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Die Rheumatoide Arthritis ist eine Autoimmunerkrankung, die vor allem die Gelenke befällt. Hierbei kommt es zu einer ausgeprägten Synovialitis unter Beteiligung von Tund B-Lymphozyten, NK-Zellen, Makrophagen, dendritischen Zellen sowie Synoviozyten vom Fibroblastentyp. Dies führt zur Zerstörung des Gelenkknorpels und schliesslich des Gelenkes selbst. Eine entscheidende Rolle bei der Ausbildung und Aufrechterhaltung der Entzündung spielen synoviale T-Zellen, die unter anderem eine gesteigerte Apoptoseresistenz zeigen. Der Insulin-like Growth Factor Type 1 Rezeptor wird auf aktivierten T-Zellen vermehrt exprimiert und führt zu einer vermehrten Proliferation und verminderten Apoptoseneigung. Insulin-like Growth Factor 2 ist ein wichtiger Ligand dieses Rezeptors und wird normalerweise nur vom väterlichen Allel transkribiert. Unter Loss of Imprinting von Insulin-like Growth Factor 2 versteht man die biallelische Expression dieses Wachstumsfaktors. LOI von IGF-2 wurde bei aktivierten, proliferienden T-Zellen beobachtet. In dieser Arbeit wurden Synovial Tissue Mononuclear Cells (STMC) aus Synovialisbiopsaten von Patienten mit aktiver RA auf ein LOI von IGF-2 hin untersucht, um herauszufinden ob LOI von IGF-2 eine Rolle bei der Entstehung und Aufrechterhaltung des lokalen Entzündungsgeschehens spielen könnte. Zusätzlich erfolgten Versuche mit Peripheral Blood Mononuclear Cells (PBMC) von gesunden Versuchspersonen, um mehr über die Zusammenhänge zwischen Stimulation, Proliferation und LOI von IGF-2 herauszufinden. Die Synovialisbiopsate stammten aus der orthopädischen Universitätsklinik, wo sie im Rahmen von gelenkchirurgischen Eingriffen bei RA-Patienten mit aktiver Synovialitis entnommen wurden. Alle untersuchten Biopsate zeigten ein Retention of Imprinting, also eine monoallelische Expression von IGF-2. Die Versuche mit PBMC konnten keinen direkten Zusammenhang zwischen Stimulation, Proliferation und LOI von IGF-2 zeigen, diese Ergebnisse sind mit neueren Untersuchungen vereinbar. Zusammenfassend lässt sich sagen, dass LOI von IGF-2 als Faktor für das Auftreten oder die Aufrechterhaltung einer RA keine Rolle zu spielen scheint.
Zusammenfassung Die Alzheimersche Krankheit (AD) ist mit 60% die am häufigsten auftretende Art der Demenz. Weltweit sind ca. 24 Mio. Menschen von der neurodegenerativen Krankheit betroffen, welche sich durch den Verlust der kognitiven Fähigkeiten auszeichnet. Es gibt zwei Ausprägungen der Demenz, zum einen die sporadische Verlaufsform, die bei Menschen in einem Alter ab 65 Jahren auftritt und zum anderen die familiäre Alzheimersche Krankheit (FAD), die schon weitaus jüngere Menschen betrifft und auf genetische Mutationen zurück zu führen ist. Beide Formen der Demenz zeigen den gleichen neuropathologische Phänotyp, der zur Ausbildung von extrazellulären Plaques und intrazellulären Neurofibrillen führt. Durch die Entstehung der Plaques und der Neurofibrillen werden die Verbindungen zwischen den einzelnen Neuronen verringert und die Neuronen sterben ab. Für das Auftreten der FAD sind Mutationen in den Genen des Amyloid Vorläufer Proteins (APP, Substrat) sowie der Aspartatprotease Einheit des γ-Sekretase Komplexes, Presenilin 1 (PS1) oder Presenilin 2 (PS2), verantwortlich. Die γ-Sekretase ist ein membranständiger Komplex bestehend aus den vier Untereinheiten PS1 oder PS2, Nicastrin (Nct), Aph-1 und Pen-2. Um ausreichende Informationen über den γ-Sekretase Komplex bezüglich seiner Interaktionsflächen, seines Katalysemechanismus und seiner Substraterkennung zu erhalten, wäre es hilfreich seine 3 Dimensionale Struktur aufzuklären, wozu große Mengen der sauberen und homogenen Proteine benötigt werden. Die Herstellung von ausreichenden Proteinmengen stellt derzeit aber einen Engpass für die strukturelle und funktionelle Charakterisierung des γ-Sekretase Komplexes in-vitro dar. Alzheimer’s disease (AD) is the most common cause of dementia, which affects 24 million people worldwide. It is a neurodegenerative disorder, which occurs either in its most common form in people over 65 years or in the rare early-onset familial AD (FAD). Responsible for the autosomal dominant FAD are mutations in the genes encoding for the β-amyloid precursor protein (APP) and the two homologues integral membrane proteins Presenilin 1 (PS1) and Presenilin 2 (PS2). The two PSs are major but alternative components of the intramembrane aspartyl protease γ-secretase. Further components are the membrane proteins Nicastrin (Nct), Aph-1 and Pen-2. Production of sufficient amounts of protein samples is still the major bottleneck for the detailed functional and structural in-vitro characterization of the γ-secretase complex. Due to toxicity, stability and targeting problems, the overproduction of MPs in conventional in-vivo systems often has only limited success. Therefore, efficient expression protocols using the cell-free (CF) system were established in this work. After optimization, I was able to produce up to milligram amounts of the single proteins PS1 and PS2, the cleavage products PS1-NTF and PS1-CTF, and Pen-2. The in-vitro produced γ-secretase subunits were further characterized, concerning their purity, secondary fold, thermal stability and homogeneity. Highest purities with over 90% after affinity chromatography could be achieved for PS1-CTF and Pen-2. Reconstitution