatly influence plant metabolism. Moreover, dioxygenase inhibitors were found to enhance plant resistance to a wide range of pathogens. In particular, dioxygenase inhibitors application seems a promising method to control fire blight. From cited literature, it is assumed that these compounds increase plant defence mainly by a transient alteration of flavonoids metabolism. We tried to demonstrate, that the reduction of susceptibility to disease could be partially due to an indirect influence on the microbial community established on plant surface. The possibility to influence the interactions occurring in the epiphytic microbial community is particularly interesting, in fact, the relationships among different bacterial populations on plant surface is a key factor for a more effective biological control of plant diseases. Furthermore, we evaluated the possibility to combine the application of dioxygenase inhibitors with biological control in order to develop an integrate strategy for control of fire blight. The first step for this study was the isolation of a pathogenic strain of E. amylovora. In addition, we isolated different epiphytic bacteria, which respond to general requirements for biological control agents. Successively, the effect of dioxygenase inhibitors treatment on microbial community was investigated on different plant organs (stigmas, nectaries and leaves). An increase in epiphytic microbial population was found. Further experiments were performed with aim to explain this effect. In particular, changes in sugar content of nectar were observed. These changes, decreasing the osmotic potential of nectar, might allow a more consistent growth of epiphytic bacteria on blossoms. On leaves were found similar differences as well. As far as the interactions between E. amylovora and host plant, they were deeply investigated by advanced microscopical analysis. The influence of dioxygenase inhibitors and SAR inducers application on the infection process and migration of pathogen inside different plant tissues was studied. These microscopical techniques, combined with the use of gpf-labelled E. amylovora, allowed the development of a bioassay method for resistance inducers efficacy screening. The final part of the work demonstrated that the reduction of disease susceptibility observed in plants treated with prohexadione-calcium is mainly due to the accumulation of a novel phytoalexins: luteoforol. This 3-deoxyflavonoid was proven to have a strong antimicrobial activity.

Control of Steroid 21-oic Acid Synthesis by Peroxisome Proliferator-activated Receptor and Role of the Hypothalamic-Pituitary-Adrenal Axis

A previous study identified the peroxisome proliferator-activated receptor alpha (PPARalpha) activation biomarkers 21-steroid carboxylic acids 11beta-hydroxy-3,20-dioxopregn-4-en-21-oic acid (HDOPA) and 11beta,20-dihydroxy-3-oxo-pregn-4-en-21-oic acid (DHOPA). In the present study, the molecular mechanism and the metabolic pathway of their production were determined. The PPARalpha-specific time-dependent increases in HDOPA and 20alpha-DHOPA paralleled the development of adrenal cortex hyperplasia, hypercortisolism, and spleen atrophy, which was attenuated in adrenalectomized mice. Wy-14,643 activation of PPARalpha induced hepatic FGF21, which caused increased neuropeptide Y and agouti-related protein mRNAs in the hypothalamus, stimulation of the agouti-related protein/neuropeptide Y neurons, and activation of the hypothalamic-pituitary-adrenal (HPA) axis, resulting in increased adrenal cortex hyperplasia and corticosterone production, revealing a link between PPARalpha and the HPA axis in controlling energy homeostasis and immune regulation. Corticosterone was demonstrated as the precursor of 21-carboxylic acids both in vivo and in vitro. Under PPARalpha activation, the classic reductive metabolic pathway of corticosterone was suppressed, whereas an alternative oxidative pathway was uncovered that leads to the sequential oxidation on carbon 21 resulting in HDOPA. The latter was then reduced to the end product 20alpha-DHOPA. Hepatic cytochromes P450, aldehyde dehydrogenase (ALDH3A2), and 21-hydroxysteroid dehydrogenase (AKR1C18) were found to be involved in this pathway. Activation of PPARalpha resulted in the induction of Aldh3a2 and Akr1c18, both of which were confirmed as target genes through introduction of promoter luciferase reporter constructs into mouse livers in vivo. This study underscores the power of mass spectrometry-based metabolomics combined with genomic and physiologic analyses in identifying downstream metabolic biomarkers and the corresponding upstream molecular mechanisms.

