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Different factors have been related with interictal anxiety, reported in 10%-25% of patients with epilepsy. We determined the frequency of interictal anxiety in 196 patients with active epilepsy in a cross-sectional survey to know which symptoms of anxiety were most frequently reported in patients with epilepsy and to analyze the factors associated with their presence. Patients were assessed with the Beck Depression Inventory (BDI), MontgomeryAsberg Depression Rating Scale (MADRS), and the Hamilton Anxiety Scale (HAMA). Data were analyzed with a logistic regression model. The HAMA ratings revealed that 38.8% experienced signifi cant anxiety symptoms, as defi ned by a rating above 18 points. Use of primidone, depression, cryptogenic, and posttraumatic etiologies signifi cantly predicted anxiety after logistic regression. Symptoms related to higher scores on HAMA were anxious mood, tension, insomnia, intellectual function, depressed mood, cardiovascular and genitourinary symptoms. Further studies should be performed to defi ne the role of psychosocial factors in the development and evolution of anxiety among these patients.

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Abstract. Spatial patterns in an image that shows a visual perception of roughness or softness of the surface is known as the texture of the image. Most of the analysis and description of texture found in the literature is based on statistical or structural properties of this attribute [2]. The field of cellular automata (CA), which has been developed mainly to model the dynamical behavior of systems, is based on the behavior or arrangements of pixel values and their neighborhood which, according to some rules behaves in different manners [2,8]. In this paper, within the frame of structural approach, a novel method based on the properties of linear cellular automata is proposed to characterize different sort of textures. To this purpose, it is assumed that a binary version of the image under study was generated by a cellular automata technique. By using this model a number of textural primitives are found which allows the production of a characterizing image. In order to verify the feasibility of the proposed method, texture images generated by CA techniques as well as natural images has been used.