of PS1, PS1-NTF, PS1-CTF and Pen-2 into E. coli liposomes results in a homogeneously distribution, which gives evidence for a structural folding. This was confirmed by CD spectroscopy of PS1-CTF and Pen-2. The thermal stability of Pen-2 shows a transition at 68°C, whereas PS1-CTF is stable up to 95°C. Both proteins show in addition homogeneous elution profiles investigated by analytical SEC and exhibit a monomeric (Pen-2) or dimeric (PS1-CTF) character analyzed by blue native PAGE. Different methods were performed to get evidence about the assembly of the complex, like pull-down experiments, immunoprecipitation, co-expression of radioactive labeled subunits and titration assays by liquid-state NMR. First hints for an interaction of the CF synthesized proteins could be observed by co-expression. Supplemental, Pen-2 and CTF could be purified in sufficient amounts and to apparent homogeneity that allow structural approaches by X-ray crystallography and liquid-state NMR spectroscopy. First conditions for protein crystals were achieved for Pen-2 and structural investigations of PS1-CTF by liquid-state NMR could be performed after optimization of the expression-, purification- and detergent conditions.
The mitsva reflects one of the most pivotal concepts of Judaism. It sanctifies those who answer its calling, and the Jew and Judaism is unique and “chosen” because of it. In this article we highlight the various ways the mitsvot and Halakha transform us and mold the Jewish personality: (a) by converting the “ought” into a “must”; (b) by transforming daily prosaic acts of man into sacred deeds; (c) by converting simple chronological, linear time into special moments of kedusha. The mitsva involves the total personality - “head, heart and hand” and makes the body equally important with the soul in the service of Hashem. Sanctification is accomplished both through deed and thought. The Torah wants the Jew to build an environment which strengthens his religious values and has designated Erets Yisrael as the most fitting place for kedusha.
We propose a variation of online paging in two-level memory systems where pages in the fast cache get modified and therefore have to be explicitly written back to the slow memory upon evictions. For increased performance, up to alpha arbitrary pages can be moved from the cache to the slow memory within a single joint eviction, whereas fetching pages from the slow memory is still performed on a one-by-one basis. The main objective in this new alpha-paging scenario is to bound the number of evictions. After providing experimental evidence that alpha-paging can adequately model flash-memory devices in the context of translation layers we turn to the theoretical connections between alpha-paging and standard paging. We give lower bounds for deterministic and randomized alpha-paging algorithms. For deterministic algorithms, we show that an adaptation of LRU is strongly competitive, while for the randomized case we show that by adapting the classical Mark algorithm we get an algorithm with a competitive ratio larger than the lower bound by a multiplicative factor of approximately 1.7.
Die Menge digital zur Verfügung stehender Dokumente wächst zunehmend. Umso wichtiger sind adäquate Methoden, um sehr große Dokumentkollektionen durch-suchen zu können. Im Gegensatz zur exakten Suche, bei der nach Dokumenten mit bekannten Dateinamen gesucht wird, werden Techniken des Information Retrieval (IR) dazu eingesetzt, relevante Ergebnisse zu einer Anfrage ausfindig zu machen. Seit einigen Jahren werden verstärkt Kollektionen mit strukturierten Dokumenten durch¬sucht, insbesondere seit Durchsetzung der eXtensible Markup Language (XML) als offizieller Standard des World Wide Web Consortiums (W3C). Mittlerweile gibt es eine Reihe von Forschungsansätzen, bei denen IR-Methoden auf XML-Dokumente angewendet werden. XML Information Retrieval (XML-IR) nutzt dabei die Struktur der Dokumente, um die Suche nach und in denselben effektiver zu machen, d.h. die Qualität von Suchergebnissen zu verbessern, beispielsweise durch Fokussierung auf besonders relevante Dokumentteile. Die bisherigen Lösungen beziehen sich jedoch alle auf zentralisierte Stand-Alone Suchmaschinen zu Forschungszwecken. Sehr große, über eine Vielzahl von Rechnern verteilte Datenkollektionen lassen sich damit nicht durchsuchen. Techniken für verteiltes XML-IR werden in der Praxis auch dort benötigt, wo das zu durchsuchende System aus einer Vielzahl lokaler, heterogener XML-Kollektionen besteht, deren Benutzer ihre Dokumente nicht auf einem zent¬ralen Server speichern wollen oder können; solche Benutzer schließen sich häufig in Form eines dezentralen Peer-to-Peer (P2P) Netzes zusammen. Dennoch gibt es derzeit weder für Systeme im Allgemeinen, noch für P2P-Systeme im Speziellen Suchmaschinen, mit denen nach relevanten Dokumenten gesucht werden kann. In der vorliegenden Dissertation wird daher am Beispiel von P2P-Netzen erstmalig untersucht, inwiefern XML-IR in verteilten Systemen überhaupt effektiv und effizient möglich ist. Dazu wird ein allgemeines Architekturmodell für die Entwick-lung von P2P-Suchmaschinen für XML-Retrieval entworfen, in dem Funktionalität aus den Bereichen XML-IR und P2P in abstrakten Schichten angeordnet ist. Das Modell wird als Grundlage für den Entwurf einer konkreten P2P-Suchmaschine für XML-IR verwendet. Es