Mejora de la segmentación de espinas en imágenes de microscopía confocal

La reconstrucción y caracterización de las espinas dendríticas es hoy en día un área de trabajo de gran interés en la investigación neurobiológica. Las dendritas son prolongaciones en forma de ramas de la neurona. Las espinas dendríticas se encuentran a lo largo de las dendritas y son las encargadas de transmitir los impulsos electroquímicos al cuerpo de la neurona. El objetivo de este trabajo es desarrollar un algoritmo con el objetivo de mejorar las reconstrucciones 3D de las espinas dendríticas. Se ha utilizado un algoritmo de segmentación basado en los contornos activos morfológicos para analizar las imágenes de partida y conseguir nuevas reconstrucciones 3D fieles a estas imágenes. En este documento presentamos todo el desarrollo necesario para llevar a cabo los objetivos del proyecto. Por último también se presentarán los resultados obtenidos con este método comparándolo con las reconstrucciones de partida. ABSTRACT The reconstruction and characterization of dendritic spines is a hot topic in modern neurobiology research. Dendrites are the branched ramifications of a neuron. Dendritic spines are found along the dendrites and are responsible for transmitting electrochemical signals to the neuron’s main body. The purpose of this work is to develop an algorithm to improve the 3D reconstruction of dendritic spines. We use a segmentation algorithm based on morphological active contours to analyze the images and get new faithful 3D reconstructions of these images. In this document we present all the development necessary to accomplish the project goals. Finally, we will compare present results obtained by this method with the starting reconstructions.

Clustering basado en redes bayesianas con predictoras continuas: aplicaciones en neurociencia

Desentrañar el funcionamiento del cerebro es uno de los principales desafíos a los que se enfrenta la ciencia actual. Un área de estudio que ha despertado muchas expectativas e interés es el análisis de la estructura cortical desde el punto de vista morfológico, de manera que se cree una simulación del cerebro a nivel molecular. Con ello se espera poder profundizar en el estudio de numerosas enfermedades neurológicas y patológicas. Con el desarrollo de este proyecto se persigue el estudio del soma y de las espinas desde el punto de vista de la neuromorfología teórica. Es común en el estado del arte que en el análisis de las características morfológicas de una neurona en tres dimensiones el soma sea ignorado o, en el mejor de los casos, que sea sustituido por una simple esfera. De hecho, el concepto de soma resulta abstracto porque no se dispone de una dfinición estricta y robusta que especifique exactamente donde finaliza y comienzan las dendritas. En este proyecto se alcanza por primera vez una definición matemática de soma para determinar qué es el soma. Con el fin de simular somas se ahonda en los atributos utilizados en el estado del arte. Estas propiedades, de índole genérica, no especifican una morfología única. Es por ello que se propone un método que agrupe propiedades locales y globales de la morfología. En disposición de las características se procede con la categorización del cuerpo celular en distintas clases a partir de un nuevo subtipo de red bayesiana dinámica adaptada al espacio. Con ello se discute la existencia de distintas clases de somas y se descubren las diferencias entre los somas piramidales de distintas capas del cerebro. A partir del modelo matemático se simulan por primera vez somas virtuales. Algunas morfologías de espinas han sido atribuidas a ciertos comportamientos cognitivos. Por ello resulta de interés dictaminar las clases existentes y relacionarlas con funciones de la actividad cerebral. La clasificación más extendida (Peters y Kaiserman-Abramof, 1970) presenta una definición ambigua y subjetiva dependiente de la interpretación de cada individuo y por tanto discutible. Este estudio se sustenta en un conjunto de descriptores extraídos mediante una técnica de análisis topológico local para representaciones 3D. Sobre estos datos se trata de alcanzar el conjunto de clases más adecuado en el que agrupar las espinas así como de describir cada grupo mediante reglas unívocas. A partir de los resultados, se discute la existencia de un continuo de espinas y las propiedades que caracterizan a cada subtipo de espina. ---ABSTRACT---Unravel how the brain works is one of the main challenges faced by current science. A field of study which has aroused great expectations and interest is the analysis of the cortical structure from a morphological point of view, so that a molecular level simulation of the brain is achieved. This is expected to deepen the study of many neurological and pathological diseases. This project seeks the study of the soma and spines from the theoretical neuromorphology point of view. In the state of the art it is common that when it comes to analyze the morphological characteristics of a three dimension neuron the soma is ignored or, in the best case, it is replaced by a simple sphere. In fact, the concept of soma is abstract because there is not a robust and strict definition on exactly where it ends and dendrites begin. In this project a mathematical definition is reached for the first time to determine what a soma is. With the aim to simulate somas the atributes applied in the state of the art are studied. These properties, generic in nature, do not specify a unique morphology. It is why it was proposed a method to group local and global morphology properties. In arrangement of the characteristics it was proceed with the categorization of the celular body into diferent classes by using a new subtype of dynamic Bayesian network adapted to space. From the result the existance of different classes of somas and diferences among pyramidal somas from distinct brain layers are discovered. From the mathematical model virtual somas were simulated for the first time. Some morphologies of spines have been attributed to certain cognitive behaviours. For this reason it is interesting to rule the existent classes and to relate them with their functions in the brain activity. The most extended classification (Peters y Kaiserman-Abramof, 1970) presents an ambiguous and subjective definition that relies on the interpretation of each individual and consequently it is arguable. This study was based on the set of descriptors extracted from a local topological analysis technique for 3D representations. On these data it was tried to reach the most suitable set of classes to group the spines as well as to describe each cluster by unambiguous rules. From these results, the existance of a continuum of spines and the properties that characterize each spine subtype were discussed .

