Detecção de refletores sísmicos por rede neural discreta

As redes neurais artificiais têm provado serem uma poderosa técnica na resolução de uma grande variedade de problemas de otimização. Nesta dissertação é desenvolvida uma nova rede neural, tipo recorrente, sem realimentação (self-feedback loops) e sem neurônios ocultos, para o processamento do sinal sísmico, para fornecer a posição temporal, a polaridade e as amplitudes estimadas dos refletores sísmicos, representadas pelos seus coeficientes de reflexão. A principal característica dessa nova rede neural consiste no tipo de função de ativação utilizada, a qual permite três possíveis estados para o neurônio. Busca-se estimar a posição dos refletores sísmicos e reproduzir as verdadeiras polaridades desses refletores. A idéia básica desse novo tipo de rede, aqui denominada rede neural discreta (RND), é relacionar uma função objeto, que descreve o problema geofísico, com a função de Liapunov, que descreve a dinâmica da rede neural. Deste modo, a dinâmica da rede leva a uma minimização local da sua função de Liapunov e consequentemente leva a uma minimização da função objeto. Assim, com uma codificação conveniente do sinal de saída da rede tem-se uma solução do problema geofísico. A avaliação operacional da arquitetura desta rede neural artificial é realizada em dados sintéticos gerados através do modelo convolucional simples e da teoria do raio. A razão é para explicar o comportamento da rede com dados contaminados por ruído, e diante de pulsos fonte de fases mínima, máxima e misturada.

Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

A decaying factor accounts for contained activity in neuronal networks with no need of hierarchical or modular organization

The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabasi-Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists.

Dinâmica de constituição e eventos geradores em redes de colaboração científica: estudo exploratório entre relações de coautoria e em bancas de defesas de teses e dissertações na área da Ciências da Comunicação.

O estudo da dinâmica de constituição de uma rede visa identificar que tipos de eventos ocorreram nas conexões entre os nós que levaram a formação da estrutura atual da rede em análise. Entender esses eventos é entender as formas específicas e estratégias de conectividade que deram origem a rede. O presente trabalho tem por objetivo analisar esses eventos geradores com foco específico em redes de colaboração científica, considerando relações de coautoria e participação em bancas de defesas de teses e dissertações. Analisando mais de 11.000 documentos específicos da área das Ciências da Comunicação, propomos dois tipos característicos de eventos que pretendem explicar a dinâmica de formação das redes em análise.

Cross-layer optimizations in multi-hop ad hoc networks

Unlike traditional wireless networks, characterized by the presence of last-mile, static and reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by collections of mobile and static terminals that exchange data by enabling each other's communication. Supporting multi-hop communication in a MANET is a challenging research area because it requires cooperation between different protocol layers (MAC, routing, transport). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. Conversely, the contention at MAC layer may cause a routing protocol to respond by initiating new routes queries and routing table updates. Multi-hop communication may also benefit the presence of pseudo-centralized virtual infrastructures obtained by grouping nodes into clusters. Clustering structures may facilitate the spatial reuse of resources by increasing the system capacity: at the same time, the clustering hierarchy may be used to coordinate transmissions events inside the network and to support intra-cluster routing schemes. Again, MAC and clustering protocols could be considered mutually cooperative protocol layers: the clustering scheme could support MAC layer coordination among nodes, by shifting the distributed MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the system benefits of the clustering scheme could be emphasized by the pseudo-centralized MAC layer with the support for differentiated access priorities and controlled contention. In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering and routing protocols in MANETs. As main contribution, we study and analyze the integration of MAC and clustering schemes to support multi-hop communication in large-scale ad hoc networks. A novel clustering protocol, named Availability Clustering (AC), is defined under general nodes' heterogeneity assumptions in terms of connectivity, available energy and relative mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol, named Differentiated Distributed Coordination Function (DDCF), whose focus is to implement adaptive access differentiation based on the node roles, which have been assigned by the upper-layer's clustering scheme. We extensively simulate the proposed clustering scheme by showing its effectiveness in dominating the network dynamics, under some stressing mobility models and different mobility rates. Based on these results, we propose a possible application of the cross-layer MAC+Clustering scheme to support the fast propagation of alert messages in a vehicular environment. At the same time, we investigate the integration of MAC and routing protocols in large scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by extending the AOMDV protocol with a novel load-balancing approach to concurrently distribute the traffic among the multiple paths. We also study the composition effect of a IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF), used to reduce the effects of self-contention among frames at the MAC layer. The protocol framework is modelled and extensively simulated for a large set of metrics and scenarios. For both the schemes, the simulation results reveal the benefits of the cross-layer MAC+routing and MAC+clustering approaches over single-layer solutions.

