Assessing the depth of cognitive processing as the basis for potential user-state adaptation

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces.DFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität Berli

Assessing the depth of cognitive processing as the basis for potential user-state adaptation - Data set

EEG and behavioral data of seventeen participants recorded by members of the Neurotechnology Group at Technische Universität Berlin. Details of the study are published in "Nicolae I-E, Acqualagna L and Blankertz B. (2017). Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation. Front. Neurosci. 11:548, 2017a. doi: https://doi.org/10.3389/fnins.2017.00548EC/FP7/611570/EU/MindSee Symbiotic Mind Computer Interaction for Information SeekingBMBF, 01GQ0850, Verbundprojekt: Bernstein Fokus Neurotechnologie - Nichtinvasive; Neurotechnologie für Mensch-Maschine InteraktionPOSDRU/159/1.5/S/134398/Knowledg

Enhanced Classification Methods for the Depth of Cognitive Processing Depicted in Neural Signals

Analyzing brain states is a difficult problem due to high variability between subjects and trials, therefore improved techniques are requested to be developed for a better discrimination between the neural components. This paper investigates multiple enhanced classification methods for neurological feature selection and discrimination of the depth of cognitive processing. The aim is to detect the strengths and weaknesses of different classification methods and benefit from their highest performances, so that the neural information could optimally be detected. As a result, we obtained a classification rate improved by at least 5% by integrating complementary information that better describe the neural activity.EC/FP7/611570/EU/Symbiotic Mind Computer Interaction for Information Seeking/MindSeeBMBF, 01GQ0850, Verbundprojekt: Bernstein Fokus Neurotechnologie - Nichtinvasive Neurotechnologie für Mensch-Maschine Interaktion - Teilprojekte A1, A3, A4, B4, W3, Zentru

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain.Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing.Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs.Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces

Erweiterte EEG-Signalverarbeitung mit Anwendungen in Gehirn-Computer-Schnittstellen : Bewertung benutzerorientierter Paradigmen zur Verbesserung der Gehirn-Computer-Interaktion

