4 resultados para temporal activity

em Indian Institute of Science - Bangalore - Índia


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In a complex multitrophic plant-animal interaction system in which there are direct and indirect interactions between species, comprehending the dynamics of these multiple partners is very important for an understanding of how the system is structured. We investigated the plant Ficus racemosa L. (Moraceae) and its community of obligatory mutualistic and parasitic fig wasps (Hymenoptera: Chalcidoidea) that develop within the fig inflorescence or syconium, as well as their interaction with opportunistic ants. We focused on temporal resource partitioning among members of the fig wasp community over the development cycle of the fig syconia during which wasp oviposition and development occur and we studied the activity rhythm of the ants associated with this community. We found that the seven members of the wasp community partitioned their oviposition across fig syconium development phenology and showed interspecific variation in activity across the day-night cycle. The wasps presented a distinct sequence in their arrival at fig syconia for oviposition, with the parasitoid wasps following the galling wasps. Although fig wasps are known to be largely diurnal, we documented night oviposition in several fig wasp species for the first time. Ant activity on the fig syconia was correlated with wasp activity and was dependent on whether the ants were predatory or trophobiont-tending species; only numbers of predatory ants increased during peak arrivals of the wasps.

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The subiculum, a para-hippocampal structure positioned between the cornu ammonis 1 subfield and the entorhinal cortex, has been implicated in temporal lobe epilepsy in human patients and in animal models of epilepsy. The structure is characterized by the presence of a significant population of burst firing neurons that has been shown previously to lead epileptiform activity locally. Phase transitions in epileptiform activity in neurons following a prolonged challenge with an epileptogenic stimulus has been shown in other brain structures, but not in the subiculum. Considering the importance of the subicular burst firing neurons in the propagation of epileptiform activity to the entorhinal cortex, we have explored the phenomenon of phase transitions in the burst firing neurons of the subiculum in an in vitro rat brain slice model of epileptogenesis. Whole-cell patch-clamp and extracellular field recordings revealed a distinct phenomenon in the subiculum wherein an early hyperexcitable state was followed by a late suppressed state upon continuous perfusion with epileptogenic 4-aminopyridine and magnesium-free medium. The suppressed state was characterized by inhibitory post-synaptic potentials in pyramidal excitatory neurons and bursting activity in local fast-spiking interneurons at a frequency of 0.1-0.8Hz. The inhibitory post-synaptic potentials were mediated by GABA(A) receptors that coincided with excitatory synaptic inputs to attenuate action potential discharge. These inhibitory post-synaptic potentials ceased following a cut between the cornu ammonis 1 and subiculum. The suppression of epileptiform activity in the subiculum thus represents a homeostatic response towards the induced hyperexcitability. Our results suggest the importance of feedforward inhibition in exerting this homeostatic control.

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The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

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We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.