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Vladislav Volman
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Journal Articles
Publisher: Journals Gateway
Neural Computation (2013) 25 (10): 2646–2681.
Published: 01 October 2013
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Diffusion imaging and postmortem studies of patients with mild traumatic brain injury (mTBI) of the concussive type are consistent with the observations of diffuse axonal injury to the white matter axons. Mechanical trauma to axons affects the properties of tetrodotoxin-sensitive sodium channels at the nodes of Ranvier, leading to axonal degeneration through intra-axonal accumulation of calcium ions and activation of calcium proteases; however, the immediate implications of axonal trauma regarding axonal functionality and their relevance to transient impairment of function as observed in concussion remain elusive. A biophysically realistic computational model of a myelinated axon was developed to investigate how mTBI could immediately affect axonal function. Traumatized axons showed alterations in signal propagation properties that nonlinearly depended on the level of trauma; subthreshold traumatized axons had decreased spike propagation time, whereas suprathreshold traumatized axons exhibited a slowdown of spike propagation and spike propagation failure. Trauma had consistently reduced axonal spike amplitude. The susceptibility of an axon to trauma could be modulated by the function of an ATP-dependent sodium-potassium pump. The results suggest a mechanism by which concussive mTBI could lead to the immediate impairment of signal propagation through the axon and the emerging dysfunctional neuronal information exchange.
Journal Articles
Publisher: Journals Gateway
Neural Computation (2011) 23 (4): 927–957.
Published: 01 April 2011
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Small networks of cultured hippocampal neurons respond to transient stimulation with rhythmic network activity (reverberation) that persists for several seconds, constituting an in vitro model of synchrony, working memory, and seizure. This mode of activity has been shown theoretically and experimentally to depend on asynchronous neurotransmitter release (an essential feature of the developing hippocampus) and is supported by a variety of developing neuronal networks despite variability in the size of populations (10–200 neurons) and in patterns of synaptic connectivity. It has previously been reported in computational models that “small-world” connection topology is ideal for the propagation of similar modes of network activity, although this has been shown only for neurons utilizing synchronous (phasic) synaptic transmission. We investigated how topological constraints on synaptic connectivity could shape the stability of reverberations in small networks that also use asynchronous synaptic transmission. We found that reverberation duration in such networks was resistant to changes in topology and scaled poorly with network size. However, normalization of synaptic drive, by reducing the variance of synaptic input across neurons, stabilized reverberation in such networks. Our results thus suggest that the stability of both normal and pathological states in developing networks might be shaped by variance-normalizing constraints on synaptic drive. We offer an experimental prediction for the consequences of such regulation on the behavior of small networks.
Journal Articles
Publisher: Journals Gateway
Neural Computation (2007) 19 (2): 303–326.
Published: 01 February 2007
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We present a simple biophysical model for the coupling between synaptic transmission and the local calcium concentration on an enveloping astrocytic domain. This interaction enables the astrocyte to modulate the information flow from presynaptic to postsynaptic cells in a manner dependent on previous activity at this and other nearby synapses. Our model suggests a novel, testable hypothesis for the spike timing statistics measured for rapidly firing cells in culture experiments.
Journal Articles
Publisher: Journals Gateway
Neural Computation (2004) 16 (12): 2577–2595.
Published: 01 December 2004
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Cultured in vitro neuronal networks are known to exhibit synchronized bursting events (SBE), during which most of the neurons in the system spike within a time window of approximately 100 msec. Such phenomena can be obtained in model networks based on Markram-Tsodyks frequency-dependent synapses. In order to account correctly for the detailed behavior of SBEs, several modifications have to be implemented in such models. Random input currents have to be introduced to account for the rising profile of SBEs. Dynamic thresholds and inhomogeneity in the distribution of neuronal resistances enable us to describe the profile of activity within the SBE and the heavy-tailed distributions of interspike intervals and interevent intervals. Thus, we can account for the interesting appearance of Lévy distributions in the data.