Robust control of underactuated wheeled mobile manipulators using GPI disturbance observers

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.

3D segmentations of neuronal nuclei from confocal microscope image stacks

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario?the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

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.

Análisis de la actividad neuronal y cerebral mediante técnicas de redes complejas

El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

The oculomotor system as a model for the study of neuronal interaction processes

Identified neurons that control eye movements offer an excellent experimental target for the study of Information coding and neuronal interaction processes wíthin the central nervous system. Here are presented some prelimínary results of the motoneuron behaviour during steady eye fíxation, obtained by regressíon and analysis of variance techniques. A flexible information system intended for the systematic acquisitíon and analysis of simultaneous records of neuronal activity and both eyes angular position in a great amount of cells, oriented to the defínition of mathematical models, is also briefly outlíned.

Coordinate regulation of gonadotropin-releasing hormone neuronal firing patterns by cytosolic calcium and store depletion

Elevation of cytosolic free Ca2+ concentration ([Ca2+]i) in excitable cells often acts as a negative feedback signal on firing of action potentials and the associated voltage-gated Ca2+ influx. Increased [Ca2+]i stimulates Ca2+-sensitive K+ channels (IK-Ca), and this, in turn, hyperpolarizes the cell and inhibits Ca2+ influx. However, in some cells expressing IK-Ca the elevation in [Ca2+]i by depletion of intracellular stores facilitates voltage-gated Ca2+ influx. This phenomenon was studied in hypothalamic GT1 neuronal cells during store depletion caused by activation of gonadotropin-releasing hormone (GnRH) receptors and inhibition of endoplasmic reticulum (Ca2+)ATPase with thapsigargin. GnRH induced a rapid spike increase in [Ca2+]i accompanied by transient hyperpolarization, followed by a sustained [Ca2+]i plateau during which the depolarized cells fired with higher frequency. The transient hyperpolarization was caused by the initial spike in [Ca2+]i and was mediated by apamin-sensitive IK-Ca channels, which also were operative during the subsequent depolarization phase. Agonist-induced depolarization and increased firing were independent of [Ca2+]i and were not mediated by inhibition of K+ current, but by facilitation of a voltage-insensitive, Ca2+-conducting inward current. Store depletion by thapsigargin also activated this inward depolarizing current and increased the firing frequency. Thus, the pattern of firing in GT1 neurons is regulated coordinately by apamin-sensitive SK current and store depletion-activated Ca2+ current. This dual control of pacemaker activity facilitates voltage-gated Ca2+ influx at elevated [Ca2+]i levels, but also protects cells from Ca2+ overload. This process may also provide a general mechanism for the integration of voltage-gated Ca2+ influx into receptor-controlled Ca2+ mobilization.

Src interacts with dynamin and synapsin in neuronal cells

The nonreceptor tyrosine kinase Src is expressed at a high level in cells that are specialized for regulated secretion, such as the neuron, and is concentrated on secretory vesicles or at the site of exocytosis. To investigate the possibility that Src may play a role in regulating membrane traffic, we searched for neuronal proteins that will interact with Src. The SH3 domain of Src, but not that of the splice variant N-Src, bound to three proteins from mouse synaptosomes or PC12 cells: dynamin, synapsin Ia, and synapsin Ib. Dynamin and the synapsins coprecipitated with Src from PC12 cell extracts, and they colocalized with a subset of Src in the PC12 cell by immunofluorescence. Neither dynamin nor the synapsins were phosphorylated by Src, suggesting that the interaction of these proteins serves to direct the kinase activity of Src toward other proteins in the vesicle population. In immunoprecipitates containing Src and dynamin, the clathrin adaptor protein α-adaptin was also found. The association of Src and synapsin suggests a role for Src in the life cycle of the synaptic vesicle. The identification of a complex containing Src, dynamin, and α-adaptin indicates that Src may play a more general role in membrane traffic as well.

Cardiac arrest in rodents: Maximal duration compatible with a recovery of neuronal activity

We report here that during a permanent cardiac arrest, rodent brain tissue is “physiologically” preserved in situ in a particular quiescent state. This state is characterized by the absence of electrical activity and by a critical period of 5–6 hr during which brain tissue can be reactivated upon restoration of a simple energy (glucose/oxygen) supply. In rat brain slices prepared 1–6 hr after cardiac arrest and maintained in vitro for several hours, cells with normal morphological features, intrinsic membrane properties, and spontaneous synaptic activity were recorded from various brain regions. In addition to functional membrane channels, these neurons expressed mRNA, as revealed by single-cell reverse transcription–PCR, and could synthesize proteins de novo. Slices prepared after longer delays did not recover. In a guinea pig isolated whole-brain preparation that was cannulated and perfused with oxygenated saline 1–2 hr after cardiac arrest, cell activity and functional long-range synaptic connections could be restored although the electroencephalogram remained isoelectric. Perfusion of the isolated brain with the γ-aminobutyric acid A receptor antagonist picrotoxin, however, could induce self-sustained temporal lobe epilepsy. Thus, in rodents, the duration of cardiac arrest compatible with a short-term recovery of neuronal activity is much longer than previously expected. The analysis of the parameters that regulate this duration may bring new insights into the prevention of postischemic damages.