Classifying GABAergic interneurons with semi-supervised projected model-based clustering

Objectives: A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names.We sought to automatically classify digitally reconstructed interneuronal morphologies according tothis scheme. Simultaneously, we sought to discover possible subtypes of these types that might emergeduring automatic classification (clustering). We also investigated which morphometric properties weremost relevant for this classification.Materials and methods: A set of 118 digitally reconstructed interneuronal morphologies classified into thecommon basket (CB), horse-tail (HT), large basket (LB), and Martinotti (MA) interneuron types by 42 of theworld?s leading neuroscientists, quantified by five simple morphometric properties of the axon and fourof the dendrites. We labeled each neuron with the type most commonly assigned to it by the experts. Wethen removed this class information for each type separately, and applied semi-supervised clustering tothose cells (keeping the others? cluster membership fixed), to assess separation from other types and lookfor the formation of new groups (subtypes). We performed this same experiment unlabeling the cells oftwo types at a time, and of half the cells of a single type at a time. The clustering model is a finite mixtureof Gaussians which we adapted for the estimation of local (per-cluster) feature relevance. We performedthe described experiments on three different subsets of the data, formed according to how many expertsagreed on type membership: at least 18 experts (the full data set), at least 21 (73 neurons), and at least26 (47 neurons).Results: Interneurons with more reliable type labels were classified more accurately. We classified HTcells with 100% accuracy, MA cells with 73% accuracy, and CB and LB cells with 56% and 58% accuracy,respectively. We identified three subtypes of the MA type, one subtype of CB and LB types each, andno subtypes of HT (it was a single, homogeneous type). We got maximum (adapted) Silhouette widthand ARI values of 1, 0.83, 0.79, and 0.42, when unlabeling the HT, CB, LB, and MA types, respectively,confirming the quality of the formed cluster solutions. The subtypes identified when unlabeling a singletype also emerged when unlabeling two types at a time, confirming their validity. Axonal morphometricproperties were more relevant that dendritic ones, with the axonal polar histogram length in the [pi, 2pi) angle interval being particularly useful.Conclusions: The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heteroge-neous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones fordistinguishing among the CB, HT, LB, and MA interneuron types.

