Entwicklung massenspektrometrischer Isotopenverdünnungstechniken für die zuverlässige Bestimmung von Elementspuren und Schwefelspezies in Erdölprodukten

Einer der Hauptschwerpunkte der Arbeit lag in der Entwicklung einer spezies-spezifischen und einer spezies-unspezifischen GC-ICP-Q-MSIVA von Schwefelspezies in Petroprodukten. Es wurden hierzu Indikatoren, ausgehend von elementarem 34S-angereichertem Schwefel, im Mikromaßstab synthetisiert. Für die spezies-spezifische GC-ICP-Q-MSIVA wurde die erstmalige Synthese von 34S-markiertem Thiophen, Dibenzothiophen und 4-Methyldibenzothiophen verwirklicht. Als Indikatorsynthese für die spezies-unspezifische GC-ICP-Q-MSIVA erfolgte die erstmalige Darstellung von 34S-angereichertem Dimethyldisulid. Mit Hilfe der synthetisierten Verbindungen wurden spezies-spezifische und spezies-unspezifische massenspektrometrische Isotopenverdünnungsanalysen von Schwefelspezies in Petroprodukten durchgeführt. Vor allen GC-ICP-Q-MSIVA-Analysen erfolgte eine umfangreiche Speziesidentifizierung durch Aufstockexperimente mit kommerziell erhältlichen Standards und mit einem mit der GC gekoppelten Elektronenstoß (EI)-MS. Beide ICP-Q-MS Methoden zeichnen sich durch sehr niedrige Nachweisgrenzen (7 ng S/g) aus, welche auch eine Anwendbarkeit auf tiefentschwefelte Kraftstoffe garantieren. Mit der spezies-unspezifischen GC-ICP-Q-MSIVA ist neben einer Speziesanalyse auch eine Gesamtschwefelanalyse durch Aufsummierung aller in der Probe vorhandenen Spezies möglich. Es wurde im Rahmen dieser Arbeit auch der Einfluss möglicher Empfindlichkeitsänderungen des ICP-Q-MS durch koeluierende Kohlenwasserstoffe überprüft, wobei diese erwartungsgemäß auf das Ergebnis der spezies-spezifischen und spezies-unspezifischen GC-ICP-Q-MSIVA keinerlei Einfluss haben. Der zweite Hauptschwerpunkt der Arbeit lag auf der Ausarbeitung routinefähiger, schneller und zuverlässiger Methoden zur Gesamtelementspurenanalytik von Schwefel und Schwermetallen in Erdölen und Petroprodukten. Für die Gesamtschwefelanalyse wurde eine MSIVA nach thermaler Verdampfung mit 34S-markierten Dibenzothiophen als Indikator entwickelt. Die neu entwickelte Methode erlaubt eine sehr schnelle Bestimmung des Gesamtschwefelgehalts, wobei die eigentliche Messung des Isotopenverhältnisses innerhalb von Sekunden nach der Injektion der Probe erfolgt. Weiterhin zeichnet sich die Methode durch Robustheit und eine niedrige Nachweisgrenze (40 ng S/g) aus. Für die Analyse von Schwermetallen wurden erstmals Möglichkeiten einer direkten MSIVA von Erdölproben ohne zeitraubenden, kontaminationsträchtigen Aufschluss bzw. die schwierige Erzeugung einer Mikroemulsion zwischen hydrophober Probe und wässrigem Indikator entwickelt. Um eine homogene Verteilung des Indikators in der hydrophoben Probe zu ermöglichen, musste ausgehend von den zur Verfügung stehenden wässrigen Indikatorlösungen, eine Überführung des Indikators in ein organisches Lösungsmittel erfolgen. Hierzu wurde der jeweilige Metallindikator unter Komplexierung aus wässrigen Metallindikatorlösungen extrahiert. Für die Analyse der mit diesen Indikatorlösungen in organischer Phase versetzten Proben wurden zwei alternative Methoden ausgearbeitet. Bei der mit der Laserablation (LA) kombinierten ICP-SF-MSIVA wird die isotopenverdünnte Probe aus einer eigens für diesen Zweck entwickelten Probenhalterung ablatiert und so dem ICP-SF-MS zugeführt wird. Bei zeitlich sich verändernden Intensitäten der gemessenen Isotope werden aber reproduzierbare und konstante Isotopenverhältnisse erhalten. Im Falle einer homogenen Verteilung der Metallspuren wurde eine hervorragende Übereinstimmung mit Vergleichsmethoden und einem Referenzmaterial festgestellt. Im Falle einer heterogenen partikulären Verteilung der Metallspuren, wie sie z.B. bei Eisenspuren in den Erdölen vorlag, ist die Anwendbarkeit der LA-ICP-SF-MSIVA aufgrund des kleinen Probenvolumens (20 µL) jedoch begrenzt. Als Alternative zur LA-ICP-SF-MSIVA wurde ein System unter Verwendung der Fließinjektion für die Zuführung der isotopenverdünnten Probe zum ICP-SF-MS ausgearbeitet. Die isotopenverdünnte Probe wird hierbei in einen Eluentenstrom von Toluol injiziert und mit Hilfe einer Total-Consumption-Zerstäuber/Sprühkammer-Einheit vollständig bei einer Flussrate von 10 µL/min in das Plasma eingebracht. Neben einer nochmaligen Verkürzung der Analysenzeit und Vereinfachung der Probenvorbereitung bietet diese Methode zusätzlich stark verbesserte Nachweisgrenzen (z.B. Ni 0,9 ng/g). Leider sind mit diesem Verfahren bis jetzt nur Ni und Mo zuverlässig bestimmbar. Das in dieser Arbeit ausgearbeitete Methodenpaket erlaubt erstmals eine breite Einführung der ICP-MSIVA als zuverlässige Methode in die Routineanalytik der Petroindustrie. Durch die bewiesene Zuverlässigkeit, den geringen Zeitaufwand und die Robustheit der Methoden steht ihrem routinemäßigen Einsatz, außer einer weitergehenderen Automatisierung einzelner Verfahrensteile, prinzipiell nichts entgegen.

