Feeding ecology of the Brazilian silverside Atherinella brasiliensis (Atherinopsidae) in a sub-tropical estuarine ecosystem

The feeding ecology of the Brazilian silverside, Atherinella brasiliensis, in a sub-tropical estuary of Brazil was investigated through the gut analysis of 1431 individuals. We described dietary composition and analysed seasonal, estuarine habitat, and body size variations in the diet; trophic level; feeding diversity; and gut fullness indices. Results reveal that A. brasiliensis is a typical, generalistic and opportunistic predator that makes use of a wide array of prey types (at least 89 different types), with zooplankton (mainly calanoids), diatoms, terrestrial insects, and plant detritus making up the bulk of the overall diet. The exotic calanoid Temora turbinata ranked as the primary prey. A wide feeding diversity (mean H` = 2.26), low trophic level (mean TROPH = 2.57), and high gut replenishment were persistent across seasons and habitats. Diet composition varied largely and significantly with respect to habitat, season, and body size. A closer assessment showed that habitat and season had a stronger effect on diet than fish size.

Theoretical models for the antitrypanosomal activity of thiosemicarbazone derivatives

Thiosemicarbazones are cruzain inhibitors which have been identified as potential antitrypanosomal agents. In this work, several molecular properties were calculated at the density functional theory (DFT)/B3LYP/6-311G* level for a set of 44 thiosemicarbazones. Unsupervised and supervised pattern recognition techniques (hierarchical cluster analysis, principal component analysis, kth-nearest neighbors, and soft independent modeling by class analogy) were used to obtain structureactivity relationship models, which are able to classify unknown compounds according to their activities. The chemometric analyses performed here revealed that 12 descriptors can be considered responsible for the discrimination between high and low activity compounds. Classification models were validated with an external test set, showing that predictive classifications were achieved with the selected variable set. The results obtained here are in good agreement with previous findings from the literature, suggesting that our models can be useful on further investigations on the molecular determinants for the antichagasic activity. (C) 2012 Wiley Periodicals, Inc.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Low-Level Laser Therapy Influences Mouse Odontoblast-Like Cell Response in Vitro

Objective: The purpose of this study was to analyze the influence of two different irradiation times with 85mW/cm(2) 830nm laser on the behavior of mouse odontoblast-like cells. Background data: The use of low-level laser therapy (LLLT) to stimulate pulp tissue is a reality, but few reports relate odontoblastic responses to irradiation in in vitro models. Methods: Odontoblast-like cells (MDPC-23) were cultivated and divided into three groups: control/nonirradiated (group 1); or irradiated with 85mW/cm(2), 830nm laser for 10 sec (0.8 J/cm(2)) (group 2); or for 50 sec (4.2 J/cm(2)) (group 3) with a wavelength of 830 nm. After 3, 7, and 10 days, it was analyzed: growth curve and cell viability, total protein content, alkaline phosphatase (ALP) activity, calcified nodules detection and quantification, collagen immunolocalization, vascular endothelial growth factor (VEGF) expression, and real-time polymerase chain reaction (PCR) for DMP1 gene. Data were analyzed by Kruskall-Wallis test (alpha = 0.05). Results: Cell growth was smaller in group 2 (p < 0.01), whereas viability was similar in all groups and at all periods. Total protein content and ALP activity increased on the 10th day with 0.8 J/cm(2) (p < 0.01), as well as the detection and quantification of mineralization nodules (p < 0.05), collagen, and VEGF expression (p < 0.01). The expression of DMP1 increased in all groups (p < 0.05) compared with control at 3 days, except for 0.8 J/cm(2) at 3 days and control at 10 days. Conclusions: LLLT influenced the behavior of odontoblast-like cells; the shorter time/smallest energy density promoted the expression of odontoblastic phenotype in a more significant way.

Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.

High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract Background The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery. Results Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer. Conclusions Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.

The role of asymmetries in rock-paper-scissors biodiversity models.

The maintenance of biodiversity is a long standing puzzle in ecology. It is a classical result that if the interactions of the species in an ecosystem are chosen in a random way, then complex ecosystems can't sustain themselves, meaning that the structure of the interactions between the species must be a central component on the preservation of biodiversity and on the stability of ecosystems. The rock-paper-scissors model is one of the paradigmatic models that study how biodiversity is maintained. In this model 3 species dominate each other in a cyclic way (mimicking a trophic cycle), that is, rock dominates scissors, that dominates paper, that dominates rock. In the original version of this model, this dominance obeys a 'Z IND 3' symmetry, in the sense that the strength of dominance is always the same. In this work, we break this symmetry, studying the effects of the addition of an asymmetry parameter. In the usual model, in a two dimensional lattice, the species distribute themselves according to spiral patterns, that can be explained by the complex Landau-Guinzburg equation. With the addition of asymmetry, new spatial patterns appear during the transient and the system either ends in a state with spirals, similar to the ones of the original model, or in a state where unstable spatial patterns dominate or in a state where only one species survives (and biodiversity is lost).