A computational model coupling mechanics and electrophysiology in spinal cord injury

Traumatic brain injury and spinal cord injury have recently been put under the spotlight as major causes of death and disability in the developed world. Despite the important ongoing experimental and modeling campaigns aimed at understanding the mechanics of tissue and cell damage typically observed in such events, the differentiated roles of strain, stress and their corresponding loading rates on the damage level itself remain unclear. More specifically, the direct relations between brain and spinal cord tissue or cell damage, and electrophysiological functions are still to be unraveled. Whereas mechanical modeling efforts are focusing mainly on stress distribution and mechanistic-based damage criteria, simulated function-based damage criteria are still missing. Here, we propose a new multiscale model of myelinated axon associating electrophysiological impairment to structural damage as a function of strain and strain rate. This multiscale approach provides a new framework for damage evaluation directly relating neuron mechanics and electrophysiological properties, thus providing a link between mechanical trauma and subsequent functional deficits

Neuronanatomy, neurology and Bayesian networks

Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related quality of life in Parkinson's disease. Most of these challenging problems posed by neuroscience involve new Bayesian network designs that can cope with multiple class variables, small sample sizes, or labels annotated by several experts.

Distributed, layered and reliable computing nets to represent neuronal receptive fields

Abstract. Receptive fields of retinal and other sensory neurons show a large variety of spatiotemporal linear and non linear types of responses to local stimuli. In visual neurons, these responses present either asymmetric sensitive zones or center-surround organization. In most cases, the nature of the responses suggests the existence of a kind of distributed computation prior to the integration by the final cell which is evidently supported by the anatomy. We describe a new kind of discrete and continuous filters to model the kind of computations taking place in the receptive fields of retinal cells. To show their performance in the analysis of diferent non-trivial neuron-like structures, we use a computer tool specifically programmed by the authors to that efect. This tool is also extended to study the efect of lesions on the whole performance of our model nets.

Caracterización y simulación de arborizaciones dentríticas con redes bayesianas incluyendo variables angulares

El funcionamiento interno del cerebro es todavía hoy en día un misterio, siendo su comprensión uno de los principales desafíos a los que se enfrenta la ciencia moderna. El córtex cerebral es el área del cerebro donde tienen lugar los procesos cerebrales de más alto nivel, cómo la imaginación, el juicio o el pensamiento abstracto. Las neuronas piramidales, un tipo específico de neurona, suponen cerca del 80% de los cerca de los 10.000 millones de que componen el córtex cerebral, haciendo de ellas un objetivo principal en el estudio del funcionamiento del cerebro. La morfología neuronal, y más específicamente la morfología dendrítica, determina cómo estas procesan la información y los patrones de conexión entre neuronas, siendo los modelos computacionales herramientas imprescindibles para el estudio de su rol en el funcionamiento del cerebro. En este trabajo hemos creado un modelo computacional, con más de 50 variables relativas a la morfología dendrítica, capaz de simular el crecimiento de arborizaciones dendríticas basales completas a partir de reconstrucciones de neuronas piramidales reales, abarcando desde el número de dendritas hasta el crecimiento los los árboles dendríticos. A diferencia de los trabajos anteriores, nuestro modelo basado en redes Bayesianas contempla la arborización dendrítica en su conjunto, teniendo en cuenta las interacciones entre dendritas y detectando de forma automática las relaciones entre las variables morfológicas que caracterizan la arborización. Además, el análisis de las redes Bayesianas puede ayudar a identificar relaciones hasta ahora desconocidas entre variables morfológicas. Motivado por el estudio de la orientación de las dendritas basales, en este trabajo se introduce una regularización L1 generalizada, aplicada al aprendizaje de la distribución von Mises multivariante, una de las principales distribuciones de probabilidad direccional multivariante. También se propone una distancia circular multivariante que puede utilizarse para estimar la divergencia de Kullback-Leibler entre dos muestras de datos circulares. Comparamos los modelos con y sin regularizaci ón en el estudio de la orientación de la dendritas basales en neuronas humanas, comprobando que, en general, el modelo regularizado obtiene mejores resultados. El muestreo, ajuste y representación de la distribución von Mises multivariante se implementa en un nuevo paquete de R denominado mvCircular.---ABSTRACT---The inner workings of the brain are, as of today, a mystery. To understand the brain is one of the main challenges faced by current science. The cerebral cortex is the region of the brain where all superior brain processes, like imagination, judge and abstract reasoning take place. Pyramidal neurons, a specific type of neurons, constitute approximately the 80% of the more than 10.000 million neurons that compound the cerebral cortex. It makes the study of the pyramidal neurons crucial in order to understand how the brain works. Neuron morphology, and specifically the dendritic morphology, determines how the information is processed in the neurons, as well as the connection patterns among neurons. Computational models are one of the main tools for studying dendritic morphology and its role in the brain function. We have built a computational model that contains more than 50 morphological variables of the dendritic arborizations. This model is able to simulate the growth of complete dendritic arborizations from real neuron reconstructions, starting with the number of basal dendrites, and ending modeling the growth of dendritic trees. One of the main diferences between our approach, mainly based on the use of Bayesian networks, and other models in the state of the art is that we model the whole dendritic arborization instead of focusing on individual trees, which makes us able to take into account the interactions between dendrites and to automatically detect relationships between the morphologic variables that characterize the arborization. Moreover, the posterior analysis of the relationships in the model can help to identify new relations between morphological variables. Motivated by the study of the basal dendrites orientation, a generalized L1 regularization applied to the multivariate von Mises distribution, one of the most used distributions in multivariate directional statistics, is also introduced in this work. We also propose a circular multivariate distance that can be used to estimate the Kullback-Leibler divergence between two circular data samples. We compare the regularized and unregularized models on basal dendrites orientation of human neurons and prove that regularized model achieves better results than non regularized von Mises model. Sampling, fitting and plotting functions for the multivariate von Mises are implemented in a new R packaged called mvCircular.