Statistical problems related to excitation threshold and reset value of membrane potentials

Die vorliegende Arbeit ist motiviert durch biologische Fragestellungen bezüglich des Verhaltens von Membranpotentialen in Neuronen. Ein vielfach betrachtetes Modell für spikende Neuronen ist das Folgende. Zwischen den Spikes verhält sich das Membranpotential wie ein Diffusionsprozess X der durch die SDGL dX_t= beta(X_t) dt+ sigma(X_t) dB_t gegeben ist, wobei (B_t) eine Standard-Brown'sche Bewegung bezeichnet. Spikes erklärt man wie folgt. Sobald das Potential X eine gewisse Exzitationsschwelle S überschreitet entsteht ein Spike. Danach wird das Potential wieder auf einen bestimmten Wert x_0 zurückgesetzt. In Anwendungen ist es manchmal möglich, einen Diffusionsprozess X zwischen den Spikes zu beobachten und die Koeffizienten der SDGL beta() und sigma() zu schätzen. Dennoch ist es nötig, die Schwellen x_0 und S zu bestimmen um das Modell festzulegen. Eine Möglichkeit, dieses Problem anzugehen, ist x_0 und S als Parameter eines statistischen Modells aufzufassen und diese zu schätzen. In der vorliegenden Arbeit werden vier verschiedene Fälle diskutiert, in denen wir jeweils annehmen, dass das Membranpotential X zwischen den Spikes eine Brown'sche Bewegung mit Drift, eine geometrische Brown'sche Bewegung, ein Ornstein-Uhlenbeck Prozess oder ein Cox-Ingersoll-Ross Prozess ist. Darüber hinaus beobachten wir die Zeiten zwischen aufeinander folgenden Spikes, die wir als iid Treffzeiten der Schwelle S von X gestartet in x_0 auffassen. Die ersten beiden Fälle ähneln sich sehr und man kann jeweils den Maximum-Likelihood-Schätzer explizit angeben. Darüber hinaus wird, unter Verwendung der LAN-Theorie, die Optimalität dieser Schätzer gezeigt. In den Fällen OU- und CIR-Prozess wählen wir eine Minimum-Distanz-Methode, die auf dem Vergleich von empirischer und wahrer Laplace-Transformation bezüglich einer Hilbertraumnorm beruht. Wir werden beweisen, dass alle Schätzer stark konsistent und asymptotisch normalverteilt sind. Im letzten Kapitel werden wir die Effizienz der Minimum-Distanz-Schätzer anhand simulierter Daten überprüfen. Ferner, werden Anwendungen auf reale Datensätze und deren Resultate ausführlich diskutiert.

