Minimizing the distortions in electrophysiological source imaging of cortical oscillatory activity via Spectral Structured Sparse Bayesian Learning.

Oscillatory processes at all spatial scales and on all frequencies underpin brain function. Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that provides the inverse solutions to the source processes of the EEG, MEG, or ECoG data. This study aimed to carry out an ESI of the source cross-spectrum while controlling common distortions of the estimates. As with all ESI-related problems under realistic settings, the main obstacle we faced is a severely ill-conditioned and high-dimensional inverse problem. Therefore, we opted for Bayesian inverse solutions that posited a priori probabilities on the source process. Indeed, rigorously specifying both the likelihoods and a priori probabilities of the problem leads to the proper Bayesian inverse problem of cross-spectral matrices. These inverse solutions are our formal definition for cross-spectral ESI (cESI), which requires a priori of the source cross-spectrum to counter the severe ill-condition and high-dimensionality of matrices. However, inverse solutions for this problem were NP-hard to tackle or approximated within iterations with bad-conditioned matrices in the standard ESI setup. We introduce cESI with a joint a priori probability upon the source cross-spectrum to avoid these problems. cESI inverse solutions are low-dimensional ones for the set of random vector instances and not random matrices. We achieved cESI inverse solutions through the variational approximations via our Spectral Structured Sparse Bayesian Learning (ssSBL) algorithm https://github.com/CCC-members/Spectral-Structured-Sparse-Bayesian-Learning. We compared low-density EEG (10-20 system) ssSBL inverse solutions with reference cESIs for two experiments: (a) high-density MEG that were used to simulate EEG and (b) high-density macaque ECoG that were recorded simultaneously with EEG. The ssSBL resulted in two orders of magnitude with less distortion than the state-of-the-art ESI methods. Our cESI toolbox, including the ssSBL method, is available at https://github.com/CCC-members/BC-VARETA_Toolbox.

Crystallized and fluid intelligence are predicted by microstructure of specific white-matter tracts.

Studies of the neural basis of intelligence have focused on comparing brain imaging variables with global scales instead of the cognitive domains integrating these scales or quotients. Here, the relation between mean tract-based fractional anisotropy (mTBFA) and intelligence indices was explored. Deterministic tractography was performed using a regions of interest approach for 10 white-matter fascicles along which the mTBFA was calculated. The study sample included 83 healthy individuals from the second wave of the Cuban Human Brain Mapping Project, whose WAIS-III intelligence quotients and indices were obtained. Inspired by the "Watershed model" of intelligence, we employed a regularized hierarchical Multiple Indicator, Multiple Causes model (MIMIC), to assess the association of mTBFA with intelligence scores, as mediated by latent variables summarizing the indices. Regularized MIMIC, used due to the limited sample size, selected relevant mTBFA by means of an elastic net penalty and achieved good fits to the data. Two latent variables were necessary to describe the indices: Fluid intelligence (Perceptual Organization and Processing Speed indices) and Crystallized Intelligence (Verbal Comprehension and Working Memory indices). Regularized MIMIC revealed effects of the forceps minor tract on crystallized intelligence and of the superior longitudinal fasciculus on fluid intelligence. The model also detected the significant effect of age on both latent variables.

Spatio Temporal EEG Source Imaging with the Hierarchical Bayesian Elastic Net and Elitist Lasso Models.

The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods, Quality Measures and Visualization Routines are freely available in a public website.

Tendencia de la fecundidad en Cuba, sus principales causas y consecuencias / Trends in fecundity in Cuba, main causes and consequences