Use of Biological Motion based Cues and Ecological Sounds in the Neurorehabilitation of Apraxia

Technological progress in the area of informatics and human interface platforms create a window of opportunities for the neurorehablitation of patients with motor impairments. The CogWatch project (www.cogwatch.eu) aims to create an intelligent assistance system to improve motor planning and execution in patients with apraxia during their daily activities. Due to the brain damage caused by cardiovascular incident these patients suffer from impairments in the ability to use tools, and to sequence actions during daily tasks (such as making breakfast). Based on the common coding theory (Hommel et al., 2001) and mirror neuron primate research (Rizzolatti et al., 2001) we aim to explore use of cues, which incorporate aspects of biological motion from healthy adults performing everyday tasks requiring tool use and ecological sounds linked to the action goal. We hypothesize that patients with apraxia will benefit from supplementary sensory information relevant to the task, which will reinforce the selection of the appropriate motor plan. Findings from this study determine the type of sensory guidance in the CogWatch interface. Rationale for the experimental design is presented and the relevant literature is discussed.

Safety study of transcranial static magnetic field stimulation (tSMS) of the human cortex

Transcranial static magnetic field stimulation (tSMS) in humans reduces cortical excitability. Objective: The objective of this study was to determine if prolonged tSMS (2 h) could be delivered safely in humans. Safety limits for this technique have not been described. Methods: tSMS was applied for 2 h with a cylindric magnet on the occiput of 17 healthy subjects. We assessed tSMS-related safety aspects at tissue level by measuring levels of neuron-specific enolase (NSE,a marker of neuronal damage) and S100 (a marker of glial reactivity and damage). We also included an evaluation of cognitive side effects by using a battery of visuomotor and cognitive tests. Results: tSMS did not induce any significant increase in NSE or S100. No cognitive alteration was detected. Conclusions: Our data indicate that the application of tSMS is safe in healthy human subjects, at least within these parameters