Lipopolysaccharide induces intestinal glucocorticoid synthesis in a TNFalpha-dependent manner

Stringent control of immune responses in the intestinal mucosa is critical for the maintenance of immune homeostasis and prevention of tissue damage, such as observed during inflammatory bowel disease. Intestinal epithelial cells, primarily thought to form a simple physical barrier, critically regulate intestinal immune cell functions by producing immunoregulatory glucocorticoids on T-cell activation. In this study we investigated whether stimulation of cells of the innate immune system results in the induction of intestinal glucocorticoids synthesis and what role TNF-alpha plays in this process. Stimulation of the innate immune system with lipopolysaccharide (LPS) led to an up-regulation of colonic steroidogenic enzymes and the induction of intestinal glucocorticoid synthesis. The observed induction was dependent on macrophage effector functions, as depletion of macrophages using clodronate-containing liposomes, but not absence of T and B cells, inhibited intestinal glucocorticoid synthesis. LPS-induced glucocorticoid synthesis was critically dependent on TNF-alpha as it was significantly decreased in TNF-alpha-deficient animals. Both TNF receptor-1 and -2 were found to be equally involved in LPS- and T-cell-induced intestinal GC synthesis. These results describe a novel and critical role of TNF-alpha in immune cell-induced intestinal glucocorticoid synthesis.

Neuronal polarity selection by topography-induced focal adhesion control

Interaction between differentiating neurons and the extracellular environment guides the establishment of cell polarity during nervous system development. Developing neurons read the physical properties of the local substrate in a contact-dependent manner and retrieve essential guidance cues. In previous works we demonstrated that PC12 cell interaction with nanogratings (alternating lines of ridges and grooves of submicron size) promotes bipolarity and alignment to the substrate topography. Here, we investigate the role of focal adhesions, cell contractility, and actin dynamics in this process. Exploiting nanoimprint lithography techniques and a cyclic olefin copolymer, we engineered biocompatible nanostructured substrates designed for high-resolution live-cell microscopy. Our results reveal that neuronal polarization and contact guidance are based on a geometrical constraint of focal adhesions resulting in an angular modulation of their maturation and persistence. We report on ROCK1/2-myosin-II pathway activity and demonstrate that ROCK-mediated contractility contributes to polarity selection during neuronal differentiation. Importantly, the selection process confined the generation of actin-supported membrane protrusions and the initiation of new neurites at the poles. Maintenance of the established polarity was independent from NGF stimulation. Altogether our results imply that focal adhesions and cell contractility stably link the topographical configuration of the extracellular environment to a corresponding neuronal polarity state.

Innate-like control of human iNKT cell autoreactivity via the hypervariable CDR3beta loop

Invariant Natural Killer T cells (iNKT) are a versatile lymphocyte subset with important roles in both host defense and immunological tolerance. They express a highly conserved TCR which mediates recognition of the non-polymorphic, lipid-binding molecule CD1d. The structure of human iNKT TCRs is unique in that only one of the six complementarity determining region (CDR) loops, CDR3beta, is hypervariable. The role of this loop for iNKT biology has been controversial, and it is unresolved whether it contributes to iNKT TCR:CD1d binding or antigen selectivity. On the one hand, the CDR3beta loop is dispensable for iNKT TCR binding to CD1d molecules presenting the xenobiotic alpha-galactosylceramide ligand KRN7000, which elicits a strong functional response from mouse and human iNKT cells. However, a role for CDR3beta in the recognition of CD1d molecules presenting less potent ligands, such as self-lipids, is suggested by the clonal distribution of iNKT autoreactivity. We demonstrate that the human iNKT repertoire comprises subsets of greatly differing TCR affinity to CD1d, and that these differences relate to their autoreactive functions. These functionally different iNKT subsets segregate in their ability to bind CD1d-tetramers loaded with the partial agonist alpha-linked glycolipid antigen OCH and structurally different endogenous beta-glycosylceramides. Using surface plasmon resonance with recombinant iNKT TCRs and different ligand-CD1d complexes, we demonstrate that the CDR3beta sequence strongly impacts on the iNKT TCR affinity to CD1d, independent of the loaded CD1d ligand. Collectively our data reveal a crucial role for CDR3beta for the function of human iNKT cells by tuning the overall affinity of the iNKT TCR to CD1d. This mechanism is relatively independent of the bound CD1d ligand and thus forms the basis of an inherent, CDR3beta dependent functional hierarchy of human iNKT cells.

