974 resultados para neural development
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The focus of this work is to develop the knowledge of prediction of the physical and chemical properties of processed linear low density polyethylene (LLDPE)/graphene nanoplatelets composites. Composites made from LLDPE reinforced with 1, 2, 4, 6, 8, and 10 wt% grade C graphene nanoplatelets (C-GNP) were processed in a twin screw extruder with three different screw speeds and feeder speeds (50, 100, and 150 rpm). These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN). The three first properties increased with increase in both screw speed and C-GNP content. The tensile strength reached a maximum value at 4 wt% C-GNP and a speed of 150 rpm as this represented the optimum condition for the stress transfer through the amorphous chains of the matrix to the C-GNP. ANN can be confidently used as a tool to predict the above material properties before investing in development programs and actual manufacturing, thus significantly saving money, time, and effort.
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Thesis (Ph.D.)--University of Washington, 2016-08
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This paper outlines the development of a crosscorrelation algorithm and a spiking neural network (SNN) for sound localisation based on real sound recorded in a noisy and dynamic environment by a mobile robot. The SNN architecture aims to simulate the sound localisation ability of the mammalian auditory pathways by exploiting the binaural cue of interaural time difference (ITD). The medial superior olive was the inspiration for the SNN architecture which required the integration of an encoding layer which produced biologically realistic spike trains, a model of the bushy cells found in the cochlear nucleus and a supervised learning algorithm. The experimental results demonstrate that biologically inspired sound localisation achieved using a SNN can compare favourably to the more classical technique of cross-correlation.
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Pour ce projet, nous avons développé une plateforme pour l’analyse pangénomique de la méthylation de l’ADN chez le bovin qui est compatible avec des échantillons de petites tailles. Cet outil est utilisé pour étudier les caractéristiques génétiques et épigénétiques (méthylation de l’ADN) des gamètes soumis aux procédures de procréation médicalement assisitée et des embryons précoces. Dans un premier temps, une plateforme d’analyse de biopuces spécifiques pour l’étude de la méthylation de l’ADN chez l’espèce bovine a été développée. Cette plateforme a ensuite été optimisée pour produire des analyses pangénomiques de méthylation de l’ADN fiables et reproductibles à partir d’échantillons de très petites tailles telle que les embryons précoces (≥ 10 ng d’ADN a été utilisé, ce qui correspond à 10 blastocystes en expansion). En outre, cet outil a permis d’évaluer de façon simultanée la méthylation de l’ADN et le transcriptome dans le même échantillon, fournissant ainsi une image complète des profils génétiques et épigénétiques (méthylation de l’ADN). Comme preuve de concept, les profils comparatifs de méthylation de l’ADN spermatique et de blastocystes bovins ont été analysés au niveau de l’ensemble du génome. Dans un deuxième temps, grâce à cette plateforme, les profils globaux de méthylation de l’ADN de taureaux jumeaux monozygotes (MZ) ont été analysés. Malgré qu’ils sont génétiquement identiques, les taureaux jumeaux MZ ont des descendants avec des performances différentes. Par conséquent, l’hypothèse que le profil de méthylation de l’ADN spermatique de taureaux jumeaux MZ est différent a été émise. Dans notre étude, des différences significatives entre les jumeaux MZ au niveau des caractéristiques de la semence ainsi que de la méthylation de l’ADN ont été trouvées, chacune pouvant contribuer à l’obtention de performances divergentes incongrues des filles engendrées par ces jumeaux MZ. Dans la troisième partie de ce projet, la même plateforme a été utilisée pour découvrir les impacts d’une supplémentation à forte concentration en donneur de méthyle universel sur les embryons précoces bovins. La supplémentation avec de grandes quantités d’acide folique (AF) a été largement utilisée et recommandée chez les femmes enceintes pour sa capacité bien établie à prévenir les malformations du tube neural chez les enfants. Cependant, plus récemment, plusieurs études ont rapporté des effets indésirables de l’AF utilisé à des concentrations élevées, non seulement sur le développement de l’embryon, mais aussi chez les adultes. Au niveau cellulaire, l’AF entre dans le métabolisme monocarboné, la seule voie de production de S-adénosyl méthionine (SAM), un donneur universel de groupements méthyles pour une grande variété de biomolécules, y compris l’ADN. Par conséquent, pour résoudre cette controverse, une forte dose de SAM a été utilisée pour traiter des embryons produits in vitro chez le bovin. Ceci a non seulement permis d’influencer le phénotype des embryons précoces, mais aussi d’avoir un impact sur le transcriptome et le méthylome de l’ADN. En somme, le projet en cours a permis le développement d’une plateforme d’analyse de la méthylation de l’ADN à l’échelle du génome entier chez le bovin à coût raisonnable et facile à utiliser qui est compatible avec les embryons précoces. De plus, puisque c’est l’une des premières études de ce genre en biologie de la reproduction bovine, ce projet avait trois objectifs qui a donné plusieurs nouveaux résultats, incluant les profils comparatifs de méthylation de l’ADN au niveau : i) blastocystes versus spermatozoïdes ; ii) semence de taureaux jumeaux MZ et iii) embryons précoces traités à de fortes doses de SAM versus des embryons précoces non traités.