Resa diagnostica di anamnesi, EEG intercritico ed home-made video negli episodi parossistici notturni: confronto con la VEPSG

Poiché la diagnosi differenziale degli episodi parossistici notturni è affidata alla VEPSG, tenendo conto dei limiti di tale metodica, il progetto attuale ha lo scopo di definire la resa diagnostica di strumenti alternativi alla VEPSG: anamnesi, home-made video ed EEG intercritico. Sono stati reclutati consecutivamente 13 pazienti, afferiti al nostro Dipartimento per episodi parossistici notturni. Ciascun paziente è stato sottoposto ad un protocollo diagnostico standardizzato. A 5 Medici Esperti in Epilessia e Medicina del Sonno è stato chiesto di formulare un orientamento diagnostico sulla base di anamnesi, EEG intercritico, home-made video e VEPSG. Attraverso l’elaborazione degli orientamenti diagnostici è stata calcolata la resa diagnostica delle procedure esaminate, a confronto con la VEPSG, attraverso il concetto di “accuratezza diagnostica”. Per 6 pazienti è stato possibile porre una diagnosi di Epilessia Frontale Notturna, per 2 di parasonnia, in 5 la diagnosi è rimasta dubbia. L’accuratezza diagnostica di ciascuna procedura è risultata moderata, con lievi differenze tra le diverse procedure (61.5% anamnesi; 66% home-made video; 69,2 % EEG intercritico). E’ essenziale migliorare ulteriormente l’accuratezza diagnostica di anamnesi, EEG intercritico ed home-made video, che possono risultare cruciali nei casi in cui la diagnosi non è certa o quando la VEPSG non è disponibile.

A new global wheat marketmodel (GLOWMM) for the analysis of wheat export prices

Food commodity prices fluctuations have important impacts on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, while there is an urgent need for appropriate policy responses. Perhaps new approaches are needed in order to better understand international spill-overs, the feedback between the real and the financial sectors and also the link between food and energy prices. In this paper, we present results from a new worldwide dynamic model that provides short and long-run impulse responses of wheat international prices to various real shocks.

Rationale for an adjunctive therapy with fenofibrate in pharmacoresistant nocturnal frontal lobe epilepsy (NFLE).

Nocturnal Frontal Lobe Epilepsy (NFLE) is characterized by onset during infancy or childhood with persistence in adulthood, family history of similar nocturnal episodes simulating non-REM parasomnias (sleep terrors or sleepwalking), general absence of morphological substrates, often by normal interictal electroencephalographical recordings (EEGs) during wakefulness. A family history of epilepsy may be present with Mendelian autosomal dominant inheritance has been described in some families. Recent studies indicate the involvement of neuronal nicotinic acetylcholine receptors (nAChRs) in the molecular mechanisms of NFLE. Mutations in the genes encoding for the α4 (CHRNA4) and ß2 (CHRNB2) subunits of the nAChR induce changes in the biophysical properties of nAChR, resulting generally in a “gain of function”. Preclinical studies report that activation of a nuclear receptor called type peroxisome proliferator-activated receptor (PPAR-α) by endogenous molecules or by medications (e.g. fenofibrate) reduces the activity of the nAChR and, therefore, may decrease the frequency of seizures. Thus, we hypothesize that negative modulation of nAChRs might represent a therapeutic strategy to be explored for pharmacological treatment of this form of epilepsy, which only partially responds to conventional antiepileptic drugs. In fact, carbamazepine, the current medication for NFLE, abolishes the seizures only in one third of the patients. The aim of the project is: 1)_to verify the clinical efficacy of adjunctive therapy with fenofibrate in pharmacoresistant NFLE and ADNFLE patients; focousing on the analysis of the polysomnographic action of the PPAR- agonist (fenofibrate). 2)_to demonstrate the subtended mechanism of efficacy by means of electrophysiological and behavioral experiments in an animal model of the disease: particularly, transgenic mice carrying the mutation in the nAChR 4 subunit (Chrna4S252F) homologous to that found in the humans. Given that a PPAR-α agonist, FENOFIBRATE, already clinically utilized for lipid metabolism disorders, provides a promising therapeutic avenue in the treatment of NFLE\ADNFLE.

