Detail
Článek
Článek online
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity

I. Balzekas, J. Trzasko, G. Yu, TJ. Richner, F. Mivalt, V. Sladky, NM. Gregg, J. Van Gompel, K. Miller, PE. Croarkin, V. Kremen, GA. Worrell

. 2024 ; 20 (4) : e1011152. [pub] 20240425

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem, Research Support, U.S. Gov't, Non-P.H.S.

Perzistentní odkaz   https://www.medvik.cz/link/bmc24014255

Grantová podpora
T32 GM145408 NIGMS NIH HHS - United States
UH2 NS095495 NINDS NIH HHS - United States

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc24014255
003      
CZ-PrNML
005      
20240905133940.0
007      
ta
008      
240725s2024 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1371/journal.pcbi.1011152 $2 doi
035    __
$a (PubMed)38662736
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Balzekas, Irena $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America $u Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, Minnesota, United States of America $u Mayo Clinic Alix School of Medicine, Rochester, Minnesota, United States of America $u Mayo Clinic Medical Scientist Training Program, Rochester, Minnesota, United States of America $1 https://orcid.org/0000000327319188
245    10
$a Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity / $c I. Balzekas, J. Trzasko, G. Yu, TJ. Richner, F. Mivalt, V. Sladky, NM. Gregg, J. Van Gompel, K. Miller, PE. Croarkin, V. Kremen, GA. Worrell
520    9_
$a Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.
650    _2
$a lidé $7 D006801
650    _2
$a algoritmy $7 D000465
650    _2
$a výpočetní biologie $x metody $7 D019295
650    _2
$a elektrokortikografie $x metody $7 D000069280
650    _2
$a elektroencefalografie $x metody $7 D004569
650    12
$a epilepsie $x patofyziologie $x diagnóza $7 D004827
650    _2
$a hipokampus $x patofyziologie $x fyziologie $7 D006624
650    _2
$a modely neurologické $7 D008959
650    _2
$a záchvaty $x patofyziologie $x diagnóza $7 D012640
650    _2
$a počítačové zpracování signálu $7 D012815
650    _2
$a ženské pohlaví $7 D005260
655    _2
$a časopisecké články $7 D016428
655    _2
$a Research Support, N.I.H., Extramural $7 D052061
655    _2
$a práce podpořená grantem $7 D013485
655    _2
$a Research Support, U.S. Gov't, Non-P.H.S. $7 D013486
700    1_
$a Trzasko, Joshua $u Department of Radiology, Mayo Clinic, Rochester, Minnesota, United States of America
700    1_
$a Yu, Grace $u Mayo Clinic Alix School of Medicine, Rochester, Minnesota, United States of America $u Mayo Clinic Medical Scientist Training Program, Rochester, Minnesota, United States of America
700    1_
$a Richner, Thomas J $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
700    1_
$a Mivalt, Filip $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America $u International Clinic Research Center, St. Anne's University Research Hospital, Brno, Czech Republic $u Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering, Brno University of Technology, Brno, Czechia
700    1_
$a Sladky, Vladimir $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America $u International Clinic Research Center, St. Anne's University Research Hospital, Brno, Czech Republic $u Faculty of Biomedical Engineering, Czech Technical University in Prague, Czechia
700    1_
$a Gregg, Nicholas M $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
700    1_
$a Van Gompel, Jamie $u Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, United States of America
700    1_
$a Miller, Kai $u Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, United States of America $1 https://orcid.org/0000000266876422
700    1_
$a Croarkin, Paul E $u Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, United States of America
700    1_
$a Kremen, Vaclav $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America $u Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czechia
700    1_
$a Worrell, Gregory A $u Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America $u Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, Minnesota, United States of America
773    0_
$w MED00008919 $t PLoS computational biology $x 1553-7358 $g Roč. 20, č. 4 (2024), s. e1011152
856    41
$u https://pubmed.ncbi.nlm.nih.gov/38662736 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y - $z 0
990    __
$a 20240725 $b ABA008
991    __
$a 20240905133934 $b ABA008
999    __
$a ok $b bmc $g 2143819 $s 1226121
BAS    __
$a 3
BAS    __
$a PreBMC-MEDLINE
BMC    __
$a 2024 $b 20 $c 4 $d e1011152 $e 20240425 $i 1553-7358 $m PLoS computational biology $n PLoS Comput Biol $x MED00008919
GRA    __
$a T32 GM145408 $p NIGMS NIH HHS $2 United States
GRA    __
$a UH2 NS095495 $p NINDS NIH HHS $2 United States
LZP    __
$a Pubmed-20240725

Najít záznam

Citační ukazatele

Možnosti archivace