werden dazu verschiedene Techniken für verteiltes XML-IR entwickelt, um die einzelnen Phasen der Suche umzusetzen: Indizierung der Doku¬mente, Routing der Anfragen, Ranking geeigneter Dokumente und Retrieval von Ergebnissen. Insbesondere die Problematik von aus mehreren Suchbegriffen bestehenden Multitermanfragen sowie Verteilungsaspekte werden berücksichtigt. Neben der zu erzie-lenden Suchqualität steht vor allem der notwendige Kommunikations¬aufwand im Vordergrund. Die entwickelten Methoden werden in Form einer P2P-Suchmaschine für verteiltes XML-Retrieval implementiert, die aus fast 40.000 Zeilen Java-Code besteht. Diese Suchmaschine namens SPIRIX kann voll-funktionsfähig nach XML-Dokumenten in einem P2P-Netz suchen und deren Relevanz inhaltsbasiert bewerten. Für die Kommunikation zwischen Peers wird ein P2P-Protokoll namens SpirixDHT entworfen, das auf Basis von Chord arbeitet und speziell für den Einsatz von XML-IR angepasst wird. Für die Evaluierung der entworfenen Techniken wird zunächst die Suchqualität von SPIRIX nachgewiesen. Dies geschieht durch die Teilnahme an INEX, der internationalen Initiative für die Evaluierung von XML-Retrieval. Im Rahmen von INEX werden jedes Jahr XML-IR Lösungen weltweit miteinander verglichen. Für 2008 konnte mit SPIRIX eine Suchpräzision erreicht werden, die vergleichbar mit der Qualität der Top-10 XML-IR Lösungen ist. In weiteren Experimenten werden die entworfenen Methoden für verteiltes XML-Retrieval mit INEX-Werkzeugen evaluiert; dabei werden jeweils die erzielte Such-qualität und der notwendige Aufwand gegenübergestellt. Die gewonnenen Er¬kenn-tnisse werden auf den Routingprozess angewendet; hier ist speziell die Frage-stellung interessant, wie XML-Struktur zur Performanzverbesserung in Bezug auf die Effizienz eines verteilten Systems genutzt werden kann. Die Evaluierung der konzi¬pier¬ten Routingtechniken zeigt eine signifikante Reduzierung der Anzahl versendeter Nachrichten, ihrer Größe und somit der Netzlast, wobei gleichzeitig eine Steigerung der Suchqualität erreicht wird. Im Rahmen der Dissertation wird somit der Nachweis erbracht, dass verteiltes XML-IR sowohl effektiv als auch effizient möglich ist. Zugleich wird gezeigt, wie die Ver¬wendung von XML-IR Techniken beim Routing der Anfragen dazu beitragen kann, den notwendige Suchaufwand – insbesondere den für die Kommunikation zwischen Peers – so weit zu reduzieren, dass das System auch zu einer großen Anzahl von teil¬nehmenden Peers skaliert und trotzdem eine hohe Suchqualität aufrecht erhalten werden kann.
Background Multidirectional interactions in social (or communication) networks can have a profound effect on mate choice behavior. For example, Poecilia mexicana males show weaker expression of mating preferences when being observed by an audience male. It was suggested that this behavior is an adaptation to reduce sperm competition risk, which arises because commonly preferred female phenotypes will receive attention also by surrounding males, and/or because the audience male can copy the focal male's mate choice. Do P. mexicana males indeed respond to perceived sperm competition risk? We gave males a choice between two females and repeated the tests under one of the following conditions: (1) during the 2nd part of the tests an empty transparent cylinder was presented (control); (2) an audience male inside the cylinder observed the focal male throughout the 2nd part, or (3) the audience male was presented only before the tests, but could not eavesdrop during the actual choice tests (non-specific sperm competition risk treatments); (4) the focal male could see a rival male sexually interacting with the previously preferred, or (5) with the non-preferred female before the 2nd part of the tests (specific sperm competition risk treatments). Results When comparing the strength of individual male preferences between the 1st and 2nd part of the tests (before and after presentation of an audience), male preferences declined slightly also during the control treatment (1). However, the decrease in strength of male preferences was more than two-fold stronger in audience treatment (2), i.e., with non-specific sperm competition risk including the possibility for visual eavesdropping by the audience male. No audience effect was found in treatments (3) and (5), but a weak effect was also seen when the focal male had seen the previously preferred female sexually interact with a rival male (treatment 4; specific sperm competition risk). Conclusions When comparing the two 'non-specific sperm competition risk' treatments (2 and 3), a very strong effect was found only when the audience male could actually observe the focal male during mate choice in treatment (2). This suggests that focal males indeed attempt to conceal their mating preferences in the visual presence of other males so as to avoid mate choice copying. When there is no potential for eavesdropping [treatment (3)], non-specific specific sperm competition risk seems to play a minor or no role. Congruent with studies on other poeciliid species, our results also show that P. mexicana males respond to perceived specific sperm competition risk, and tend to share their mating effort more equally among females when the resource value of their previously preferred mate decreases (after mating with a rival male). However, this effect is comparatively weak.