Introducción: la disminución de la fecundidad en Cuba es el factor que más afecta el crecimiento de la población y conlleva a que el país no alcance los niveles de reemplazo poblacional desde hace más de 30 años. Objetivo: describir el descenso de la fecundidad y analizar algunas de sus causas y principales consecuencias. Métodos: consulta de los Anuarios Demográficos de Cuba de los últimos tres años y de otros documentos considerados indispensables. Se utilizaron indicadores de razón, porcentaje y tasas para la construcción de gráficos ilustrativos. Resultados: entre el 1965 y el 2006, años que recogen el mayor y menor número de nacimientos en la historia revolucionaria, respectivamente, se produjo una reducción de 156 288 nacimientos. Las causas de esta disminución se ubican en cambios en el patrón sociocultural tradicional y económico, entre ellos, la incorporación de la mujer a todas la esferas de la vida y la influencia al interior de las familias cubanas de la difícil situación económica que presenta el país desde hace varias décadas; su consecuencia principal es el envejecimiento poblacional y el decrecimiento paulatino del tamaño de los grupos poblacionales mas jóvenes. Conclusiones: teniendo en cuenta la naturaleza multicausal y tiempo posible de cambio, el descenso de la fecundidad debe mantener en el futuro a corto y mediano plazo un comportamiento similar a los últimos cinco años. Esta situación así como el envejecimiento de la población cubana, requieren de cambios en la gestión de aquellos organismos que puedan contribuir a enfrentar esta situación(AU)

Introduction: the reduction of fecundity in Cuba is a factor affecting the population growth and implies that the country has not reached population replacement levels for over 30 years. Objective: to describe the decline in fecundity and to analyze some of its causes and main consequences. Methods: consulting the demographic yearbooks of Cuba of the last three years and other indispensable documents. For creating the illustrative graphs, ratio indexes, percentages and rates were used. Results: from 1965 through 2006 when the highest and the lowest number of births occurred in the revolutionary history of Cuba, respectively, there was a reduction of 156 288 births. The causes were found in changes of the traditional socio-cultural and economic patterns, namely, the incorporation of the women to all the life spheres and the influence of the difficult economic situation over the Cuban families for several decades. The main consequence was population aging and gradual decrease of the size of younger population groups. Conclusions: taking into account the multicausal nature and the possible time of change, the decline in fecundity should behave at short and medium term in a way similar to that of the last five years. This situation as well as the aging of the Cuban population requires changes in the work of those bodies that may help to face these realities(AU)

Tendencia de la fecundidad en Cuba, sus principales causas y consecuencias / Trends in fecundity in Cuba, main causes and consequences

Introducción: la disminución de la fecundidad en Cuba es el factor que más afecta el crecimiento de la población y conlleva a que el país no alcance los niveles de reemplazo poblacional desde hace más de 30 años. Objetivo: describir el descenso de la fecundidad y analizar algunas de sus causas y principales consecuencias. Métodos: consulta de los Anuarios Demográficos de Cuba de los últimos tres años y de otros documentos considerados indispensables. Se utilizaron indicadores de razón, porcentaje y tasas para la construcción de gráficos ilustrativos. Resultados: entre el 1965 y el 2006, años que recogen el mayor y menor número de nacimientos en la historia revolucionaria, respectivamente, se produjo una reducción de 156 288 nacimientos. Las causas de esta disminución se ubican en cambios en el patrón sociocultural tradicional y económico, entre ellos, la incorporación de la mujer a todas la esferas de la vida y la influencia al interior de las familias cubanas de la difícil situación económica que presenta el país desde hace varias décadas; su consecuencia principal es el envejecimiento poblacional y el decrecimiento paulatino del tamaño de los grupos poblacionales mas jóvenes. Conclusiones: teniendo en cuenta la naturaleza multicausal y tiempo posible de cambio, el descenso de la fecundidad debe mantener en el futuro a corto y mediano plazo un comportamiento similar a los últimos cinco años. Esta situación así como el envejecimiento de la población cubana, requieren de cambios en la gestión de aquellos organismos que puedan contribuir a enfrentar esta situación(AU)

Introduction: the reduction of fecundity in Cuba is a factor affecting the population growth and implies that the country has not reached population replacement levels for over 30 years. Objective: to describe the decline in fecundity and to analyze some of its causes and main consequences. Methods: consulting the demographic yearbooks of Cuba of the last three years and other indispensable documents. For creating the illustrative graphs, ratio indexes, percentages and rates were used. Results: from 1965 through 2006 when the highest and the lowest number of births occurred in the revolutionary history of Cuba, respectively, there was a reduction of 156 288 births. The causes were found in changes of the traditional socio-cultural and economic patterns, namely, the incorporation of the women to all the life spheres and the influence of the difficult economic situation over the Cuban families for several decades. The main consequence was population aging and gradual decrease of the size of younger population groups. Conclusions: taking into account the multicausal nature and the possible time of change, the decline in fecundity should behave at short and medium term in a way similar to that of the last five years. This situation as well as the aging of the Cuban population requires changes in the work of those bodies that may help to face these realities(AU)

