Person: Cuesta Prieto, Pablo
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First Name
Pablo
Last Name
Cuesta Prieto
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
RadiologÃa, Rehabilitación y Fisioterapia
Area
RadiologÃa y Medicina FÃsica
Identifiers
8 results
Search Results
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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) RodrÃguez Rojo, Inmaculada Concepción; Cuesta Prieto, Pablo; López GarcÃa, MarÃa Eugenia; De Frutos Lucas, Jaisalmer; Bruña Fernández, Ricardo; Pereda de Pablo, Ernesto; Barabash Bustelo, Ana; Montejo, Pedro; Montenegro Peña, MarÃa 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 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 GarcÃa, MarÃa 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 The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment(Frontiers in Human Neuroscience, 2023) Torres Simón, LucÃa; Cuesta Prieto, Pablo; del Cerro León, Alberto; Chino, Brenda; Orozco, Lucia H.; Marsh, Elisabeth B.; Gil Gregorio, Pedro; Maestu Unturbe, FernandoCerebrovascular disease is responsible for up to 20% of cases of dementia worldwide, but also it is a major comorbid contributor to the progression of other neurodegenerative diseases, like Alzheimer’s disease. White matter hyperintensities (WMH) are the most prevalent imaging marker in cerebrovascular disease. The presence and progression of WMH in the brain have been associated with general cognitive impairment and the risk to develop all types of dementia. The aim of this piece of work is the assessment of brain functional differences in an MCI population based on the WMH volume. One-hundred and twenty-nine individuals with mild cognitive impairment (MCI) underwent a neuropsychological evaluation, MRI assessment (T1 and Flair), and MEG recordings (5 min of eyes closed resting state). Those participants were further classified into vascular MCI (vMCI; n = 61, mean age 75 ± 4 years, 35 females) or non-vascular MCI (nvMCI; n = 56, mean age 72 ± 5 years, 36 females) according to their WMH total volume, assessed with an automatic detection toolbox, LST (SPM12). We used a completely data-driven approach to evaluate the differences in the power spectra between the groups. Interestingly, three clusters emerged: One cluster with widespread larger theta power and two clusters located in both temporal regions with smaller beta power for vMCI compared to nvMCI. Those power signatures were also associated with cognitive performance and hippocampal volume. Early identification and classification of dementia pathogenesis is a crucially important goal for the search for more effective management approaches. These findings could help to understand and try to palliate the contribution of WMH to particular symptoms in mixed dementia progress.Item Differential patterns of functional connectivity in Progressive and Stable Mild Cognitive Impairment subjects(Brain Connectivity, 2012) Bajo Bretón, Ricardo; Castellanos, Nazareth P.; Cuesta Prieto, Pablo; Aurtenetxe, Sara; Gil Gregorio, Pedro; Pozo, Francisco del; Maestu Unturbe, FernandoIt is now widely accepted that Alzheimer's disease is characterized by a functional disconnection between brain regions. The disease appears to begin up to decades prior to clinical diagnosis. Therefore, in the present study, we combined magnetoencephalography, a memory task, and functional connectivity analysis in mild cognitive impairment subjects in order to identify functional connectivity patterns that could characterize subjects who would eventually go on to develop the disease. We monitored 19 subjects and finally 5 of them developed Alzheimer's disease. These progressive patients showed a differential profile of functional connectivity values compared with those patients who remained stable over time. Specifically there were higher synchronization values over the parieto-occipital region in α and β frequency bands. The involvement of this brain region in amyloid-β accumulation and its possible association with hyper-synchronization are also discussed.Item Gamma band functional connectivity reduction in patients with amnestic mild cognitive impairment and epileptiform activity(Brain Communications, 2022) Cuesta Prieto, Pablo; Ochoa Urrea, Manuela; Funke, Michael; Hasan, Omar; Zhu, Ping; Marcos Dolado, Alberto; López GarcÃa, MarÃa Eugenia; Schulz, Paul E.; Lhatoo, Samden; Pantazis, Dimitrios; Mosher, John C.; Maestu Unturbe, FernandoThere is growing evidence for neuronal hyperexcitability in Alzheimer's disease. Hyperexcitability is associated with an increase in epileptiform activity and the disruption of inhibitory activity of interneurons. Interneurons fire at a high rate and are frequently associated with high-frequency oscillations in the gamma frequency band (30-150 Hz). It is unclear how hyperexcitability affects the organization of functional brain networks. A sample of 63 amnestic mild cognitive impairment patients underwent a magnetoencephalography resting-state recording with eyes closed. Twenty (31.75%) mild cognitive impairment patients had epileptiform activity. A cluster-based analysis of the magnetoencephalography functional connectivity revealed a region within the right temporal cortex whose global connectivity in the gamma frequency band was significantly reduced in patients with epileptiform activity relative to those without epileptiform activity. A subsequent seed-based analysis showed that this was largely due to weaker gamma band connectivity of this region with ipsilateral frontal and medial regions, and the upper precuneus area. In addition, this reduced functional connectivity was associated with higher grey matter atrophy across several cortical regions in the patients with epileptiform activity. These functional network disruptions and changes in brain physiology and morphology have important clinical implications as they may contribute to cognitive decline in mild cognitive impairment and Alzheimer's disease.Item Episodic memory dysfunction and hypersynchrony in brain functional networks in cognitively intact subjects and MCI: a study of 379 individuals(Geroscience, 2022) Chino, Brenda; Cuesta Prieto, Pablo; Pacios GarcÃa, Javier; De Frutos Lucas, Jaisalmer; Torres Simón, LucÃa; Doval Moreno, Sandra; Marcos Dolado, Alberto; Bruña Fernández, Ricardo; Maestu Unturbe, FernandoDelayed recall (DR) impairment is one of the most significant predictive factors in defining the progression to Alzheimer’s disease (AD). Changes in brain functional connectivity (FC) could accompany this decline in the DR performance even in a resting state condition from the preclinical stages to the diagnosis of AD itself, so the characterization of the relationship between the two phenomena has attracted increasing interest. Another aspect to contemplate is the potential moderator role of the APOE genotype in this association, considering the evidence about their implication for the disease. 