Studies of OPA1 pathogenic mechanisms in Dominant Optic Atrophy and novel protein function in mitochondrial DNA stability

The mitochondrion is an essential cytoplasmic organelle that provides most of the energy necessary for eukaryotic cell physiology. Mitochondrial structure and functions are maintained by proteins of both mitochondrial and nuclear origin. These organelles are organized in an extended network that dynamically fuses and divides. Mitochondrial morphology results from the equilibrium between fusion and fission processes, controlled by a family of “mitochondria-shaping” proteins. It is becoming clear that defects in mitochondrial dynamics can impair mitochondrial respiration, morphology and motility, leading to apoptotic cell death in vitro and more or less severe neurodegenerative disorders in vivo in humans. Mutations in OPA1, a nuclear encoded mitochondrial protein, cause autosomal Dominant Optic Atrophy (DOA), a heterogeneous blinding disease characterized by retinal ganglion cell degeneration leading to optic neuropathy (Delettre et al., 2000; Alexander et al., 2000). OPA1 is a mitochondrial dynamin-related guanosine triphosphatase (GTPase) protein involved in mitochondrial network dynamics, cytochrome c storage and apoptosis. This protein is anchored or associated on the inner mitochondrial membrane facing the intermembrane space. Eight OPA1 isoforms resulting from alternative splicing combinations of exon 4, 4b and 5b have been described (Delettre et al., 2001). These variants greatly vary among diverse organs and the presence of specific isoforms has been associated with various mitochondrial functions. The different spliced exons encode domains included in the amino-terminal region and contribute to determine OPA1 functions (Olichon et al., 2006). It has been shown that exon 4, that is conserved throughout evolution, confers functions to OPA1 involved in maintenance of the mitochondrial membrane potential and in the fusion of the network. Conversely, exon 4b and exon 5b, which are vertebrate specific, are involved in regulation of cytochrome c release from mitochondria, and activation of apoptosis, a process restricted to vertebrates (Olichon et al., 2007). While Mgm1p has been identified thanks to its role in mtDNA maintenance, it is only recently that OPA1 has been linked to mtDNA stability. Missense mutations in OPA1 cause accumulation of multiple deletions in skeletal muscle. The syndrome associated to these mutations (DOA-1 plus) is complex, consisting of a combination of dominant optic atrophy, progressive external ophtalmoplegia, peripheral neuropathy, ataxia and deafness (Amati- Bonneau et al., 2008; Hudson et al., 2008). OPA1 is the fifth gene associated with mtDNA “breakage syndrome” together with ANT1, PolG1-2 and TYMP (Spinazzola et al., 2009). In this thesis we show for the first time that specific OPA1 isoforms associated to exon 4b are important for mtDNA stability, by anchoring the nucleoids to the inner mitochondrial membrane. Our results clearly demonstrate that OPA1 isoforms including exon 4b are intimately associated to the maintenance of the mitochondrial genome, as their silencing leads to mtDNA depletion. The mechanism leading to mtDNA loss is associated with replication inhibition in cells where exon 4b containing isoforms were down-regulated. Furthermore silencing of exon 4b associated isoforms is responsible for alteration in mtDNA-nucleoids distribution in the mitochondrial network. In this study it was evidenced that OPA1 exon 4b isoform is cleaved to provide a 10kd peptide embedded in the inner membrane by a second transmembrane domain, that seems to be crucial for mitochondrial genome maintenance and does correspond to the second transmembrane domain of the yeasts orthologue encoded by MGM1 or Msp1, which is also mandatory for this process (Diot et al., 2009; Herlan et al., 2003). Furthermore in this thesis we show that the NT-OPA1-exon 4b peptide co-immuno-precipitates with mtDNA and specifically