CONSCIÊNCIA E EMOÇÃO: O EFEITO DO PRIMING AFETIVO SUBLIMINAR EM TAREFAS DE ATENÇÃO

Esta tese revisou duas linhas de pesquisa, desenvolvidas nas últimas décadas: o estudo de efeitos de estimulação subliminar priming , e de desencadeamento de reações emocionais por estímulos controlados. Este estudo tem o objetivo de combinar tais linhas para o estudo da consciência com pré-preparo afetivo: efeito de estímulos de conteúdo aversivo, subliminares e supraliminares, sobre a cognição, pela análise do desempenho em tarefa de atenção. Três tarefas experimentais foram realizadas por 35 indivíduos em laboratório de neuropsicologia: a tarefa base onde testamos à detecção de alvo visual simples, e a mesma tarefa de base, porém com estímulos distratores aversivos intercalados, de forma supraliminar ou subliminar (500 ms ou 50 ms de duração), em blocos aleatorizados entre os indivíduos. Calcularam-se índices de detectabilidade e critério de resposta, que serviram para a comparação estatística entre condições (medidas repetidas). Os resultados mostram uma mudança significativa do índice critério , indicando mudança de estratégia na presença de distratores subliminares aversivos. Concluiu-se que a tarefa subliminar fez um efeito destruidor ou devastador na tarefa supraliminar, cometendo menos falso-alarmes protegendo a tarefa supraliminar, tendo um efeito protetor . Os resultados são discutidos no contexto da relevância de influências emocionais sobre o comportamento para a Psicologia da Saúde.

CONSCIÊNCIA E EMOÇÃO: O EFEITO DO PRIMING AFETIVO SUBLIMINAR EM TAREFAS DE ATENÇÃO

Esta tese revisou duas linhas de pesquisa, desenvolvidas nas últimas décadas: o estudo de efeitos de estimulação subliminar priming , e de desencadeamento de reações emocionais por estímulos controlados. Este estudo tem o objetivo de combinar tais linhas para o estudo da consciência com pré-preparo afetivo: efeito de estímulos de conteúdo aversivo, subliminares e supraliminares, sobre a cognição, pela análise do desempenho em tarefa de atenção. Três tarefas experimentais foram realizadas por 35 indivíduos em laboratório de neuropsicologia: a tarefa base onde testamos à detecção de alvo visual simples, e a mesma tarefa de base, porém com estímulos distratores aversivos intercalados, de forma supraliminar ou subliminar (500 ms ou 50 ms de duração), em blocos aleatorizados entre os indivíduos. Calcularam-se índices de detectabilidade e critério de resposta, que serviram para a comparação estatística entre condições (medidas repetidas). Os resultados mostram uma mudança significativa do índice critério , indicando mudança de estratégia na presença de distratores subliminares aversivos. Concluiu-se que a tarefa subliminar fez um efeito destruidor ou devastador na tarefa supraliminar, cometendo menos falso-alarmes protegendo a tarefa supraliminar, tendo um efeito protetor . Os resultados são discutidos no contexto da relevância de influências emocionais sobre o comportamento para a Psicologia da Saúde.

Functional identification and reconstitution of an odorant receptor in single olfactory neurons

The olfactory system is remarkable in its capacity to discriminate a wide range of odorants through a series of transduction events initiated in olfactory receptor neurons. Each olfactory neuron is expected to express only a single odorant receptor gene that belongs to the G protein coupled receptor family. The ligand–receptor interaction, however, has not been clearly characterized. This study demonstrates the functional identification of olfactory receptor(s) for specific odorant(s) from single olfactory neurons by a combination of Ca2+-imaging and reverse transcription–coupled PCR analysis. First, a candidate odorant receptor was cloned from a single tissue-printed olfactory neuron that displayed odorant-induced Ca2+ increase. Next, recombinant adenovirus-mediated expression of the isolated receptor gene was established in the olfactory epithelium by using green fluorescent protein as a marker. The infected neurons elicited external Ca2+ entry when exposed to the odorant that originally was used to identify the receptor gene. Experiments performed to determine ligand specificity revealed that the odorant receptor recognized specific structural motifs within odorant molecules. The odorant receptor-mediated signal transduction appears to be reconstituted by this two-step approach: the receptor screening for given odorant(s) from single neurons and the functional expression of the receptor via recombinant adenovirus. The present approach should enable us to examine not only ligand specificity of an odorant receptor but also receptor specificity and diversity for a particular odorant of interest.

