Browsing by Author "Kiyi, Ilayda"

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Alzheimer Hastaliği Klinik Olcutlerine Gore Demans ve Hafif Kognitif Bozukluk Ayriminda Sozel Akicilik Testlerinin Mini Mental Durum Testi ile Birlikte Kullanilmasi Yararli Olabilir
(Cukurova Univ, Fac Medicine, 2022) Isbitiren, Yagmur Ozbek; Kiyi, Ilayda; Yener, Görsev
Purpose: The aim of this study is to present the sensitivity, specificity and cut-off points of Mini Mental State Examination (MMSE), semantic and phonemic fluency tests determined by ROC curve analysis in differentiating between Alzheimer's dementia (AD) and mild cognitive impairment (MCI).Materials and Methods: Age-education-sex matched 72 healthy individuals, 72 MCI and 72 AD dementia individuals were included in the study. MMSE, semantic and phonemic fluency tests were applied to all participants. Sensitivity and specificity values and cut-off scores of MMSE, semantic and phonemic fluency tests in distinguishing healthy, MCI and ADD individuals were obtained by ROC curve analysis.Results: ROC analyses show that all three tests can significantly discriminate between healthy, ADD and MCI individuals. It was seen that the discrimination power of the MMSE was higher than the verbal fluency tests when the areas under the ROC curve were compared. The specificity of semantic fluency was found to be higher than MMSE and phonemic fluency in distinguishing individuals with ADD and MCI.Conclusion: The findings of the study show that MMSE is stronger than semantic and phonemic fluency in distinguishing healthy individuals, but its specificity is lower than semantic fluency in distinguishing MCI and AD dementia. In order to increase the diagnostic accuracy, it may be effective to add verbal fluency tests, especially semantic fluency test, which can be applied in a short time, to clinical practice.
Citation - WoS: 2
Citation - Scopus: 2
Cognitive Evidence on Eeg-P300 in Healthy Individuals With High Depression Scores
(Wolters Kluwer Medknow Publications, 2022) Oz, Didem; Ozbek, Yagmur; Kiyi, Ilayda; Ozturk, Bilge Targitay; Oztura, Ibrahim; Yener, Görsev
Background:Depression is common among elderly and middle-aged individuals and is a reason for decreased quality of life. Depression may lead to impairments in cognitive abilities. The P300 potential is one of the most used event-related potentials (ERPs) to evaluate cognition. This study investigated the P300 amplitude differences between individuals with depressive symptoms and nondepressed healthy elderly individuals. Materials and Methods:The current study included twenty individuals with high depression scores (high DS, age: 64.80 +/- 7.22, 6 M/14 F) and twenty demographically matched participants with low depression scores (low DS, age: 64.20 +/- 6.21, 7 M/13 F). The Geriatric Depression Scale (GDS) was used to evaluate whether participants have depressive symptoms. All of the participants were underwent a comprehensive neuropsychological battery. The ERPs were recorded with a visual classical oddball paradigm. The P300 amplitudes were measured in the 250-550 ms time window. Results:High DS group had lower P300 amplitudes than low DS individuals regardless of electrode location. Correlation analyses showed that there was a significant correlation between GDS scores and the P300 amplitudes recorded from the F-z electrode. Conclusion:The current study showed the reduced P300 amplitudes on individuals with high GDS scores. The P300 potential may be a useful tool to determine possible changes or impairments due to subthreshold depressive symptoms.
Citation - WoS: 17
Citation - Scopus: 24
Eeg Biomarkers in Alzheimer's and Prodromal Alzheimer's: a Comprehensive Analysis of Spectral and Connectivity Features
(BMC, 2024) Chetty, Chowtapalle Anuraag; Bhardwaj, Harsha; Kumar, G. Pradeep; Devanand, T.; Sekhar, C. S. Aswin; Akturk, Tuba; Kiyi, Ilayda
BackgroundBiomarkers of Alzheimer's disease (AD) and mild cognitive impairment (MCI, or prodromal AD) are highly significant for early diagnosis, clinical trials and treatment outcome evaluations. Electroencephalography (EEG), being noninvasive and easily accessible, has recently been the center of focus. However, a comprehensive understanding of EEG in dementia is still needed. A primary objective of this study is to investigate which of the many EEG characteristics could effectively differentiate between individuals with AD or prodromal AD and healthy individuals.MethodsWe collected resting state EEG data from individuals with AD, prodromal AD, and normal cognition. Two distinct preprocessing pipelines were employed to study the reliability of the extracted measures across different datasets. We extracted 41 different EEG features. We have also developed a stand-alone software application package, Feature Analyzer, as a comprehensive toolbox for EEG analysis. This tool allows users to extract 41 EEG features spanning various domains, including complexity measures, wavelet features, spectral power ratios, and entropy measures. We performed statistical tests to investigate the differences in AD or prodromal AD from age-matched cognitively normal individuals based on the extracted EEG features, power spectral density (PSD), and EEG functional connectivity.ResultsSpectral power ratio measures such as theta/alpha and theta/beta power ratios showed significant differences between cognitively normal and AD individuals. Theta power was higher in AD, suggesting a slowing of oscillations in AD; however, the functional connectivity of the theta band was decreased in AD individuals. In contrast, we observed increased gamma/alpha power ratio, gamma power, and gamma functional connectivity in prodromal AD. Entropy and complexity measures after correcting for multiple electrode comparisons did not show differences in AD or prodromal AD groups. We thus catalogued AD and prodromal AD-specific EEG features.ConclusionsOur findings reveal that the changes in power and connectivity in certain frequency bands of EEG differ in prodromal AD and AD. The spectral power, power ratios, and the functional connectivity of theta and gamma could be biomarkers for diagnosis of AD and prodromal AD, measure the treatment outcome, and possibly a target for brain stimulation.
