Center for Biomedical Technology

Madrid, Spain

Center for Biomedical Technology

Madrid, Spain

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Cashdollar N.,University of California at San Francisco | Cashdollar N.,University of Trento | Fukuda K.,University of Oregon | Bocklage A.,University of Mannheim | And 3 more authors.
Psychology and Aging | Year: 2013

Older adults are more vulnerable to a negative impact of irrelevant information on cognitive performance. We used a psychophysical approach to evaluate which aspects of distraction are altered in aging: susceptibility for attention to be captured by a distractor, or the timing of disengagement from processing a distractor. We found that younger and older adults were equally susceptible to a detrimental influence of attentional capture on target detection in the initial moments after distractor presentation, but older adults exhibited a longer time window for the negative effects of capture to resolve. As was recently shown in younger adults, the timing of disengagement from capture correlated with individual differences in visual working memory capacity in the older cohort. These results suggest that the larger impact by distraction on perceptual abilities in normal aging is not the result of a greater susceptibility to attentional capture by distraction, but rather the prolonged processing of distractors. © 2012 American Psychological Association.


Buldu J.M.,Rey Juan Carlos University | Buldu J.M.,Center for Biomedical Technology | Bajo R.,Complutense University of Madrid | Maestu F.,Complutense University of Madrid | And 12 more authors.
PLoS ONE | Year: 2011

Whether the balance between integration and segregation of information in the brain is damaged in Mild Cognitive Impairment (MCI) subjects is still a matter of debate. Here we characterize the functional network architecture of MCI subjects by means of complex networks analysis. Magnetoencephalograms (MEG) time series obtained during a memory task were evaluated by synchronization likelihood (SL), to quantify the statistical dependence between MEG signals and to obtain the functional networks. Graphs from MCI subjects show an enhancement of the strength of connections, together with an increase in the outreach parameter, suggesting that memory processing in MCI subjects is associated with higher energy expenditure and a tendency toward random structure, which breaks the balance between integration and segregation. All features are reproduced by an evolutionary network model that simulates the degenerative process of a healthy functional network to that associated with MCI. Due to the high rate of conversion from MCI to Alzheimer Disease (AD), these results show that the analysis of functional networks could be an appropriate tool for the early detection of both MCI and AD. © 2011 Buldú et al.


Ariza P.,Technical University of Madrid | Solesio-Jofre E.,Autonomous University of Madrid | Martinez J.H.,Technical University of Madrid | Martinez J.H.,El Rosario University | And 8 more authors.
Frontiers in Human Neuroscience | Year: 2015

In this study we used graph theory analysis to investigate age-related reorganization of functional networks during the active maintenance of information that is interrupted by external interference. Additionally, we sought to investigate network differences before and after averaging network parameters between both maintenance and interference windows. We compared young and older adults by measuring their magnetoencephalographic recordings during an interference-based working memory task restricted to successful recognitions. Data analysis focused on the topology/temporal evolution of functional networks during both the maintenance and interference windows. We observed that: (a) Older adults require higher synchronization between cortical brain sites in order to achieve a successful recognition, (b) The main differences between age groups arise during the interference window, (c) Older adults show reduced ability to reorganize network topology when interference is introduced, and (d) Averaging network parameters leads to a loss of sensitivity to detect age differences. © 2015 Ariza, Solesio-Jofre, Martínez, Pineda-Pardo, Niso, Maestú and Buldú.


PubMed | Autonomous University of Madrid, Technical University of Madrid, University of San Pablo - CEU, Center for Biomedical Technology and 2 more.
Type: | Journal: Frontiers in human neuroscience | Year: 2015

In this study we used graph theory analysis to investigate age-related reorganization of functional networks during the active maintenance of information that is interrupted by external interference. Additionally, we sought to investigate network differences before and after averaging network parameters between both maintenance and interference windows. We compared young and older adults by measuring their magnetoencephalographic recordings during an interference-based working memory task restricted to successful recognitions. Data analysis focused on the topology/temporal evolution of functional networks during both the maintenance and interference windows. We observed that: (a) Older adults require higher synchronization between cortical brain sites in order to achieve a successful recognition, (b) The main differences between age groups arise during the interference window,


Martin-Buro M.C.,Center for Biomedical Technology | Martin-Buro M.C.,Complutense University of Madrid | Martin-Buro M.C.,CIBER ISCIII | Garces P.,Center for Biomedical Technology | And 5 more authors.
Human Brain Mapping | Year: 2016

Several studies have reported changes in spontaneous brain rhythms that could be used as clinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), low beta (13-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC>0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted in high within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials. © 2015 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.