Die 5-Lipoxygenase (5-LO) ist das Schlüsselenzym in der Biosynthese proinflammatorischer Leukotriene, die maßgeblich an der Entstehung allergischer und entzündlicher Erkrankungen wie Arthritis, Asthma und kardiovaskulären Erkrankungen beteiligt sind (23). Humane 5-LO besteht aus 673 Aminosäuren und besitzt ein Molekulargewicht von 77,8 kDa (25). Das Protein besteht aus einer größeren katalytischen Domäne, die ein zentrales Eisen(II)-Atom enthält, dass für die zweistufige LTA4-Bildung aus Arachidonsäure benötigt wird, und einer kleineren C2-ähnlichen Domäne, die Bereiche für die Membran- sowie Ca2+-Bindung enthält. Durch Stimulation von intakten Zellen kommt es zu einer Translokation der 5-LO an die Kernmembran. Die Wechselwirkung mit dem membranständigen FLAP fördert die 5-LO-Leukotrienbildung. Die vorliegende Arbeit beschäftigte sich mit niedermolekularen Modifikationen der 5-LO durch U-73122 und Glutathion sowie mit der Charakterisierung von 5-LO-Inhibitoren. U-73122 ist ein Inhibitor, der in vitro und in vivo mit einem IC50-Wert von 30 nM bzw. 2,4 µM die 5-LO-Aktivität hemmt (2). U-73122 verfügt über eine thiol-reaktive Maleinimid-Gruppe, wodurch die Substanz kovalent an einige 5-LO-Cysteine (Cys-99, -159 und weitere) binden kann. Entsprechende U-73122-5-LO-Peptide konnten nach Trypsin-Verdau der 5-LO mit MALDI-MS-Messungen nachgewiesen werden. Für diesen Zweck musste eine effiziente Aufreinigung für native 5-LO (Reinheit > 95%) entwickelt werden. Um die Veränderung der 5-LO-Aktivität nach U-73122-Zugabe zu untersuchen, wurden Cystein/Serin-5-LO-Mutanten hergestellt. Es konnte festgestellt werden, dass die Mutante C416S-5-LO nicht mehr effektiv durch U-73122 gehemmt werden konnte. Daher ist anzunehmen, dass U-73122 an Cystein-416 der 5-LO bindet und die 5-LO-Produktbildung hemmt. Auf der 5-LO-Oberfläche kann ein Bereich lokalisiert werden, der einen Zugang für das Substrat zum aktiven Zentrum der 5-LO bilden könnte (238,239). Dieser Bereich liegt in unmittelbarer Nähe zu Cystein-416. Daher besteht die Möglichkeit, dass U-73122, nachdem es an Cystein-416 gebunden hat, diesen Bereich hemmend beeinflussen kann. Es konnte nachgewiesen werden, dass Glutathion an mehrere Cysteine der 5-LO (Cystein-99, -264 und -449) kovalent binden kann. Um Veränderungen der 5-LO-Aktivität durch in vivo Glutathionylierungen zu zeigen, wurden HeLa-Zellen mit 5-LO, Cystein-/Serin-5-LO-Mutanten sowie FLAP transfiziert und mit Diamid inkubiert. Es konnte festgestellt werden, dass die native sowie FLAP-gesteigerte 5-LO-Produktbildung durch Diamid gehemmt wird. Dies konnte ebenfalls für die Mutante 3W-5-LO beobachtet werden. Zusätzlich wurden verschiedene Cystein-/Serin-5-LO-Punktmutanten sowie eine 4fach Mutante (C159S/C300S/C416S/C418S-5-LO = 2D-5-LO) untersucht. Das Verhalten dieser Mutanten konnte in drei Gruppen eingeteilt werden. Gruppe A (C159S-, C300S- und C418S-5-LO) wurde durch Diamid nicht beeinflusst. Gruppe B (C416S- und 2D-5-LO) zeigte eine sehr starke Stimulation der 5-LO±FLAP-Leukotrienbildung nach Zugabe von Diamid. Bei Gruppe C (C99S-, C264S- und C449S-5-LO) konnte eine FLAP-gesteigerte 5-HETE-Bildung beobachtet werden. Durch Diamid kommt es zu Glutathionylierungen von zellulären Proteinen, da reduziertes Glutathion (GSH) zu reaktiveren oxidierten Glutathion (GSSG) umgesetzt wird. An der 5-LO-Oberfläche können in Folge an verschiedenen Cysteinen Glutathione binden. Durch die Glutathion-Bindung wird eine stark polare Struktur auf der 5-LO-Oberfläche eingebracht. Dadurch kommt es zu einer verminderten Membranbindung und Produktbildung der nativen 5-LO. Die 5-LO-Oberfläche der 2D-5-LO-Mutante kann an verschiedenen Positionen keine Glutathione mehr binden, es kommt es zu einer stärkeren Wechselwirkung mit Membranbestandteilen und zu einer erhöhten 5-LO-Leukotrienbildung. Für Celecoxib konnte gezeigt werden, dass neben der COX2-Hemmung auch die 5-LO-Aktivität mit einem IC50-Wert von 3-10 µM gehemmt werden kann (268). Im Rahmen dieser Arbeit wurden HeLa-Zellen mit 5-LO±FLAP transfiziert, um den Einfluss von Celecoxib auf FLAP zu untersuchen. Celecoxib führt zu einer direkten Hemmung der 5-LO. ML3000 (Licofelon) wurde als dualer COX/5-LO-Inhibitor entwickelt und hemmt die 5-LO-Aktivität in intakten Zellen, aber nicht im Homogenat. Daher wurden Versuche mit 5-LO±FLAP-tranfizierten HeLa-Zellen durchgeführt, um den Einfluss von ML3000 auf die FLAP-gesteigerte 5-LO-Leukotrienbildung zu zeigen. Aus diesen und weiteren Ergebnissen unserer Arbeitsgruppe konnte gefolgert werden, dass ML3000 ein FLAP-Inhibitor ist (277). Garsubellin