Fast estimation of motion from selected populations of retinal ganglion cells.

We explore how the reconstruction efficiency of fast spike population codes varies with population size, population composition and code complexity. Our study is based on experiments with moving light patterns which are projected onto the isolated retina of a turtle Pseudemys scripta elegans. The stimulus features to reconstruct are sequences of velocities kept constant throughout segments of 500 ms. The reconstruction is based on the spikes of a retinal ganglion cell (RGC) population recorded extracellularly via a multielectrode array. Subsequent spike sorting yields the parallel spike trains of 107 RGCs as input to the reconstruction method, here a discriminant analysis trained and tested in jack-knife fashion. Motivated by behavioral response times, we concentrate on fast reconstruction, i.e., within 150 ms following a trigger event defined via significant changes of the population spike rate. Therefore, valid codes involve only few (≤3) spikes per cell. Using only the latency t(1) of each cell (with reference to the trigger event) corresponds to the most parsimonious population code considered. We evaluate the gain in reconstruction efficiency when supplementing t(1) by spike times t(2) and t(3). Furthermore, we investigate whether sub-populations of smaller size benefit significantly from a selection process or whether random compilations are equally efficient. As selection criteria we try different concepts (directionality, reliability, and discriminability). Finally, we discuss the implications of a selection process and its inter-relation with code complexity for optimized reconstruction.

Sleep apnea: Tracking effects of a first session of CPAP therapy by means of Granger causality.

Connectivity between physiological networks is an issue of particular importance for understanding the complex interaction brain-heart. In the present study, this interaction was analyzed in polysomnography recordings of 28 patients diagnosed with obstructive sleep apnea (OSA) and compared with a group of 10 control subjects. Electroencephalography and electrocardiography signals from these polysomnography time series were characterized employing Granger causality computation to measure the directed connectivity among five brain waves and three spectral subbands of heart rate variability. Polysomnography data from OSA patients were recorded before and during a first session of continuous positive air pressure (CPAP) therapy in a split-night study. Results showed that CPAP therapy allowed the recovery of inner brain connectivities, mainly in subsystems involving the theta wave. In addition, differences between control and OSA patients were established in connections that involve lower frequency ranges of heart rate variability. This information can be potentially useful in the initial diagnosis of OSA, and determine the role of cardiac activity in sleep dynamics based on the use of three subbands of heart rate variability.

Nonlinear Recurrent Dynamics and Long-Term Nonstationarities in EEG Alpha Cortical Activity: Implications for Choosing Adequate Segment Length in Nonlinear EEG Analyses.

Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder.

Comparing EEG Nonlinearity in Deficit and Nondeficit Schizophrenia Patients: Preliminary Data.

Electroencephalogram (EEG) contains valuable information obtained noninvasively that can be used for assessment of brain's processing capacity of patients with psychiatric disorders. The purpose of the present work was to evaluate possible differences in EEG complexity between deficit (DS) and nondeficit (NDS) subtypes of schizophrenia as a reflection of the cognitive processing capacities in these groups. A particular nonlinear metric known as Lempel-Ziv complexity (LZC) was used as a computational tool in order to determine the randomness in EEG alpha band time series from 3 groups (deficit schizophrenia [n = 9], nondeficit schizophrenia [n = 10], and healthy controls [n = 10]) according to time series randomness. There was a significant difference in frontal EEG complexity between the DS and NDS subgroups ( p = .013), with DS group showing less complexity. A significant positive correlation was found between LZC values and Positive and Negative Syndrome Scale (PANSS) general psychopathology scores (ie, larger frontal EEG complexity correlated with more severe psychopathology), explained partially by the emotional component subscore of the PANSS. These findings suggest that cognitive processing occurring in the frontal networks in DS is less complex compared to NDS patients as reflected by EEG complexity measures. The data also suggest that there may be a relationship between the degree of emotionality and the complexity of the frontal EEG signal.

Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder.