Lopez-Higes R.,Complutense University of Madrid | Gallego C.,Complutense University of Madrid | Martin-Aragoneses M.T.,Spanish University for Distance Education (UNED) | Martin-Aragoneses M.T.,Center for Biomedical Technology | Melle N.,Complutense University of Madrid
Journal of Deaf Studies and Deaf Education | Year: 2014

This study explores morpho-syntactic reading comprehension in 19 Spanish children who received a cochlear implant (CI) before 24 months of age (early CI [e-CI]) and 19 Spanish children who received a CI after 24 months (late CI [l-CI]). They all were in primary school and were compared to a hearing control (HC) group of 19 children. Tests of perceptual reasoning, working memory, receptive vocabulary, and morpho-syntactic comprehension were used in the assessment. It was observed that while children with l-CI showed a delay, those with e-CI reached a level close to that which was obtained by their control peers in morpho-syntactic comprehension. Thus, results confirm a positive effect of early implantation on morpho-syntactic reading comprehension. Inflectional morphology and simple sentence comprehension were noted to be better in the e-CI group than in the l-CI group. The most important factor in distinguishing between the HC and l-CI groups or the e-CI and l-CI groups was verbal inflectional morphology. © The Author 2014. Published by Oxford University Press.


News Article | October 6, 2016
Site: www.biosciencetechnology.com

Parkinson’s disease is the second most common neurodegenerative disorder in the developed world, with around 60,000 people diagnosed in the U.S. each year. Although there is no cure for the disease, there are treatments that can reduce the severity of a patient’s symptoms. But for these treatments to be effective, clinicians need a method to regularly monitor the patient’s symptoms in the home. In a paper published in the journal Scientific Reports, researchers at MIT and elsewhere describe a technique they have developed to monitor Parkinson’s disease progression as patients interact with a computer keyboard. In this way the technique, which is based on technology originally developed to replace computer passwords, allows Parkinson’s signs to be monitored as people perform ordinary tasks such as typing emails or updating their Facebook status, according to Luca Giancardo, a former Catalyst Fellow in the Madrid-MIT M+Vision Consortium in the Research Laboratory of Electronics at MIT, and one of the paper’s lead authors. “This approach uses something we do normally — interacting with a digital device — so it does not add any additional burden or take time away from daily activities,” he said. Parkinson’s disease, which is caused by a loss of nerve cells in the brain leading to a reduction in levels of the chemical dopamine, is a progressive disorder with signs including tremors and motor difficulties, and ultimately severe disability and dementia. Medication to replace dopamine levels or mimic dopamine’s activity can help to lessen the severity of its signs. If Parkinson’s could be diagnosed earlier, researchers may even be able to develop drugs that could potentially stall the progression of the disease, according to Álvaro Sánchez-Ferro, joint lead author and a former Catalyst Fellow in the Madrid-MIT M+Vision Consortium. “The problem is that so far there has not been an easy method to provide this early detection, and one reason is that the progression of the disease is very slow,” he said. Existing methods to evaluate the severity of Parkinson’s signs are based on trained medical personnel assessing the patient’s ability to perform a number of movement activities. However, these assessments tend to be carried out in a clinical setting, limiting how often they can be undertaken. So the researchers set out to investigate whether keystroke dynamics, a technique used to identify a computer user by the time they take to press down and release each key — typically around 100 milliseconds — could be used to monitor the motor effects of Parkinson’s disease in the home. In previous work the researchers had demonstrated that the technique can be used to spot signs of sleep inertia, or the decline in motor dexterity caused by grogginess on being suddenly woken. In the new experiments, at Spanish medical clinics 12 de Octubre, Hospital Clinico, and HM CINAC, coordinated by Sánchez Ferro and co-author José Obeso at HM CINAC, the researchers asked 42 patients with early stage Parkinson’s disease and 43 healthy subjects to type out a text of their choosing for 10-15 minutes on a computer keyboard. The computer was installed with software designed to measure the timing of each press and release. When they analyzed the typing data, they found a significant variation in the timing of each press and release in patients with early stage Parkinson’s disease, while in the healthy control group this was much more uniform, Giancardo said. “By looking at the variation of this press and release, we were able to find a signature that allows us to detect Parkinson’s disease in our cohort.” To ensure the privacy of patients taking part in the test, the software does not monitor the words people type, he said. The system can be installed as software on a standard computer, or added to the hardware of a device, or even deployed on a webpage. “We envisage that this could be used to fill in the gaps between visits to the neurologist, for example, or between other tests that cannot be carried out continuously,” said Giancardo. Monitoring patients’ signs as they go about their daily activities could help doctors determine the most effective dosage of medication to prescribe at that time, and could ultimately help researchers to develop treatments to halt the disease, said Sanchez-Ferro. It could also help patients to monitor the effectiveness of activities that can reduce the effects of Parkinson’s disease, he said. “There are activities such as sports and yoga that can significantly help with the symptoms, and so the Parkinson’s community has been looking for a way to measure Parkinson’s signs quantitatively, which has so far proven very difficult to do,” said Giancardo. This is a very important piece of work, according to Bryan Strange, director of the Laboratory for Clinical Neuroscience within the Technical University of Madrid’s Center for Biomedical Technology, in Spain. “At present the ability to monitor the motor signs of those with Parkinson’s or those who are starting to develop the disease is limited to a clinical setting,” he said. This restricts the frequency with which such tests can be carried out. “This [test] is not something that requires the patient to do something out of the ordinary,” he added. The researchers hope the technique could ultimately be used to create algorithms that can detect signs of other neurological or motor-based disorders. They have already received interest from technology startup companies interested in helping the team translate the technology.