A ist strukturverwandt zu Hyperforin, einem dualen COX/5-LO-Inhibitor (204). Garsubellin A hemmt die 5-LO-Aktivität im Homogenat von PMNL und am gereinigten Enzym mit einer IC50 von 10-30 µM. Verbindungen, die den Bicyclo[3.3.1]nonan-Grundkörper des Garsubellin A und Hyperforin enthalten, wurden auf ihr inhibitorisches Potential getestet. Es konnte gezeigt werden, dass der Bicyclo[3.3.1]nonan-Grundkörper alleine nicht für eine 5-LO-Hemmung ausreicht, sondern eine freie Carbonsäure sowie eine bis zwei Prenylierungen vorliegen müssen, um eine 5-LO-Hemmung zu erzielen. Sind diese Voraussetzungen vorhanden, wird die 5-LO-Aktivität in intakten PMNL mit einer IC50 von 10 µM und an gereinigter 5-LO mit 0,3-1 µM gehemmt.
Background: Nitric oxide (NO) is an essential vasodilator. In vascular diseases, oxidative stress attenuates NO signaling by both chemical scavenging of free NO and oxidation and down-regulation of its major intracellular receptor, the alpha/beta heterodimeric heme-containing soluble guanylate cyclase (sGC). Oxidation can also induce loss of sGC's heme and responsiveness to NO.
Results: sGC activators such as BAY 58-2667 bind to oxidized/heme-free sGC and reactivate the enzyme to exert disease-specific vasodilation. Here we show that oxidation-induced down-regulation of sGC protein extends to isolated blood vessels. Mechanistically, degradation was triggered through sGC ubiquitination and proteasomal degradation. The heme-binding site ligand, BAY 58-2667, prevented sGC ubiquitination and stabilized both alpha and beta subunits.
Conclusion: Collectively, our data establish oxidation-ubiquitination of sGC as a modulator of NO/cGMP signaling and point to a new mechanism of action for sGC activating vasodilators by stabilizing their receptor, oxidized/heme-free sGC.
Poster presentation: Self-organized critical (SOC) systems are complex dynamical systems that may express cascades of events, called avalanches [1]. The SOC state was proposed to govern brain function, because of its activity fluctuations over many orders of magnitude, its sensitivity to small input and its long term stability [2,3]. In addition, the critical state is optimal for information storage and processing [4]. Both hallmark features of SOC systems, a power law distribution f(s) for the avalanche size s and a branching parameter (bp) of unity, were found for neuronal avalanches recorded in vitro [5]. However, recordings in vivo yielded contradictory results [6]. Electrophysiological recordings in vivo only cover a small fraction of the brain, while criticality analysis assumes that the complete system is sampled. We hypothesized that spatial subsampling might influence the observed avalanche statistics. In addition, SOC models can have different connectivity, but always show a power law for f(s) and bp = 1 when fully sampled. This may not be the case under subsampling, however. Here, we wanted to know whether a state change from awake to asleep could be modeled by changing the connectivity of a SOC model without leaving the critical state. We simulated a SOC model [1] and calculated f(s) and bp obtained from sampling only the activity of a set of 4 × 4 sites, representing the electrode positions in the cortex. We compared these results with results obtained from multielectrode recordings of local field potentials (LFP) in the cortex of behaving monkeys. We calculated f(s) and bp for the LFP activity recorded while the monkey was either awake or asleep and compared these results to results obtained from two subsampled SOC model with different connectivity. f(s) and bp were very similar for both the experiments and the subsampled SOC model, but in contrast to the fully sampled model, f(s) did not show a power law and bp was smaller than unity. With increasing the distance between the sampling sites, f(s) changed from "apparently supercritical" to "apparently subcritical" distributions in both the model and the LFP data. f(s) and bp calculated from LFP recorded during awake and asleep differed. These changes could be explained by altering the connectivity in the SOC model. Our results show that subsampling can prevent the observation of the characteristic power law and bp in SOC systems, and misclassifications of critical systems as sub- or supercritical are possible. In addition, a change in f(s) and bp for different states (awake/asleep) does not necessarily imply a change from criticality to sub- or supercriticality, but can also be explained by a change in the effective connectivity of the network without leaving the critical state.