The Evaluation of P300 Component Differences Across Sensory Modalities in Healthy Individuals Aged 50 and Over: Auditory and Visual
(Elsevier, 2021) Kiyi, Ilayda; Öztura, İbrahim; Yener, Görsev
[Abstract Not Available]
Investigating EEG Spectral Power and Inter-Trial Coherence Responses in OCD Using the Checkerboard/Go No-Go Paradigm
(Elsevier, 2025) Yener, Gorsev; Altuntas, Kubra; Ari, Ozge; Gulpinar, Aybars; Kiyi, Ilayda; Babalioglu, Merve; Basar-Eroglu, Canan
Citation - WoS: 2
Citation - Scopus: 2
Senior Moments Are Never-Ending Times When You Are Old (are They?): First Step of Turquoise Project
(Turkish Neuropsychiatry Assoc-Turk Noropsikiyatri Dernegi, 2022) Oz, Didem; Yildirim, Zerrin; Kiyi, Ilayda; Ozbek, Yagmur; Kulac, Ibrahim; Erkol, Gokhan; Tihan, Tarik; Yener, Görsev
Introduction: The number of dementia patients is increasing in Turkey,, as well as all over the world. However, we do not know how much the society knows about dementia. The aim of this study is to evaluate people's concept of dementia, their awareness of dementia research and treatment, whether dementia and forgetfulness are considered normal in old age, and whether having dementia is associated with a lack of mental abilities. Methods: A Dementia Awareness Questionnaire was created in the form of a self-report questionnaire, consisting of 20 questions and using a five-point Likert-type answering method in order to question participants' information about dementia. In addition, we asked for demographic information such as age, gender, occupation, education level of the participants, as well as whether they have had relatives diagnosed with a neurodegenerative disease. The surveys were administered online. Results: A total of 1551 participants from 53 cities were included in the study. Approximately half of the participants did not know the definition of dementia, 20.9% thought that dementia and Alzheimer's disease were the same; 50.4% considered forgetfulness, and 55.2% considered dementia as a natural consequence of aging. While 34.5% of the participants thought that dementia patients could be dangerous, 10.3% thought they could not continue living as a part of society. While 38.5% of healthcare professionals do not know the definition of dementia, 18.5% of them say that dementia and Alzheimer's disease are the same, 58.5% think that dementia patients are not fit to make their own decisions, 40.6% believe that dementia patients have criminal liability. 15.8% of healthcare professionals thought that dementia is only seen in elderly people; 21.4% thought that dementia, and 49.2% thought that forgetfulness was a result of normal aging. Conclusion: Our study confirms that dementia is still an unknown concept in society and among healthcare professionals. It is widely believed that forgetfulness and dementia are part of normal aging, and there is no cure for dementia. This study, which we have done in order to understand the level of dementia awareness in Turkish society, reveals the necessity for research on dementia and studies on how to increase dementia awareness.
Citation - WoS: 2
Citation - Scopus: 2
Telling Functional Networks Apart Using Ranked Network Features Stability
(Nature Portfolio, 2022) Zanin, Massimiliano; Guntekin, Bahar; Akturk, Tuba; Yildirim, Ebru; Yener, Görsev; Kiyi, Ilayda; Hunerli-Gunduz, Duygu
Over the past few years, it has become standard to describe brain anatomical and functional organisation in terms of complex networks, wherein single brain regions or modules and their connections are respectively identified with network nodes and the links connecting them. Often, the goal of a given study is not that of modelling brain activity but, more basically, to discriminate between experimental conditions or populations, thus to find a way to compute differences between them. This in turn involves two important aspects: defining discriminative features and quantifying differences between them. Here we show that the ranked dynamical stability of network features, from links or nodes to higher-level network properties, discriminates well between healthy brain activity and various pathological conditions. These easily computable properties, which constitute local but topographically aspecific aspects of brain activity, greatly simplify inter-network comparisons and spare the need for network pruning. Our results are discussed in terms of microstate stability. Some implications for functional brain activity are discussed.