Pedro Valdes Sosa

Publications of Pedro Valdes Sosa

• Mesoscale in neuroimaging: creating bridges between the microscopic and system levels.

  Authors: Jorge Riera, Pedro Valdes Sosa

  Journal of integrative neuroscience. 12/2010; 9(4):v-vii.

• Minimum Overlap Component Analysis (MOCA) of EEG/MEG data for more than two sources.

  Authors: Guido Nolte, Laura Marzetti, Pedro Valdes Sosa

  Journal of neuroscience methods. 08/2009;

  In many situations various methods to analyze EEG/MEG data result in subspaces of the sensor space spanned by potentials of a set of sources. We propose a general model free method to decompose suchIn many situations various methods to analyze EEG/MEG data result in subspaces of the sensor space spanned by potentials of a set of sources. We propose a general model free method to decompose such a subspace into contributions from distinct sources. This unique decomposition can be achieved by first finding the respective subspace in source space using a linear inverse method and then finding the linear transformation such that the source distributions are mutually orthogonal and have a minimum overlap. The corresponding algorithm is a generalization of the recently presented 'Minimum Overlap Component Analysis' (MOCA) to more than two sources. The computational cost is negligible and the algorithm is almost never trapped in local minima. The method is illustrated with results for alpha rhythm.

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• ERP generator anomalies in presymptomatic carriers of the Alzheimer's disease E280A PS-1 mutation.

  Authors: María A Bobes, Yuriem Fernández García, Francisco Lopera, Yakeel T Quiroz, Lídice Galán, Mayrim Vega, Nelson Trujillo, Mitchell Valdes-Sosa, Pedro Valdes-Sosa

  Human brain mapping. 08/2009;

  Although subtle anatomical anomalies long precede the onset of clinical symptoms in Alzheimer's disease, their impact on the reorganization of brain networks underlying cognitive functions has notAlthough subtle anatomical anomalies long precede the onset of clinical symptoms in Alzheimer's disease, their impact on the reorganization of brain networks underlying cognitive functions has not been fully explored. A unique window into this reorganization is provided by presymptomatic cases of familial Alzheimer's disease (FAD). Here we studied neural circuitry related to semantic processing in presymptomatic FAD cases by estimating the intracranial sources of the N400 event-related potential (ERP). ERPs were obtained during a semantic-matching task from 24 presymptomatic carriers and 25 symptomatic carriers of the E280A presenilin-1 (PS-1) mutation, as well as 27 noncarriers (from the same families). As expected, the symptomatic-carrier group performed worse in the matching task and had lower N400 amplitudes than both asymptomatic groups, which did not differ from each other on these variables. However, N400 topography differed in mutation carrier groups with respect to the noncarriers. Intracranial source analysis evinced that the presymptomatic-carriers presented a decrease of N400 generator strength in right inferior-temporal and medial cingulate areas and increased generator strength in the left hippocampus and parahippocampus compared to the controls. This represents alterations in neural function without translation into behavioral impairments. Compared to controls, the symptomatic-carriers presented a similar anatomical shift in the distribution of N400 generators to that found in presymptomatic-carriers, albeit with a larger reduction in generator strength. The redistribution of N400 generators in presymptomatic-carriers indicates that early focal degeneration associated with the mutation induces neural reorganization, possibly contributing to a functional compensation that enables normal performance in the semantic task. Hum Brain Mapp, 2009. (c) 2009 Wiley-Liss, Inc.

• Recursive penalized least squares solution for dynamical inverse problems of EEG generation.

  Authors: Okito Yamashita, Andreas Galka, Tohru Ozaki, Rolando Biscay, Pedro Valdes-Sosa

  Human brain mapping. 05/2004; 21(4):221-35.

  In the dynamical inverse problem of electroencephalogram (EEG) generation where a specific dynamics for the electrical current distribution is assumed, we can impose general spatiotemporalIn the dynamical inverse problem of electroencephalogram (EEG) generation where a specific dynamics for the electrical current distribution is assumed, we can impose general spatiotemporal constraints onto the solution by casting the problem into a state space representation and assuming a specific class of parametric models for the dynamics. The Akaike Bayesian Information Criterion (ABIC), which is based on the Type II likelihood, was used to estimate the parameters and evaluate the model. In addition, dynamic low-resolution brain electromagnetic tomography (LORETA), a new approach for estimating the current distribution is introduced. A recursive penalized least squares (RPLS) step forms the main element of our implementation. To obtain improved inverse solutions, dynamic LORETA exploits both spatial and temporal information, whereas LORETA uses only spatial information. A considerable improvement in performance compared to LORETA was found when dynamic LORETA was applied to simulated EEG data, and the new method was applied also to clinical EEG data.