Induced brain activity as indicator of cognitive processes: experimental-methodical analyses and algorithms for online-applications

Die Signalverarbeitung von elektroenzephalographischen (EEG) Signalen ist ein entscheidendes Werkzeug, um die kognitiven Prozessen verstehen zu können. Beispielweise wird induzierte Hirnaktivität in mehreren Untersuchungen mit kognitiver Leistung assoziiert. Deshalb ist die Gewinnung von elektrophysiologischen Parametern grundlegend für die Charakterisierung von kognitiven Prozessen sowie von kognitiven Dysfunktionen in neurologischen Erkrankungen. Besonders bei Epilepsie treten häufig Störungen wie Gedächtnis-, oder Aufmerksamkeitsprobleme auf, zusätzlich zu Anfällen. Neurofeedback (bzw. EEG-Biofeedback) ist eine Therapiemethode, die zusätzlich zu medikamentösen- und chirurgischen Therapien bei der Behandlung vieler neurologischer Krankheiten, einschließlich Epilepsie, erfolgreich praktiziert wird. Neurofeedback wird jedoch meist dafür angewendet, eine Anfallsreduzierung zu erzielen. Dagegen wird eine Verbesserung kognitiver Fähigkeiten auf der Basis elektrophysiologischer Änderungen selten vorgesehen. Darüber hinaus sind die aktuellen Neurofeedbackstrategien für diesen Zweck ungeeignet. Der Grund dafür sind unter anderem nicht adäquate Verfahren für die Gewinnung und Quantifizierung induzierter Hirnaktivität. Unter Berücksichtigung der oben genannten Punkten wurden die kognitiven Leistungen von einer Patientengruppe (Epilepsie) und einer Probandengruppe anhand der ereignisbezogenen De-/Synchronisation (ERD/ERS) Methode untersucht. Signifikante Unterschiede wurden im Theta bzw. Alpha Band festgestellt. Diese Ergebnisse unterstützen die Verwertung von auf ERD/ERS basierten kognitiven Parametern bei Epilepsie. Anhand einer methodischen Untersuchung von dynamischen Eigenschaften wurde ein onlinefähiger ERD/ERS Algorithmus für zukünftige Neurofeedback Applikationen ausgewählt. Basierend auf dem ausgewählten Parameter wurde eine Methodik für die online Gewinnung und Quantifizierung von kognitionsbezogener induzierter Hirnaktivität entwickelt. Die dazugehörigen Prozeduren sind in Module organisiert, um die Prozessapplikabilität zu erhöhen. Mehrere Bestandteile der Methodik, einschließlich der Rolle von Elektrodenmontagen sowie die Eliminierung bzw. Reduktion der evozierten Aktivität, wurden anhand kognitiver Aufgaben evaluiert und optimiert. Die Entwicklung einer geeigneten Neurofeedback Strategie sowie die Bestätigung der psychophysiologischen Hypothese anhand einer Pilotstudie sollen Gegenstand der zukünftigen Arbeitschritte sein.Processing of electroencephalographic (EEG) signals is a key step towards understanding cognitive brain processes. Particularly, there is growing evidence that the analysis of induced brain oscillations is a powerful tool to analyze cognitive performance. Thus, the extraction of electrophysiological features characterizing not only cognitive processes but also cognitive dysfunctions by neurological diseases is fundamental. Especially in the case of epilepsy, cognitive dysfunctions such as memory or attentional problems are often present additionally to seizures. Neurofeedback (or EEG-biofeedback) is a psychological technique that, as a supplement to medication and surgical therapies, has been demonstrated to provide further improvement in many neurological diseases, including epilepsy. However, most efforts of neurofeedback have traditionally been dedicated to the reduction of seizure frequency, and little attention has been paid for improving cognitive deficits by means of specific electrophysiological changes. Furthermore, current neurofeedback approaches are not suitable for these purposes because the parameters used do not take into consideration the relationship between memory performance and event-induced brain activity. Considering all these aspects, the cognitive performance of a group of epilepsy patients and a group of healthy controls was analyzed based on the event-related de /synchronization (ERD/ERS) method. Significant differences between both populations in the theta and upper alpha bands were observed. These findings support the possible exploitation of cognitive quantitative parameters in epilepsy based on ERD/ERS. An algorithm for the online ERD/ERS calculation was selected for future neurofeedback applications, as the result of a comparative dynamic study. Subsequently, a methodology for the online extraction and quantification of cognitive-induced brain activity was developed based on the selected algorithm. The procedure is functionally organized in blocks of algorithms in order to increase applicability. Several aspects, including the role of electrode montages and the reduction or minimization of the evoked activity, were examined based on cognitive studies as part of the optimization process. Future steps should include the design of a special training paradigm as well as a pilot study for confirming the theoretical approach proposed in this work

