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Biomedical subjects

Murat Ozgören

Publications and source records attributed to Murat Ozgören.

3 recordsLinked to original sources

Brain oscillations differentiate the picture of one's own grandmother.

The present report introduces, as a first study, the concept and methods of oscillatory brain dynamics to analyze well-known (familiar) and unfamiliar face processing in the 800 ms following a face presentation. We analyzed event-related oscillations in young, healthy subjects (N=26) by using three types of stimulation: (1) a simple light signal, (2) the picture of the face of an anonymous elderly lady and (3) the picture of the subjects' own grandmother. We found a number of significant peak to peak amplitude measures in all frequency bands in the time period of 0-500 ms, allowing a differentiation between perception of the subjects' own grandmother, the unknown elderly face and the light stimulation. The results showed increased event-related oscillatory responses elicited by the unknown face compared to the known grandmother a) in the theta responses (4-8 Hz) at T(6) (46%), b) in the gamma (28-48 Hz) responses at C(z) (22%) and C(3) (38%) and c) in the beta responses at F(4) (46%), C(z) (47%) and P(3) (105%). In contrast, the subjects' own grandmother elicited 20% increased fast theta (6-8 Hz) oscillations at F(4) compared to the unknown face. Delta responses dissociated face from simple light processing, as reflected in the observation of approx. 50% higher amplitudes at the occipital compared to the frontal locations during face perception. We conclude that the described multiple brain oscillations clearly differentiate the known and unknown faces with varied degrees of selective-responsiveness in a short time window between 0 and 800 ms. Furthermore, the results are in conceptual accordance with the "selectively distributed processing" hypothesis.

Adolescent↗

Beta oscillations in face recognition.

This report presents an analysis of the brain's beta oscillations in face recognition. We performed experiments on 26 subjects with a strategy consisting of two types of stimulations: (1) the picture of an elder anonymous lady (unknown face) and (2) the picture of the subject's own grandmother (known face). The subjects were healthy, young people between the ages of 15-32 years. Data were analyzed by means of amplitude frequency characteristics and digital filtering. Our results show the significant role of beta response in face recognition and the differentiation of known and unknown faces. Furthermore, this report supports our former view that the presentation of grandmother face evokes selectively distributed multiple oscillations in the brain. Together with the scope of other frequencies (e.g., delta, theta, and alpha), this method can serve as a tool for research studies or clinical studies in memory and cognition.

Adolescent↗

Wavelet entropy analysis of event-related potentials indicates modality-independent theta dominance.

Sensory/cognitive stimulation elicits multiple electroencephalogram (EEG)-oscillations that may be partly or fully overlapping over the time axis. To evaluate co-existent multi-frequency oscillations, EEG responses to unimodal (auditory or visual) and bimodal (combined auditory and visual) stimuli were analyzed by applying a new method called wavelet entropy (WE). The method is based on the wavelet transform (WT) and quantifies entropy of short segments of the event-related brain potentials (ERPs). For each modality, a significant transient decrease of WE emerged in the post-stimulus EEG epoch indicating a highly-ordered state in the ERP. WE minimum was always determined by a prominent dominance of theta (4-8 Hz) ERP components over other frequency bands. Event-related 'transition to order' was most pronounced and stable at anterior electrodes, and after bimodal stimulation. Being consistently observed across different modalities, a transient theta-dominated state may reflect a processing stage that is obligatory for stimulus evaluation, during which interfering activations from other frequency networks are minimized.

Acoustic Stimulation↗