interacts with two major components of the mitochondrial nucleoids: the polymerase gamma and Tfam. Thus, from these experiments the conclusion is that NT-OPA1- exon 4b peptide contributes to the nucleoid anchoring in the inner mitochondrial membrane, a process that is required for the initiation of mtDNA replication and for the distribution of nucleoids along the network. These data provide new crucial insights in understanding the mechanism involved in maintenance of mtDNA integrity, because they clearly demonstrate that, besides genes implicated in mtDNA replications (i.e. polymerase gamma, Tfam, twinkle and genes involved in the nucleotide pool metabolism), OPA1 and mitochondrial membrane dynamics play also an important role. Noticeably, the effect on mtDNA is different depending on the specific OPA1 isoforms down-regulated, suggesting the involvement of two different combined mechanisms. Over two hundred OPA1 mutations, spread throughout the coding region of the gene, have been described to date, including substitutions, deletions or insertions. Some mutations are predicted to generate a truncated protein inducing haploinsufficiency, whereas the missense nucleotide substitutions result in aminoacidic changes which affect conserved positions of the OPA1 protein. So far, the functional consequences of OPA1 mutations in cells from DOA patients are poorly understood. Phosphorus MR spectroscopy in patients with the c.2708delTTAG deletion revealed a defect in oxidative phosphorylation in muscles (Lodi et al., 2004). An energetic impairment has been also show in fibroblasts with the severe OPA1 R445H mutation (Amati-Bonneau et al., 2005). It has been previously reported by our group that OPA1 mutations leading to haploinsufficiency are associated in fibroblasts to an oxidative phosphorylation dysfunction, mainly involving the respiratory complex I (Zanna et al., 2008). In this study we have evaluated the energetic efficiency of a panel of skin fibroblasts derived from DOA patients, five fibroblast cell lines with OPA1 mutations causing haploinsufficiency (DOA-H) and two cell lines bearing mis-sense aminoacidic substitutions (DOA-AA), and compared with control fibroblasts. Although both types of DOA fibroblasts maintained a similar ATP content when incubated in a glucose-free medium, i.e. when forced to utilize the oxidative phosphorylation only to produce ATP, the mitochondrial ATP synthesis through complex I, measured in digitonin-permeabilized cells, was significantly reduced in cells with OPA1 haploinsufficiency only, whereas it was similar to controls in cells with the missense substitutions. Furthermore, evaluation of the mitochondrial membrane potential (DYm) in the two fibroblast lines DOA-AA and in two DOA-H fibroblasts, namely those bearing the c.2819-2A>C mutation and the c.2708delTTAG microdeletion, revealed an anomalous depolarizing response to oligomycin in DOA-H cell lines only. This finding clearly supports the hypothesis that these mutations cause a significant alteration in the respiratory chain function, which can be unmasked only when the operation of the ATP synthase is prevented. Noticeably, oligomycin-induced depolarization in these cells was almost completely prevented by preincubation with cyclosporin A, a well known inhibitor of the permeability transition pore (PTP). This results is very important because it suggests for the first time that the voltage threshold for PTP opening is altered in DOA-H fibroblasts. Although this issue has not yet been addressed in the present study, several are the mechanisms that have been proposed to lead to PTP deregulation, including in particular increased reactive oxygen species production and alteration of Ca2+ homeostasis, whose role in DOA fibroblasts PTP opening is currently under investigation. Identification of the mechanisms leading to altered threshold for PTP regulation will help our understanding of the pathophysiology of DOA, but also provide a strategy for therapeutic intervention.