Modulation of pain threshold by virtual body ownership

Appropriate sensorimotor correlations can result in the illusion of ownership of exogenous body parts. Nevertheless, whether and how the illusion of owning a new body part affects human perception, and in particular pain detection, is still poorly investigated. Recent findings have shown that seeing one's own body is analgesic, but it is not known whether this effect is transferable to newly embodied, but exogenous, body parts. In recent years, results from our laboratory have demonstrated that a virtual body can be felt as one's own, provided realistic multisensory correlations

What Color is My Arm? Changes in Skin Color of an Embodied Virtual Arm Modulates Pain Threshold

It has been demonstrated that visual inputs can modulate pain. However, the influence of skin color on pain perception is unknown. Red skin is associated to inflamed, hot and more sensitive skin, while blue is associated to cyanotic, cold skin. We aimed to test whether the color of the skin would alter the heat pain threshold. To this end, we used an immersive virtual environment where we induced embodiment of a virtual arm that was co-located with the real one and seen from a first-person perspective. Virtual reality allowed us to dynamically modify the color of the skin of the virtual arm. In order to test pain threshold, increasing ramps of heat stimulation applied on the participants' arm were delivered concomitantly with the gradual intensification of different colors on the embodied avatar's arm. We found that a reddened arm significantly decreased the pain threshold compared with normal and bluish skin. This effect was specific when red was seen on the arm, while seeing red in a spot outside the arm did not decrease pain threshold. These results demonstrate an influence of skin color on pain perception. This top-down modulation of pain through visual input suggests a potential use of embodied virtual bodies for pain therapy

The contribution of real-time mirror reflections of motor actions on virtual body ownership in an immersive virtual environment

This paper reports an experiment that investigated people"s body ownership of an avatar that was observed in a virtual mirror. Twenty subjects were recruited in a within-groups study where 10 first experienced a virtual character that synchronously reflected their upper-body movements as seen in a virtual mirror, and then an asynchronous condition where the mirror avatar displayed prerecorded actions, unrelated to those of the participant. The other 10 subjects experienced the conditions in the opposite order. In both conditions the participant could carry out actions that led to elevation above ground level, as seen from their first person perspective and correspondingly in the mirror. A rotating virtual fan eventually descended to 2m above the ground. The hypothesis was that synchronous mirror reflection would result in higher subjective sense of ownership. A questionnaire analysis showed that the body ownership illusion was significantly greater for thesynchronous than asynchronous condition. Additionally participants in the synchronous condition avoided collision with the descending fan significantly more often than those in the asynchronous condition. The results of this experiment are put into context within similar experiments on multisensory correlation and body ownership within cognitive neuroscience

Towards a digital body: the virtual arm illusion

The integration of the human brain with computers is an interesting new area of applied neuroscience, where one application is replacement of a person"s real body by a virtual representation. Here we demonstrate that a virtual limb can be made to feel part of your body if appropriate multisensory correlations are provided. We report an illusion that is invoked through tactile stimulation on a person"s hidden real right hand with synchronous virtual visual stimulation on an aligned 3D stereo virtual arm projecting horizontally out of their shoulder. An experiment with 21 male participants showed displacement of ownership towards the virtual hand, as illustrated by questionnaire responses and proprioceptive drift. A control experiment with asynchronous tapping was carried out with a different set of 20 male participants who did not experience the illusion. After 5 min of stimulation the virtual arm rotated. Evidence suggests that the extent of the illusion was also correlated with the degree of muscle activity onset in the right arm as measured by EMG during this period that the arm was rotating, for the synchronous but not the asynchronous condition. A completely virtual object can therefore be experienced as part of one"s self, which opens up the possibility that an entire virtual body could be felt as one"s own in future virtual reality applications or online games, and be an invaluable tool for the understanding of the brain mechanisms underlying body ownership

Capturing Upper Body Motion in Conversation: an Appearance Quasi-Invariant Approach