Self-sufficient control of urate homeostasis in mice by a synthetic circuit

Synthetic biology has shown that the metabolic behavior of mammalian cells can be altered by genetic devices such as epigenetic and hysteretic switches, timers and oscillators, biocomputers, hormone systems and heterologous metabolic shunts. To explore the potential of such devices for therapeutic strategies, we designed a synthetic mammalian circuit to maintain uric acid homeostasis in the bloodstream, disturbance of which is associated with tumor lysis syndrome and gout. This synthetic device consists of a modified Deinococcus radiodurans-derived protein that senses uric acids levels and triggers dose-dependent derepression of a secretion-engineered Aspergillus flavus urate oxidase that eliminates uric acid. In urate oxidase-deficient mice, which develop acute hyperuricemia, the synthetic circuit decreased blood urate concentration to stable sub-pathologic levels in a dose-dependent manner and reduced uric acid crystal deposits in the kidney. Synthetic gene-network devices providing self-sufficient control of pathologic metabolites represent molecular prostheses, which may foster advances in future gene- and cell-based therapies.

Plasma membrane repair and cellular damage control: the annexin survival kit

Plasmalemmal injury is a frequent event in the life of a cell. Physical disruption of the plasma membrane is common in cells that operate under conditions of mechanical stress. The permeability barrier can also be breached by chemical means: pathogens gain access to host cells by secreting pore-forming toxins and phospholipases, and the host's own immune system employs pore-forming proteins to eliminate both pathogens and the pathogen-invaded cells. In all cases, the influx of extracellular Ca(2+) is being sensed and interpreted as an "immediate danger" signal. Various Ca(2+)-dependent mechanisms are employed to enable plasma membrane repair. Extensively damaged regions of the plasma membrane can be patched with internal membranes delivered to the cell surface by exocytosis. Nucleated cells are capable of resealing their injured plasmalemma by endocytosis of the permeabilized site. Likewise, the shedding of membrane microparticles is thought to be involved in the physical elimination of pores. Membrane blebbing is a further damage-control mechanism, which is triggered after initial attempts at plasmalemmal resealing have failed. The members of the annexin protein family are ubiquitously expressed and function as intracellular Ca(2+) sensors. Most cells contain multiple annexins, which interact with distinct plasma membrane regions promoting membrane segregation, membrane fusion and--in combination with their individual Ca(2+)-sensitivity--allow spatially confined, graded responses to membrane injury.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Stress and Strain Adaptation in Load-Dependent Remodeling of the Embryonic Left Ventricle

Altered pressure in the developing left ventricle (LV) results in altered morphology and tissue material properties. Mechanical stress and strain may play a role in the regulating process. This study showed that confocal microscopy, three-dimensional reconstruction, and finite element analysis can provide a detailed model of stress and strain in the trabeculated embryonic heart. The method was used to test the hypothesis that end-diastolic strains are normalized after altered loading of the LV during the stages of trabecular compaction and chamber formation. Stage-29 chick LVs subjected to pressure overload and underload at stage 21 were reconstructed with full trabecular morphology from confocal images and analyzed with finite element techniques. Measured material properties and intraventricular pressures were specified in the models. The results show volume-weighted end-diastolic von Mises stress and strain averaging 50–82% higher in the trabecular tissue than in the compact wall. The volume-weighted-average stresses for the entire LV were 115, 64, and 147Pa in control, underloaded, and overloaded models, while strains were 11, 7, and 4%; thus, neither was normalized in a volume-weighted sense. Localized epicardial strains at mid-longitudinal level were similar among the three groups and to strains measured from high-resolution ultrasound images. Sensitivity analysis showed changes in material properties are more significant than changes in geometry in the overloaded strain adaptation, although resulting stress was similar in both types of adaptation. These results emphasize the importance of appropriate metrics and the role of trabecular tissue in evaluating the evolution of stress and strain in relation to pressure-induced adaptation.