Cambios con la edad en la respuesta electrofisiológica de seguimiento a la modulación del estímulo acústico / Maturational changes in the human envelope-following responses

Introducción: La capacidad de detectar cambios temporales en la amplitud de modulación de los sonidos del habla es esencial para el adecuado desarrollo y comprensión del lenguaje. El potencial evocado auditivo de seguimiento a la envolvente (PEA-SE) permite estudiar objetivamente la respuesta auditiva a los cambios en la modulación del estímulo acústico en sujetos que no cooperan con exámenes conductuales. Objetivo: Evaluar posibles cambios maduracionales en los parámetros del PEA-SE durante los 2 primeros años de vida. Métodos: se estudiaron 16 bebés normooyentes (12 recién nacidos y 4 bebés de 2 años de edad). Se registró el PEA-SE obtenido con un ruido blanco al que se le realizó un barrido continuo de modulación entre 20-200Hz a 50dB HL. Resultados: Las principales diferencias con respecto al patrón morfológico descrito en los adultos estuvieron a expensas de las frecuencias inferiores a 50Hz, donde el componente P1, a diferencia del P2, no se registró de forma definida y estable en ninguno de los grupos. Con la edad existe, además, un incremento significativo en la amplitud y detectabilidad del potencial en todas las frecuencias de modulación estudiadas. Conclusiones: Se caracterizan por primera vez las modificaciones del PEA-SE con la maduración del sistema auditivo en seres humanos. Los resultados sugieren que el PEA-SE obtenido entre 80-200Hz podría ser útil para estudiar los cambios maduracionales del procesamiento auditivo temporal en la población infantil(AU)

Introduction: The auditory ability to discriminate rapid changes in the envelope of language sounds is essential for speech comprehension. Human envelope-following responses (EFRs) are useful for objective measurement of temporal auditory processing in subjects who are unable to give accurate behavioural responses (e.g., young children). Objective: To evaluate age-dependent changes in EFRs during the first 2 years of life. Methods: The EFRs were recorded in a sample of 16 well babies distributed into 2 age groups (G1: 12 newborns; G2: 4 babies of 2 years). The EFRs were evoked by white noise carrier stimuli with a sweep of modulation frequencies from 20 to 200Hz presented at 50dB HL. Results: The age-related changes affected both morphology and EFR detectability. The main morphological differences were at the expense of frequencies below 50Hz, where the first component P1 was not well defined in either of the 2 age groups. For all modulation frequencies, age significantly affected EFR amplitude and detectability. Conclusions: The present study provides the first evidence on EFR maturation. Some understanding of normal EFR development would facilitate a better use of this technique in clinically-objective measurement of auditory temporal processing in infants who cannot provide reliable behavioural responses(AU)

Maturational changes in the human envelope-following responses.

INTRODUCTION: The auditory ability to discriminate rapid changes in the envelope of language sounds is essential for speech comprehension. Human envelope-following responses (EFRs) are useful for objective measurement of temporal auditory processing in subjects who are unable to give accurate behavioural responses (e.g., young children). OBJECTIVE: To evaluate age-dependent changes in EFRs during the first 2 years of life. METHODS: The EFRs were recorded in a sample of 16 well babies distributed into 2 age groups (G1: 12 newborns; G2: 4 babies of 2 years). The EFRs were evoked by white noise carrier stimuli with a sweep of modulation frequencies from 20 to 200 Hz presented at 50 dB HL. RESULTS: The age-related changes affected both morphology and EFR detectability. The main morphological differences were at the expense of frequencies below 50 Hz, where the first component P1 was not well defined in either of the 2 age groups. For all modulation frequencies, age significantly affected EFR amplitude and detectability. CONCLUSIONS: The present study provides the first evidence on EFR maturation. Some understanding of normal EFR development would facilitate a better use of this technique in clinically-objective measurement of auditory temporal processing in infants who cannot provide reliable behavioural responses.

