About
34
Publications
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Introduction
I am a researcher in the field of neuroscience. I am using my engineering and programming skills for biological signal and image processing.
Current institution
Additional affiliations
September 2018 - November 2023
October 2016 - August 2018
November 2014 - October 2016
Education
March 2007 - August 2007
January 2006 - April 2012
July 2002 - November 2005
Publications
Publications (34)
This study aims to compare human and machine vision using fuzzy logic with YOLOV3 algorithm based on brightness and contrast values in the images. In order to determine detection thresholds for the contrast and the brightness parameters, we conducted a survey including 50 participants. We also examined how these two parameters affect each other dep...
This study focuses on controlling a quadcopter system using a steady-state visual evoked potential (SSVEP)-based brain-computer interface system. In the literature, researchers report the accuracy and information transfer rate. However, these measures do not provide sufficient information about the predicted and target path similarity. The drone is...
A USW based diagnostic procedure is presented for estimating the depth of surface-breaking cracks. The diagnosis is demonstrated on seven lab-scale SFRC beam specimens, which are subjected to the CMOD controlled three-point bending test to create real bending cracks. Then, the recorded multiple ultrasonic signals are examined with the signal proces...
Brain-computer interfaces (BCIs) offer a very high potential to help those who cannot use their organs properly. In the literature, many electroencephalogram based BCIs exist. Steady state visual evoked potential (SSVEP) based BCIs provide relatively higher accuracy values which make them very popular in BCI research. Recently, deep learning (DL) b...
Periodic signals called Steady-State Visual Evoked Potentials (SSVEP) are elicited in the brain by flickering stimuli. They are usually detected by means of regression techniques that need relatively long trial lengths to provide feedback and/or sufficient number of calibration trials to be reliably estimated in the context of brain-computer interf...
Self-initiated movements are known to be preceded by the readiness potential or RP, a gradual increase in surface-negativity of cortical potentials that can begin up to 1 second or more before movement onset. The RP has been extensively studied for decades, and yet we still lack a clear understanding of its functional role. Attempts to model the RP...
There has been a growing interest in the role of pre-stimulus oscillations on cortical excitability in visual and motor systems. Prior studies focused on the relationship between pre-stimulus neuronal activity and TMS-evoked motor evoked potentials (MEPs) have reported heterogeneous results. We aimed to assess the role of pre-stimulus neural activi...
Brain-computer interface (BCI) paradigms are usually tested when environmental and biological artifacts are intentionally avoided. In this study, we deliberately introduced different perturbations in order to test the robustness of a steady state visual evoked potential (SSVEP) based BCI. Specifically we investigated to what extent a drop in perfor...
A demonstrative video showing several trials from the online task.
Subject focuses on one of the four flickering circles for three seconds and confirms (presses ‘Y’ key) or rejects (presses ‘N’ key and then specifies the correct response with the arrow keys) the classification result using keyboard.
(MP4)
A demonstrative video showing one trial from the offline task.
Subject focuses on each of the four randomly presented flickering circles indicated by the red oval frame for three seconds with an inter-stimulus interval (ISI) of one second.
(MP4)
The Readiness Potential (RP) is a slowly increasing surface-negative cortical potential that precedes spontaneous voluntary movements. A recent interpretation provided by the stochastic decision model suggests that this slow exponential preceding the motor event could be the result of a time-locked average of ongoing sub-threshold fluctuations in n...
The Readiness Potential (RP) is a slowly increasing surface-negative cortical potential that precedes spontaneous voluntary movements. A recent interpretation provided by the stochastic decision model [2] suggests that this slow exponential preceding the motor event could be the result of a time-locked average of ongoing sub-threshold fluctuations...
Symptoms of anxiety are highly comorbid with major depressive disorder (MDD) and are known to alter the course of the disease. To help elucidate the biological underpinnings of these prevalent disorders, we previously examined the relationship between components of anxiety (somatic, psychic and motoric) and serotonin 1A receptor (5-HT1A) binding in...
Inter- and intra-subject variability of the motor evoked potentials (MEPs) to TMS is a well-known phenomenon. Although a possible link between this variability and ongoing brain oscillations was demonstrated, the results of the studies are not consistent with each other. Exploring this topic further is important since the modulation of MEPs provide...