Modulating the granularity of category formation by global cortical states

The unsupervised categorization of sensory stimuli is typically attributed to feedforward processing in a hierarchy of cortical areas. This purely sensory-driven view of cortical processing, however, ignores any internal modulation, e.g., by top-down attentional signals or neuromodulator release. To isolate the role of internal signaling on category formation, we consider an unbroken continuum of stimuli without intrinsic category boundaries. We show that a competitive network, shaped by recurrent inhibition and endowed with Hebbian and homeostatic synaptic plasticity, can enforce stimulus categorization. The degree of competition is internally controlled by the neuronal gain and the strength of inhibition. Strong competition leads to the formation of many attracting network states, each being evoked by a distinct subset of stimuli and representing a category. Weak competition allows more neurons to be co-active, resulting in fewer but larger categories. We conclude that the granularity of cortical category formation, i.e., the number and size of emerging categories, is not simply determined by the richness of the stimulus environment, but rather by some global internal signal modulating the network dynamics. The model also explains the salient non-additivity of visual object representation observed in the monkey inferotemporal (IT) cortex. Furthermore, it offers an explanation of a previously observed, demand-dependent modulation of IT activity on a stimulus categorization task and of categorization-related cognitive deficits in schizophrenic patients.

Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Climate change mitigation policy is driven by scientific knowledge and involves actors from the international, national and local decision-making levels. This multi-level and cross-sectoral context requires collaborative management when designing mitigation solutions over time and space. But collaboration in general policymaking settings, and particularly in the complex domain of climate mitigation, is not an easy task. This paper addresses the question of what drives collaboration among collective actors involved in climate mitigation policy. We wish to investigate whether common beliefs or power structures influence collaboration among actors. We adopt a longitudinal approach to grasp differences between the early and more advanced stages of mitigation policy design. We use survey data to investigate actors’ collaboration, beliefs and power, and apply a Stochastic Actor-oriented Model for network dynamics to three subsequent networks in Swiss climate policy between 1995 and 2012. Results show that common beliefs among actors, as well as formal power structures, have a higher impact on collaboration relations than perceived power structures. Furthermore, those effects hold true for decision-making about initial mitigation strategies, but less so for the implementation of those measures.

Context-Aware Adaptive Opportunistic Routing in Mobile Ad-hoc and Sensor Networks

Mobile ad-hoc networks (MANETs) and wireless sensor networks (WSNs) have been attracting increasing attention for decades due to their broad civilian and military applications. Basically, a MANET or WSN is a network of nodes connected by wireless communication links. Due to the limited transmission range of the radio, many pairs of nodes in MANETs or WSNs may not be able to communicate directly, hence they need other intermediate nodes to forward packets for them. Routing in such types of networks is an important issue and it poses great challenges due to the dynamic nature of MANETs or WSNs. On the one hand, the open-air nature of wireless environments brings many difficulties when an efficient routing solution is required. The wireless channel is unreliable due to fading and interferences, which makes it impossible to maintain a quality path from a source node to a destination node. Additionally, node mobility aggravates network dynamics, which causes frequent topology changes and brings significant overheads for maintaining and recalculating paths. Furthermore, mobile devices and sensors are usually constrained by battery capacity, computing and communication resources, which impose limitations on the functionalities of routing protocols. On the other hand, the wireless medium possesses inherent unique characteristics, which can be exploited to enhance transmission reliability and routing performance. Opportunistic routing (OR) is one promising technique that takes advantage of the spatial diversity and broadcast nature of the wireless medium to improve packet forwarding reliability in multihop wireless communication. OR combats the unreliable wireless links by involving multiple neighboring nodes (forwarding candidates) to choose packet forwarders. In opportunistic routing, a source node does not require an end-to-end path to transmit packets. The packet forwarding decision is made hop-by-hop in a fully distributed fashion. Motivated by the deficiencies of existing opportunistic routing protocols in dynamic environments such as mobile ad-hoc networks or wireless sensor networks, this thesis proposes a novel context-aware adaptive opportunistic routing scheme. Our proposal selects packet forwarders by simultaneously exploiting multiple types of cross-layer context information of nodes and environments. Our approach significantly outperforms other routing protocols that rely solely on a single metric. The adaptivity feature of our proposal enables network nodes to adjust their behaviors at run-time according to network conditions. To accommodate the strict energy constraints in WSNs, this thesis integrates adaptive duty-cycling mechanism to opportunistic routing for wireless sensor nodes. Our approach dynamically adjusts the sleeping intervals of sensor nodes according to the monitored traffic load and the estimated energy consumption rate. Through the integration of duty cycling of sensor nodes and opportunistic routing, our protocol is able to provide a satisfactory balance between good routing performance and energy efficiency for WSNs.

Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons.

We study the dynamical states of a small-world network of recurrently coupled excitable neurons, through both numerical and analytical methods. The dynamics of this system depend mostly on both the number of long-range connections or ?shortcuts?, and the delay associated with neuronal interactions. We find that persistent activity emerges at low density of shortcuts, and that the system undergoes a transition to failure as their density reaches a critical value. The state of persistent activity below this transition consists of multiple stable periodic attractors, whose number increases at least as fast as the number of neurons in the network. At large shortcut density and for long enough delays the network dynamics exhibit exceedingly long chaotic transients, whose failure times follow a stretched exponential distribution. We show that this functional form arises for the ensemble-averaged activity if the failure time for each individual network realization is exponen- tially distributed

Visual stimuli induce waves of electrical activity in turtle cortex

The computations involved in the processing of a visual scene invariably involve the interactions among neurons throughout all of visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334–337] support a view in which only synchronous (no phase lags) activity carries information about the visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by visual stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of ≈π/2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during visual processing.