Caracterización electrofisiológica del potencial evocado auditivo de seguimiento a la modulación del estímulo acústico / Electrophysiological characterisation of envelope-following responses

Introducción: Comprender el lenguaje implica percibir adecuadamente los cambios temporales que se producen en la amplitud de modulación de los sonidos del habla. La detección de estos cambios disminuye en las afecciones neurológicas como la esclerosis múltiple, la neuropatía auditiva, las hipoacusias neurosensoriales, la presbiacusia y el retraso primario del lenguaje. El potencial evocado auditivo de seguimiento a la envolvente (PEA-SE) permite estudiar electrofisiológicamente la respuesta auditiva a los cambios en la modulación de un estímulo acústico. Objetivos: Caracterizar el PEA-SE en adultos sanos y estudiar los efectos del sueño sobre este potencial. Métodos: Se estudiaron 11 sujetos, 6 en condiciones de vigilia y 5 en sueño espontáneo. Se registró el PEA-SE obtenido con un ruido blanco al que se le hizo un barrido de frecuencias de modulación entre 20-200Hz a 50dB HL de intensidad. Resultados: El PEA-SE mostró una morfología similar en todos los sujetos, caracterizándose por presentar dos componentes principales. La amplitud del primer componente (localizado entre 30-50Hz de modulación) fue significativamente mayor que la del segundo componente (entre 80-110Hz) tanto en los sujetos despiertos como en los dormidos. Existió además un efecto significativo del estado de vigilia sobre la amplitud del PEA-SE para las frecuencias entre 88-110Hz, 155-165Hz y 190-200Hz. Sin embargo, no hubo un efecto significativo del sueño sobre los componentes principales del PEA-SE. Conclusiones: En este trabajo se corrobora el patrón morfológico del PEA-SE sustentándose su utilidad para el estudio objetivo del procesamiento temporal del sistema auditivo (AU)

Introduction: The auditory ability to discriminate rapid changes in the envelope of language sounds is essential for speech comprehension. This ability is deteriorated in some neurological diseases such as multiple sclerosis, auditory neuropathy, sensorineural hearing loss, presbycusis, and primary developmental language disorder. Envelope-following responses (EFRs) in humans are useful in objective measurement of temporal processing in the auditory nervous system. Objectives: To evaluate EFRs in healthy younger subjects and to investigate the effects of subject states on the EFRs recorded. Methods: Eleven young subjects were included; 6 of them were awake and 5 were asleep. EFRs were evoked by white noise carrier stimuli with a sweep of modulation frequencies from 20 to 200Hz presented at 50dB HL. Results: The EFRs we recorded were similar in all subjects. There were two principal components. During both subject sleep and wakefulness, the first component (located between 30 and 50Hz) was significantly larger than the second component (located between 80 and 110Hz). There was also a significant effect of sleep on the EFR amplitude for the modulation frequencies between 88 and 110Hz, 155 and 165Hz, and 190 and 200Hz. However, there were no significant effects of sleep on the principal EFR components. Conclusions: These results corroborate the usefulness of the EFR technique for objective measurement of human auditory temporal processing (AU)

[Electrophysiological characterisation of envelope-following responses]. / Caracterización electrofisiológica del potencial evocado auditivo de seguimiento a la modulación del estímulo acústico.

INTRODUCTION: The auditory ability to discriminate rapid changes in the envelope of language sounds is essential for speech comprehension. This ability is deteriorated in some neurological diseases such as multiple sclerosis, auditory neuropathy, sensorineural hearing loss, presbycusis and primary developmental language disorder. Envelope-following responses (EFRs) in humans are useful in objective measurement of temporal processing in the auditory nervous system. OBJECTIVES: To evaluate EFRs in healthy younger subjects and to investigate the effects of subject states on the EFRs recorded. METHODS: Eleven young subjects were included; six of them were awake and five were asleep. EFRs were evoked by white noise carrier stimuli with a sweep of modulation frequencies from 20 to 200Hz presented at 50dB HL. RESULTS: The EFRs we recorded were similar in all subjects. There were two principal components. During both subject sleep and wakefulness, the first component (located between 30-50Hz) was significantly larger than the second component (located between 80-110Hz). There was also a significant effect of sleep on the EFR amplitude for the modulation frequencies between 88-110, 155-165 and 190-200Hz. However, there were no significant effects of sleep on the principal EFR components. CONCLUSIONS: These results corroborate the usefulness of the EFR technique for objective measurement of human auditory temporal processing.