Mesoscale dynamics and boundary-layer structure in topographically forced low-level jets

Two types of mesoscale wind-speed jet and their effects on boundary-layer structure were studied. The first is a coastal jet off the northern California coast, and the second is a katabatic jet over Vatnajökull, Iceland. Coastal regions are highly populated, and studies of coastal meteorology are of general interest for environmental protection, fishing industry, and for air and sea transportation. Not so many people live in direct contact with glaciers but properties of katabatic flows are important for understanding glacier response to climatic changes. Hence, the two jets can potentially influence a vast number of people. Flow response to terrain forcing, transient behavior in time and space, and adherence to simplified theoretical models were examined. The turbulence structure in these stably stratified boundary layers was also investigated. Numerical modeling is the main tool in this thesis; observations are used primarily to ensure a realistic model behavior. Simple shallow-water theory provides a useful framework for analyzing high-velocity flows along mountainous coastlines, but for an unexpected reason. Waves are trapped in the inversion by the curvature of the wind-speed profile, rather than by an infinite stability in the inversion separating two neutral layers, as assumed in the theory. In the absence of blocking terrain, observations of steady-state supercritical flows are not likely, due to the diurnal variation of flow criticality. In many simplified models, non-local processes are neglected. In the flows studied here, we showed that this is not always a valid approximation. Discrepancies between simulated katabatic flow and that predicted by an analytical model are hypothesized to be due to non-local effects, such as surface inhomogeneity and slope geometry, neglected in the theory. On a different scale, a reason for variations in the shape of local similarity scaling functions between studies is suggested to be differences in non-local contributions to the velocity variance budgets.

Reduced-order modelling, circuit-level design and SOI fabrication of microelectromechanical resonators

This thesis deals with two important research aspects concerning radio frequency (RF) microresonators and switches. First, a new approach for compact modeling and simulation of these devices is presented. Then, a combined process flow for their simultaneous fabrication on a SOI substrate is proposed. Compact models for microresonators and switches are extracted by applying mathematical model order reduction (MOR) to the devices finite element (FE) description in ANSYS c° . The behaviour of these devices includes forms of nonlinearities. However, an approximation in the creation of the FE model is introduced, which enables the use of linear model order reduction. Microresonators are modeled with the introduction of transducer elements, which allow for direct coupling of the electrical and mechanical domain. The coupled system element matrices are linearized around an operating point and reduced. The resulting macromodel is valid for small signal analysis around the bias point, such as harmonic pre-stressed analysis. This is extremely useful for characterizing the frequency response of resonators. Compact modelling of switches preserves the nonlinearity of the device behaviour. Nonlinear reduced order models are obtained by reducing the number of nonlinearities in the system and handling them as input to the system. In this way, the system can be reduced using linear MOR techniques and nonlinearities are introduced directly in the reduced order model. The reduction of the number of system nonlinearities implies the approximation of all distributed forces in the model with lumped forces. Both for microresonators and switches, a procedure for matrices extraction has been developed so that reduced order models include the effects of electrical and mechanical pre-stress. The extraction process is fast and can be done automatically from ANSYS binary files. The method has been applied for the simulation of several devices both at devices and circuit level. Simulation results have been compared with full model simulations, and, when available, experimental data. Reduced order models have proven to conserve the accuracy of finite element method and to give a good description of the overall device behaviour, despite the introduced approximations. In addition, simulation is very fast, both at device and circuit level. A combined process-flow for the integrated fabrication of microresonators and switches has been defined. For this purpose, two processes that are optimized for the independent fabrication of these devices are merged. The major advantage of this process is the possibility to create on-chip circuit blocks that include both microresonators and switches. An application is, for example, aswitched filter bank for wireless transceiver. The process for microresonators fabrication is characterized by the use of silicon on insulator (SOI) wafers and on a deep reactive ion etching (DRIE) step for the creation of the vibrating structures in single-crystal silicon and the use of a sacrificial oxide layer for the definition of resonator to electrode distance. The fabrication of switches is characterized by the use of two different conductive layers for the definition of the actuation electrodes and by the use of a photoresist as a sacrificial layer for the creation of the suspended structure. Both processes have a gold electroplating step, for the creation of the resonators electrodes, transmission lines and suspended structures. The combined process flow is designed such that it conserves the basic properties of the original processes. Neither the performance of the resonators nor the performance of the switches results affected by the simultaneous fabrication. Moreover, common fabrication steps are shared, which allows for cheaper and faster fabrication.

