Biomedical subjects

Orhan Arikan

Publications and source records attributed to Orhan Arikan.

3 recordsLinked to original sources

PubMed2006

Early gamma response of sleep is sensory/perceptual in origin.

The goal of the study was to investigate the gamma response of the brain and its functional correlates in rapid eye movements (REM) sleep and the three stages of non-REM sleep. Data on overnight sleep were acquired from 16 healthy, young adult, volunteer males. Neuroelectric activity was recorded from seven recording sites (Fz, Cz, Pz, F3, F4, P3, P4) in response to auditory stimuli (2000 Hz deviant and 1000 Hz standard stimuli: 65 dB, 10 ms r/f time, 50 ms duration) under passive oddball paradigm. Data were analyzed with the Fourier transform and digital filtering and also the recently developed technique of time-frequency component analysis (TFCA). TFCA displayed the gamma response under all stages of sleep. Statistical analysis did not reveal a significant effect of stimulus type, recording site or sleep stage on the three parameters of TFCA, which included maximum value of the time-frequency representation of the extracted gamma component, maximum magnitude of the time-domain representation of the component and the energy of this component. The gamma period included N1 and the early theta response, both of which are related to sensory-perceptual processing in the literature. According to these findings, the gamma response is possibly related, as in wakefulness, to early stimulus processing that also includes sensory/perceptual operations.

Acoustic Stimulation↗

PubMed2005

Early time-locked gamma response and gender specificity.

The aim was to investigate whether gender is a causative factor in the gamma status according to which some individuals respond with time-locked, early gamma response, G+, while the others do not show this response, G-. The sample consisted of 42 volunteer participants (between 19 and 37 years of age with at least 9 years of education). There were 22 females and 20 males. Data were collected under the oddball paradigm. Auditory stimulation (10 ms r/f time, 50 ms duration, 65 dB SPL) consisted of target (2000 Hz; p = .20) stimuli that occurred randomly within a series of standard stimuli (1000 Hz; p = .80). Gamma responses were studied in the amplitude frequency characteristics, in the digitally filtered event-related potentials (f-ERPs) and in the distributions which were obtained using the recently developed time-frequency component analysis (TFCA) technique. Participants were classified into G+ and G- groups with a criterion of full agreement between the results of an automated gamma detection technique and expert opinion. The 2 x 2 x 2 ANOVA on f-ERPs and 2 x 2 x 2 multivariate ANOVA on TFCA distributions showed the main effect of gamma status and gender as significant, and the interaction between gamma status and gender as nonsignificant. Accordingly, individual difference in gamma status is a reliable phenomenon, but this does not depend on gender. There are conflicting findings in the literature concerning the effect of gender on ERP components (N100, P300). The present study showed that if the gamma status is not included in research designs, it may produce a confounding effect on ERP parameters.

Acoustic Stimulation↗

PubMed2005

Time-frequency component analyser and its application to brain oscillatory activity.

Currently, event-related potential (ERP) signals are analysed in the time domain (ERP technique) or in the frequency domain (Fourier analysis and variants). In techniques of time-domain and frequency-domain analysis (short-time Fourier transform, wavelet transform) assumptions concerning linearity, stationarity, and templates are made about the brain signals. In the time-frequency component analyser (TFCA), the assumption is that the signal has one or more components with non-overlapping supports in the time-frequency plane. In this study, the TFCA technique was applied to ERPs. TFCA determined and extracted the oscillatory components from the signal and, simultaneously, localized them in the time-frequency plane with high resolution and negligible cross-term contamination. The results obtained by means of TFCA were compared with those obtained by means of other commonly used techniques of ERP analysis, such as bilinear time-frequency distributions and wavelet analysis. It is suggested that TFCA may serve as an appropriate tool for capturing the localized ERP components in the time-frequency domain and for studying the intricate, frequency-based dynamics of the human brain.

Adolescent↗