TY - JOUR
T1 - K-complexes, spindles, and ERPs as impulse responses
T2 - unification via neural field theory
AU - Zobaer, M. S.
AU - Anderson, R. M.
AU - Kerr, C. C.
AU - Robinson, P. A.
AU - Wong, K. K. H.
AU - D’Rozario, A. L.
PY - 2017/4
Y1 - 2017/4
N2 - To interrelate K-complexes, spindles, evoked response potentials (ERPs), and spontaneous electroencephalography (EEG) using neural field theory (NFT), physiology-based NFT of the corticothalamic system is used to model cortical excitatory and inhibitory populations and thalamic relay and reticular nuclei. The impulse response function of the model is used to predict the responses to impulses, which are compared with transient waveforms in sleep studies. Fits to empirical data then allow underlying brain physiology to be inferred and compared with other waves. Spontaneous K-complexes, spindles, and other transient waveforms can be reproduced using NFT by treating them as evoked responses to impulsive stimuli with brain parameters appropriate to spontaneous EEG in sleep stage 2. Using this approach, spontaneous K-complexes and sleep spindles can be analyzed using the same single theory as previously been used to account for waking ERPs and other EEG phenomena. As a result, NFT can explain a wide variety of transient waveforms that have only been phenomenologically classified to date. This enables noninvasive fitting to be used to infer underlying physiological parameters. This physiology-based model reproduces the time series of different transient EEG waveforms; it has previously reproduced experimental EEG spectra, and waking ERPs, and many other observations, thereby unifying transient sleep waveforms with these phenomena.
AB - To interrelate K-complexes, spindles, evoked response potentials (ERPs), and spontaneous electroencephalography (EEG) using neural field theory (NFT), physiology-based NFT of the corticothalamic system is used to model cortical excitatory and inhibitory populations and thalamic relay and reticular nuclei. The impulse response function of the model is used to predict the responses to impulses, which are compared with transient waveforms in sleep studies. Fits to empirical data then allow underlying brain physiology to be inferred and compared with other waves. Spontaneous K-complexes, spindles, and other transient waveforms can be reproduced using NFT by treating them as evoked responses to impulsive stimuli with brain parameters appropriate to spontaneous EEG in sleep stage 2. Using this approach, spontaneous K-complexes and sleep spindles can be analyzed using the same single theory as previously been used to account for waking ERPs and other EEG phenomena. As a result, NFT can explain a wide variety of transient waveforms that have only been phenomenologically classified to date. This enables noninvasive fitting to be used to infer underlying physiological parameters. This physiology-based model reproduces the time series of different transient EEG waveforms; it has previously reproduced experimental EEG spectra, and waking ERPs, and many other observations, thereby unifying transient sleep waveforms with these phenomena.
KW - corticothalamic system
KW - electroencephalography
KW - evoked response potentials
KW - impulse responses
KW - K-complexes
KW - modeling
KW - neural field theory
KW - neurophysiology
KW - sleep spindles
UR - http://www.scopus.com/inward/record.url?scp=85014112526&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/arc/CE140100007
UR - http://purl.org/au-research/grants/arc/DE140101375
UR - http://purl.org/au-research/grants/nhmrc/571421
UR - http://purl.org/au-research/grants/nhmrc/1060992
U2 - 10.1007/s00422-017-0713-2
DO - 10.1007/s00422-017-0713-2
M3 - Article
C2 - 28251306
SN - 1432-0770
VL - 111
SP - 149
EP - 164
JO - Biological Cybernetics
JF - Biological Cybernetics
IS - 2
ER -