While variability of the motor responses to TMS is widely acknowledged, little is known about its central origin. One plausible explanation for such variability may relate to different neuronal states defining the reactivity of the cortex to TMS. In this study intrinsic spatio-temporal neuronal dynamics were estimated with Long-Range Temporal Corre...
In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of inter...
In this paper, Multi-Class T-Weight Method (MCTW) is presented for classification in brain-computer interface (BCI) systems. Proposed method is an extension of the existing Improved T-Weight method for multi-class problems. The method was tested on the frequency and correlation based features obtained from electroencephalogram data of 20 Subjects i...
Background / Purpose:
We analyzed the test-retest reliability of automated cortical thickness (CT) and cortical volume (CV) measures acquired from different sites.
Main conclusion:
Cortical thickness and cortical volume measures should be used carefully.
In this paper, an electroencephalogram-based innovative brain–computer interface (BCI), known as “Character Plotter”, is presented. The proposed design uses steady-state visually evoked potentials. The subjects generate characters by drawing, step by step, lines between six circles on the computer screen. Additionally, there are three circles for c...
In this paper, T-Weight Method is improved by integration of a threshold determination step into the original algorithm. The new method is called Improved T-Weight (ITW) Method and the performance of the ITW Method is evaluated on classification of slow cortical potentials (SCPs) for a brain-computer interface (BCI) task. Two different datasets fro...
In this paper, successful detection of P300 wave embedded into electroencephalogram (EEG) data is aimed. Detection performance
of a previously applied method is increased by using proper pre-processing scheme. Development in the detection performance
in terms of overall classification accuracy is presented in a detailed manner. The proposed method...
In this paper, electroencephalogram (EEG) signals of 20 subjects are classified in a steady state visual evoked potential
(SSVEP) based brain computer interface (BCI) system by using 4 different stimulation frequencies in a program created by Visual
C#. After applying proper pre-processing methods, power spectral density (PSD) based features are e...
In this paper, the classification method which generated the second highest AUC (the area under the ROC curve) in the MLSP 2010 Competition is presented. After application of some pre-processing steps to the dataset, by using statistical information, proper weights are found which maximize the separability between the P300 and the non-P300 response...
In the study, an automated system was proposed for the evaluation of survey sheets filled by different students. In this method, the regions related to the answers on the survey sheets digitized by a scanner are determined. For this purpose, after finding the right edge of the survey, upper-right corner of the survey is marked by a developed edge t...
X-ray bone images are used in the areas such as bone age assessment, bone mass assessment and examination of bone fractures. Medical image analysis is a very challenging problem due to large variability in topologies, medical structure complexities and poor image modalities such as noise, low contrast, several kinds of artifacts and restrictive sca...
In this study, a novel method is proposed for the detection of tumor in magnetic resonance (MR) brain images. The performance of the novel method is investigated on one phantom and 20 original MR brain images with tumor and 50 normal (healthy) MR brain images.Before the segmentation process, 2D continuous wavelet transform (CWT) is applied to revea...
In the study, the method used in the 6th Annual MLSP Competition (Mind Reading) organized in the 2010 IEEE International Workshop on Machine Learning For Signal Processing (MLSP 2010) is explained. The goal in the competition is to select or design a method (feature extraction, pre-processing and classifier) in order to classify the acquired electr...
In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment th...
In this study, discrimination between different art categories was presented. To be able to classify different art images, features capable of including the characteristic properties of art types were extracted. Extracted features are based on RGB histogram characteristics, coarseness and edge ratio in the images. Obtained features were used in dif...
This paper presents an Improved Incremental Self-Organizing Map (I2SOM) network that utilizes automatic threshold (AT) value
for the segmentation of ultrasound (US) images. I2SOM network has been compared with the well-known unsupervised Kohonen’s
SOM network (KSOM) and a supervised Grow and Learn (GAL) network in terms of classification accuracy,...
This paper presents a novel method that uses incremental self-organizing map (ISOM) network and wavelet transform together
for the segmentation of magnetic resonance (MR), computer tomography (CT) and ultrasound (US) images. In order to show the
validity of the proposed scheme, ISOM has been compared with Kohonen’s SOM. Two-dimensional continuous w...