379 subjects (118 mild cognitive impairment (MCI) and 261 cognitively intact (CI) individuals) underwent an extensive evaluation, including MEG recording. Applying cluster-based permutation test, we identified a cluster of differences in FC and studied which connections drove such an effect in DR. The moderation effect of APOE genotype between FC results and delayed recall was evaluated too. Higher FC in beta band in the right occipital region is associated with lower DR scores in both groups. A significant anteroposterior link emerged in the seed-based analysis with higher values in MCI. Moreover, APOE genotype appeared as a moderator between beta FC and DR performance only in the CI group. An increased beta FC in the anteroposterior brain region appears to be associated with lower memory performance in MCI. This finding could help discriminate the pattern of the progression of healthy aging to MCI and the relation between resting state and memory performance.Item Early functional network alterations in asymptomatic elders at risk for Alzheimer’s disease(Scientific Reports, 2017) Cuesta Prieto, Pablo; Nakamura, Akinori; Kato, Takashi; Arahata, Yutaka; Iwata, Kaori; Yamagishi, Misako; Kuratsubo, Izumi; Kato, Kimiko; Bundo, Masahiko; Diers, Kersten; Maestu Unturbe, Fernando; Fernández Lucas, Alberto Amable; Ito, KengoAmyloid-β (Aβ) deposition is known to starts decades before the onset of clinical symptoms of Alzheimer’s disease (AD), however, the detailed pathophysiological processes underlying this preclinical period are not well understood. This study aimed to investigate functional network alterations in cognitively intact elderly individuals at risk for AD, and assessed the association between these network alterations and changes in Aβ deposition, glucose metabolism, and brain structure. Forty-five cognitively normal elderly subjects, who were classified into Aβ-positive (CN+) and Aβ-negative (CN−) groups using 11C-Pittsburgh compound B PET, underwent resting state magnetoencephalography measurements, 18F-fluorodeoxyglucose PET (FDG-PET) and structural MRI. Results demonstrated that in the CN+ group, functional connectivity (FC) within the precuneus was significantly decreased, whereas it was significantly enhanced between the precuneus and the bilateral inferior parietal lobules in the low-frequency bands (theta and delta). These changes were suggested to be associated with local cerebral Aβ deposition. Most of Aβ+ individuals in this study did not show any metabolic or anatomical changes, and there were no significant correlations between FC values and FDG-PET or MRI volumetry data. These results demonstrate that functional network alterations, which occur in association with Aβ deposition, are detectable using magnetoencephalography before metabolic and anatomical changes are seen.Item An individual data-driven virtual resection model based on epileptic network dynamics in children with intractable epilepsy: a magnetoencephalography interictal activity application(Brain Communications, 2023) Cuesta Prieto, Pablo; Bruña Fernández, Ricardo; Shah, Ekta; Laohathai, Christopher; Garcia-Tarodo, Stephanie; Funke, Michael; Von Allmen, Gretchen; Maestu Unturbe, FernandoEpilepsy surgery continues to be a recommended treatment for intractable (medication-resistant) epilepsy; however, 30–70% of epilepsy surgery patients can continue to have seizures. Surgical failures are often associated with incomplete resection or inaccurate localization of the epileptogenic zone. This retrospective study aims to improve surgical outcome through in silico testing of surgical hypotheses through a personalized computational neurosurgery model created from individualized patient’s magnetoencephalography recording and MRI. The framework assesses the extent of the epileptic network and evaluates underlying spike dynamics, resulting in identification of one single brain volume as a candidate for resection. Dynamic-locked networks were utilized for virtual cortical resection. This in silico protocol was tested in a cohort of 24 paediatric patients with focal drug-resistant epilepsy who underwent epilepsy surgery. Of 24 patients who were included in the analysis, 79% (19 of 24) of the models agreed with the patient's clinical surgery outcome and 21% (5 of 24) were considered as model failures (accuracy 0.79, sensitivity 0.77, specificity 0.82). Patients with unsuccessful surgery outcome typically showed a model cluster outside of the resected cavity, while those with successful surgery showed the cluster model within the cavity. Two of the model failures showed the cluster in the vicinity of the resected tissue and either a functional disconnection or lack of precision of the magnetoencephalography–MRI overlapping could explain the results. Two other cases were seizure free for 1 year but developed late recurrence. This is the first study that provides in silico personalized protocol for epilepsy surgery planning using magnetoencephalography spike network analysis. This model could provide complementary information to the traditional pre-surgical assessment methods and increase the proportion of patients achieving seizure-free outcome from surgery.