Poster presentation: The brain is autonomously active and this self-sustained neural activity is in general modulated, but not driven, by the sensory input data stream [1,2]. Traditionally one has regarded this eigendynamics as resulting from inter-modular recurrent neural activity [3]. Understanding the basic modules for cognitive computation is, in this view, the primary focus of research and the overall neural dynamics would be determined by the the topology of the intermodular pathways. Here we examine an alternative point of view, asking whether certain aspects of the neural eigendynamics have a central functional role for overall cognitive computation [4,5]. Transiently stable neural activity is regularly observed on the cognitive time-scale of 80–100 ms, with indications that neural competition [6] plays an important role in the selection of the transiently stable neural ensembles [7], also denoted winning coalitions [8]. We report on a theory approach which implements these two principles, transient-state dynamics and neural competition, in terms of an associative neural network with clique encoding [9]. A cognitive system [10] with a non-trivial internal eigendynamics has two seemingly contrasting tasks to fulfill. The internal processes need to be regular and not chaotic on one side, but sensitive to the afferent sensory stimuli on the other side. We show, that these two contrasting demands can be reconciled within our approach based on competitive transient-state dynamics, when allowing the sensory stimuli to modulate the competition for the next winning coalition. By testing the system with the bars problem, we find an emerging cognitive capability. Only based on the two basic architectural principles, neural competition and transient-state dynamics, with no explicit algorithmic encoding, the system performs on its own a non-linear independent component analysis of input data stream. The system has rudimentary biological features. All learning is local Hebbian-style, unsupervised and online. It exhibits an ever-ongoing eigendynamics and at no time is the state or the value of synaptic strengths reset or the system restarted; there is no separation between training and performance. We believe that this kind of approach – cognitive computation with autonomously active neural networks – to be an emerging field, relevant both for system neuroscience and synthetic cognitive systems.
Poster presentation: How can two distant neural assemblies synchronize their firings at zero-lag even in the presence of non-negligible delays in the transfer of information between them? Neural synchronization stands today as one of the most promising mechanisms to counterbalance the huge anatomical and functional specialization of the different brain areas. However, and albeit more evidence is being accumulated in favor of its functional role as a binding mechanism of distributed neural responses, the physical and anatomical substrate for such a dynamic and precise synchrony, especially zero-lag even in the presence of non-negligible delays, remains unclear. Here we propose a simple network motif that naturally accounts for zero-lag synchronization of spiking assemblies of neurons for a wide range of temporal delays. We demonstrate that when two distant neural assemblies do not interact directly but relaying their dynamics via a third mediating single neuron or population and eventually achieve zero-lag coherent firing. Extensive numerical simulations of populations of Hodgkin-Huxley neurons interacting in such a network are analyzed. The results show that even with axonal delays as large as 15 ms the distant neural populations can synchronize their firings at zero-lag in a millisecond precision after the exchange of a few spikes. The role of noise and a distribution of axonal delays in the synchronized dynamics of the neural populations are also studied confirming the robustness of this sync mechanism. The proposed network module is densely embedded within the complex functional architecture of the brain and especially within the reciprocal thalamocortical interactions where the role of indirect pathways mimicking direct cortico-cortical fibers has been already suggested to facilitate trans-areal cortical communication. In summary the robust neural synchronization mechanism presented here arises as a consequence of the relay and redistribution of the dynamics performed by a mediating neuronal population. In opposition to previous works, neither inhibitory, gap junctions, nor complex networks need to be invoked to provide a stable mechanism of zero-phase correlated activity of neural populations in the presence of large conduction delays.
Poster presentation: The analysis of neuronal processes distributed across multiple cortical areas aims at the identification of interactions between signals recorded at different sites. Such interactions can be described by measuring the stability of phase angles in the case of oscillatory signals or other forms of signal dependencies for less regular signals. Before, however, any form of interaction can be analyzed at a given time and frequency, it is necessary to assess whether all potentially contributing signals are present. We have developed a new statistical procedure for the detection of coincident power in multiple simultaneously recorded analog signals, allowing the classification of events as 'non-accidental co-activation'. This method can effectively operate on single trials, each lasting only for a few seconds. Signals need to be transformed into time-frequency space, e.g. by applying a short-time Fourier transformation using a Gaussian window. The discrete wavelet transform (DWT) is used in order to weight the resulting power patterns according to their frequency. Subsequently, the weighted power patterns are binarized via applying a threshold. At this final stage, significant power coincidence is determined across all subgroups of channel combinations for individual frequencies by selecting the maximum ratio between observed and expected duration of co-activation as test statistic. The null hypothesis that the activity in each channel is independent from the activity in every other channel is simulated by independent, random rotation of the respective activity patterns. We applied this procedure to single trials of multiple simultaneously sampled local field potentials (LFPs) obtained from occipital, parietal, central and precentral areas of three macaque monkeys. Since their task was to use visual cues to perform a precise arm movement, co-activation of numerous cortical sites was expected. In a data set with 17 channels analyzed, up to 13 sites expressed simultaneous power in the range between 5 and 240 Hz. On average, more than 50% of active channels participated at least once in a significant power co-activation pattern (PCP). Because the significance of such PCPs can be evaluated at the level of single trials, we are confident that this procedure is useful to study single trial variability with sufficient accuracy that much of the behavioral variability can be explained by the dynamics of the underlying distributed neuronal processes.
