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Yayın Shrinkage of olfactory amygdala connotes cognitive impairment in patients with Parkinson’s disease(Springer, 2023-10) Ay, Ulaş; Yıldırım, Zerrin; Erdoğdu, Emel; Kıçik, Ani; Öztürk Işık, Esin; Demiralp, Tamer; Gürvit, HakanDuring the caudo-rostral progression of Lewy pathology, the amygdala is involved relatively early in Parkinson’s disease (PD). However, lesser is known about the volumetric differences at the amygdala subdivisions, although the evidence mainly implicates the olfactory amygdala. We aimed to investigate the volumetric differences between the amygdala’s nuclear and sectoral subdivisions in the PD cognitive impairment continuum compared to healthy controls (HC). The volumes of nine nuclei of the amygdala were estimated with FreeSurfer (nuclear parcellation-NP) from T1-weighted images of PD patients with normal cognition (PD-CN), PD with mild cognitive impairment (PD-MCI), PD with dementia (PD-D), and HC. The appropriate nuclei were then merged to obtain three sectors of the amygdala (sectoral parcellation-SP). The nuclear and sectoral volumes were compared among the four groups and between the hyposmic and normosmic PD patients. There was a significant difference in the total amygdala volume among the four groups. In terms of nuclei, the bilateral cortico-amygdaloid transition area (CAT) and sectors superficial cortex-like region (sCLR) volumes of PD-MCI and PD-D were less than those of the PD-CN and HC. A linear discriminant analysis revealed that left CAT and left sCLR volumes classified the PD-CN and cognitively impaired PD (PD-CI: PD-MCI plus PD-D) with 90.7% accuracy according to NP and 85.2% accuracy to SP. Similarly, left CAT and sCLR volumes correctly identified the hyposmic and normosmic PD with 64.8% and 61.1% accuracies. Notably, the left olfactory amygdala volume successfully discriminated cognitive impairment in PD and could be used as neuroimaging-based support for PD-CI diagnosis.Yayın White-matter changes in early and late stages of mild cognitive impairment(Churchill Livingstone, 2020-08) Femir Gürtuna, Banu; Kurt, Elif; Ulaşoğlu Yıldız, Çiğdem; Bayram, Ali; Yıldırım, Elif; Soncu Büyükişcan, Ezgi; Bilgiç, BaşarMild Cognitive Impairment (MCI) is characterized by cognitive deficits that exceed age-related decline, but not interfering with daily living activities. Amnestic type of the disorder (aMCI) is known to have a high risk to progress to Alzheimer's Disease (AD), the most common type of dementia. Identification of very early structural changes in the brain related to the cognitive decline in MCI patients would further contribute to the understanding of the dementias. In the current study, we target to investigate whether the white-matter changes are related to structural changes, as well as the cognitive performance of MCI patients. Forty-nine MCI patients were classified as Early MCI (E-MCI, n = 24) and Late MCI (L-MCI, n = 25) due to their performance on The Free and Cued Selective Reminding Test (FCSRT). Age-Related White-Matter Changes (ARWMC) scale was used to evaluate the white-matter changes in the brain. Volumes of specific brain regions were calculated with the FreeSurfer program. Both group and correlation analyses were conducted to show if there was any association between white-matter hyperintensities (WMHs) and structural changes and cognitive performance. Our results indicate that, L-MCI patients had significantly more WMHs not in all but only in the frontal regions compared to E-MCI patients. Besides, ARWMC scores were not correlated with total hippocampal and white-matter volumes. It can be concluded that WMHs play an important role in MCI and cognitive functions are affected by white-matter changes of MCI patients, especially in the frontal regions.Yayın Investigation of symptom-specific functional connectivity patterns in Parkinson’s disease(Springer-Verlag Italia S.R.L., 2025-06-14) Kıçik, Ani; Bayram, Ali; Erdoğdu, Emel; Kurt, Elif; Sarıdede, Dilek Betül; Cengiz, Sevim; Bilgiç, Başar; Hanağası, Haşmet; Öztürk Işık, Esin; Gürvit, Hakan; Tüzün, Erdem; Demiralp, TamerParkinson’s disease (PD) is a complex neurodegenerative disease, characterized by pronounced heterogeneity in symptoms. This study investigates the functional connectivity (FC) patterns associated with distinct symptom clusters, aiming to elucidate the heterogeneity in PD and uncover the neural mechanisms underlying its motor and cognitive symptoms. Resting-state functional MRI (rs-fMRI) data from 55 non-demented PD patients and 24 healthy controls (HC) were used to perform seed-to-seed FC analyses. A clustering algorithm was applied to the cognitive and motor scores of all PD patients to generate relatively homogeneous symptomatic subgroups. PD patients exhibited a general decrease in FC within a network comprising the sensorimotor network (SMN) and the visual network (VN) regions. Symptom-based clustering revealed three relatively homogeneous subgroups, exhibiting a gradient pattern: patients with greater motor deficits showed significant disconnection within the SMN, whereas patients with greater visuospatial deficits exhibited reduced FC in an extended subnetwork, with pronounced disconnections between the VN and SMN areas. Our study demonstrated a notable disconnection between the SMN and VN, indicating impaired visual-motor integration in PD. Stronger disconnection within the SMN was associated with greater motor dysfunction, and stronger visual-sensorimotor disconnections were associated with greater visuospatial deficits. These findings suggest that at least two separate routes of functional disconnection may be responsible for the inhomogeneous symptom distribution in PD.