Stem Cells as a therapy for myocardial infarction in animal models

Advances in stem cell biology have challenged the notion that infarcted myocardium is irreparable. The pluripotent ability of stem cells to differentiate into specialized cell lines began to garner intense interest within cardiology when it was shown in animal models that intramyocardial injection of bone marrow stem cells (MSCs), or the mobilization of bone marrow stem cells with spontaneous homing to myocardium, could improve cardiac function and survival after induced myocardial infarction (MI) [1, 2]. Furthermore, the existence of stem cells in myocardium has been identified in animal heart [3, 4], and intense research is under way in an attempt to clarify their potential clinical application for patients with myocardial infarction. To date, in order to identify the best one, different kinds of stem cells have been studied; these have been derived from embryo or adult tissues (i.e. bone marrow, heart, peripheral blood etc.). Currently, three different biologic therapies for cardiovascular diseases are under investigation: cell therapy, gene therapy and the more recent “tissue-engineering” therapy . During my Ph.D. course, first I focalised my study on the isolation and characterization of Cardiac Stem Cells (CSCs) in wild-type and transgenic mice and for this purpose I attended, for more than one year, the Cardiovascular Research Institute of the New York Medical College, in Valhalla (NY, USA) under the direction of Doctor Piero Anversa. During this period I learnt different Immunohistochemical and Biomolecular techniques, useful for investigating the regenerative potential of stem cells. Then, during the next two years, I studied the new approach of cardiac regenerative medicine based on “tissue-engineering” in order to investigate a new strategy to regenerate the infracted myocardium. Tissue-engineering is a promising approach that makes possible the creation of new functional tissue to replace lost or failing tissue. This new discipline combines isolated functioning cells and biodegradable 3-dimensional (3D) polymeric scaffolds. The scaffold temporarily provides the biomechanical support for the cells until they produce their own extracellular matrix. Because tissue-engineering constructs contain living cells, they may have the potential for growth and cellular self-repair and remodeling. In the present study, I examined whether the tissue-engineering strategy within hyaluron-based scaffolds would result in the formation of alternative cardiac tissue that could replace the scar and improve cardiac function after MI in syngeneic heterotopic rat hearts. Rat hearts were explanted, subjected to left coronary descending artery occlusion, and then grafted into the abdomen (aorta-aorta anastomosis) of receiving syngeneic rat. After 2 weeks, a pouch of 3 mm2 was made in the thickness of the ventricular wall at the level of the post-infarction scar. The hyaluronic scaffold, previously engineered for 3 weeks with rat MSCs, was introduced into the pouch and the myocardial edges sutured with few stitches. Two weeks later we evaluated the cardiac function by M-Mode echocardiography and the myocardial morphology by microscope analysis. We chose bone marrow-derived mensenchymal stem cells (MSCs) because they have shown great signaling and regenerative properties when delivered to heart tissue following a myocardial infarction (MI). However, while the object of cell transplantation is to improve ventricular function, cardiac cell transplantation has had limited success because of poor graft viability and low cell retention, that’s why we decided to combine MSCs with a biopolimeric scaffold. At the end of the experiments we observed that the hyaluronan fibres had not been substantially degraded 2 weeks after heart-transplantation. Most MSCs had migrated to the surrounding infarcted area where they were especially found close to small-sized vessels. Scar tissue was moderated in the engrafted region and the thickness of the corresponding ventricular wall was comparable to that of the non-infarcted remote area. Also, the left ventricular shortening fraction, evaluated by M-Mode echocardiography, was found a little bit increased when compared to that measured just before construct transplantation. Therefore, this study suggests that post-infarction myocardial remodelling can be favourably affected by the grafting of MSCs delivered through a hyaluron-based scaffold

Can zooplankton secondary production models predict growth in the marine mysid Leptomysis lingvura (G.O. Sars, 1866)?

[EN]Zooplankton growth and secondary production are key input parameters in marine ecosystem models, but their direct measurement is difficult to make. Accordingly, zooplanktologists have developed several statistical-based secondary production models. Here, three of these secondary production models are tested in the marine mysid Leptomysis lingvura (Mysidacea, Crustacea). Mysid length was measured in two cultures twice a day, which were grown on two different food concentrations. Growth rates ranged from 0.11 to 0.64 day-1, while secondary production rates ranged from 1.77 to 12.23 mg dry- mass day-1. None of the three selected models were good predictors of growth and secondary production in this mysid species.

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.