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Yayın The effect of the interaction between autistic traits and psychotic proneness on empathy: a cross-sectional study with a non-clinical sample(Emerald Publishing, 2023-11-08) Yıldırım, ElifPurpose: Recent evidence indicates an improving effect of the co-occurrence of autistic traits and psychotic symptoms on social cognition, but there is no agreement on the effect of the interaction between autistic traits and psychotic proneness on empathy. The aim of this study is to examine the effect of the interaction between autistic traits and positive psychotic experiences on cognitive and affective empathy. Design/methodology/approach: The sample consisted of 420 adults aged between 18 and 60. Assessments were administered anonymously online. Empathic abilities were evaluated by the Interpersonal Reactivity Index (IRI). While Autism Spectrum Quotient (AQ) was applied to measure autistic traits, The Community Assessment of Psychic Experience (CAPE) was used as a measurement of positive psychotic experiences. Findings: A series of regression analyses showed that although AQ and CAPE scores were not correlated with cognitive-IRI, the interaction between these scores predicted cognitive-IRI scores. It was found that the personal distress subscale of IRI was significantly associated with AQ, but this relationship was moderated by CAPE scores. Originality/value: These findings provide a different perspective on understanding social cognitive impairments in autism, which may have potential clinical implications. Findings also contribute to explaining the individual differences in empathic abilities.Yayın A new method for the source localization in sectionally homogeneous bounded domains involving finitely many inner interfaces of arbitrary shapes(Pergamon-Elsevier Science, 2001-05) İdemen, Mehmet Mithat; Alkumru, AliA new method to localize a static point source buried in a nonhomogeneous bounded domain composed of finitely many homogeneous parts separated by interfaces of arbitrary shapes was established. The source can be a simple point charge or current or a dipole of them. The method requires only the knowledge of the potential function Phi (x, y, z) at five or six points on the outermost interface depending on whether the source is simple or dipole. The new and basic feature of the method consists of determining the potential function Phi (0)(x, y, z) which would be observed if the whole space was filled with a homogeneous material. Then, in the case of a simple source, the position P-0 as well as the strengths can be determined, in general, by solving a system of three linear algebraic equations. When the source consists of a dipole, its position P-0 and moment (p) over right arrow can be found by solving a system of six nonlinear algebraic equations. The determination of Phi (0) P-0 and s (or (p) over right arrow) is achieved iteratively by solving the above-mentioned algebraic equations along with a singular integral equation satisfied by Phi (0) Some illustrative examples show the applicability and accuracy of the method. The method can have effective applications in heat conduction, matter diffusion, electrostatics, steady-state current flow, electroencephalography, electrocardiography, etc.Yayın Automated cell nucleus detection for large-volume electron microscopy of neural tissue(IEEE, 2014-04-29) Tek, Faik Boray; Kroeger, Thorben; Hamprecht, Fred A.; Mikula, ShawnVolumetric electron microscopy techniques, such as serial block-face electron microscopy (SBEM), generate massive amounts of image data that are used for reconstructing neural circuits. Typically, this requires time-intensive manual annotation of cells and their connections. To facilitate this analysis, we study the problem of automated detection of cell nuclei in a new SBEM dataset that contains cerebral cortex, white matter, and striatum from an adult mouse brain. The dataset was manually annotated to identify the locations of all 3309 cell nuclei in the volume. We make both dataset and annotations available here. Using a hybrid approach that combines interactive learning, morphological processing, and object level feature classification, we demonstrate automated detection of cell nuclei at 92.4% recall and 95.1% precision. These algorithms are not RAM-limited and can scale to arbitrarily large datasets.Yayın Convolutional attention network for MRI-based Alzheimer's disease classification and its interpretability analysis(IEEE, 2021-09-17) Türkan, Yasemin; Tek, Faik BorayNeuroimaging techniques, such as Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET), help to identify Alzheimer's disease (AD). These techniques generate large-scale, high-dimensional, multimodal neuroimaging data, which is time-consuming and difficult to interpret and classify. Therefore, interest in deep learning approaches for the classification of 3D structural MRI brain scans has grown rapidly. In this research study, we improved the 3D VGG model proposed by Korolev et al. [2]. We increased the filters in the 3D convolutional layers and then added an attention mechanism for better classification. We compared the performance of the proposed approaches for the classification of Alzheimer's disease versus mild cognitive impairments and normal cohorts on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We observed that both the accuracy and area under curve results improved with the proposed models. However, deep neural networks are black boxes that produce predictions that require further explanation for medical usage. We compared the 3D-data interpretation capabilities of the proposed models using four different interpretability methods: Occlusion, 3D Ultrametric Contour Map, 3D Gradient-Weighted Class Activation Mapping, and SHapley Additive explanations (SHAP). We observed that explanation results differed in different network models and data classes.Yayın