Person: Bruña Fernández, Ricardo
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First Name
Ricardo
Last Name
Bruña Fernández
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
Radiología, Rehabilitación y Fisioterapia
Area
Radiología y Medicina Física
Identifiers
6 results
Search Results
Now showing 1 - 6 of 6
Item Searching for Primary Predictors of Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: A Multivariate Follow-Up Study(Journal of Alzheimer's Disease, 2016) López García, María Eugenia; Turrero Nogués, Agustín; Cuesta Prieto, Pablo; López Sanz, David; Bruña Fernández, Ricardo; Marcos Dolado, Alberto; Gil Gregorio, Pedro; Yus, Miguel; Barabash Bustelo, Ana; Cabranes Díaz, José Antonio; Maestu Unturbe, Fernando; Fernández Lucas, Alberto AmableRecent proposals of diagnostic criteria within the healthy aging-Alzheimer’s disease (AD) continuum stressed the role of biomarker information. More importantly, such information might be critical to predict those mild cognitive impairment (MCI) patients at a higher risk of conversion to AD. Usually, follow-up studies utilize a reduced number of potential markers although the conversion phenomenon may be deemed as multifactorial in essence. In addition, not only biological but also cognitive markers may play an important role. Considering this background, we investigated the role of cognitive reserve, cognitive performance in neuropsychological testing, hippocampal volumes, APOE genotype, and magnetoencephalography power sources to predict the conversion to AD in a sample of 33 MCI patients. MCIs were followed up during a 2-year period and divided into two subgroups according to their outcome: The “stable” MCI group (sMCI, 21 subjects) and the “progressive” MCI group (pMCI, 12 subjects). Baseline multifactorial information was submitted to a hierarchical logistic regression analysis to build a predictive model of conversion to AD. Results indicated that the combination of left hippocampal volume, occipital cortex theta power, and clock drawing copy subtest scores predicted conversion to AD with a 100% of sensitivity and 94.7% of specificity. According to these results it might be suggested that anatomical, cognitive, and neurophysiological markers may be considered as “first order” predictors of progression to AD, while APOE or cognitive reserve proxies might play a more secondary role.Item BDNF Val66Met polymorphism and gamma band disruption in resting state brain functional connectivity: A magnetoencephalography study in cognitively intact older females(Frontiers in Neuroscience, 2018) Rodríguez Rojo, Inmaculada Concepción; Cuesta Prieto, Pablo; López García, María Eugenia; De Frutos Lucas, Jaisalmer; Bruña Fernández, Ricardo; Pereda de Pablo, Ernesto; Barabash Bustelo, Ana; Montejo, Pedro; Montenegro Peña, María Mercedes; Marcos Dolado, Alberto; López-Higes, Ramón; Fernández Lucas, Alberto Amable; Maestu Unturbe, FernandoThe pathophysiological processes undermining brain functioning decades before the onset of the clinical symptoms associated with dementia are still not well understood. Several heritability studies have reported that the Brain Derived Neurotrophic Factor (BDNF) Val66Met genetic polymorphism could contribute to the acceleration of cognitive decline in aging. This mutation may affect brain functional connectivity (FC), especially in those who are carriers of the BDNF Met allele. The aim of this work was to explore the influence of the BDNF Val66Met polymorphism in whole brain eyes-closed, resting-state magnetoencephalography (MEG) FC in a sample of 36 cognitively intact (CI) older females. All of them were ε3ε3 homozygotes for the apolipoprotein E (APOE) gene and were divided into two subgroups according to the presence of the Met allele: Val/Met group (n = 16) and Val/Val group (n = 20). They did not differ in age, years of education, Mini-Mental State Examination scores, or normalized hippocampal volumes. Our results showed reduced antero-posterior gamma band FC within the Val/Met genetic risk group, which may be caused by a GABAergic network impairment. Despite the lack of cognitive decline, these results might suggest a selective brain network vulnerability due to the carriage of the BDNF Met allele, which is linked to a potential progression to dementia. This neurophysiological signature, as tracked with MEG FC, indicates that age-related brain functioning changes could be mediated by the influence of particular genetic risk factors.Item Enhancement of posterior brain functional networks in bilingual older adults(Bilingualism: Language and Cognition, 2019) De Frutos Lucas, Jaisalmer; López Sanz, David; Cuesta Prieto, Pablo; Bruña Fernández, Ricardo; Fuente, Sofía de la; Serrano Martínez, Noelia; López García, María Eugenia; Delgado Losada, María Luisa; López Sánchez, Ramón; Marcos Dolado, Alberto; Maestu Unturbe, FernandoBilingualism has been said to improve cognition and even delay the onset of Alzheimer's disease (AD). This research aimed to investigate whether bilingualism leaves a neurophysiological trace even when people are highly educated. We expected bilinguals to present better preserved brain functional networks, which could be a trace of higher cognitive reserve. With this purpose, we conducted a magnetoencephalographic study with a group of healthy older adults. We estimated functional connectivity using phase-locking value and found five clusters in parieto-occipital regions in which bilinguals exhibited greater functional connectivity than monolinguals. These clusters included brain regions typically implicated in language processing. Furthermore, these functional changes correlated with caudate volumes (a key region in language shifting and control) in the bilingual sample. Interestingly, decreased Functional Connectivity between posterior brain regions had already been identified as an indicator of aging/preclinical AD but, according to our study, bilingualism seems to exert the opposite effect.Item How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters(Frontiers in Neuroscience, 2018) López García, María Eugenia; Bruña Fernández, Ricardo; Cuesta Prieto, Pablo; Marcos Dolado, Alberto; Maestu Unturbe, FernandoOur work aimed to demonstrate the combination of machine learning and graph theory for the designing of a connectomic biomarker for mild cognitive impairment (MCI) subjects using eyes-closed neuromagnetic recordings. The whole analysis based on source-reconstructed neuromagnetic activity. As ROI representation, we employed the principal component analysis (PCA) and centroid approaches. As representative bi-variate connectivity estimators for the estimation of intra and cross-frequency interactions, we adopted the phase locking value (PLV), the imaginary part (iPLV) and the correlation of the envelope (CorrEnv). Both intra and cross-frequency interactions (CFC) have been estimated with the three connectivity estimators within the seven frequency bands (intra-frequency) and in pairs (CFC), correspondingly. We demonstrated how different versions of functional connectivity graphs single-layer (SL-FCG) and multi-layer (ML-FCG) can give us a different view of the functional interactions across the brain areas. Finally, we applied machine learning techniques with main scope to build a reliable connectomic biomarker by analyzing both SL-FCG and ML-FCG in two different options: as a whole unit using a tensorial extraction algorithm and as single pair-wise coupling estimations. We concluded that edge-weighed feature selection strategy outperformed the tensorial treatment of SL-FCG and ML-FCG. The highest classification performance was obtained with the centroid ROI representation and edge-weighted analysis of the SL-FCG reaching the 98% for the CorrEnv in α1:α2 and 94% for the iPLV in α2. Classification performance based on the multi-layer participation coefficient, a multiplexity index reached 52% for iPLV and 52% for CorrEnv. Selected functional connections that build the multivariate connectomic biomarker in the edge-weighted scenario are located in default-mode, fronto-parietal, and cingulo-opercular network. Our analysis supports the notion of analyzing FCG simultaneously in intra and cross-frequency whole brain interactions with various connectivity estimators in beamformed recordings.Item Hypersynchronization in mild cognitive impairment: the ‘X’ model(Brain, 2019) Pusil Arce, Sandra Angélica; López García, María Eugenia; Cuesta Prieto, Pablo; Bruña Fernández, Ricardo; Pereda, Ernesto; Maestu Unturbe, FernandoHypersynchronization has been proposed as a synaptic dysfunction biomarker in the Alzheimer's disease continuum, reflecting the alteration of the excitation/inhibition balance. While animal models have verified this idea extensively, there is still no clear evidence in humans. Here we test this hypothesis, evaluating the risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease in a longitudinal study. We compared the functional resting state eyes-closed magnetoencephalographic networks of 54 patients with MCI who were followed-up every 6 months. According to their clinical outcome, they were split into: (i) the 'progressive' MCI (n = 27) group; and (ii) the 'stable' MCI group (n = 27). They did not differ in gender or educational level. For all participants, two magnetoencephalographic recordings were acquired. Functional connectivity was evaluated using the phase locking value. To extract the functional connectivity network with significant changes between both magnetoencephalographic recordings, we evaluated the functional connectivity ratio, defined as functional connectivity post-/pre-condition, in a network-based statistical model with an ANCOVA test with age as covariate. Two significant networks were found in the theta and beta bands, involving fronto-temporal and fronto-occipital connections, and showing a diminished functional connectivity ratio in the progressive MCI group. These topologies were then evaluated at each condition showing that at baseline, patients with progressive MCI showed higher synchronization than patients with stable MCI, while in the post-condition this pattern was reversed. These results may be influenced by two main factors in the post-condition: the increased synchrony in the stable MCI patients and the network failure in the progressive MCI patients. These findings may be explained as an 'X' form model where the hypersynchrony predicts conversion, leading subsequently to a network breakdown in progressive MCI. Patients with stable MCI showed an opposite phenomenon, which could indicate that they were a step beyond in the Alzheimer's disease continuum. This model would be able to predict the risk for the conversion to dementia in MCI patients.Item Influence of the APOE ε4 allele and mild cognitive impairment diagnosis in the disruption of the MEG resting state functional connectivity in sources space(Journal of Alzheimer's Disease, 2015) Cuesta Prieto, Pablo; Garcés, Pilar; Castellanos, Nazareth P; López García, María Eugenia; Aurtenetxe, Sara; Bajo, Ricardo; Pineda-Pardo, José Angel; Bruña Fernández, Ricardo; Marín, Antonio García; Delgado Losada, María Luisa; Barabash Bustelo, Ana; Ancín, Inés; Cabranes Díaz, José Antonio; Fernández Lucas, Alberto Amable; del Pozo, Francisco; Sancho Ruiz, Miguel; Marcos Dolado, Alberto; Nakamura, Akinori; Maestu Unturbe, FernandoThe apolipoprotein E (APOE) ε4 allele constitutes the major genetic risk for the development of late onset Alzheimer's disease (AD). However, its influence on the neurodegeneration that occurs in early AD remains unresolved. In this study, the resting state magnetoencephalography(MEG) recordings were obtained from 27 aged healthy controls and 36 mild cognitive impairment (MCI) patients. All participants were divided into carriers and non-carriers of the ε4 allele. We have calculated the functional connectivity (FC) in the source space along brain regions estimated using the Harvard-Oxford atlas and in the classical bands. Then, a two way ANOVA analysis (diagnosis and APOE) was performed in each frequency band. The diagnosis effect consisted of a diminished FC within the high frequency bands in the MCI patients, affecting medial temporal and parietal regions. The APOE effect produced a decreased long range FC in delta band in ε4 carriers. Finally, the interaction effect showed that the FC pattern of the right frontal-temporal region could be reflecting a compensatory/disruption process within the ε4 allele carriers. Several of these results correlated with cognitive decline and neuropsychological performance. The present study characterizes how the APOE ε4 allele and MCI status affect the brain's functional organization by analyzing the FC patterns in MEG resting state in the sources space. Therefore a combination of genetic, neuropsychological, and neurophysiological information might help to detect MCI patients at higher risk of conversion to AD and asymptomatic subjects at higher risk of developing a manifest cognitive deterioration.