EEG source imaging with spatio-temporal tomographic nonnegative independent component analysis.

This article describes a spatio-temporal EEG/MEG source imaging (ESI) that extracts a parsimonious set of "atoms" or components, each the outer product of both a spatial and a temporal signature. The sources estimated are localized as smooth, minimally overlapping patches of cortical activation that are obtained by constraining spatial signatures to be nonnegative (NN), orthogonal, sparse, and smooth-in effect integrating ESI with NN-ICA. This constitutes a generalization of work by this group on the use of multiple penalties for ESI. A multiplicative update algorithm is derived being stable, fast and converging within seconds near the optimal solution. This procedure, spatio-temporal tomographic NN ICA (STTONNICA), is equally able to recover superficial or deep sources without additional weighting constraints as tested with simulations. STTONNICA analysis of ERPs to familiar and unfamiliar faces yields an occipital-fusiform atom activated by all faces and a more frontal atom that only is active with familiar faces. The temporal signatures are at present unconstrained but can be required to be smooth, complex, or following a multivariate autoregressive model.

Identifying complex brain networks using penalized regression methods.

The recorded electrical activity of complex brain networks through the EEG reflects their intrinsic spatial, temporal and spectral properties. In this work we study the application of new penalized regression methods to i) the spatial characterization of the brain networks associated with the identification of faces and ii) the PARAFAC analysis of resting-state EEG. The use of appropriate constraints through non-convex penalties allowed three types of inverse solutions (Loreta, Lasso Fusion and ENet L) to spatially localize networks in agreement with previous studies with fMRI. Furthermore, we propose a new penalty based in the Information Entropy for the constrained PARAFAC analysis of resting EEG that allowed the identification in time, frequency and space of those brain networks with minimum spectral entropy. This study is an initial attempt to explicitly include complexity descriptors as a constraint in multilinear EEG analysis.

Estimating brain functional connectivity with sparse multivariate autoregression.

There is much current interest in identifying the anatomical and functional circuits that are the basis of the brain's computations, with hope that functional neuroimaging techniques will allow the in vivo study of these neural processes through the statistical analysis of the time-series they produce. Ideally, the use of techniques such as multivariate autoregressive (MAR) modelling should allow the identification of effective connectivity by combining graphical modelling methods with the concept of Granger causality. Unfortunately, current time-series methods perform well only for the case that the length of the time-series Nt is much larger than p, the number of brain sites studied, which is exactly the reverse of the situation in neuroimaging for which relatively short time-series are measured over thousands of voxels. Methods are introduced for dealing with this situation by using sparse MAR models. These can be estimated in a two-stage process involving (i) penalized regression and (ii) pruning of unlikely connections by means of the local false discovery rate developed by Efron. Extensive simulations were performed with idealized cortical networks having small world topologies and stable dynamics. These show that the detection efficiency of connections of the proposed procedure is quite high. Application of the method to real data was illustrated by the identification of neural circuitry related to emotional processing as measured by BOLD.

Estimating brain functional connectivity with sparse multivariate autoregression / s. t

There is much current interest in identifying the anatomical and functional circuits that are the basis of the brain's computations, with hope that functional neuroimaging techniques will allow the in vivo study of these neural processes through the statistical analysis of the time-series they produce. Ideally, the use of techniques such as multivariate autoregressive (MAR) modelling should allow the identification of effective connectivity by combining graphical modelling methods with the concept of Granger causality. Unfortunately, current time-series methods perform well only for the case that the length of the time-series Nt is much larger than p, the number of brain sites studied, which is exactly the reverse of the situation in neuroimaging for which relatively short time-series are measured over thousands of voxels. Methods are introduced for dealing with this situation by using sparse MAR models. These can be estimated in a two-stage process involving (i) penalized regression and (ii) pruning of unlikely connections by means of the local false discovery rate developed by Efron. Extensive simulations were performed with idealized cortical networks having small world topologies and stable dynamics. These show that the detection efficiency of connections of the proposed procedure is quite high. Application of the method to real data was illustrated by the identification of neural circuitry related to emotional processing as measured by BOLD(AU)