172 resultados para spiking
Resumo:
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.
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A hallmark of schizophrenia pathophysiology is the dysfunction of cortical inhibitory GABA neurons expressing parvalbumin, which are essential for coordinating neuronal synchrony during various sensory and cognitive tasks. The high metabolic requirements of these fast-spiking cells may render them susceptible to redox dysregulation and oxidative stress. Using mice carrying a genetic redox imbalance, we demonstrate that extracellular perineuronal nets, which constitute a specialized polyanionic matrix enwrapping most of these interneurons as they mature, play a critical role in the protection against oxidative stress. These nets limit the effect of genetically impaired antioxidant systems and/or excessive reactive oxygen species produced by severe environmental insults. We observe an inverse relationship between the robustness of the perineuronal nets around parvalbumin cells and the degree of intracellular oxidative stress they display. Enzymatic degradation of the perineuronal nets renders mature parvalbumin cells and fast rhythmic neuronal synchrony more susceptible to oxidative stress. In parallel, parvalbumin cells enwrapped with mature perineuronal nets are better protected than immature parvalbumin cells surrounded by less-condensed perineuronal nets. Although the perineuronal nets act as a protective shield, they are also themselves sensitive to excess oxidative stress. The protection might therefore reflect a balance between the oxidative burden on perineuronal net degradation and the capacity of the system to maintain the nets. Abnormal perineuronal nets, as observed in the postmortem patient brain, may thus underlie the vulnerability and functional impairment of pivotal inhibitory circuits in schizophrenia.
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Voltage-gated K+ channels of the Kv3 subfamily have unusual electrophysiological properties, including activation at very depolarized voltages (positive to −10 mV) and very fast deactivation rates, suggesting special roles in neuronal excitability. In the brain, Kv3 channels are prominently expressed in select neuronal populations, which include fast-spiking (FS) GABAergic interneurons of the neocortex, hippocampus, and caudate, as well as other high-frequency firing neurons. Although evidence points to a key role in high-frequency firing, a definitive understanding of the function of these channels has been hampered by a lack of selective pharmacological tools. We therefore generated mouse lines in which one of the Kv3 genes, Kv3.2, was disrupted by gene-targeting methods. Whole-cell electrophysiological recording showed that the ability to fire spikes at high frequencies was impaired in immunocytochemically identified FS interneurons of deep cortical layers (5-6) in which Kv3.2 proteins are normally prominent. No such impairment was found for FS neurons of superficial layers (2-4) in which Kv3.2 proteins are normally only weakly expressed. These data directly support the hypothesis that Kv3 channels are necessary for high-frequency firing. Moreover, we found that Kv3.2 −/− mice showed specific alterations in their cortical EEG patterns and an increased susceptibility to epileptic seizures consistent with an impairment of cortical inhibitory mechanisms. This implies that, rather than producing hyperexcitability of the inhibitory interneurons, Kv3.2 channel elimination suppresses their activity. These data suggest that normal cortical operations depend on the ability of inhibitory interneurons to generate high-frequency firing.
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The in situ hybridization Allen Mouse Brain Atlas was mined for proteases expressed in the somatosensory cerebral cortex. Among the 480 genes coding for protease/peptidases, only four were found enriched in cortical interneurons: Reln coding for reelin; Adamts8 and Adamts15 belonging to the class of metzincin proteases involved in reshaping the perineuronal net (PNN) and Mme encoding for Neprilysin, the enzyme degrading amyloid β-peptides. The pattern of expression of metalloproteases (MPs) was analyzed by single-cell reverse transcriptase multiplex PCR after patch clamp and was compared with the expression of 10 canonical interneurons markers and 12 additional genes from the Allen Atlas. Clustering of these genes by K-means algorithm displays five distinct clusters. Among these five clusters, two fast-spiking interneuron clusters expressing the calcium-binding protein Pvalb were identified, one co-expressing Pvalb with Sst (PV-Sst) and another co-expressing Pvalb with three metallopeptidases Adamts8, Adamts15 and Mme (PV-MP). By using Wisteria floribunda agglutinin, a specific marker for PNN, PV-MP interneurons were found surrounded by PNN, whereas the ones expressing Sst, PV-Sst, were not.
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BACKGROUND: Oxidative stress and the specific impairment of perisomatic gamma-aminobutyric acid circuits are hallmarks of the schizophrenic brain and its animal models. Proper maturation of these fast-spiking inhibitory interneurons normally defines critical periods of experience-dependent cortical plasticity. METHODS: Here, we linked these processes by genetically inducing a redox dysregulation restricted to such parvalbumin-positive cells and examined the impact on critical period plasticity using the visual system as a model (3-6 mice/group). RESULTS: Oxidative stress was accompanied by a significant loss of perineuronal nets, which normally enwrap mature fast-spiking cells to limit adult plasticity. Accordingly, the neocortex remained plastic even beyond the peak of its natural critical period. These effects were not seen when redox dysregulation was targeted in excitatory principal cells. CONCLUSIONS: A cell-specific regulation of redox state thus balances plasticity and stability of cortical networks. Mistimed developmental trajectories of brain plasticity may underlie, in part, the pathophysiology of mental illness. Such prolonged developmental plasticity may, in turn, offer a therapeutic opportunity for cognitive interventions targeting brain plasticity in schizophrenia.
