scholarly journals Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

2014 ◽  
Vol 10 (11) ◽  
pp. e1003923 ◽  
Author(s):  
Arne Weigenand ◽  
Michael Schellenberger Costa ◽  
Hong-Viet Victor Ngo ◽  
Jens Christian Claussen ◽  
Thomas Martinetz
2021 ◽  
Author(s):  
Nipuni D. Nagahawatte ◽  
Niranchan Paskaranandavadivel ◽  
Leo K. Cheng

SLEEP ◽  
2017 ◽  
Vol 40 (suppl_1) ◽  
pp. A105-A105
Author(s):  
G Garcia-Molina ◽  
K Baehr ◽  
B Steele ◽  
T Tsoneva ◽  
S Pfundtner ◽  
...  

2009 ◽  
Vol 136 (5) ◽  
pp. A-643
Author(s):  
Juliana H. Kim ◽  
Leonard A. Bradshaw ◽  
Andrew J. Pullan ◽  
Leo K. Cheng

2020 ◽  
Vol 158 (6) ◽  
pp. S-364
Author(s):  
Suseela Somarajan ◽  
Nicole D. Muszynski ◽  
Aurelia s. Monk ◽  
Joseph D. Olson ◽  
Alexandra Russell ◽  
...  

2016 ◽  
Vol 30 (4) ◽  
pp. 141-154 ◽  
Author(s):  
Kira Bailey ◽  
Gregory Mlynarczyk ◽  
Robert West

Abstract. Working memory supports our ability to maintain goal-relevant information that guides cognition in the face of distraction or competing tasks. The N-back task has been widely used in cognitive neuroscience to examine the functional neuroanatomy of working memory. Fewer studies have capitalized on the temporal resolution of event-related brain potentials (ERPs) to examine the time course of neural activity in the N-back task. The primary goal of the current study was to characterize slow wave activity observed in the response-to-stimulus interval in the N-back task that may be related to maintenance of information between trials in the task. In three experiments, we examined the effects of N-back load, interference, and response accuracy on the amplitude of the P3b following stimulus onset and slow wave activity elicited in the response-to-stimulus interval. Consistent with previous research, the amplitude of the P3b decreased as N-back load increased. Slow wave activity over the frontal and posterior regions of the scalp was sensitive to N-back load and was insensitive to interference or response accuracy. Together these findings lead to the suggestion that slow wave activity observed in the response-to-stimulus interval is related to the maintenance of information between trials in the 1-back task.


2021 ◽  
Author(s):  
Áine Byrne ◽  
James Ross ◽  
Rachel Nicks ◽  
Stephen Coombes

AbstractNeural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.


SLEEP ◽  
1984 ◽  
Vol 7 (4) ◽  
pp. 380-385 ◽  
Author(s):  
S. Scott Bowersox ◽  
Tom Floyd ◽  
William C. Dement

NeuroImage ◽  
2007 ◽  
Vol 34 (4) ◽  
pp. 1466-1472 ◽  
Author(s):  
M. Kaltenhäuser ◽  
G. Scheler ◽  
S. Rampp ◽  
A. Paulini ◽  
H. Stefan

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