Primary sex determination of placental mammals: a modelling study uncovers dynamical developmental constraints in the formation of Sertoli and granulosa cells

Primary sex determination in placental mammals is a very well studied developmental process. Here, we aim to investigate the currently established scenario and to assess its adequacy to fully recover the observed phenotypes, in the wild type and perturbed situations. Computational modelling allows clarifying network dynamics, elucidating crucial temporal constrains as well as interplay between core regulatory modules.

Europeanization and the inclusive strategies of executive actors

In Europeanized policy domains, executive actors are considered especially powerful because they are directly responsible for international negotiations. However, in order to avoid failing in the ratification process, they are also highly dependent on the support of domestic, non-state actors. We argue that in Europeanized decision-making processes, state actors are not passively lobbied, but actively seek collaboration with - and support from - domestic actors. We apply stochastic actor-based modelling for network dynamics to collaboration data on two successive bilateral agreements on the free movement of persons between Switzerland and the European Union (EU). Results confirm our hypotheses that state actors are not passively lobbied, but actively look for collaboration with other actors, and especially with potential veto players and euro-sceptical actors from both the conservative Right and the Left.

Can we observe collective neuronal activity from macroscopic aggregate signals?

The fundamental problem faced by noninvasive neuroimaging techniques such as EEG/MEG1 is to elucidate functionally important aspects of the microscopic neuronal network dynamics from macroscopic aggregate measurements. Due to the mixing of the activities of large neuronal populations in the observed macroscopic aggregate, recovering the underlying network that generates the signal in the absence of any additional information represents a considerable challenge. Recent MEG studies have shown that macroscopic measurements contain sufficient information to allow the differentiation between patterns of activity, which are likely to represent different stimulus-specific collective modes in the underlying network (Hadjipapas, A., Adjamian, P., Swettenham, J.B., Holliday, I.E., Barnes, G.R., 2007. Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex. NeuroImage 35, 518–530). The next question arising in this context is whether aspects of collective network activity can be recovered from a macroscopic aggregate signal. We propose that this issue is most appropriately addressed if MEG/EEG signals are to be viewed as macroscopic aggregates arising from networks of coupled systems as opposed to aggregates across a mass of largely independent neural systems. We show that collective modes arising in a network of simulated coupled systems can be indeed recovered from the macroscopic aggregate. Moreover, we show that nonlinear state space methods yield a good approximation of the number of effective degrees of freedom in the network. Importantly, information about hidden variables, which do not directly contribute to the aggregate signal, can also be recovered. Finally, this theoretical framework can be applied to experimental MEG/EEG data in the future, enabling the inference of state dependent changes in the degree of local synchrony in the underlying network.

Human brain slices for epilepsy research:pitfalls, solutions and future challenges

Increasingly, neuroscientists are taking the opportunity to use live human tissue obtained from elective neurosurgical procedures for electrophysiological studies in vitro. Access to this valuable resource permits unique studies into the network dynamics that contribute to the generation of pathological electrical activity in the human epileptic brain. Whilst this approach has provided insights into the mechanistic features of electrophysiological patterns associated with human epilepsy, it is not without technical and methodological challenges. This review outlines the main difficulties associated with working with epileptic human brain slices from the point of collection, through the stages of preparation, storage and recording. Moreover, it outlines the limitations, in terms of the nature of epileptic activity that can be observed in such tissue, in particular, the rarity of spontaneous ictal discharges, we discuss manipulations that can be utilised to induce such activity. In addition to discussing conventional electrophysiological techniques that are routinely employed in epileptic human brain slices, we review how imaging and multielectrode array recordings could provide novel insights into the network dynamics of human epileptogenesis. Acute studies in human brain slices are ultimately limited by the lifetime of the tissue so overcoming this issue provides increased opportunity for information gain. We review the literature with respect to organotypic culture techniques that may hold the key to prolonging the viability of this material. A combination of long-term culture techniques, viral transduction approaches and electrophysiology in human brain slices promotes the possibility of large scale monitoring and manipulation of neuronal activity in epileptic microcircuits.