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The ability to recognize a shape is linked to figure-ground (FG) organization. Cell preferences appear to be correlated across contrast-polarity reversals and mirror reversals of polygon displays, but not so much across FG reversals. Here we present a network structure which explains both shape-coding by simulated IT cells and suppression of responses to FG reversed stimuli. In our model FG segregation is achieved before shape discrimination, which is itself evidenced by the difference in spiking onsets of a pair of output cells. The studied example also includes feature extraction and illustrates a classification of binary images depending on the dominance of vertical or horizontal borders.
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Brock Women's Volleyball in a 1977 match.
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An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.
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Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to the number and interconnectedness of neurons in the brain. Furthermore, where such simulations are used in an embodied setting, the simulation must be real-time in order to be useful. In this paper we present NeMo, a platform for such simulations which achieves high performance through the use of highly parallel commodity hardware in the form of graphics processing units (GPUs). NeMo makes use of the Izhikevich neuron model which provides a range of realistic spiking dynamics while being computationally efficient. Our GPU kernel can deliver up to 400 million spikes per second. This corresponds to a real-time simulation of around 40 000 neurons under biologically plausible conditions with 1000 synapses per neuron and a mean firing rate of 10 Hz.
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Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.
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Desde os descobrimentos pioneiros de Hubel e Wiesel acumulou-se uma vasta literatura descrevendo as respostas neuronais do córtex visual primário (V1) a diferentes estímulos visuais. Estes estímulos consistem principalmente em barras em movimento, pontos ou grades, que são úteis para explorar as respostas dentro do campo receptivo clássico (CRF do inglês classical receptive field) a características básicas dos estímulos visuais como a orientação, direção de movimento, contraste, entre outras. Entretanto, nas últimas duas décadas, tornou-se cada vez mais evidente que a atividade de neurônios em V1 pode ser modulada por estímulos fora do CRF. Desta forma, áreas visuais primárias poderiam estar envolvidas em funções visuais mais complexas como, por exemplo, a separação de um objeto ou figura do seu fundo (segregação figura-fundo) e assume-se que as conexões intrínsecas de longo alcance em V1, assim como as conexões de áreas visuais superiores, estão ativamente envolvidas neste processo. Sua possível função foi inferida a partir da análise das variações das respostas induzidas por um estímulo localizado fora do CRF de neurônios individuais. Mesmo sendo muito provável que estas conexões tenham também um impacto tanto na atividade conjunta de neurônios envolvidos no processamento da figura quanto no potencial de campo, estas questões permanecem pouco estudadas. Visando examinar a modulação do contexto visual nessas atividades, coletamos potenciais de ação e potenciais de campo em paralelo de até 48 eletrodos implantados na área visual primária de gatos anestesiados. Estimulamos com grades compostas e cenas naturais, focando-nos na atividade de neurônios cujo CRF estava situado na figura. Da mesma forma, visando examinar a influência das conexões laterais, o sinal proveniente da área visual isotópica e contralateral foi removido através da desativação reversível por resfriamento. Fizemos isso devido a: i) as conexões laterais intrínsecas não podem ser facilmente manipuladas sem afetar diretamente os sinais que estão sendo medidos, ii) as conexões inter-hemisféricas compartilham as principais características anatômicas com a rede lateral intrínseca e podem ser vistas como uma continuação funcional das mesmas entre os dois hemisférios e iii) o resfriamento desativa as conexões de forma causal e reversível, silenciando temporariamente seu sinal, permitindo conclusões diretas a respeito da sua contribuição. Nossos resultados demonstram que o mecanismo de segmentação figurafundo se reflete nas taxas de disparo de neurônios individuais, assim como na potência do potencial de campo e na relação entre sua fase e os padrões de disparo produzidos pela população. Além disso, as conexões laterais inter-hemisféricas modulam estas variáveis dependendo da estimulação feita fora do CRF. Observamos também uma influência deste circuito lateral na coerência entre potenciais de campo entre eletrodos distantes. Em conclusão, nossos resultados dão suporte à ideia de um mecanismo complexo de segmentação figura-fundo atuando desde as áreas visuais primárias em diferentes escalas de frequência. Esse mecanismo parece envolver grupos de neurônios ativos sincronicamente e dependentes da fase do potencial de campo. Nossos resultados também são compatíveis com a hipótese que conexões laterais de longo alcance também fazem parte deste mecanismo