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Neural field models of firing rate activity have had a major impact in helping to develop an understanding of the dynamics seen in brain slice preparations. These models typically take the form of integro-differential equations. Their non-local nature has led to the development of a set of analytical and numerical tools for the study of waves, bumps and patterns, based around natural extensions of those used for local differential equation models. In this paper we present a review of such techniques and show how recent advances have opened the way for future studies of neural fields in both one and two dimensions that can incorporate realistic forms of axo-dendritic interactions and the slow intrinsic currents that underlie bursting behaviour in single neurons.
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Children develop in a sea of reciprocal social interaction, but their brain development is predominately studied in non-interactive contexts (e.g., viewing photographs of faces). This dissertation investigated how the developing brain supports social interaction. Specifically, novel paradigms were used to target two facets of social experience—social communication and social motivation—across three studies in children and adults. In Study 1, adults listened to short vignettes—which contained no social information—that they believed to be either prerecorded or presented over an audio-feed by a live social partner. Simply believing that speech was from a live social partner increased activation in the brain’s mentalizing network—a network involved in thinking about others’ thoughts. Study 2 extended this paradigm to middle childhood, a time of increasing social competence and social network complexity, as well as structural and functional social brain development. Results showed that, as in adults, regions of the mentalizing network were engaged by live speech. Taken together, these findings indicate that the mentalizing network may support the processing of interactive communicative cues across development. Given this established importance of social-interactive context, Study 3 examined children’s social motivation when they believed they were engaged in a computer-based chat with a peer. Children initiated interaction via sharing information about their likes and hobbies and received responses from the peer. Compared to a non-social control, in which children chatted with a computer, peer interaction increased activation in mentalizing regions and reward circuitry. Further, within mentalizing regions, responsivity to the peer increased with age. Thus, across all three studies, social cognitive regions associated with mentalizing supported real-time social interaction. In contrast, the specific social context appeared to influence both reward circuitry involvement and age-related changes in neural activity. Future studies should continue to examine how the brain supports interaction across varied real-world social contexts. In addition to illuminating typical development, understanding the neural bases of interaction will offer insight into social disabilities such as autism, where social difficulties are often most acute in interactive situations. Ultimately, to best capture human experience, social neuroscience ought to be embedded in the social world.
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One of the challenges to biomedical engineers proposed by researchers in neuroscience is brain machine interaction. The nervous system communicates by interpreting electrochemical signals, and implantable circuits make decisions in order to interact with the biological environment. It is well known that Parkinson’s disease is related to a deficit of dopamine (DA). Different methods has been employed to control dopamine concentration like magnetic or electrical stimulators or drugs. In this work was automatically controlled the neurotransmitter concentration since this is not currently employed. To do that, four systems were designed and developed: deep brain stimulation (DBS), transmagnetic stimulation (TMS), Infusion Pump Control (IPC) for drug delivery, and fast scan cyclic voltammetry (FSCV) (sensing circuits which detect varying concentrations of neurotransmitters like dopamine caused by these stimulations). Some softwares also were developed for data display and analysis in synchronously with current events in the experiments. This allowed the use of infusion pumps and their flexibility is such that DBS or TMS can be used in single mode and other stimulation techniques and combinations like lights, sounds, etc. The developed system allows to control automatically the concentration of DA. The resolution of the system is around 0.4 µmol/L with time correction of concentration adjustable between 1 and 90 seconds. The system allows controlling DA concentrations between 1 and 10 µmol/L, with an error about +/- 0.8 µmol/L. Although designed to control DA concentration, the system can be used to control, the concentration of other substances. It is proposed to continue the closed loop development with FSCV and DBS (or TMS, or infusion) using parkinsonian animals models.
