Eric S. Kuebler

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Discriminating amongst stimuli in the environment is a fundamental aspect of brain function. Research has shown that chaotic neural networks are exquisitely sensitive to small perturbations making them unreliable and unpredictable. Here, we examine how neuronal oscillations (i.e., temporal waves of activity) may be tuned to enhance the discrimination(More)
Neuronal activity in vitro exhibits network bursts characterized by brief periods of increased spike rates. Recent work shows that a subpopulation of neurons reliably predicts the occurrence of network bursts. Here, we examined the role of burst predictors in cultures undergoing an in vitro model of cerebral ischemia. Dissociated primary cortical neurons(More)
Recordings of neuronal networks in cortex show evidence of asynchronous – or out-of-phase – activity. Cells are known to generate asynchronous outputs despite strongly shared synaptic inputs [1], yet the computational benefits of this coding remain unclear. By comparison, synchronized activity in neuronal networks has been reported in a broad range of(More)
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