Caratterizzazione bio-molecolar e ruolo di specie di Fusarium associate alla Fusariosi della spiga su frumento duro

La Fusariosi della spiga (FDS) è una fitopatia diffusa a livello mondiale che colpisce le colture cerealicole, tra cui il frumento duro, ed è in grado di causare gravi danni di tipo qualitativo ed economico. Le specie fungine responsabili appartengono al genere Fusarium, tra cui F. graminearum, F. culmorum e più recentemente F. poae. La conseguenza più rilevante riguarda la contaminazione della granella da micotossine, molecole prodotte dai miceti, considerate dalla comunità scientifica ad alto rischio per la salute dell’uomo e animali. L’eziologia è molto complessa, dal momento che su una stessa spiga di frumento possono coesistere più specie fungine che contribuiscono ad influenzare i quantitativi di micotossine prodotte. Lo scopo della ricerca è incentrato sulla caratterizzazione di ceppi di F. poae, in termini di potenziale patogeno e aggressività. Tramite l’allestimento di un saggio di inoculazione in vitro “Petri-dish” è stato possibile attribuire un indice di aggressività a ciascun isolato fungino, basato su parametri quali AUHPC e AUDPC standard, insieme ad altre variabili come la riduzione della lunghezza del coleottile e del tasso di germinazione. Il saggio è stato esteso anche a F. culmorum, per valutare la riproducibilità del test su altre specie fungine. Il test in vitro offre diversi vantaggi, tra cui affidabilità e rapidità di esecuzione ed è quindi adatto allo screening di ceppi patogeni da utilizzare in successive sperimentazioni. Gli stessi ceppi di F. poae, provenienti da una prova di inoculazione artificiale in serra su piante di frumento duro, sono stati caratterizzati dal punto di vista bio-molecolare. Poichè lo studio della fusariosi della spiga richiede la determinazione quantitativa della biomassa dei patogeni nei tessuti della pianta-ospite, anche in assenza di sintomi, il protocollo di Real-Time PCR con chimica SYBR® Green I qui sviluppato, ha dimostrato essere un buon compromesso tra attendibilità, rapidità e costi complessivi della metodica.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.

Interactions between short-term and long-term plasticity: shooting for a moving target

Far from being static transmission units, synapses are highly dynamical elements that change over multiple time scales depending on the history of the neural activity of both the pre- and postsynaptic neuron. Moreover, synaptic changes on different time scales interact: long-term plasticity (LTP) can modify the properties of short-term plasticity (STP) in the same synapse. Most existing theories of synaptic plasticity focus on only one of these time scales (either STP or LTP or late-LTP) and the theoretical principles underlying their interactions are thus largely unknown. Here we develop a normative model of synaptic plasticity that combines both STP and LTP and predicts specific patterns for their interactions. Recently, it has been proposed that STP arranges for the local postsynaptic membrane potential at a synapse to behave as an optimal estimator of the presynaptic membrane potential based on the incoming spikes. Here we generalize this approach by considering an optimal estimator of a non-linear function of the membrane potential and the long-term synaptic efficacy—which itself may be subject to change on a slower time scale. We find that an increase in the long-term synaptic efficacy necessitates changes in the dynamics of STP. More precisely, for a realistic non-linear function to be estimated, our model predicts that after the induction of LTP, causing long-term synaptic efficacy to increase, a depressing synapse should become even more depressing. That is, in a protocol using trains of presynaptic stimuli, as the initial EPSP becomes stronger due to LTP, subsequent EPSPs should become weakened and this weakening should be more pronounced with LTP. This form of redistribution of synaptic efficacies agrees well with electrophysiological data on synapses connecting layer 5 pyramidal neurons.