We address the problem of body communication retrieval and measuring in seated conversations by means of marker-less motion capture. In psychological studies, the use of au-tomatic methods is key to reduce the subjectivity present in manual behavioral coding used to extract these cues. These studies usually involve hundreds of subjects with different clothing, non-acted poses, or different distances to the cam-era in uncalibrated, RGB-only video. However, range cam-eras are not yet common in psychology research, especially in existing recordings. Therefore, it becomes highly relevant to develop a fast method that is able to work in these con-ditions. Given the known relationship between depth and motion estimates, we propose to robustly integrate highly appearance-invariant image motion features in a machine learning approach, complemented with an effective tracking scheme. We evaluate the method’s performance with exist-ing databases and a database of upper body poses displayed in job interviews that we make public, showing that in our scenario it is comparable to that of Kinect without using a range camera, and state-of-the-art w.r.t. the HumanEva and ChaLearn 2011 evaluation datasets

Particle-Filtering-Based State-of-Health Estimation and End-of-Life Prognosis for Lithium-Ion Batteries at Operation Temperature

We present the implementation of a particle-filtering-based framework that estimates the State-of-Health (SOH) and predicts the End-of-Life (EOL) of Lithium-Ion batteries, efficiently incorporating variations of ambient temperature in the analysis. The proposed approach uses an empirical state-space model, in which inputs are explicitly defined as the average temperature of operation and the output of an external module that detects self-recharge phenomena, on the other hand the output is a function that relates the current SOH and temperature with the Usable Capacity in that cycle. In addition, this approach allows to deal with data losses and outliers. In order to correct erroneous initial conditions in state estimates, an Outer Feedback Correction Loop is implemented. Finally, this framework is validated using degradation data from four sources: experimental degradation data from two Li-Ion 18650 cells, accelerated degradation data openly provided by NASA Ames Research Center, and artificially generated degradation data at different ambient temperatures.We present the implementation of a particle-filtering-based framework that estimates the State-of-Health (SOH) and predicts the End-of-Life (EOL) of Lithium-Ion batteries, efficiently incorporating variations of ambient temperature in the analysis. The proposed approach uses an empirical state-space model, in which inputs are explicitly defined as the average temperature of operation and the output of an external module that detects self-recharge phenomena, on the other hand the output is a function that relates the current SOH and temperature with the Usable Capacity in that cycle. In addition, this approach allows to deal with data losses and outliers. In order to correct erroneous initial conditions in state estimates, an Outer Feedback Correction Loop is implemented. Finally, this framework is validated using degradation data from four sources: experimental degradation data from two Li-Ion 18650 cells, accelerated degradation data openly provided by NASA Ames Research Center, and artificially generated degradation data at different ambient temperatures

La emigración internacional, las remesas y el desarrollo económico en México

La migración es un fenómeno que ocurre desde el momento en que el hombre busca nuevas alternativas para mejorar su bienestar social, su aspecto benéfico radica en el flujo de remesas captadas en las regiones expulsoras de mano de obra, las cuales se encuentran concentradas principalmente en las zonas rurales. La tendencia en el uso de las remesas está encaminada hacia la satisfacción de las necesidades básicas, así como a la adquisición de bienes de consumo y a la compra y mejora de la vivienda de las familias de los migrantes. Existen países que tienen flujos migratorios masivos, motivo por el cual reciben flujos importantes de remesas para su contabilidad nacional y en este trabajo se analizan desde la perspectiva de países expulsores y de destino de la mano de obra migrante. Por facilidad de análisis de esta obra los países se agrupan en cinco regiones, a saber; África, Asia, Europa, Latinoamérica y Oceanía. Para nuestro país la captación de divisas por concepto de las exportaciones petroleras es la más importante, pero a partir del año 2000, éstas constantemente se ven amenazadas por los flujos monetarios que ingresan al país por concepto de remesas y que desde el año 2003 se colocaron como la segunda fuente más importante de divisas para México. La necesidad de conocer los efectos de las remesas sobre la conomía mexicana se debe a que representan un flujo monetario que en más del 80% es destinado al autoconsumo y el resto a la inversión o ahorro, lo que sin duda genera burbujas inflacionarias para las regiones que mayoritariamente reciben tales ingresos como en el caso de los estados de Jalisco, Michoacán, Zacatecas, o el mismo Estado de México