Browsing by Author "Gonul, Ali Saffet"

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The Effects of Late-Onset Depression on Brain Activity During an Episodic Memory Task
(Turkish Neuropsychiatry Assoc-Turk Noropsikiyatri Dernegi, 2025) Gulec, Zeynep Naz; Ercan, Melis; Erdogan, Yigit; Oguz, Kaya; Uyar, Aslihan; Burhanoglu, Birce Begum; Gonul, Ali Saffet
Introduction: Late-onset depression (LOD) has been implicated in irreversible cognitive decline, potentially mirroring early Alzheimer's Disease (AD) pathology. This study aimed to investigate brain activity differences during an episodic memory (EM) task in LOD patients compared to healthy controls (HC). Methods: We recruited 15 LOD patients and 13 HC matched for age and gender. Participants completed a face-name association task during functional magnetic resonance imaging (fMRI) focusing on both the encoding and retrieval phases of EM. Results: The statistical contrast between the groups revealed that the HC group showed increased activity in the left visual association cortex (VAC) and left caudate compared to the LOD group during the encoding task. During the face recognition task, the HC group showed increased activity in the right caudate, and during the name recognition task, they showed increased activity in the right frontal eye field (FEF) compared to the LOD group. Conclusion: The differences observed between the HC and LOD groups in the VAC, caudate, and FEF suggest early changes in maintaining attention, goal-directed learning, EM formation, and coordination of information from storage to retrieval before apparent impairment develops in LOD. Although we did not find statistically significant activations in areas linked to increased vulnerability to AD, our findings of hypoactivation regions responsible for visual processing and attentional orienting in LOD patients are consistentwith hypoactivation patterns observed in AD patients in previous research. These results enhance our understanding of the neural mechanisms underlying memory impairments in LOD and their potential overlap with AD pathology.
Citation - WoS: 1
Citation - Scopus: 1
Robust Activation Detection Methods for Real-Time and Offline Fmri Analysis
(Elsevier Ireland Ltd, 2017) Oguz, Kaya; Cinsdikici, Muhammed G.; Gonul, Ali Saffet
We propose two contributions with novel approaches to fMRI activation analysis. The first is to apply confidence intervals to locate activations in real-time, and second is a new metric based on robust regression of fMRI signals. These contributions are implemented in our four proposed methods; Instantaneous Activation Method (TAM), Instantaneous Activation Method with Past Blocks (TAMP) for real-time analysis, Task Robust Regression Distance Method (TRRD) for the new metric with robust regression and Instantaneous Robust Regression Distance Method (IRRD) for both contributions. For comparison, a statistical offline method called Task Activation Method (TAM) and a correlation analysis method are also implemented. The methods are initially evaluated with synthetic data generated using two different approaches; first using varying hemodynamic response function signals to simulate a wide range of stimuli responses, along with a Gaussian white noise, and second using no activity state data of a real fMRI experiment, which removes the need to generate noise. The methods are also tested with real fMRI experiments and compared with the results obtained by the widely used SPM tool. The results show that instantaneous methods reveal activations that are lost statistically in an offline analysis. They also reveal further improvements by robust fitting application, which minimizes the outlier effect. TRRD has an area under the ROC curve of 0,7127 for very noisy synthetic images, is reaching up to 0,9608 as the noise decreases, while the instantaneous score is in the range of 0,6124 to 0,8019 in the same noise levels. (C) 2017 Elsevier B.V. All rights reserved.