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Spinal cord injury (SCI) is a devastating condition, which results from trauma to the cord, resulting in a primary injury response which leads to a secondary injury cascade, causing damage to both glial and neuronal cells. Following trauma, the central nervous system (CNS) fails to regenerate due to a plethora of both intrinsic and extrinsic factors. Unfortunately, these events lead to loss of both motor and sensory function and lifelong disability and care for sufferers of SCI. There have been tremendous advancements made in our understanding of the mechanisms behind axonal regeneration and remyelination of the damaged cord. These have provided many promising therapeutic targets. However, very few have made it to clinical application, which could potentially be due to inadequate understanding of compound mechanism of action and reliance on poor SCI models. This thesis describes the use of an established neural cell co-culture model of SCI as a medium throughput screen for compounds with potential therapeutic properties. A number of compounds were screened which resulted in a family of compounds, modified heparins, being taken forward for more intense investigation. Modified heparins (mHeps) are made up of the core heparin disaccharide unit with variable sulphation groups on the iduronic acid and glucosamine residues; 2-O-sulphate (C2), 6-O-sulphate (C6) and N-sulphate (N). 2-O-sulphated (mHep6) and N-sulphated (mHep7) heparin isomers were shown to promote both neurite outgrowth and myelination in the SCI model. It was found that both mHeps decreased oligodendrocyte precursor cell (OPC) proliferation and increased oligodendrocyte (OL) number adjacent to the lesion. However, there is a difference in the direct effects on the OL from each of the mHeps; mHep6 increased myelin internode length and mHep7 increased the overall cell size. It was further elucidated that these isoforms interact with and mediate both Wnt and FGF signalling. In OPC monoculture experiments FGF2 treated OPCs displayed increased proliferation but this effect was removed when co-treated with the mHeps. Therefore, suggesting that the mHeps interact with the ligand and inhibit FGF2 signalling. Additionally, it was shown that both mHeps could be partially mediating their effects through the Wnt pathway. mHep effects on both myelination and neurite outgrowth were removed when co-treated with a Wnt signalling inhibitor, suggesting cell signalling mediation by ligand immobilisation and signalling activation as a mechanistic action for the mHeps. However, the initial methods employed in this thesis were not sufficient to provide a more detailed study into the effects the mHeps have on neurite outgrowth. This led to the design and development of a novel microfluidic device (MFD), which provides a platform to study of axonal injury. This novel device is a three chamber device with two chambers converging onto a central open access chamber. This design allows axons from two points of origin to enter a chamber which can be subjected to injury, thus providing a platform in which targeted axonal injury and the regenerative capacity of a compound study can be performed. In conclusion, this thesis contributes to and advances the study of SCI in two ways; 1) identification and investigation of a novel set of compounds with potential therapeutic potential i.e. desulphated modified heparins. These compounds have multiple therapeutic properties and could revolutionise both the understanding of the basic pathological mechanisms underlying SCI but also be a powered therapeutic option. 2) Development of a novel microfluidic device to study in greater detail axonal biology, specifically, targeted axonal injury and treatment, providing a more representative model of SCI than standard in vitro models. Therefore, the MFD could lead to advancements and the identification of factors and compounds relating to axonal regeneration.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade Gama, Programa de Pós-Graduação em Engenharia Biomédica, 2015.
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Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.
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Vocal differentiation is widely documented in birds and mammals but has been poorly investigated in other vertebrates, including fish, which represent the oldest extant vertebrate group. Neural circuitry controlling vocal behaviour is thought to have evolved from conserved brain areas that originated in fish, making this taxon key to understanding the evolution and development of the vertebrate vocal-auditory systems. This study examines ontogenetic changes in the vocal repertoire and whether vocal differentiation parallels auditory development in the Lusitanian toadfish Halobatrachus didactylus (Batrachoididae). This species exhibits a complex acoustic repertoire and is vocally active during early development. Vocalisations were recorded during social interactions for four size groups (fry: <2 cm; small juveniles: 2-4 cm; large juveniles: 5-7 cm; adults >25 cm, standard length). Auditory sensitivity of juveniles and adults was determined based on evoked potentials recorded from the inner ear saccule in response to pure tones of 75-945 Hz. We show an ontogenetic increment in the vocal repertoire from simple broadband-pulsed 'grunts' that later differentiate into four distinct vocalisations, including low-frequency amplitude-modulated 'boatwhistles'. Whereas fry emitted mostly single grunts, large juveniles exhibited vocalisations similar to the adult vocal repertoire. Saccular sensitivity revealed a three-fold enhancement at most frequencies tested from small to large juveniles; however, large juveniles were similar in sensitivity to adults. We provide the first clear evidence of ontogenetic vocal differentiation in fish, as previously described for higher vertebrates. Our results suggest a parallel development between the vocal motor pathway and the peripheral auditory system for acoustic social communication in fish.
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Early human development offers a unique perspective in investigating the potential cognitive and social implications of action and perception. Specifically, during infancy, action production and action perception undergo foundational developments. One essential component to examine developments in action processing is the analysis of others’ actions as meaningful and goal-directed. Little research, however, has examined the underlying neural systems that may be associated with emerging action and perception abilities, and infants’ learning of goal-directed actions. The current study examines the mu rhythm—a brain oscillation found in the electroencephalogram (EEG)—that has been associated with action and perception. Specifically, the present work investigates whether the mu signal is related to 9-month-olds’ learning of a novel goal-directed means-end task. The findings of this study demonstrate a relation between variations in mu rhythm activity and infants’ ability to learn a novel goal-directed means-end action task (compared to a visual pattern learning task used as a comparison task). Additionally, we examined the relations between standardized assessments of early motor competence, infants’ ability to learn a novel goal-directed task, and mu rhythm activity. We found that: 1a) mu rhythm activity during observation of a grasp uniquely predicted infants’ learning on the cane training task, 1b) mu rhythm activity during observation and execution of a grasp did not uniquely predict infants’ learning on the visual pattern learning task (comparison learning task), 2) infants’ motor competence did not predict infants’ learning on the cane training task, 3) mu rhythm activity during observation and execution was not related to infants’ measure of motor competence, and 4) mu rhythm activity did not predict infants’ learning on the cane task above and beyond infants’ motor competence. The results from this study demonstrate that mu rhythm activity is a sensitive measure to detect individual differences in infants’ action and perception abilities, specifically their learning of a novel goal-directed action.
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We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models we build to spatially extended cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale.