1,721,132 research outputs found
Statistical causality in the EEG for the study of cognitive functions in healthy and pathological brains
Full text linkUnderstanding brain functions requires not only information about the spatial localization of neural activity, but also about the dynamic functional links between the involved groups of neurons, which do not work in an isolated way, but rather interact together through ingoing and outgoing connections. The work carried on during the three years of PhD course returns a methodological framework for the estimation of the causal brain connectivity and its validation on simulated and real datasets (EEG and pseudo-EEG) at scalp and source level. Important open issues like the selection of the best algorithms for the source reconstruction and for time-varying estimates were addressed. Moreover, after the application of such approaches on real datasets recorded from healthy subjects and post-stroke patients, we extracted neurophysiological indices describing in a stable and reliable way the properties of the brain circuits underlying different cognitive states in humans (attention, memory). More in detail: I defined and implemented a toolbox (SEED-G toolbox) able to provide a useful validation instrument addressed to researchers who conduct their activity in the field of brain connectivity estimation. It may have strong implication, especially in methodological advancements. It allows to test the ability of different estimators in increasingly less ideal conditions: low number of available samples and trials, high inter-trial variability (very realistic situations when patients are involved in protocols) or, again, time varying connectivity patterns to be estimate (where stationary hypothesis in wide sense failed). A first simulation study demonstrated the robustness and the accuracy of the PDC with respect to the inter-trials variability under a large range of conditions usually encountered in practice. The simulations carried on the time-varying algorithms allowed to highlight the performance of the existing methodologies in different conditions of signals amount and number of available trials. Moreover, the adaptation of the Kalman based algorithm (GLKF) I implemented, with the introduction of the preliminary estimation of the initial conditions for the algorithm, lead to significantly better performance. Another simulation study allowed to identify a tool combining source localization approaches and brain connectivity estimation able to provide accurate and reliable estimates as less as possible affected to the presence of spurious links due to the head volume conduction. The developed and tested methodologies were successfully applied on three real datasets. The first one was recorded from a group of healthy subjects performing an attention task that allowed to describe the brain circuit at scalp and source level related with three important attention functions: alerting, orienting and executive control. The second EEG dataset come from a group of healthy subjects performing a memory task. Also in this case, the approaches under investigation allowed to identify synthetic connectivity-based descriptors able to characterize the three main memory phases (encoding, storage and retrieval). For the last analysis I recorded EEG data from a group of stroke patients performing the same memory task before and after one month of cognitive rehabilitation. The promising results of this preliminary study showed the possibility to follow the changes observed at behavioural level by means of the introduced neurophysiological indices
Assessment of complexity and dynamical coupling between complex systems using Entropy Rate and Mutual Information Rate Measures: simulations and application to physiological data
Full text linkIn this work, after defining the theoretical formulation of ER and MIR dynamical measures, different approaches for their estimation are compared: a linear model-based estimator relying on Gaussian data, two model-free estimators based on discretization of the variables carried out either via uniform quantization through binning or rank ordering through permutations, and a model-free estimator based on direct computation of the differential entropy via k-nearest neighbor searches. The various estimators are first validated and compared on simulated univariate and coupled dynamic systems, including linear autoregressive or mixed non-linear deterministic and linear stochastic dynamics processes. Then, the framework is applied to different datasets of real-world time series describing the dynamics of coupled biomedical physiological systems, including physiological variability series descriptive of cardiovascular and cardiorespiratory interactions assessed at rest and during physiological stress or during controlled breathing conditions
Information flow in EEG source networks in epileptic children with focal seizure activity
No full textScalp electroencephalographic (EEG) signals are influenced by several factors, including volume conduction and low spatial resolution, which can jeopardize the validity of brain connectivity analysis performed on the raw recordings. One possible solution is to identify, starting from scalp EEG signals, the underlying cortical source activations, and to apply connectivity metrics on the reconstructed source time series. In this work, the dynamics of information flow between cortical EEG signals obtained after source reconstruction were assessed in children suffering from focal epilepsy. In a group of 10 children with focal seizures, 5-second windows of the 19-channel EEG were obtained in the baseline, pre-ictal, and post-ictal phases. After filtering and artifact removal, 19 baseline, 19 pre-ictal, and 12 post-ictal stationary trials were selected for the analysis. Source reconstruction was performed combining a common spatial pattern algorithm with linear modeling and Indiapendent component analysis. Finally, linear measures of functional connectivity (information storage, total and conditional information transfer) were obtained from vector autoregressive models of the source signals. While the average information stored in the nodes of the source EEG network did not change significantly across conditions, the total information transferred to each node increased significantly just before the seizure onset (p=0.001) and remained high after the seizure (p=0.009). The number of directed links in the network (statistically significant values of the conditional information transfer) also increased comparing the pre-ictal and post-ictal phases with the baseline period (p=0.134, p=0.109). These results indicate that a reorganization of the source EEG network, characterized by dense topology and increased information transfer, occurs before the onset of focal seizures, which is promising for seizure prediction algorithms
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Nonlinear brain-heart interactions in children with focal epilepsy assessed by mutual information of EEG and heart rate variability
No full textNetwork physiology is a recent approach describing the human body as an integrated network composed of several organ systems which continuously interact to produce healthy and diseased states. In this work, we apply the network physiology paradigm to study dynamical interactions between EEG activity and heart rate variability in children suffering from focal epilepsy. We aim to study the characteristics of brainheart coupling between, before, and after seizures to better understand the physiological mechanisms underlying seizure onset in the pre-ictal phase and the recovery of normal autonomic function in the post-ictal phase. In perspective, linking the dynamic information of brain-heart can provide useful information for a better seizure prediction. EEG and ECG data were recorded in 10 patients with focal epilepsy. After removal of baseline drift and muscle artifacts, the variability of heart rate and brain activity were measured extracting R-R intervals from the ECG and computing the spectral power of the EEG. 143 synchronous time series of 300 points were obtained in 4 different time windows (10 min and 10 sec before and after the seizure) and analyzed computing the cross-correlation coefficient (CC) and the mutual information (MI). A statistically significant increase of MI was observed just after seizure episodes (pvalue equal to 0.04, 10s before vs 10s after distributions, electrode O2), while a recovery of the baseline value was obtained 10 minutes after the episodes. This trend was found for several other EEG electrodes (Fp2, F3, F8, T3, C4, T4). On the contrary, CC did not change significantly across time windows. These results suggest that focal seizures are associated with an increased brain-heart coupling which is noticeable after seizure termination only in terms of mutual information. We conclude that focal epilepsy in childhood is associated with nonlinear brain-heart interaction mechanisms
Mutual Information Rate Decomposition as a Tool to Investigate Coupled Dynamical Systems: Estimation Approaches, Simulations and Application to Physiological Signals
Full text linkIn this work, we present a framework for the computation of the MIR between two random processes X and Y, expressed equivalently as the sum of the individual entropy rates of X and Y minus their joint entropy rate, or as the sum of the transfer entropies from X to Y and from Y to X plus the instantaneous information shared by the processes at zero lag. After defining the theoretical formulation of the framework, different approaches for the estimation of each dynamic measure composing the MIR are provided: the linear model-based estimator relying on Gaussian data; two model-free estimators based on discretization, performed via uniform quantization through binning or rank ordering through permutations; a model-free estimator based on direct computation of the differential entropy via k-nearest neighbor searches
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A portable electronic system for non-invasive real-time acquisition of multiple physiological signals
No full textIn this work, we have designed and realised a portable and compact electronic system for the synchronous acquisition of multiple physiological signals. The system employs a Texas Instruments ADS1298 front-end with 24-bit resolution for data acquisition and supports up to 8 channels and 4 kHz sampling rate. The front-end communicates via SPI with a STM32 microcontroller which pre-processes the data and sends them through USB or Bluetooth to a suitable PC application. The system has been realized for the simultaneous acquisition of electrocardiographic (ECG) and photoplethysmographic (PPG) signals, but it can also be employed for acquiring other typologies of signals, e.g. breathing or electro-dermal activity, for a potential use in the automotive field to assess the driver’s health status in real-time or, in perspective, the stress level. PPG probes have also been realised, each one including dual wavelength LED (emitting at 735 and 850 nm), and a Silicon Photomultiplier (SiPM) detector (provided by STMicroelectronics) having high responsivity and gain [1]. The system integrates an I2C interface, 8-channel, 16-levels current LED driver for PPG probes and includes a Graphical User Interface (GUI) able, in real time, to (i) plot the signals, (ii) save the data, (iii) calculate and display main cardiovascular parameters (i.e., heart rate, breath rate, pulse arrival time, pulse transit time, pulse wave velocity). Both instantaneous or averaged values of heart rate are shown, also to display the time variation of the considered parameters and thus assess the so-called Heart Rate Variability [2]. Current version of the system is able to acquire up to 5 PPG waveforms and 3 ECG leads. Figure 1 shows a photo of the system, alongside with the PPG probes (on the right) and the standard ECG electrodes (on the left) which are used for signals acquisition. Figure 2 illustrates some screenshots of the developed GUI showing 2 ECG leads and 2 PPG waveforms. In detail, Fig. 2(a) depicts the windows displaying the waveforms, while, Fig. 2(b) exhibits the window dedicated to show in real-time the instantaneous and averaged values of the above-mentioned physiological parameters. Several measurement campaigns have been carried out on healthy volunteers of different ages to both test the correct functioning of the system, and also to compare the Pulse Arrival Time values computed between different body locations. In the future, by performing measurements on other typologies of subjects (e.g., hypertensive or diabetic patients), a statistical analysis of the collected data will be carried out, in order to evaluate the capability of using our system for distinguishing between different pathologies or for early disease detection, or even for assessing various stress levels.
This activity was supported by Advancing Smart Optical Imaging and Sensing for Health (ASTONISH) Project (Grant no. 692470), funded by H2020-EU.2.1.1.7.-ECSEL programme
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