Neuronal coincidence detection by voltage-sensitive electrical synapses

Coincidence detection is important for functions as diverse as Hebbian learning, binaural localization, and visual attention. We show here that extremely precise coincidence detection is a natural consequence of the normal function of rectifying electrical synapses. Such synapses open to bidirectional current flow when presynaptic cells depolarize relative to their postsynaptic targets and remain open until well after completion of presynaptic spikes. When multiple input neurons fire simultaneously, the synaptic currents sum effectively and produce a large excitatory postsynaptic potential. However, when some inputs are delayed relative to the rest, their contributions are reduced because the early excitatory postsynaptic potential retards the opening of additional voltage-sensitive synapses, and the late synaptic currents are shunted by already opened junctions. These mechanisms account for the ability of the lateral giant neurons of crayfish to sum synchronous inputs, but not inputs separated by only 100 μsec. This coincidence detection enables crayfish to produce reflex escape responses only to very abrupt mechanical stimuli. In light of recent evidence that electrical synapses are common in the mammalian central nervous system, the mechanisms of coincidence detection described here may be widely used in many systems.

Relax promotes ectopic neuronal differentiation in Xenopus embryos

We previously isolated a novel rat cDNA encoding a basic helix–loop–helix transcription factor named Relax, whose expression in the developing central nervous system is strictly limited to discrete domains containing precursor cells. The timing of Relax expression coincides with neuronal differentiation. To investigate the involvement of Relax in neurogenesis we tested whether Relax activated neural genes in the ectoderm by injecting Relax RNA into Xenopus embryos. We demonstrate that ectopic Relax expression induces a persistent enlargement of the neural plate and converts presumptive epidermal cells into neurons. This indicates that Relax, when overexpressed in Xenopus embryos, has a neuronal fate-determination function. Analyses both of Relax overexpression in the frog and of the distribution of Relax in the rat neural tube strongly suggest that Relax is a neuronal fate-determination gene.

The role of the synthetic enzyme GAD65 in the control of neuronal γ-aminobutyric acid release

We have studied GABAergic synaptic transmission in retinal ganglion cells and hippocampal pyramidal cells to determine, at a cellular level, what is the effect of the targeted disruption of the gene encoding the synthetic enzyme GAD65 on the synaptic release of γ-aminobutyric acid (GABA). Neither the size nor the frequency of GABA-mediated spontaneous inhibitory postsynaptic currents (IPSCs) were reduced in retina or hippocampus in GAD65−/− mice. However, the release of GABA during sustained synaptic activation was substantially reduced. In the retina both electrical- and K+-induced increases in IPSC frequency were depressed without a change in IPSC amplitude. In the hippocampus the transient increase in the probability of inhibitory transmitter release associated with posttetanic potentiation was absent in the GAD65−/− mice. These results indicate that during and immediately after sustained stimulation the increase in the probability of transmitter release is not maintained in GAD65−/− mice. Such a finding suggests a decrease in the size or refilling kinetics of the releasable pool of vesicles, and various mechanisms are discussed that could account for such a defect.

Pattern of neuronal activity associated with conscious and unconscious processing of visual signals

Following striate cortex damage in monkeys and humans there can be residual function mediated by parallel visual pathways. In humans this can sometimes be associated with a “feeling” that something has happened, especially with rapid movement or abrupt onset. For less transient events, discriminative performance may still be well above chance even when the subject reports no conscious awareness of the stimulus. In a previous study we examined parameters that yield good residual visual performance in the “blind” hemifield of a subject with unilateral damage to the primary visual cortex. With appropriate parameters we demonstrated good discriminative performance, both with and without conscious awareness of a visual event. These observations raise the possibility of imaging the brain activity generated in the “aware” and the “unaware” modes, with matched levels of discrimination performance, and hence of revealing patterns of brain activation associated with visual awareness. The intact hemifield also allows a comparison with normal vision. Here we report the results of a functional magnetic resonance imaging study on the same subject carried out under aware and unaware stimulus conditions. The results point to a shift in the pattern of activity from neocortex in the aware mode, to subcortical structures in the unaware mode. In the aware mode prestriate and dorsolateral prefrontal cortices (area 46) are active. In the unaware mode the superior colliculus is active, together with medial and orbital prefrontal cortical sites.

Using resilience to predict the effects of disturbance

Acknowledgements This work was funded by the Office of Naval Research (N00014-13-1-0696). We thank C Asher for her comments on an earlier version of this manuscript.

Neuronal human BACE1 knock-in induces systemic diabetes in mice

Funding We would like to thank R. Simcox, Romex Oilfield Chemicals, for financial support for KP, and acknowledge additional contributions from the Scottish Alzheimer’s Research UK network for the lipidomics work. The College of Life Science and Medicine, University of Aberdeen, sponsored the imaging study. MD was funded by British Heart Foundation and Diabetes UK; NM was funded by a British Heart Foundation Intermediate Fellowship; KS was funded by a European Foundation for the Study of Diabetes/Lilly programme grant; and RD was funded by an Institute of Medical Sciences PhD studentship.

Neuronal death in the central nervous system demonstrates a non-fibrin substrate for plasmin

Mice deficient for plasminogen exhibit a variety of pathologies, all of which examined to date are reversed when the animals are also made fibrin(ogen) deficient. These results suggested that the predominant, and perhaps exclusive, physiological role of plasminogen is clearance of fibrin. Plasminogen-deficient mice also display resistance to excitotoxin-induced neurodegeneration, in contrast with wild-type mice, which are sensitive. Based on the genetic interaction between plasminogen and fibrinogen, we investigated whether resistance to neuronal cell death in the plasminogen-deficient mice is dependent on fibrin(ogen). Unexpectedly, mice lacking both plasminogen and fibrinogen are resistant to neurodegeneration to levels comparable to plasminogen-deficient mice. Therefore, plasmin acts on substrates other than fibrin during experimental neuronal degeneration, and may function similarly in other pathological settings in the central nervous system.