Cross-sectional thermoacoustic imaging using multi-layer cylindrical media(IEEE, 2017-11-10) Elmas, Demet; Ünalmış Uzun, Banu; İdemen, Mehmet Mithat; Karaman, MustafaFor cross-sectional two-dimensional thermoacustic imaging of breast and brain, we explored solution of the wave equation using layered tissue model consisting of concentric annular layers on a cylindrical cross-section. To obtain the forward and inverse solutions of the thermoacoustic wave equation, we derived the Green's function involving Bessel and Hankel functions by employing the geometrical and acoustic parameters (densities and velocities) of layered media together with temporal initial condition, radiation conditions and continuity conditions on the layers' boundaries. The image reconstruction based on this approach involves the layer parameters as the apriori information which can be estimated from the acquired thermoacoustic data. To test and compare our layered solution with conventional solution based on homogeneous medium assumption, we performed simulations using numerical test phantoms consisting of sources distributed in the layered structure.Yayın Cognitive functions among healthy older adults using online social networking(Routledge, 2023-07-04) Yıldırım, Elif; Ögel Balaban, HaleOnline social network sites provide possibilities to enhance social relationships and engage in cognitive activities for older adults. The present study aimed to investigate the relationship between the use of one social network site, Facebook, and cognitive functions in older adults considering different dimensions of Facebook use together with different cognitive functions. Seventy healthy older adults completed the use of Facebook form, Multidimensional Scale of Perceived Social Support, and Social Network Index. Their cognitive functions were measured with Digit Span Tasks, Free and Cued Selective Reminding Test, Letter and Category Fluency Tests, Stroop Test, Digit Symbol Substitution Test, and Trail Making Test (TMT-A and TMT-B). After controlling for age, gender, education level, we found that Facebook users performed better on TMT-A compared to non-users. Among Facebook users, the length of having an account, the network size, the daily duration of use, and the frequency of active and passive use correlated with cognitive performance after controlling offline sociality. These findings, which need confirmation by experimental and longitudinal studies, suggested that being connected to a larger network via more prolonged and active use of social media might be associated with higher cognitive functioning.Yayın Analyzing language ability in first-episode psychosis and their unaffected siblings: a diffusion tensor imaging tract-based spatial statistics analysis study(Elsevier Ltd, 2024-11) Çabuk, Tuğçe; Şahin Çevik, Didenur; Çakmak, Işık Batuhan; Yılmaz Kafalı, Helin; Şenol, Bedirhan; Avcı, Hanife; Karlı Oğuz, Kader; Toulopoulou, TimotheaSchizophrenia (SZ) is a highly heritable mental disorder, and language dysfunctions play a crucial role in diagnosing it. Although language-related symptoms such as disorganized speech were predicted by the polygenic risk for SZ which emphasized the common genetic liability for the disease, few studies investigated possible white matter integrity abnormalities in the language-related tracts in those at familial high-risk for SZ. Also, their results are not consistent. In this current study, we examined possible aberrations in language-related white matter tracts in patients with first-episode psychosis (FEP, N = 20), their siblings (SIB, N = 20), and healthy controls (CON, N = 20) by applying whole-brain Tract-Based Spatial Statistics and region-of-interest analyses. We also assessed language ability by Thought and Language Index (TLI) using Thematic Apperception Test (TAT) pictures and verbal fluency to see whether the scores of these language tests would predict the differences in these tracts. We found significant alterations in language-related tracts such as inferior longitudinal fasciculus (ILF) and uncinate fasciculus (UF) among three groups and between SIB and CON. We also proved partly their relationship with the language test as indicated by the significant correlation detected between TLI Impoverished thought/language sub-scale and ILF. We could not find any difference between FEP and CON. These results showed that the abnormalities, especially in the ILF and UF, could be important pathophysiological vulnerability indexes of schizophrenia. Further studies are required to understand better the role of language as a possible endophenotype in schizophrenia with larger samples.Yayın Boundary element method for EEG single-dipole localization: a study in patients with OCD(Institute of Electrical and Electronics Engineers Inc., 2025-08-15) Abdullahi, Fatima I.; Demirer, Rüştü MuratThis study investigates EEG dipole localization in patients diagnosed with obsessive-compulsive disorder (OCD) using the Boundary Element Method (BEM) implemented via Brainstorm and OpenMEEG. EEG signals from 33 OCD patients were analyzed using a realistic, multi-layer head model consisting of scalp, skull, and brain tissues with respective conductivity values. Dipoles were accurately localized for each discrete time instant within the gamma frequency range (20-50 Hz) using a single dipole assumption per time point. EEG potentials measured from 19 standard electrodes were numerically computed by solving the forward EEG problem with the boundary element approach provided by OpenMEEG. Spectral clustering analysis identified distinct neural patterns corresponding to clinically recognized OCD subtypes, facilitating better diagnostic interpretations. Our results address previous methodological limitations by combining realistic head geometry modeling and precise temporal and spatial dipole estimation, offering promising directions for enhanced EEG-based diagnostic tools in psychiatry.
