@article {964, title = {Default mode network components and its relationship with anomalous self-experiences in schizophrenia: A rs-fMRI exploratory study}, journal = {Psychiatry Research: Neuroimaging}, volume = {324}, year = {2022}, pages = {111495}, abstract = {

Anomalous self-experiences (ASEs) in schizophrenia have been under research for the last 20 years. However, no neuroimage studies have provided insight of the possible biological underpinning of ASEs. In this novel approach, the connectivity within the default mode network, calculated through a ROI-based analysis of functional magnetic resonance imaging data, was correlated to the ASEs scores assessed by the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) in a sample of 22 schizophrenia patients. The Pearson{\textquoteright}s correlation coefficients between IPASE scores and intrahemispheric connectivity of the parahippocampal gyrus with the isthmus cingulate cortex in both hemispheres, and right parahippocampal gyrus with the right rostral anterior cingulate cortex were positive and significant suggesting a relation between hyperactive functional connectivity and anomalous self-experiences intensity. Prior literature reported these areas to have a role in self-processing and consciousness as well as being anatomically connected. Further research with larger sample size and comparison with controls are needed to confirm the relationship of this connectivity with anomalous self-experiences.

}, keywords = {Anterior cingulate cortex, Metacognition, Parahippocampal gyrus, Psychosis, functional magnetic resonance imaging}, issn = {0925-4927}, doi = {https://doi.org/10.1016/j.pscychresns.2022.111495}, url = {https://www.sciencedirect.com/science/article/pii/S0925492722000567}, author = {Roig-Herrero, Alejandro and {\'A}lvaro Planchuelo-G{\'o}mez and Hern{\'a}ndez-Garc{\'\i}a, Marta and de Luis-Garc{\'\i}a, Rodrigo and Fern{\'a}ndez-Linsenbarth, In{\'e}s and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and Molina, Vicente} } @article {946, title = {A deep learning approach for synthetic MRI based on two routine sequences and training with synthetic data}, journal = {Computer Methods and Programs in Biomedicine}, volume = {210}, year = {2021}, pages = {106371}, issn = {0169-2607}, doi = {10.1016/j.cmpb.2021.106371}, url = {https://doi.org/10.1016/j.cmpb.2021.106371}, author = {Moya-S{\'a}ez, Elisa and {\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {904, title = {Deep Phenotyping of Headache in Hospitalized COVID-19 Patients via Principal Component Analysis}, journal = {Frontiers in Neurology}, volume = {11}, year = {2020}, pages = {1751}, abstract = {

Objectives: Headache is a common symptom in systemic infections, and one of the symptoms of the novel coronavirus disease 2019 (COVID-19). The objective of this study was to characterize the phenotype of COVID-19 headache via machine learning.Methods: We performed a cross-sectional study nested in a retrospective cohort. Hospitalized patients with COVID-19 confirmed diagnosis who described headache were included in the study. Generalized Linear Models and Principal Component Analysis were employed to detect associations between intensity and self-reported disability caused by headache, quality and topography of headache, migraine features, COVID-19 symptoms, and results from laboratory tests.Results: One hundred and six patients were included in the study, with a mean age of 56.6 {\textpm} 11.2, including 68 (64.2\%) females. Higher intensity and/or disability caused by headache were associated with female sex, fever, abnormal platelet count and leukocytosis, as well as migraine symptoms such as aggravation by physical activity, pulsating pain, and simultaneous photophobia and phonophobia. Pain in the frontal area (83.0\% of the sample), pulsating quality, higher intensity of pain, and presence of nausea were related to lymphopenia. Pressing pain and lack of aggravation by routine physical activity were linked to low C-reactive protein and procalcitonin levels.Conclusion: Intensity and disability caused by headache attributed to COVID-19 are associated with the disease state and symptoms. Two distinct headache phenotypes were observed in relation with COVID-19 status. One phenotype seems to associate migraine symptoms with hematologic and inflammatory biomarkers of severe COVID-19; while another phenotype would link tension-type headache symptoms to milder COVID-19.

}, issn = {1664-2295}, doi = {10.3389/fneur.2020.583870}, url = {https://www.frontiersin.org/article/10.3389/fneur.2020.583870}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Trigo, Javier and Rodrigo de Luis-Garc{\'\i}a and {\'A}ngel L. Guerrero and Porta-Etessam, Jes{\'u}s and Garc{\'\i}a-Azor{\'\i}n, David} } @proceedings {723, title = {Determination of the optimal set of b-values for ADC mapping under a Rician noise assumption}, year = {2017}, pages = {3341}, address = {Honolulu, HI, USA}, abstract = {

Mapping of the apparent diffusion coefficient (ADC), estimated from a set of diffusion-weighted (DW) images acquired with different b-values, often suffers from low SNR, which can introduce large variance in ADC maps. Unfortunately, there is no consensus on the optimal b-values to maximize the noise performance of ADC map. In this work, we determine the optimal b-values to maximize the noise performance of ADC mapping by using a Cram{\'e}r-Rao Lower Bound (CRLB) approach under realistic noise assumptions. The strong agreement between the CRLB-based analysis, Monte-Carlo simulations, and ADC phantom experiment, suggests the utility of this approach to optimize DW-MRI acquisitions.

}, author = {{\'O}scar Pe{\~n}a-Nogales and Diego Hernando and Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a} }