OBJECTIVE: Several linear electroencephalographic (EEG) measures at baseline have been demonstrated to be associated with treatment outcome after antidepressant treatment. In this study we investigated the added value of non-linear EEG metrics in the alpha band in predicting treatment outcome to repetitive transcranial magnetic stimulation (rTMS). METHODS: Subjects were 90 patients with major depressive disorder (MDD) and a group of 17 healthy controls (HC). MDD patients were treated with rTMS and psychotherapy for on average 21 sessions. Three non-linear EEG metrics (Lempel-Ziv Complexity (LZC); False Nearest Neighbors and Largest Lyapunov Exponent) were applied to the alpha band (7-13 Hz) for two 1-min epochs EEG and the association with treatment outcome was investigated. RESULTS: No differences were found between a subgroup of unmedicated MDD patients and the HC. Non-responders showed a significant decrease in LZC from minute 1 to minute 2, whereas the responders and HC showed an increase in LZC. CONCLUSIONS: There is no difference in EEG complexity between MDD and HC and the change in LZC across time demonstrated value in predicting outcome to rTMS. SIGNIFICANCE: This is the first study demonstrating utility of non-linear EEG metrics in predicting treatment outcome in MDD.

Nonlinear dynamics measures applied to EEG recordings of patients with attention deficit/hyperactivity disorder: quantifying the effects of a neurofeedback treatment.

This work presents the application of nonlinear dynamics measures to electroencephalograms (EEG) acquired from patients with Attention Deficit/Hyperactivity Disorder (ADHD) before and after a neurofeedback therapy, with the aim to assess the effects of the neurofeedback in a quantitative way. The database contains EEG registers of seven patients acquired in eyes-closed and eyes-opened conditions, in pre-and post-treatment phases. Five measures were applied: largest Lyapunov exponent, Lempel-Ziv complexity, Hurst exponent, and multiscale entropy on two different scales. The purpose is to test whether these measures are apt to detect and quantify differences from EEG registers between pre- and post-treatment. The results indicate that these measures could have a potential utility for detection of quantitative changes in specific EEG channels. In addition, the performance of some of these measures improved when the bandwidth was reduced to 3-30 Hz.

Registro de actvvidad eléctrica en la retina deuna rata albina empleando una mmatriz de microelectrooos / Recording of Electrical Activity in the Retina of an Albino Rat Employing a Microelectrode Array

Las matrices de microelectrodos (MEA) son dispositivos que permiten la detección de potenciales de acción o espigas en poblaciones de células excitables, ofreciendo varias aplicaciones en el campo de las neurociencias y la biología. Este trabajo muestra un protocolo para el registro de espigas en una población de células ganglionares retinales empleando una matriz de microelectrodos. La retina de una rata albina fue extraída y preparada para ser estimulada in vitro con luz led blanca, con el fin de registrar sus espigas evocadas ante estos estímulos. Cada microelectrodo puede registrar espigas de más de una célula ganglionar, razón por la cual se determinó a qué célula pertenece cada espiga aplicando un procedimiento conocido como "clasificación de espigas". El trabajo permitió obtener el registro de un periodo de estimulación y otro de no estimulación, con el fin de representar los potenciales de acción evocados con luz y los espontáneos. Los registros fueron almacenados para visualizar las espigas de las células ganglionares y poder aplicar la herramienta de clasificación de espigas. De este modo, se almacenan los instantes de tiempo en los cuales cada célula ganglionar registrada generó potenciales de acción. Este trabajo conllevó al establecimiento de un protocolo de experimentación básico enfocado al uso de matrices MEA en el laboratorio de adquisición de potenciales extracelulares de la Universidad Antonio Nariño Sede Bogotá, no sólo para caracterizar los potenciales de acción de células ganglionares retinales, sino también para otro tipo de células que puedan ser estudiadas empleando matrices de microelectrodos.

The microelectrode arrays (MEA) are devices that allow the detection of action potentials or spikes in populations of excitable cells, offering a wide spectrum of applications in topics of Neurosciences and Biology. This work describes a protocol for recording of spikes in a population of retinal ganglion cells employing a microelectrode array. The retina of an albino rat was dissected and prepared to be stimulated in vitro with white led light and to record their evoked spikes. Each microelectrode can record spikes from more than a ganglion cell, for which it was necessary to determine which cell fires each spike applying a procedure known as spike sorting. The work allowed to obtain the recording of a stimulation period and another of non-stimulation, representing evoked and spontaneous action potentials. The recordings were saved, in order to visualize the action potentials of the ganglion cells detected and to apply a computational method for the spike sorting. In this way, it was saved the time stamps in which each action potential was fired by its respective cell. This work established a basic experimentation protocol focused to the use of MEA devices in the laboratory for acquisition of extracellular potentials at the Antonio Nariño University - Bogota Headquarters, not only for characterization of action potentials fired by retinal ganglion cells populations, but also for other kind of cells that can be studied employing MEA devices.

