Dataset Information

Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode.

ABSTRACT: Thalamic relay neurons have well-characterized dual firing modes: bursting and tonic spiking. Studies in brain slices have led to a model in which rhythmic synchronized spiking (phasic firing) in a population of relay neurons leads to hyper-synchronous oscillatory cortico-thalamo-cortical rhythms that result in absence seizures. This model suggests that blocking thalamocortical phasic firing would treat absence seizures. However, recent in vivo studies in anesthetized animals have questioned this simple model. Here we resolve this issue by developing a real-time, mode-switching approach to drive thalamocortical neurons into or out of a phasic firing mode in two freely behaving genetic rodent models of absence epilepsy. Toggling between phasic and tonic firing in thalamocortical neurons launched and aborted absence seizures, respectively. Thus, a synchronous thalamocortical phasic firing state is required for absence seizures, and switching to tonic firing rapidly halts absences. This approach should be useful for modulating other networks that have mode-dependent behaviors.

SUBMITTER: Sorokin JM

PROVIDER: S-EPMC5268077 | biostudies-other | 2017 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode.

Sorokin Jordan M JM Davidson Thomas J TJ Frechette Eric E Abramian Armen M AM Deisseroth Karl K Huguenard John R JR Paz Jeanne T JT

Neuron 20161215 1

Thalamic relay neurons have well-characterized dual firing modes: bursting and tonic spiking. Studies in brain slices have led to a model in which rhythmic synchronized spiking (phasic firing) in a population of relay neurons leads to hyper-synchronous oscillatory cortico-thalamo-cortical rhythms that result in absence seizures. This model suggests that blocking thalamocortical phasic firing would treat absence seizures. However, recent in vivo studies in anesthetized animals have questioned thi ...[more]

PMID: 27989462

Similar Datasets

Project description:Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios.

Dataset Information

Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode.

Publications

Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets