@conference {968, title = {Long-term grey matter structural changes in the transition from chronic migraine to episodic migraine}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: The objective was to assess grey matter longitudinal changes in patients with chronic migraine (CM) who reverse to episodic migraine (EM) compared to those who do not reverse.

Methods: High-resolution 3D brain T1-weighted Magnetic Resonance Imaging data were obtained twice from migraine patients. The first acquisition was performed immediately after the first visit to the Headache Unit, before taking preventive treatments. The second timepoint was at least three years after the first acquisition. From the longitudinal pipeline of FreeSurfer (v6.0), the mean values of cortical thickness, surface area and grey matter volume of 68 cortical, 14 subcortical regions and the cerebellum were extracted. Longitudinal changes between patients with CM and those who reversed to EM were assessed with linear
mixed-effects models, setting p\<0.05 (false discovery rate corrected) as threshold for statistical significance.

Results: 22 patients were included, and 10 of them (45.5\%) reversed to EM. No statistically significant differences of age (42.0+-9.0 years) and sex (21 women, 95.5\%) were found between patient groups. Higher statistically significant values of the three parameters in patients who reversed to EM were found in the pericalcarine, parietal, orbitofrontal cortex, and amygdala (Table 1, Figure 1). In contrast, lower values were detected in the cingulum, caudal middle frontal cortex, cerebellum, caudate nucleus and pallidum (Figure 2). In the insula, higher thickness but lower area was appreciated in patients who reversed.

Conclusion: Patients with CM who reverse to EM present distinct patterns of increased and decreased morphometric parameters propagated in the orbital frontal cortex and the cingulum, respectively.

Disclosure: Nothing to disclose.

}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Marchante-Re{\'\i}llo, Ginebra and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Mart{\'\i}n-Mart{\'\i}n, Carmen and de Luis-Garc{\'\i}a, Rodrigo and Aja-Fern{\'a}ndez, Santiago and Moro, Ra{\'u}l and Rodr{\'\i}guez, Margarita and Gonz{\'a}lez-Osorio, Y{\'e}sica and {\'A}ngel L. Guerrero} } @conference {945, title = {Longitudinal reduction of quality of life in patients with epilepsy and no seizure increase during the COVID-19 pandemic}, booktitle = {7th Congress of the European Academy of Neurology}, year = {2021}, month = {2021}, publisher = {Wiley}, organization = {Wiley}, address = {Virtual Congress}, abstract = {

Background and aims: In early 2020, the novel coronavirus disease (COVID-19) pandemic has impaired medical care of chronic neurological diseases, including epilepsy. The objective of this study is to evaluate the impact of the COVID-19 pandemic in the levels of anxiety, depression, somnolence and quality of life using validated scales in patients with epilepsy in real-life clinical practice.
Methods: Self-administered scales of anxiety disorders (GAD-7), depression (NDDI-E), somnolence (Epworth Sleepiness Scale; ESS) and quality of life (QOLIE-31-P) in patients with epilepsy treated in the Refractory Epilepsy Unit of a tertiary hospital were longitudinally analyzed with Generalized Linear Mixed Models. Data were collected before the beginning (December 2019-March 2020) and during the COVID-19 pandemic (September 2020-January 2021).
Results: 37 patients, 45.0+-17.3 years of age, 43.2\% women, epilepsy duration 23.0+-14.9 years, number of anti-epileptic drugs 2.1+-1.4, answered in the two periods. Significant longitudinal reduction of QOLIE-31-P scores (from 58.9+-19.7 to 56.2+-16.2, p=0.035) was identified. No statistically significant longitudinal changes in NDDI-E (from 12.3+-4.3 to 13.4+-4.4, p=0.293) or the number of seizures (from 0.9+-1.9 to 2.5+-6.2, p=0.125) were found. Significant higher ESS (from 4.9+-3.7 to 7.4+-4.9, p=0.001) and lower GAD-7 scores (from 8.8+-6.2 to 8.3+-5.9, corrected p=0.024 adjusted by refractory epilepsy and sleep disturbance) were found during the COVID-19 pandemic.
Conclusion: During the COVID-19 pandemic, quality of life was lower in patients with epilepsy, levels of anxiety were reduced and sleepiness levels were raised, without seizure change. Additional studies would be useful to adequately manage these comorbidities.
Disclosure: There is no disclosure.

}, url = {https://www.ean.org/fileadmin/user_upload/ean/congress-2021/EAN2021AbstractBook.pdf}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo, Mar{\'\i}a} } @article {890, title = {Longitudinal evaluation of the psychological impact of the COVID-19 crisis in Spain}, journal = {Journal of Affective Disorders}, volume = {277}, year = {2020}, pages = {842-849}, abstract = {Background: Strict confinement and social distancing measures have been imposed due to the COVID-19 pandemic in many countries. The aim was to assess the temporal evolution of the psychological impact of the COVID-19 crisis and lockdown from two surveys, separated by one month, performed in Spain. Methods: Symptoms of depression, anxiety and stress, and the psychological impact of the situation were longitudinally analyzed using the Depression Anxiety and Stress Scale (DASS-21) and the Impact of Event Scale (IES) respectively. Results: There was a total of 4,724 responses from both surveys. Symptomatic scores of anxiety, depression and stress were exhibited by 37.22\%, 46.42\% and 49.66\% of the second survey respondents, showing a significant increase compared to the first survey (32.45\%, 44.11\% and 37.01\%, respectively). There was no significant longitudinal change of the IES scores, with 48.30\% of the second survey participants showing moderate to severe impact of the confinement. Constant news consumption about COVID-19 was found to be positively associated with symptomatic scores in the different scales, and daily physical activity to be negatively associated with DASS-21 scores. Conclusions: Results indicated a temporal increase of anxiety, depression and stress scores during the COVID-19 lockdown. Factors such as age, consumption of information about COVID-19 and physical activity seem to have an important impact on the evolution of psychological symptoms.}, keywords = {Anxiety, COVID-19, Depression, Longitudinal study, Post-traumatic, Psychological, Stress, Stress disorders}, issn = {0165-0327}, doi = {10.1016/j.jad.2020.09.018}, url = {http://www.sciencedirect.com/science/article/pii/S0165032720327130}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Rodrigo de Luis-Garc{\'\i}a} } @article {794, title = {Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson{\textquoteright}s Disease}, journal = {Frontiers in Neuroscience}, volume = {12}, year = {2018}, pages = {967}, author = {{\'O}scar Pe{\~n}a-Nogales and Ellmore, Timothy Michael and Rodrigo de Luis-Garc{\'\i}a and Suescun, Jessika and Schiess, Mya Caryn and Giancardo, Luca} } @article {743, title = {Libstable: Fast, parallel, and high-precision computation of α-stable distributions in R, C/C++, and MATLAB}, journal = {Journal of Statistical Software}, volume = {78}, year = {2017}, pages = {1-25}, doi = {10.18637/jss.v078.i01}, author = {J Royuela-del-Val and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {534, title = {A local fuzzy thresholding methodology for multiregion image segmentation}, journal = {Knowledge-Based Systems}, volume = {83}, year = {2015}, month = {07/2015}, pages = {1-12}, abstract = {

Abstract Thresholding is a direct and simple approach to extract different regions from an image. In its basic formulation, thresholding searches for a global value that maximizes the separation between output classes. The use of a single hard threshold value is precisely the source of important segmentation errors in many scenarios like noisy images or uneven illumination. If no connectivity or closed objects are considered, the method is prone to produce isolated pixels. In this paper a new multiregion thresholding methodology is presented to overcome the common drawbacks of thresholding methods when images are corrupted with artifacts and noise. It is based on relating each pixel in the image to different output centroids via a fuzzy membership function, avoiding any initial hard decision. The starting point of the technique is the definition of the output centroids using a clustering method compatible with most thresholding techniques in the literature. The method makes use of the spatial information through a local aggregation step where the membership degree of each pixel is modified by local information that takes into account the memberships of the surrounding pixels. This makes the method robust to noise and artifacts. The general formulation of the proposed methodology allows the design of spatial aggregations for multiple applications, including the possibility of including heuristic information via a fuzzy inference rule base.

}, issn = {0950-7051}, doi = {http://dx.doi.org/10.1016/j.knosys.2015.02.029}, url = {http://www.sciencedirect.com/science/article/pii/S095070511500129X}, author = {Santiago Aja-Fern{\'a}ndez and Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @article {476, title = {Localized abnormalities in the cingulum bundle in patients with schizophrenia: A Diffusion Tensor tractography study}, journal = {NeuroImage: Clinical}, volume = {5}, year = {2014}, pages = {93{\textendash}99}, abstract = {

The cingulum bundle (CB) connects gray matter structures of the limbic system and as such has been implicated in the etiology of schizophrenia. There is growing evidence to suggest that the CB is actually comprised of a conglomeration of discrete sub-connections. The present study aimed to use Diffusion Tensor tractography to subdivide the CB into its constituent sub-connections, and to investigate the structural integrity of these sub-connections in patients with schizophrenia and matched healthy controls. Diffusion Tensor Imaging scans were acquired from 24 patients diagnosed with chronic schizophrenia and 26 matched healthy controls. Deterministic tractography was used in conjunction with FreeSurfer-based regions-of-interest to subdivide the CB into 5 sub-connections (I1 to I5). The patients with schizophrenia exhibited subnormal levels of FA in two cingulum sub-connections, specifically the fibers connecting the rostral and caudal anterior cingulate gyrus (I1) and the fibers connecting the isthmus of the cingulate with the parahippocampal cortex (I4). Furthermore, while FA in the I1 sub-connection was correlated with the severity of patients{\textquoteright} positive symptoms (specifically hallucinations and delusions), FA in the I4 sub-connection was correlated with the severity of patients{\textquoteright} negative symptoms (specifically affective flattening and anhedonia/asociality). These results support the notion that the CB is a conglomeration of structurally interconnected yet functionally distinct sub-connections, of which only a subset are abnormal in patients with schizophrenia. Furthermore, while acknowledging the fact that the present study only investigated the CB, these results suggest that the positive and negative symptoms of schizophrenia may have distinct neurobiological underpinnings.

}, author = {Whitford, Thomas J and Lee, Sun Woo and Oh, Jungsu S and Rodrigo de Luis-Garc{\'\i}a and Savadjiev, Peter and Alvarado, Jorge L and Carl-Fredik Westin and Niznikiewicz, Margaret and Nestor, Paul G and McCarley, Robert W} } @article {tristan2012least, title = {Least squares for diffusion tensor estimation revisited: Propagation of uncertainty with Rician and non-Rician signals}, journal = {NeuroImage}, volume = {59}, number = {4}, year = {2012}, pages = {4032{\textendash}4043}, publisher = {Academic Press}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin} } @article {424, title = {Leaf classification in sunflower crops by computer vision and neural networks}, journal = {Computers and Electronics in Agriculture}, volume = {78}, year = {2011}, pages = {9-18}, abstract = {

In this article, we present an automatic leaves image classification system for sunflower crops using neural networks, which could be used in selective herbicide applications. The system is comprised of four main stages. First, a segmentation based on rgb color space is performed. Second, many different features are detected and then extracted from the segmented image. Third, the most discriminable set of features are selected. Finally, the Generalized Softmax Perceptron (GSP) neural network architecture is used in conjunction with the recently proposed Posterior Probability Model Selection (PPMS) algorithm for complexity selection in order to select the leaves in an image and then classify them either as sunflower or non-sunflower. The experimental results show that the proposed system achieves a high level of accuracy with only five selected discriminative features obtaining an average Correct Classification Rate of 85\% and an area under the receiver operation curve over 90\%, for the test set. {\^A}{\textcopyright} 2011 Elsevier B.V.

}, keywords = {Classification rates, Computer vision, Crops, Discriminative features, Generalized softmax perceptron, Helianthus, Herbicide application, Herbicides, Image classification, Image classification systems, Leaf classification, Learning machines, Model selection, Network architecture, Neural networks, Posterior probability, RGB color space, Segmented images, Sunflower, Test sets, accuracy assessment, agricultural technology, algorithm, artificial neural network, automation, dicotyledon, experimental study, herbicide, segmentation}, issn = {01681699}, doi = {10.1016/j.compag.2011.05.007}, url = {https://www.sciencedirect.com/science/article/pii/S0168169911001220}, author = {J I Arribas and G V Sanchez-Ferrero and G Ruiz-Ruiz and Jaime Gomez-Gil} } @inbook {martin2009log, title = {A log-euclidean polyaffine registration for articulated structures in medical images}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {156{\textendash}164}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Miguel Angel Martin-Fernandez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {tristan2008local, title = {Local similarity measures for demons-like registration algorithms}, booktitle = {Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on}, year = {2008}, pages = {1087{\textendash}1090}, publisher = {IEEE}, organization = {IEEE}, author = {Antonio Trist{\'a}n-Vega and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {lopez2005edad, title = {La edad como factor modificador del ritmo circadiano del infarto agudo de miocardio}, journal = {Medicina intensiva}, volume = {29}, number = {9}, year = {2005}, pages = {455{\textendash}461}, publisher = {Elsevier}, author = {Juan Bautista Lopez-Messa and JR Garmendia-Leiza and MD Aguilar-Garcia and Jes{\'u}s Mar{\'\i}a And De Llano and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @inbook {ruiz2005landmark, title = {Landmark-Based Registration of Medical-Image Data}, booktitle = {Medical Image Analysis Methods, Edited by Lena Costaridou, CRC Press}, year = {2005}, author = {Juan Ruiz-Alzola and Suarez-Santana, E and Carlos Alberola-Lopez and Carl-Fredik Westin} } @conference {430, title = {A lossless compression algorithm based on predictive coding for volumetric medical datasets}, booktitle = {Proc. EUSIPCO 2005}, year = {2005}, author = {D{\'\i}ez-Garc{\'\i}a, M{\'o}nica and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {martín2005low, title = {On low order moments of the homodyned-k distribution}, journal = {Ultrasonics}, volume = {43}, number = {4}, year = {2005}, pages = {283{\textendash}290}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez} }