In vivo evidence that erythropoietin protects neurons from ischemic damage

Erythropoietin (EPO) produced by the kidney and the liver (in fetuses) stimulates erythropoiesis. In the central nervous system, neurons express EPO receptor (EPOR) and astrocytes produce EPO. EPO has been shown to protect primary cultured neurons from N-methyl-d-aspartate (NMDA) receptor-mediated glutamate toxicity. Here we report in vivo evidence that EPO protects neurons against ischemia-induced cell death. Infusion of EPO into the lateral ventricles of gerbils prevented ischemia-induced learning disability and rescued hippocampal CA1 neurons from lethal ischemic damage. The neuroprotective action of exogenous EPO was also confirmed by counting synapses in the hippocampal CA1 region. Infusion of soluble EPOR (an extracellular domain capable of binding with the ligand) into animals given a mild ischemic treatment that did not produce neuronal damage, caused neuronal degeneration and impaired learning ability, whereas infusion of the heat-denatured soluble EPOR was not detrimental, demonstrating that the endogenous brain EPO is crucial for neuronal survival. The presence of EPO in neuron cultures did not repress a NMDA receptor-mediated increase in intracellular Ca2+, but rescued the neurons from NO-induced death. Taken together EPO may exert its neuroprotective effect by reducing the NO-mediated formation of free radicals or antagonizing their toxicity.

Latent varicella–zoster virus is located predominantly in neurons in human trigeminal ganglia

Varicella–zoster virus (VZV) is a human herpesvirus that causes varicella (chicken pox) as a primary infection and, after a variable period of latency in trigeminal and dorsal root ganglia, reactivates to cause herpes zoster (shingles). Both of these conditions may be followed by a variety of neurological complications, especially in immunocompromised individuals such as those with human immunodeficiency virus (HIV) infection. There have been a number of conflicting reports regarding the cellular location of latent VZV within human ganglia. To address this controversy we examined fixed wax-embedded trigeminal ganglia from 30 individuals obtained at autopsy, including 11 with HIV infection, 2 neonates, and 17 immunocompetent individuals, for the presence of latent VZV. Polymerase chain reaction (PCR), in situ hybridization, and PCR in situ amplification techniques with oligonucleotide probes and primer sequences to VZV genes 18, 21, 29, and 63 were used. VZV DNA in ganglia was detected in 15 individuals by using PCR alone, and in 12 individuals (6 normal non-HIV and 6 positive HIV individuals, but not neonatal ganglia) by using PCR in situ amplification. When in situ hybridization alone was used, 5 HIV-positive individuals and only 1 non-HIV individual showed VZV nucleic acid signals in ganglia. In all of the VZV-positive ganglia examined, VZV nucleic acid was detected in neuronal nuclei. Only occasional nonneuronal cells contained VZV DNA. We conclude from these studies that the neuron is the predominant site of latent VZV in human trigeminal ganglia.

A third member of the synapsin gene family

Synapsins are a family of neuron-specific synaptic vesicle-associated phosphoproteins that have been implicated in synaptogenesis and in the modulation of neurotransmitter release. In mammals, distinct genes for synapsins I and II have been identified, each of which gives rise to two alternatively spliced isoforms. We have now cloned and characterized a third member of the synapsin gene family, synapsin III, from human DNA. Synapsin III gives rise to at least one protein isoform, designated synapsin IIIa, in several mammalian species. Synapsin IIIa is associated with synaptic vesicles, and its expression appears to be neuron-specific. The primary structure of synapsin IIIa conforms to the domain model previously described for the synapsin family, with domains A, C, and E exhibiting the highest degree of conservation. Synapsin IIIa contains a novel domain, termed domain J, located between domains C and E. The similarities among synapsins I, II, and III in domain organization, neuron-specific expression, and subcellular localization suggest a possible role for synapsin III in the regulation of neurotransmitter release and synaptogenesis. The human synapsin III gene is located on chromosome 22q12–13, which has been identified as a possible schizophrenia susceptibility locus. On the basis of this localization and the well established neurobiological roles of the synapsins, synapsin III represents a candidate gene for schizophrenia.