Poster presentation: Background To test the importance of synchronous neuronal firing for information processing in the brain, one has to investigate if synchronous firing strength is correlated to the experimental subjects. This requires a tool that can compare the strength of the synchronous firing across different conditions, while at the same time it should correct for other features of neuronal firing such as spike rate modulation or the auto-structure of the spike trains that might co-occur with synchronous firing. Here we present the bi- and multivariate extension of previously developed method NeuroXidence [1,2], which allows for comparing the amount of synchronous firing between different conditions. ...
Poster presentation: Introduction The ability of neurons to emit different firing patterns is considered relevant for neuronal information processing. In dopaminergic neurons, prominent patterns include highly regular pacemakers with separate spikes and stereotyped intervals, processes with repetitive bursts and partial regularity, and irregular spike trains with nonstationary properties. In order to model and quantify these processes and the variability of their patterns with respect to pharmacological and cellular properties, we aim to describe the two dimensions of burstiness and regularity in a single model framework. Methods We present a stochastic spike train model in which the degree of burstiness and the regularity of the oscillation are described independently and with two simple parameters. In this model, a background oscillation with independent and normally distributed intervals gives rise to Poissonian spike packets with a Gaussian firing intensity. The variability of inter-burst intervals and the average number of spikes in each burst indicate regularity and burstiness, respectively. These parameters can be estimated by fitting the model to the autocorrelograms. This allows to assign every spike train a position in the two-dimensional space described by regularity and burstiness and thus, to investigate the dependence of the firing patterns on different experimental conditions. Finally, burst detection in single spike trains is possible within the model because the parameter estimates determine the appropriate bandwidth that should be used for burst identification. Results and Discussion We applied the model to a sample data set obtained from dopaminergic substantia nigra and ventral tegmental area neurons recorded extracellularly in vivo and studied differences between the firing activity of dopaminergic neurons in wildtype and K-ATP channel knock-out mice. The model is able to represent a variety of discharge patterns and to describe changes induced pharmacologically. It provides a simple and objective classification scheme for the observed spike trains into pacemaker, irregular and bursty processes. In addition to the simple classification, changes in the parameters can be studied quantitatively, also including the properties related to bursting behavior. Interestingly, the proposed algorithm for burst detection may be applicable also to spike trains with nonstationary firing rates if the remaining parameters are unaffected. Thus, the proposed model and its burst detection algorithm can be useful for the description and investigation of neuronal firing patterns and their variability with cellular and experimental conditions.
Poster presentation: Coordinated neuronal activity across many neurons, i.e. synchronous or spatiotemporal pattern, had been believed to be a major component of neuronal activity. However, the discussion if coordinated activity really exists remained heated and controversial. A major uncertainty was that many analysis approaches either ignored the auto-structure of the spiking activity, assumed a very simplified model (poissonian firing), or changed the auto-structure by spike jittering. We studied whether a statistical inference that tests whether coordinated activity is occurring beyond chance can be made false if one ignores or changes the real auto-structure of recorded data. To this end, we investigated the distribution of coincident spikes in mutually independent spike-trains modeled as renewal processes. We considered Gamma processes with different shape parameters as well as renewal processes in which the ISI distribution is log-normal. For Gamma processes of integer order, we calculated the mean number of coincident spikes, as well as the Fano factor of the coincidences, analytically. We determined how these measures depend on the bin width and also investigated how they depend on the firing rate, and on rate difference between the neurons. We used Monte-Carlo simulations to estimate the whole distribution for these parameters and also for other values of gamma. Moreover, we considered the effect of dithering for both of these processes and saw that while dithering does not change the average number of coincidences, it does change the shape of the coincidence distribution. Our major findings are: 1) the width of the coincidence count distribution depends very critically and in a non-trivial way on the detailed properties of the inter-spike interval distribution, 2) the dependencies of the Fano factor on the coefficient of variation of the ISI distribution are complex and mostly non-monotonic. Moreover, the Fano factor depends on the very detailed properties of the individual point processes, and cannot be predicted by the CV alone. Hence, given a recorded data set, the estimated value of CV of the ISI distribution is not sufficient to predict the Fano factor of the coincidence count distribution, and 3) spike jittering, even if it is as small as a fraction of the expected ISI, can falsify the inference on coordinated firing. In most of the tested cases and especially for complex synchronous and spatiotemporal pattern across many neurons, spike jittering increased the likelihood of false positive finding very strongly. Last, we discuss a procedure [1] that considers the complete auto-structure of each individual spike-train for testing whether synchrony firing occurs at chance and therefore overcomes the danger of an increased level of false positives.
