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    B-tensor: brain connectome tensor factorization for Alzheimer's disease
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Durusoy, Goktekin; Yildirm, Zerrin; Dal, Demet Yuksel; Ulasoglu-Yildiz, Cigdem; Kurt, Elif; Bayir, Gunes; Ozacar, Erhan; Ozarslan, Evren; Demirtas-Tatldede, Asl; Bilgic, Basar; Demiralp, Tamer; Gurvit, Hakan; Acar, Burak; Department of Physics; Kabakçıoğlu, Alkan; Faculty Member; Department of Physics; College of Sciences; 49854
    AD is the highly severe part of the dementia spectrum and impairs cognitive abilities of individuals, bringing economic, societal and psychological burdens beyond the diseased. A promising approach in AD research is the analysis of structural and functional brain connectomes, i.e., sNETs and fNETs, respectively. We propose to use tensor representation (B-tensor) of uni-modal and multi-modal brain connectomes to define a low-dimensional space via tensor factorization. We show on a cohort of 47 subjects, spanning the spectrum of dementia, that diagnosis with an accuracy of 77% to 100% is achievable in a 5D connectome space using different structural and functional connectome constructions in a uni-modal and multi-modal fashion. We further show that multi-modal tensor factorization improves the results suggesting complementary information in structure and function. A neurological assessment of the connectivity patterns identified largely agrees with prior knowledge, yet also suggests new associations that may play a role in the disease progress.
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    Modeling reflex asymmetries with implicit delay differential equations
    (Elsevier, 1998) Mallet-Paret, J; Department of Mathematics; Atay, Fatihcan; Faculty Member; Department of Mathematics; College of Sciences; 253074
    Neuromuscular reflexes with time-delayed negative feedback, such as the pupil light reflex, have different rates depending on the direction of movement. This asymmetry is modeled by an implicit first-order delay differential equation in which the value of the rate constant depends on the direction of movement. Stability analyses are presented for the cases when the rate is: (1) an increasing and (2) a decreasing function of the direction of movement. It is shown that the stability of equilibria in these dynamical systems depends on whether the rate constant is a decreasing or increasing function. In particular, when the asymmetry has the shape of an increasing step function, it is possible to have stability which is independent of the value of the time delay or the steepness (i.e., gain) of the negative feedback. (C) 1998 Society for Mathematical Biology.
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    Obsessive-compulsive tendencies and action sequence complexity: an information theory analysis
    (Springer, 2019) Zeki, Mustafa; Moustafa, Ahmed A.; Department of Psychology; Department of Psychology; Balcı, Fuat; Öztel, Tutku; Faculty Member; Teaching Faculty; Department of Psychology; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Social Sciences and Humanities; College of Social Sciences and Humanities; 51269; N/A
    Obsessive-compulsive disorder (OCD) is a psychiatric condition that is primarily associated with anxiety provoking repetitive thoughts (i.e., obsessions) and actions that are manifested to neutralize the resultant anxiety (i.e., compulsions). Interestingly, OCD patients continue compulsive behaviors (e.g., repeatedly rechecking if the door is locked) although they are typically aware of the irrationality of these behaviors. This suggests that compulsive behaviors have habit-like features. We predicted that the motor actions (e.g., sequence of goalless key presses) would deviate from randomness in individuals with stronger obsessive-compulsive (OC) tendencies and thus expected to observe more rigid sequential action patterns in these individuals (e.g., pressing keys according to a motif). We applied entropy theory approach, defined as the rate of change of information in a given sequence, to test this hypothesis. We collected two different types of sequential behavioral data from healthy individuals and scored their obsessive-compulsive tendencies based on the Padua Inventory. In the first method, we asked participants to press one of the two buttons sequentially. In the second method, participants were asked to mark one of the four different options sequentially (on a multiple-choice optic form). The behavioral characterization was carried out by quantifying the entropy in the sequence of two sets of behavioral data using the Shannon metric entropy and Lempel-Ziv complexity measures. Our results revealed a negative relationship between the degree of washing tendencies and the level of information contained in action sequences. These results held only for the data collected with key presses and not for the choice sequences in the paper-pencil task. Based on these results, we conclude that the behavioral rigidity observed in the form of compulsive actions may generalize to some other behaviors of the individual.