Literature DB >> 22377416

Cellular-based modeling of oscillatory dynamics in brain networks.

Frances K Skinner1.   

Abstract

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2012        PMID: 22377416     DOI: 10.1016/j.conb.2012.02.001

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  14 in total

1.  Examining the limits of cellular adaptation bursting mechanisms in biologically-based excitatory networks of the hippocampus.

Authors:  K A Ferguson; F Njap; W Nicola; F K Skinner; S A Campbell
Journal:  J Comput Neurosci       Date:  2015-10-13       Impact factor: 1.621

2.  Different roles for inhibition in the rhythm-generating respiratory network.

Authors:  Kameron Decker Harris; Tatiana Dashevskiy; Joshua Mendoza; Alfredo J Garcia; Jan-Marino Ramirez; Eric Shea-Brown
Journal:  J Neurophysiol       Date:  2017-06-14       Impact factor: 2.714

Review 3.  Beyond the connectome: the dynome.

Authors:  Nancy J Kopell; Howard J Gritton; Miles A Whittington; Mark A Kramer
Journal:  Neuron       Date:  2014-09-17       Impact factor: 17.173

4.  Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations.

Authors:  Archana Proddutur; Jiandong Yu; Fatima S Elgammal; Vijayalakshmi Santhakumar
Journal:  Chaos       Date:  2013-12       Impact factor: 3.642

5.  Distinct current modules shape cellular dynamics in model neurons.

Authors:  Adel Alturki; Feng Feng; Ajay Nair; Vinay Guntu; Satish S Nair
Journal:  Neuroscience       Date:  2016-08-13       Impact factor: 3.590

6.  Fluctuating inhibitory inputs promote reliable spiking at theta frequencies in hippocampal interneurons.

Authors:  Duluxan Sritharan; Frances K Skinner
Journal:  Front Comput Neurosci       Date:  2012-05-24       Impact factor: 2.380

7.  Moving beyond Type I and Type II neuron types.

Authors:  Frances K Skinner
Journal:  F1000Res       Date:  2013-01-22

8.  A network that performs brute-force conversion of a temporal sequence to a spatial pattern: relevance to odor recognition.

Authors:  Honi Sanders; Brian E Kolterman; Roman Shusterman; Dmitry Rinberg; Alexei Koulakov; John Lisman
Journal:  Front Comput Neurosci       Date:  2014-09-17       Impact factor: 2.380

9.  Stochastic and deterministic dynamics of intrinsically irregular firing in cortical inhibitory interneurons.

Authors:  Philipe Rf Mendonça; Mariana Vargas-Caballero; Ferenc Erdélyi; Gábor Szabó; Ole Paulsen; Hugh Pc Robinson
Journal:  Elife       Date:  2016-08-18       Impact factor: 8.140

10.  Combining Theory, Model, and Experiment to Explain How Intrinsic Theta Rhythms Are Generated in an In Vitro Whole Hippocampus Preparation without Oscillatory Inputs.

Authors:  Katie A Ferguson; Alexandra P Chatzikalymniou; Frances K Skinner
Journal:  eNeuro       Date:  2017-08-07
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