Poster presentation: An important challenge in neuroscience is understanding how networks of neurons go about processing information. Synapses are thought to play an essential role in cellular information processing however quantitative and mathematical models of the underlying physiologic processes that occur at synaptic active zones are lacking. We are generating mathematical models of synaptic vesicle dynamics at a well-characterized model synapse, the Drosophila larval neuromuscular junction. This synapse's simplicity, accessibility to various electrophysiological recording and imaging techniques, and the genetic malleability intrinsic to Drosophila system make it ideal for computational and mathematical studies. We have employed a reductionist approach and started by modeling single presynaptic boutons. Synaptic vesicles can be divided into different pools; however, a quantitative understanding of their dynamics at the Drosophila neuromuscular junction is lacking [4]. We performed biologically realistic simulations of high and low release probability boutons [3] using partial differential equations (PDE) taking into account not only the evolution in time but also the spatial structure in two dimensions (the extension to three dimensions will be implemented soon). PDEs are solved using UG, a program library for the calculation of multi-dimensional PDEs solved using a finite volume approach and implicit time stepping methods leading to extended linear equation systems be solvedwith multi-grid methods [3,4]. Numerical calculations are done on multi-processor computers for fast calculations using different parameters in order to asses the biological feasibility of different models. In preliminary simulations, we modeled vesicle dynamics as a diffusion process describing exocytosis as Neumann streams at synaptic active zones. The initial results obtained with these models are consistent with experimental data. However, this should be regarded as a work in progress. Further refinements will be implemented, including simulations using morphologically realistic geometries which were generated from confocal scans of the neuromuscular junction using NeuRA (a Neuron Reconstruction Algorithm). Other parameters such as glutamate diffusion and reuptake dynamics, as well as postsynaptic receptor kinetics will be incorporated as well.
Poster presentation: Characterizing neuronal encoding is essential for understanding information processing in the brain. Three methods are commonly used to characterize the relationship between neural spiking activity and the features of putative stimuli. These methods include: Wiener-Volterra kernel methods (WVK), the spike-triggered average (STA), and more recently, the point process generalized linear model (GLM). We compared the performance of these three approaches in estimating receptive field properties and orientation tuning of 251 V1 neurons recorded from 2 monkeys during a fixation period in response to a moving bar. The GLM consisted of two formulations of the conditional intensity function for a point process characterization of the spiking activity: one with a stimulus only component and one with the stimulus and spike history. We fit the GLMs by maximum likelihood using GLMfit in Matlab. Goodness-of-fit was assessed using cross-validation with Kolmogorov-Smirnov (KS) tests based on the time-rescaling theorem to evaluate the accuracy with which each model predicts the spiking activity of individual neurons and for each movement direction (4016 models in total, for 251 neurons and 16 different directions). The GLMs that considered spike history of up to 35 ms, accurately predicted neuronal spiking activity (95% confidence intervals for KS test) with a performance of 97.0% (3895/4016) for the training data, and 96.5% (3876/4016) for the test data. If spike history was not considered, performance dropped to 73,1% in the training and 71.3% in the testing data. In contrast, the WVF and the STA predicted spiking accurately for 24.2% and 44.5% of the test data examples respectively. The receptive field size estimates obtained from the GLM (with and without history), WVF and STA were comparable. Relative to the GLM orientation tuning was underestimated on average by a factor of 0.45 by the WVF and the STA. The main reason for using the STA and WVF approaches is their apparent simplicity. However, our analyses suggest that more accurate spike prediction as well as more credible estimates of receptive field size and orientation tuning can be computed easily using GLMs implemented in Matlab with standard functions such as GLMfit.
Poster presentation: Introduction Rhythmic synchronization of neural activity in the gamma-frequency range (30–100 Hz) was observed in many brain regions; see the review in [1]. The functional relevance of these oscillations remains to be clarified, a task that requires modeling of the relevant aspects of information processing. The temporal correlation hypothesis, reviewed in [2], proposes that the temporal correlation of neural units provides a means to group the neural units into so-called neural assemblies that are supposed to represent mental objects. Here, we approach the modeling of the temporal grouping of neural units from the perspective of oscillatory neural network systems based on phase model oscillators. Patterns are assumed to be stored in the network based on Hebbian memory and assemblies are identified with phase-locked subset of these patterns. Going beyond foregoing discussions, we demonstrate the combination of two recently discussed mechanisms, referred to as "acceleration" [3] and "pooling" [4]. The combination realizes in a complementary manner a competition for activity on a local scale, while providing a competition for coherence among different assemblies on a non-local scale. ...
Poster presentation: Introduction Adequate anesthesia is crucial to the success of surgical interventions and subsequent recovery. Neuroscientists, surgeons, and engineers have sought to understand the impact of anesthetics on the information processing in the brain and to properly assess the level of anesthesia in an non-invasive manner. Studies have indicated a more reliable depth of anesthesia (DOA) detection if multiple parameters are employed. Indeed, commercial DOA monitors (BIS, Narcotrend, M-Entropy and A-line ARX) use more than one feature extraction method. Here, we propose TESPAR (Time Encoded Signal Processing And Recognition) a time domain signal processing technique novel to EEG DOA assessment that could enhance existing monitoring devices. ...
Poster presentation: Functional connectivity of the brain describes the network of correlated activities of different brain areas. However, correlation does not imply causality and most synchronization measures do not distinguish causal and non-causal interactions among remote brain areas, i.e. determine the effective connectivity [1]. Identification of causal interactions in brain networks is fundamental to understanding the processing of information. Attempts at unveiling signs of functional or effective connectivity from non-invasive Magneto-/Electroencephalographic (M/EEG) recordings at the sensor level are hampered by volume conduction leading to correlated sensor signals without the presence of effective connectivity. Here, we make use of the transfer entropy (TE) concept to establish effective connectivity. The formalism of TE has been proposed as a rigorous quantification of the information flow among systems in interaction and is a natural generalization of mutual information [2]. In contrast to Granger causality, TE is a non-linear measure and not influenced by volume conduction. ...