Strange B.A.,Center for Biomedical Technology | Strange B.A.,Alzheimerfs Disease Research Center | Witter M.P.,Norwegian University of Science and Technology | Lein E.S.,Allen Institute for Brain Science | Moser E.I.,Norwegian University of Science and Technology
Nature Reviews Neuroscience | Year: 2014

The precise functional role of the hippocampus remains a topic of much debate. The dominant view is that the dorsal (or posterior) hippocampus is implicated in memory and spatial navigation and the ventral (or anterior) hippocampus mediates anxiety-related behaviours. However, this 'dichotomy view' may need revision. Gene expression studies demonstrate multiple functional domains along the hippocampal long axis, which often exhibit sharply demarcated borders. By contrast, anatomical studies and electrophysiological recordings in rodents suggest that the long axis is organized along a gradient. Together, these observations suggest a model in which functional long-axis gradients are superimposed on discrete functional domains. This model provides a potential framework to explain and test the multiple functions ascribed to the hippocampus. © 2014 Macmillan Publishers Limited. All rights reserved.


Avalos-Gaytan V.,Autonomous University of Nuevo León | Almendral J.A.,Rey Juan Carlos University | Almendral J.A.,Center for Biomedical Technology | Papo D.,Center for Biomedical Technology | And 2 more authors.
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2012

Modular organization and degree-degree correlations are ubiquitous in the connectivity structure of biological, technological, and social interacting systems. So far most studies have concentrated on unveiling both features in real world networks, but a model that succeeds in generating them simultaneously is needed. We consider a network of interacting phase oscillators, and an adaptation mechanism for the coupling that promotes the connection strengths between those elements that are dynamically correlated. We show that, under these circumstances, the dynamical organization of the oscillators shapes the topology of the graph in such a way that modularity and assortativity features emerge spontaneously and simultaneously. In turn, we prove that such an emergent structure is associated with an asymptotic arrangement of the collective dynamical state of the network into cluster synchronization. © 2012 American Physical Society.


PubMed | Center for Biomedical Technology
Type: Journal Article | Journal: Human brain mapping | Year: 2016

Several studies have reported changes in spontaneous brain rhythms that could be used as clinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), low beta (13-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted in high within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials.

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