Spike-triggered reaction-time EEG as a possible assessment tool for driving ability

The impact of interictal epileptic activity (IEA) on driving is a rarely investigated issue. We analyzed the impact of IEA on reaction time in a pilot study. Reactions to simple visual stimuli (light flash) in the Flash test or complex visual stimuli (obstacle on a road) in a modified car driving computer game, the Steer Clear, were measured during IEA bursts and unremarkable electroencephalography (EEG) periods. Individual epilepsy patients showed slower reaction times (RTs) during generalized IEA compared to RTs during unremarkable EEG periods. RT differences were approximately 300 ms (p < 0.001) in the Flash test and approximately 200 ms (p < 0.001) in the Steer Clear. Prior work suggested that RT differences >100 ms may become clinically relevant. This occurred in 40% of patients in the Flash test and in up to 50% in the Steer Clear. When RT were pooled, mean RT differences were 157 ms in the Flash test (p < 0.0001) and 116 ms in the Steer Clear (p < 0.0001). Generalized IEA of short duration seems to impair brain function, that is, the ability to react. The reaction-time EEG could be used routinely to assess driving ability.

Inhibitory regulation of dendritic activity in vivo

The spatiotemporal control of neuronal excitability is fundamental to the inhibitory process. We now have a wealth of information about the active dendritic properties of cortical neurons including axonally generated sodium action potentials as well as local sodium spikelets generated in the dendrites, calcium plateau spikes, and NMDA spikes. All of these events have been shown to be highly modified by the spatiotemporal pattern of nearby inhibitory input which can drastically change the output firing mode of the neuron. This means that particular populations of interneurons embedded in the neocortical microcircuitry can more precisely control pyramidal cell output than has previously been thought. Furthermore, the output of any given neuron tends to feed back onto inhibitory circuits making the resultant network activity further dependent on inhibition. Network activity is therefore ultimately governed by the subcellular microcircuitry of the cortex and it is impossible to ignore the subcompartmentalization of inhibitory influence at the neuronal level in order to understand its effects at the network level. In this article, we summarize the inhibitory circuits that have been shown so far to act on specific dendritic compartments in vivo.

Gradient estimation in dendritic reinforcement learning

We study synaptic plasticity in a complex neuronal cell model where NMDA-spikes can arise in certain dendritic zones. In the context of reinforcement learning, two kinds of plasticity rules are derived, zone reinforcement (ZR) and cell reinforcement (CR), which both optimize the expected reward by stochastic gradient ascent. For ZR, the synaptic plasticity response to the external reward signal is modulated exclusively by quantities which are local to the NMDA-spike initiation zone in which the synapse is situated. CR, in addition, uses nonlocal feedback from the soma of the cell, provided by mechanisms such as the backpropagating action potential. Simulation results show that, compared to ZR, the use of nonlocal feedback in CR can drastically enhance learning performance. We suggest that the availability of nonlocal feedback for learning is a key advantage of complex neurons over networks of simple point neurons, which have previously been found to be largely equivalent with regard to computational capability.

Epileptogenic developmental venous anomaly: insights from simultaneous EEG/fMRI

Developmental venous anomalies (DVAs) are associated with epileptic seizures; however, the role of DVA in the epileptogenesis is still not established. Simultaneous interictal electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) recordings provide supplementary information to electroclinical data about the epileptic generators, and thus aid in the differentiation of clinically equivocal epilepsy syndromes. The main objective of our study was to characterize the epileptic network in a patient with DVA and epilepsy by simultaneous EEG/fMRI recordings. A 17-year-old woman with recently emerging generalized tonic-clonic seizures, and atypical generalized discharges, was investigated using simultaneous EEG/fMRI at the university hospital. Previous high-resolution MRI showed no structural abnormalities, except a DVA in the right frontal operculum. Interictal EEG recordings showed atypical generalized discharges, corresponding to positive focal blood oxygen level dependent (BOLD) correlates in the right frontal operculum, a region drained by the DVA. Additionally, widespread cortical bilateral negative BOLD correlates in the frontal and parietal lobes were delineated, resembling a generalized epileptic network. The EEG/fMRI recordings support a right frontal lobe epilepsy, originating in the vicinity of the DVA, propagating rapidly to both frontal and parietal lobes, as expressed on the scalp EEG by secondary bilateral synchrony. The DVA may be causative of focal epilepsies in cases where no concomitant epileptogenic lesions can be detected. Advanced imaging techniques, such as simultaneous EEG/fMRI, may thus aid in the differentiation of clinically equivocal epilepsy syndromes.