151 research outputs found

    Synaptic Failure Differentially Affects Pattern Formation in Heterogenous Networks

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    The communication of neurons is primarily maintained by synapses, which play a crucial role in the functioning of the nervous system. Therefore, synaptic failure may critically impair information processing in the brain and may underlie many neurodegenerative diseases. A number of studies have suggested that synaptic failure may preferentially target neurons with high connectivity (i.e., network hubs). As a result, the activity of these highly connected neurons can be significantly affected. It has been speculated that anesthetics regulate conscious state by affecting synaptic transmission at these network hubs and subsequently reducing overall coherence in the network activity. In addition, hubs in cortical networks are shown to be more vulnerable to amyloid deposition because of their higher activity within the network, causing decrease in coherence patterns and eventually Alzheimer’s disease (AD). Here, we investigate how synaptic failure can affect spatio-temporal dynamics of scale free networks, having a power law scaling of number of connections per neuron – a relatively few neurons (hubs) with a lot of emanating or incoming connections and many cells with low connectivity. We studied two types of synaptic failure: activity-independent and targeted, activity-dependent synaptic failure. We defined scale-free network structures based on the dominating direction of the connections at the hub neurons: incoming and outgoing. We found that the two structures have significantly different dynamical properties. We show that synaptic failure may not only lead to the loss of coherence but unintuitively also can facilitate its emergence. We show that this is because activity-dependent synaptic failure homogenizes the activity levels in the network creating a dynamical substrate for the observed coherence increase. Obtained results may lead to better understanding of changes in large-scale pattern formation during progression of neuro-degenerative diseases targeting synaptic transmission

    Measuring predictability of autonomous network transitions into bursting dynamics

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    http://deepblue.lib.umich.edu/bitstream/2027.42/109548/1/12868_2014_Article_3557.pd

    Neuronal network information processing through heterogeneities and resonance frequency shifts

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    http://deepblue.lib.umich.edu/bitstream/2027.42/112446/1/12868_2013_Article_3295.pd

    Dynamics of two-process astrocyte networks

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    http://deepblue.lib.umich.edu/bitstream/2027.42/112971/1/12868_2013_Article_3367.pd

    Interaction of membrane dynamics with network structure and its effects on spatio-temporal network patterning

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    http://deepblue.lib.umich.edu/bitstream/2027.42/112869/1/12868_2008_Article_970.pd
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