Tolga Esat Özkurt

E-mail

ozkurt@metu.edu.tr

Department

Graduate School of Informatics

ORCID

0000-0002-9485-559X

Scopus Author ID

15065743500

Web of Science Researcher ID

ABA-1362-2020

Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson’s disease Özkurt, Tolga Esat (2024-02-01) Biomarkers obtained from the neurophysiological signals of patients with Parkinson’s disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prom...
Spatiotemporal signal space separation for regions of interest: Application for extracting neuromagnetic responses evoked by deep brain stimulation Oswal, Ashwini; Abdi-Sargezeh, Bahman; Sharma, Abhinav; Özkurt, Tolga Esat; Taulu, Samu; Sarangmat, Nagaraja; Green, Alexander L.; Litvak, Vladimir (2024-02-01) Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources...
Efficient and Accurate Neural Fingerprints Obtained via Mean Curve Length of High Dimensional Model Representation of EEG Signals Korkmaz Özay, Evrim; Özkurt, Tolga Esat (2023-11-01) In this study, we propose and evaluate a feature extraction methodology for the purpose of EEG-based person recognition. To this end, the mean curve length (MCL) was employed subsequent to the representation of EEG sign...
Ampirik ve/ya hazır EEG kayıtlarının kullanımına dair bir tartışma Özkurt, Tolga Esat (2023-09-11) Saçlı kafa derisinden toplanan EEG, diğer nörogörüntüleme yöntemleriyle kıyaslandığında daha ucuz ve non-invazif olmasına rağmen; ampirik çalışmaların doğası gereği deney paradigması tasarımı, uygun katılımcıların bulunu...
Mean curve length: An efficient feature for brainwave biometrics Yahyaei, Reza; Özkurt, Tolga Esat (2022-07-01) Electroencephalography (EEG) as a biometric modality has gained considerable interest in recent years. Many state-of-the-art methods have focused on increasing the recognition accuracy. However, the more complex and manipu...
A Basic Nietzschean Model in Lieu of the Causal Maxim Özkurt, Tolga Esat (2021-10-01) Causal knowledge unquestionably provides useful means to describe, explain and predict both natural and daily phenomena. This article addresses whether causality as such may not be ontologically primary and looks for an al...
Identification of nonlinear features in cortical and subcortical signals of Parkinson's Disease patients via a novel efficient measure Özkurt, Tolga Esat; Zrinzo, Ludvic; Limousin, Patricia; Foltynie, Tom; Oswal, Ashwini; Litvak, Vladimir (Elsevier BV, 2020-12-01) This study offers a novel and efficient measure based on a higher order version of autocorrelative signal memory that can identify nonlinearities in a single time series. The suggested method was applied to simultaneously ...
Brain Oscillatory Correlates of Visual Short-Term Memory Errors Mapelli, Igor; Özkurt, Tolga Esat (2019-02-13) Brain dynamics of memory formation were explored during encoding and retention intervals of a visual working memory task. EEG data were acquired while subjects were exposed to grayscale images of widely known object catego...
N1-P2: Neural markers of temporal expectation and response discrimination in interval timing Duzcu, Halil; Özkurt, Tolga Esat; Mapelli, Igor; Hohenberger, Annette (2019-01-01) Humans use temporal regularities in their daily life to act in accordance with future events in the most efficient way. To achieve this, humans build temporal expectations and determine a template action that is in line wi...
Neural oscillations, circular causality and the implications for nature Özkurt, Tolga Esat (2018-09-19)

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