Advances in signal processing push forward the Neurotechnology domain along with the Brain-Computer Interface (BCI) research which deals with the analysis of brain activity. Heading for a future that will most probably happen, where either healthy persons or people with disabilities communicate and control external devices without muscle control, a symbiotic relationship between humans and machines needs to be created. Moreover, the research direction should be guided to the users’ side by evaluating users’ interests and needs. The main goal of this thesis is to provide suggestions and solutions to ease and facilitate the Brain-Computer Interaction, by the following: i) stimuli and tasks that refer to users’ mental states and interests are optimized; ii) an interpretable system is created to reveal the neural information that can further determine a controlled BCI system to act; iii) and the most important aspect that make the first two key points possible: advanced and improved methodological approaches are developed to efficiently extract and interpret human neural activity from the Electroencephalogram (EEG). The investigation is performed through two experimental studies, where the first one proposes improved stimuli and tasks regarding users’ interests and preferences in a motor-imagery-based BCI. The second study considers users’ cognitive mental states with the purpose to better control BCIs and investigates not only what the user has received from the external information, but also how and to which level of processing is the information encoded within the brain. The paradigms investigate the brain fluctuations induced by different stimuli and tasks, in order to provide the means to silently detect the meaningful neural information from the brain activity, which is critical for a BCI application. While the first paradigm considers Sensorimotor Rhythms (SMRs), the second paradigm is based on Event Related Potentials (ERPs). Most BCI paradigms consider either the temporal or the spectral information of the generated brain activity, but infrequently the investigation is performed in ensemble considering both domains. As it will be observed in this work, the analysis pipeline that considers only one domain might be suboptimal, while brain activity manifests additional information which is visible in both temporal and spectral domains. Therefore, this thesis deals with the methodological improvements that include complementary information, yielding to more accurate data analysis that outperforms most of the available methods.Fortschritte auf dem Gebiet der Signalverarbeitung beeinflussen auch die Entwicklungen (in der Neurotechnologie und somit auch die Erforschung) der Gehirn-Computer Schnittstellen (BCIs). Um Menschen mit körperlichen Einschränkungen, wie auch gesunden Menschen, die Möglichkeit zu geben ohne muskuläre Kontrolle über externe Geräte zu kommunizieren oder diese zu kontrollieren, muss eine symbiotische Beziehung zwischen Mensch und Maschine geschaffen werden. Hierfür sollte in der Forschung insbesondere ein größerer Fokus auf die Interessen und Bedürfnisse der Nutzer:innen gelegt werden. Das Ziel dieser Arbeit ist es Lösungsvorschläge für eine verbesserte Gehirn-Computer-Interaktion zu untersuchen. Dabei werden: i) Stimuli und Aufgabenstellungen die sich auf den mentalen Zustand der Nutzer:innen beziehen optimiert, ii) ein interpretierbares BCI geschaffen, um die entscheidenden neuronalen Informationen zu bestimmen, iii) die beiden ersten Punkte werden vor allem durch verbesserte methodische Ansätze ermöglicht welche effizient neuronale Aktivitäten vom Elektroenzephalogramm (EEG) extrahieren und interpretieren. Hierfür werden zwei EEG Studien analysiert. Erstere untersucht verbesserte Stimuli und Aufgabenstellungen bezüglich der Nutzerinteressen in einem motor-imagery basierten BCI. Die zweite Studie analysiert kognitive Zustände um herauszufinden wie externe Informationen im Gehirn ankommen und wie diese verarbeitet werden. Die beiden Studien untersuchen die Fluktuationen im Gehirn welche durch unterschiedliche Stimuli und Aufgabenstellungen induziert werden, um aussagekräftige neuronale Informationen, welche für die Anwendung des BCI wichtig sind, zu bestimmen. Während das erste Paradigma die sensormotorischen Rhythmen (SMRs) betrachtet, basiert das zweite Paradigma auf ereigniskorrelierten Potentialen (ERPs). Die meisten BCI Paradigmen betrachten entweder die zeitliche oder die spektrale Domäne der Gehirnaktivität, eher selten werden beide im ensemble analysiert. In dieser Dissertation kommen wir zu dem Schluss, dass die Analyse die sich nur auf eine der beiden Domänen stützt nicht optimal ist, da wichtige Informationen in beiden Domänen enthalten ist. Deshalb analysieren wir erweiterte Methoden die komplementäre Informationen aus beiden Domänen kombinieren, was zu einer genaueren Datenanalyse führt, die die Ergebnisse der bisherigen Methoden übertrifft.Progresele în analiza semnalelor impulsionează domeniul neuro-tehnologiei împreună cu cercetarea Interfețelor Creier-Calculator (en., Brain-Computes Interfaces - BCI) care se ocupă cu analiza activității cerebrale. Îndreptându-ne către un viitor care cel mai probabil se va întâmpla cât de curând, în care fie persoane sănătoase, fie persoane cu handicap comunică și controlează dispozitive externe fără intermediul controlului muscular, o relație simbiotică între oameni și mașini trebuie să fie creată. Mai mult, direcția de cercetare ar trebui să fie ghidată către utilizatori, prin evaluarea intereselor și nevoilor utilizatorilor. Scopul principal al acestei lucrări este de a oferi sugestii și soluții pentru a ușura și facilita interacțiunea creier-calculator, prin următoarele: i) stimulii și activitățile care se referă la stările mentale și interesele utilizatorilor, sunt optimizate; ii) un sistem interpretabil este creat pentru a dezvălui informația neuronală ce poate determina în continuare un sistem de tip BCI pe bază de control să acționeze; iii) și cel mai important aspect care face posibile primele doua puncte cheie: abordări metodologice avansate și îmbunătățite sunt dezvoltate pentru a extrage și interpreta, în mod eficient, activitatea neuronală umană relevată de Electroencefalogramă (EEG). Investigarea se realizează prin două studii experimentale, în care primul propune stimuli și sarcini îmbunătățite privind interesele și preferințele utilizatorilor în cadrul unei Interfețe Creier-Calculator bazate pe imaginare motorie. Al doilea studiu consideră stările mentale cognitive ale utilizatorilor vizând îmbunătățirea ulterioară a controlului în cadrul Interfețelor Creier-Calculator și investighează nu numai ceea ce utilizatorul a prelucrat din informațiile externe, ci și modul și nivelul de prelucrare al informației codificate în creier. Paradigmele investighează fluctuațiile creierului induse de diferiți stimuli și activități, pentru a oferi mijloacele de a detecta informația neuronală semnificativă din activitatea creierului, care este critică pentru o aplicație de tip BCI. În timp ce prima paradigmă consideră ritmurile sensori-motrice (SMRs), a doua paradigmă se bazează pe potențiale legate de evenimente (en., Event-Related Potentials - ERPs). Majoritatea paradigmelor BCI consideră fie informațiile temporale, fieinformațiile spectrale ale activității generate de către creier, însă rareori cercetarea se realizează în ansamblu, considerând ambele domenii, timp și frecvență. Așa cum se va observă în această lucrare, analiza care consideră un singur domeniu ar putea fi suboptimală, deoarece activitatea creierului prezintă informații suplimentare ce sunt vizibile atât în domeniul temporal, cât și în cel spectral. Prin urmare, această teză se ocupă cu îmbunătățirile metodologice ce includ informațiile complementare, obținând o analiză mai precisă a datelor ce depășește performanțele majorității metodelor disponibile.EC/FP7/611570/EU/Symbiotic Mind Computer Interaction for Information Seeking/MindSeeBMBF, 01GQ0850, Verbundprojekt: Bernstein Fokus Neurotechnologie - Nichtinvasive; Neurotechnologie für Mensch-Maschine Interaktio