Classifying the motion of visual stimuli from the spike response of a population of retinal ganglion cells.

We present an analysis of the spike response of a retinal ganglion cell ensemble. The retina of a turtle was stimulated in vitro by moving light patterns. Its non-steady motion was specified by two features: changes of direction and changes of speed. The spike response of a ganglion cell population was recorded extracellularly with a multielectrode array and responding neurons were identified through spike sorting. Restricting further analysis to a time window of greatest firing activity, we selected a subset of cells with reliable firing patterns, excluding cells that were not selective to the stimulus. The reliability of a firing pattern was assessed on the single cell level in terms of two measures: temporal precision (jitter) of the first spike and the fraction of trials in which a spike was generated. We then condensed the spike response of the extracted group by merging the multivariate spike trains into a single spike train. Finally, we compared different coding hypotheses that are based on the timing of the first and the second spike of the population or the spike count in the preselected time window. We found that the second spike of the population significantly increases the classification efficiency beyond that of the first spike. Moreover, the combination of first plus second spike is comparably efficient as the combination of the first spike plus the spike count but allows for a classification that is much faster.

Construcción de una base de datos electrocardiográfica para caninos residentes en Bogotá, con apoyo ecocardiográfico / Construction of an electrocardiographic data base for canine residents in Bogota, with ecocardiographic support

El siguiente trabajo presenta la base de datos VETUAN_I, de medidas obtenidas en datos de reseña, electrocardiogramas y ecocardiogramas correspondientes a pacientes caninos sin deficiencias cardiacas evaluados enla Clínica Veterinaria Veteriland de la ciudad de Bogotá, mediante la utilización de equipos de diagnóstico de laUniversidad Antonio Nariño. Esta base de datos está constituida por los parámetros o medidas cardiacas másutilizadas y por otros adicionales, lo cual permite comparar, revaluar y ajustar los valores estándares establecidos desde los años 60, comprender mejor su utilidad de diagnóstico, realizar análisis comparativos entre razas y otros factores, así como establecer diferentes correlaciones que mejoren la capacidad de diagnóstico.

Electrocardiogramas procesados digitalmente para la investigacion de nuevas medidas de diagnostico cardiaco / ECG FD I for research in cardiac diagnosis

Este artículo presenta la base de datos identificada con el nombre de ECG_FD_I, la cual está constituida por electrocardiogramas procesados con filtros digitales. Este trabajo nace de la necesidad de construir bases de datos para realizar estudios de alta sensibilidad de nuevos métodos para el análisis de electrocardiogramas con origen en la física estadística, que se están investigando en la actualidad. Los cambios en los electrocardiogramas originales generados por los filtros digitales utilizados para construir la base de datos ECG_FD_I, no pueden ser detectados visualmente. La información afectada por estos filtros, que escapa al análisis visual, es actualmente objeto de estudio para explotar su potencial en el apoyo de diagnósticos cardíacos utilizando el electrocardiograma como única fuente de información. La base de datos ECG_FD_I puede ser de gran utilidad en la investigación dirigida a la construcción de nuevas herramientas de diagnóstico en cardiología utilizando electrocardiogramas cada vez más simples, menos costosos y obtenidos en condiciones más diversas. El estudio de la dinámica cardíaca como un sistema complejo a partir de una fuente de información tan simple como un electrocardiograma, ofrece posibilidades de generar nuevos servicios que mejoren la calidad y la esperanza de vida del ser humano, a bajos costos y con posibilidades de gran cubrimiento gracias a los avances actuales tanto científicos como tecnológicos. Uno de los propósitos de presentar este trabajo en esta publicación especializada, es llamar la atención de la comunidad científica en estos problemas de investigación y aplicación interdisciplinarios.