Detecting and resolving position-dependent temperature effects in real-time quantitative polymerase chain reaction

Real-time quantitative polymerase chain reaction (qPCR) depends on precise temperature control of the sample during cycling. In the current study, we investigated how temperature variation in plate-based qPCR instruments influences qPCR results. Temperature variation was measured by amplicon melting analysis as a convenient means to assess well-to-well differences. Multiple technical replicates of several SYBR Green I-based qPCR assays allowed correlation of relative well temperature to quantification cycle. We found that inadequate template denaturation results in an inverse correlation and requires increasing the denaturation temperature, adding a DNA destabilizing agent, or pretreating with a restriction enzyme. In contrast, inadequate primer annealing results in a direct correlation and requires lowering the annealing temperature. Significant correlations were found in 18 of 25 assays. The critical nature of temperature-dependent effects was shown in a blinded study of 29 patients for the diagnosis of Prader-Willy and Angelman syndromes, where eight diagnoses were incorrect unless temperature-dependent effects were controlled. A method to detect temperature-dependent effects by pairwise comparisons of replicates in routine experiments is presented and applied. Systematic temperature errors in qPCR instruments can be recognized and their effects eliminated when high precision is required in quantitative genetic diagnostics and critical complementary DNA analyses.

Spine Ca2+ signaling in spike-timing-dependent plasticity

Calcium is a second messenger, which can trigger the modification of synaptic efficacy. We investigated the question of whether a differential rise in postsynaptic Ca2+ ([Ca2+]i) alone is sufficient to account for the induction of long-term potentiation (LTP) and long-term depression (LTD) of EPSPs in the basal dendrites of layer 2/3 pyramidal neurons of the somatosensory cortex. Volume-averaged [Ca2+]i transients were measured in spines of the basal dendritic arbor for spike-timing-dependent plasticity induction protocols. The rise in [Ca2+]i was uncorrelated to the direction of the change in synaptic efficacy, because several pairing protocols evoked similar spine [Ca2+]i transients but resulted in either LTP or LTD. The sequence dependence of near-coincident presynaptic and postsynaptic activity on the direction of changes in synaptic strength suggested that LTP and LTD were induced by two processes, which were controlled separately by postsynaptic [Ca2+]i levels. Activation of voltage-dependent Ca2+ channels before metabotropic glutamate receptors (mGluRs) resulted in the phospholipase C-dependent (PLC-dependent) synthesis of endocannabinoids, which acted as a retrograde messenger to induce LTD. LTP required a large [Ca2+]i transient evoked by NMDA receptor activation. Blocking mGluRs abolished the induction of LTD and uncovered the Ca2+-dependent induction of LTP. We conclude that the volume-averaged peak elevation of [Ca2+]i in spines of layer 2/3 pyramids determines the magnitude of long-term changes in synaptic efficacy. The direction of the change is controlled, however, via a mGluR-coupled signaling cascade. mGluRs act in conjunction with PLC as sequence-sensitive coincidence detectors when postsynaptic precede presynaptic action potentials to induce LTD. Thus presumably two different Ca2+ sensors in spines control the induction of spike-timing-dependent synaptic plasticity.

Dissociated lateralization of transient and sustained blood oxygen level-dependent signal components in human primary auditory cortex

Among other auditory operations, the analysis of different sound levels received at both ears is fundamental for the localization of a sound source. These so-called interaural level differences, in animals, are coded by excitatory-inhibitory neurons yielding asymmetric hemispheric activity patterns with acoustic stimuli having maximal interaural level differences. In human auditory cortex, the temporal blood oxygen level-dependent (BOLD) response to auditory inputs, as measured by functional magnetic resonance imaging (fMRI), consists of at least two independent components: an initial transient and a subsequent sustained signal, which, on a different time scale, are consistent with electrophysiological human and animal response patterns. However, their specific functional role remains unclear. Animal studies suggest these temporal components being based on different neural networks and having specific roles in representing the external acoustic environment. Here we hypothesized that the transient and sustained response constituents are differentially involved in coding interaural level differences and therefore play different roles in spatial information processing. Healthy subjects underwent monaural and binaural acoustic stimulation and BOLD responses were measured using high signal-to-noise-ratio fMRI. In the anatomically segmented Heschl's gyrus the transient response was bilaterally balanced, independent of the side of stimulation, while in opposite the sustained response was contralateralized. This dissociation suggests a differential role at these two independent temporal response components, with an initial bilateral transient signal subserving rapid sound detection and a subsequent lateralized sustained signal subserving detailed sound characterization.

Increased sensitivity in mapping task demand in visuospatial processing using reaction-time-dependent hemodynamic response predictors in rapid event-related fMRI

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.