Cryptographic Algorithm Designed by Extracting Brainwave Patterns

A new authentication method based on EEG signal is proposed here. Biometric features such as fingerprint scanning, facial recognition, iris scanning, voice recognition, and even brainwave patterns can be used for authentication methods. Brainwave patterns, also known as brain biometrics, can be captured using technologies like electroencephalography (EEG) to authenticate a user based on their unique brain activity. This method is still in the research phase and is not yet commonly used for authentication purposes. Extracting EEG features for authentication typically involves signal processing techniques to analyze the brainwave patterns. Here, a method based on statistics for extracting EEG features is designed to extract meaningful information and patterns from the brainwave data for various applications, including authentication, brain–computer interface systems, and neurofeedback training

Impact of education and economic growth on labour migration in the European union. A panel data analysis

Since migration is considered to play an important role on the attainment of the sustainable development goals (SDG’s) this study analyses the reversed perspective of the migration-SDG’s nexus. The data set consists of 308 observations on 28 European Union countries (including the United Kingdom) over a time span of 11 years (between 2008 and 2018). The analysis employed various stages of estimation in order to compare different results obtained from the panel data regression models. Besides the classical panel data regression models, the paper includes the estimation of Arellano-Bover/Blundell-Bond model that uses the Generalized Method of Moments (also known as GMM) as an econometric tool to solve the endogeneity of the selected variables. The focus is on two sustainable development goals: labour and economic growth, and education of the European Union member states plus the United Kingdom. The results showed that there is a significant influence of the selected variables on the migration flows at the European Union level. Although there are some contradictory results regarding the direction and statistical signifikance of the link between the variables of interest, most estimators do not have fundamentally different results. The GDP per capita keeps its positive impact on migration by generating an immigration flow towards countries with high GDP per capita. Economic growth proves to be the main trigger of migration, while education also plays an important role in shaping migration. The importance of this study derives from the reversed perspectives analysis, considering migration as being directly influenced by the achievement of the sustainable development goals

Versatile layered depth video coding based on distributed video coding

International audienc

Research and Science Today No. 1(7)/2014

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