title: Time-frequency analysis of spike-wave discharges using a modified wavelet transform.
abstract: The continuous Morlet wavelet transform was used for the analysis of the time-frequency pattern of spike-wave discharges (SWD) as can be recorded in a genetic animal model of absence epilepsy (rats of the WAG/Rij strain). We developed a new wavelet transform that allows to obtain the time-frequency dynamics of the dominating rhythm during the discharges. SWD were analyzed pre- and post-administration of certain drugs. SWD recorded predrug demonstrate quite uniform time-frequency dynamics of the dominant rhythm. The beginning of the discharge has a short period with the highest frequency value (up to 15 Hz). Then the frequency decreases to 7-9 Hz and frequency modulation occurs during the discharge in this range with a period of 0.5-0.7 s. Specific changes of SWD time-frequency dynamics were found after the administration of psychoactive drugs, addressing different brain mediator and modulator systems. Short multiple SWDs appeared under low (0.5 mg/kg) doses of haloperidol, they are characterized by a fast frequency decrease to 5-6 Hz at the end of every discharge. The frequency of the dominant frequency of SWD was not stable in long lasting SWD after 1.0 mg/kg or more haloperidol: then two periodicities were found. Long lasting SWD seen after the administration of vigabatrin showed a stable frequency of the discharge. The EEG after Ketamin showed a distinct 5 s quasiperiodicity. No clear changes of time-frequency dynamics of SWD were found after perilamine. It can be concluded that the use of the modified Morlet wavelet transform allows to describe significant parameters of the dynamics in the time-frequency domain of the dominant rhythm of SWD that were not previously detected.
authors.affiliation: Institute of Radioengeneering and Electronics, Russian Academy of Sciences, Moscow.
authors.forename: Daria
authors.initials: D
authors.lastname: Bosnyakova
authors.forename: Alexandra
authors.initials: A
authors.lastname: Gabova
authors.forename: Galina
authors.initials: G
authors.lastname: Kuznetsova
authors.forename: Yuri
authors.initials: Y
authors.lastname: Obukhov
authors.forename: Inna
authors.initials: I
authors.lastname: Midzyanovskaya
authors.forename: Dmitrij
authors.initials: D
authors.lastname: Salonin
authors.forename: Clementina
authors.initials: C
authors.lastname: van Rijn
authors.forename: Anton
authors.initials: A
authors.lastname: Coenen
authors.forename: Leene
authors.initials: L
authors.lastname: Tuomisto
authors.forename: Gilles
authors.initials: G
authors.lastname: van Luijtelaar
mesh_terms: D000465:Algorithms; D000778:Anesthetics, Dissociative / Q000494:pharmacology; D000818:Animals; D018926:Anti-Allergic Agents / Q000494:pharmacology; D000927:Anticonvulsants / Q000494:pharmacology*; D003627:Data Interpretation, Statistical; D018492:Dopamine Antagonists / Q000494:pharmacology; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000187:drug effects / Q000706:statistics & numerical data*; D004832:Epilepsy, Absence / Q000188:drug therapy / Q000235:genetics / Q000503:physiopathology*; D005260:Female; D005583:Fourier Analysis; D006220:Haloperidol / Q000494:pharmacology; D007649:Ketamine / Q000494:pharmacology; D008297:Male; D011738:Pyrilamine / Q000494:pharmacology; D051381:Rats; D020888:Vigabatrin / Q000494:pharmacology
chemical_list: D000778:Anesthetics, Dissociative; D018926:Anti-Allergic Agents; D000927:Anticonvulsants; D018492:Dopamine Antagonists; D007649:Ketamine; D020888:Vigabatrin; D011738:Pyrilamine; D006220:Haloperidol