Projects

Identification of Neuro-Cognitive Markers of Sarcopenia Disease by Using Functional Near Infrared Spectroscopy and Artificial Intelligence,

This project is being supported by The Scientic and Technological Research Council of Turkey (TUBITAK) 1001 Scientific Research Projects. Project Number : EEEAG 122E210


Sarcopenia is a disease characterized by decreased muscle mass and function, especially in elderly populations. Studies in recent years revealed that decreased muscle function in sarcopenia is a more effective marker to determine the negative effects of the disease, independent of muscle mass. Therefore, the function of the central nervous system in sarcopenia has become an important research topic. On the other hand, when the relationship between sarcopenia and cognitive function was revealed by behavioral tests in previous studies, understanding the relationship between this disease and neurological reflections of cognitive functions emerged as a critical research question.

In this project, we will try to observe the differences between the motor and cognitive functions of sarcopenia patients and healthy controls using functional Near Infrared Spectroscopy (fNIRS), and we will try to reveal the neurological markers of sarcopenia using artificial intelligence techniques from the features that will be extracted from fNIRS signals. Our project aims to;

  • Design three block design experiments, one of which is motor function and the other two cognitive functions as attention and working memory in computer environment and apply to the participants and to measure the hemodynamic response to be acquired with the fNIRS system simultaneously

  • To analyze the experimentally acquired fNIRS signals with both conventional statistical methods and artificial intelligence techniques,

  • To statistically associate the hemodynamic response-based cortical markers obtained with these methods with clinical findings and to reveal the relationship between cognitive findings and motor function findings.


The aspects of our project proposal that will provide original value and unique contribution can be explained as follows;

- Sarcopenia is a disease of muscle strength loss related to aging in general. However, its neurological markers are not yet fully known. In our project, these markers will be revealed with an approach focused on functional neuroimaging.

- The relationship of this disease with cognitive functions has been demonstrated only by clinical tests. In our project, to reveal the relationship of sarcopenia with specific functions such as memory and attention, with an approach focused on functional neuroimaging, which is an objective criterion.

Although the outputs to be obtained at the end of our project are thought to lead to areas to be targeted in the development of drug therapy in sarcopenia, where there is no drug therapy yet, neuro-cognitive findings will give researchers an idea about other cognitive functions and their neurological reflections, which will be focused on in future studies in sarcopenia disease.


Researchers: Assoc. Prof. Dr. Murat KARA (Hacettepe University, Faculty of Medicine, Department of Physical Treatment and Rehabilitation)

Prof. Dr. Bayram KAYMAK (Hacettepe University, Faculty of Medicine, Department of Physical Treatment and Rehabilitation)

Bora Mert ŞAHİN (MSc Student in Biomedical Engineering in TOBB ETÜ)

Examination of Executive Functions in Multilingualism Using Electroencephalography and Machine Learning Techniques

Executive functions such as working memory, inhibition control and processing speed, which contribute to an individual's brain health performance, will be examined with behavioral tests such as Stroop and "n-back", while simultaneously analyzing the P200, P300 and N2 ERP components related to cognitive performance in the EEG data to be obtained simultaneously with the behavioral data. In this way, executive function performance will be compared in a realistic and well-represented manner between groups of individuals with different numbers of language proficiency, and the cognitive performance of these groups will be analyzed.

The hypothesis of the study is that there will be a significant difference between the two groups of bilingual and trilingual individuals in terms of executive function-related ERP activities, namely P200, P300 and N2. In addition, it is aimed to show that the data to be obtained from cognitive tests, including Stroop and "n-back" tests, which aim to measure executive functions, to be performed with bilingual and trilingual individuals are related to EEG data. In this way, it is aimed to reveal the differences in executive function performance between bilingual and trilingual individuals with both cognitive and neurophysiological data and to show that increasing the number of languages mastered by the individual has an increasing effect on executive function performance. In addition, in order to better understand the effect of multilingualism on neurophysiological processes, a machine learning model that can predict multilingualism based on features to be obtained from neurophysiological data will also be developed within the scope of the study.

Co-advisor : Assoc. Prof. Dr. Gülay CEDDEN (METU Faculty of Education, Foreign Language Education Department)

Researchers: Melis Vuslat TUNÇ (MSc Student in Biomedical Engineering in TOBB ETÜ)