Influence of beta and theta binaural beat stimulation on episodic memory: an EEG study

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas) Universidade de Lisboa, Faculdade de Ciências, 2021Binaural beats (BBs) are auditory illusions created by the brain when two coherent sounds with slightly different frequencies are presented to both ears dichotically. For example, if the subject is presented a 256 Hz tone to the right ear and a 250 Hz to the left ear, the beat in this phenomenon is referred to as a 6 Hz theta binaural beat. Conversely, a mix of two sinusoids presented to the same ear is called acoustic beat (AB), resulting in a periodic amplitude fluctuation. Although BBs were shown to have positive effects on cognition, there are no sufficient studies on BBs and episodic memory. Furthermore, there is no agreement to explain the brain mechanism underlying the perception of BBs. The primary goal of this study is to investigate the influence of BBs on episodic memory and the effects of BB stimulation on brain rhythms, more concretely to examine whether they can change the power of specific EEG frequencies, comparatively to ABs. The secondary objective focuses on an exploratory study to measure cortical auditory evoked potentials (CAEPs) applying Muse, a consumer-grade EEG device used in this study, in order to assess its potential and the corresponding data quality. To meet the goals, two separate experiments were designed: a classic CAEP paradigm, with a total of 5 participants (3 male, 2 female; aged 22-25 years old); and an experiment with 32 subjects (19 male, 13 female; aged 20-28 years old), divided into two groups (depending on type of stimulation performed: 20 Hz beta or 6 Hz theta beats), each one with two stimuli conditions (BB or AB), received 15 minutes before the episodic memory task, during memory encoding phase and during the free recall test, across 2 sessions with an interval of 1 week. To quantify the power of brain oscillations during AB and BB stimulation, time-frequency analysis was performed using Discrete Wavelet Transform (DWT) and Relative Wavelet Energy (RWE). Regarding CAEP paradigm, N1-P2 complex was detected in temporal regions with acceptable signal-to-noise ratio. Parametric and non-parametric paired t-tests showed several significant changes in RWE values within each group at different time points, frequency bands and channels during both sessions, between BB and AB conditions. Moreover, entrainment of brain activity with the frequency of the beat was detected within theta BB stimulation. Regarding the effects of BB stimulation on episodic memory performance, t-tests revealed significant differences in the memory scores between AB and BB conditions during the first session (t=−2.48, p=0.0133) and second session (t=−2.67, p=0.00914) in theta group, with higher scores observed after BB stimulation. In beta group, significant differences in the scores were observed between AB and BB conditions during first session (t=−2.40, p=0.0154), with higher scores registered in BB condition. Inter-group analysis demonstrated that beta group outperformed theta group in both AB (t=3.37, p=0.00244) and BB (t=3.58, p=0.00143) conditions during the second session. This study validates the use of Muse for neuroscientific research, demonstrating that is possible to rely on consumer-grade low-cost EEG systems. Furthermore, it demonstrates that 20 Hz beta and 6 Hz theta BBs have a positive influence on episodic memory performance. Based on findings of positive effects of BBs on cognition, these results were expected. Entrainment was observed during theta BB stimulation. In addition, it is suggested that BBs have a modulatory effect on brain frequencies, with involvement of dynamical processes.Batimentos binaurais (BBs, do inglês Binaural beats) são ilusões auditivas criadas pelo cérebro quando dois sons coerentes com frequências ligeiramente diferentes são apresentados dicoticamente, isto é, cada ouvido é estimulado por frequências diferentes. Existem diferentes tipos de BBs, dependendo das frequências a partir das quais são criados e da diferença entre elas, o que determina a frequência do batimento. Por exemplo, se o sujeito é apresentado com um tom de 256 Hz no ouvido direito e 250 Hz no ouvido esquerdo, cria-se um batimento binaural de 6 Hz, na frequência do ritmo teta. Por outro lado, a mistura de duas sinusoides apresentadas ao mesmo ouvido possui o nome de batimento acústico (AB, do inglês acoustic beat) e as suas interferências são refletidas em flutuações periódicas em amplitude. Estudos demonstram que os BBs têm um efeito positivo na memória de trabalho, memória de longo prazo, capacidade de atenção e nos níveis de ansiedade e relaxamento. No entanto, existem relatos do seu efeito negativo na atenção e na memória de curto prazo. Para além disso, não existe um consenso na comunidade científica para explicar o mecanismo cerebral subjacente à perceção dos BBs. Tudo isto sublinha a necessidade de mais unificação na pesquisa. Apesar do efeito benéfico dos BBs nos diferentes tipos de memória, não existe um leque de estudos suficientemente grande relativamente à sua influência na memória episódica, um tipo de memória associado à codificação de eventos autobiográficos. Destaques na pesquisa sugerem que as oscilações teta estão associadas a um melhor desempenho na memória episódica. Presumindo que a estimulação auditiva com BBs teta possa ter um efeito modulador das frequências cerebrais por meio de resposta pós-frequência, mais especificamente no ritmo teta, é razoável supor que os BBs podem influenciar a memória episódica. O sistema de EEG usado neste estudo é o Muse, desenvolvido para ajudar em técnicas de meditação. Como não se trata de um aparelho de grau médico, é necessário entender se o material é viável para o estudo. O método para alcançar esta validação foi medir os potenciais evocados auditivos corticais, uma resposta cerebral já bem conhecida. Posto isto, a primeira parte desta tese foca-se num estudo exploratório para medir os potenciais evocados auditivos corticais usando o Muse, com o objetivo de avaliar o potencial do dispositivo e a qualidade dos dados correspondentes. A segunda parte e a meta principal deste estudo é investigar a influência do BBs na memória episódica e estudar o seu efeito nas oscilações cerebrais, em comparação com ABs. Para concretizar a primeira experiência deste estudo, um paradigma clássico foi desenhado para medir os potenciais evocados. Um total de 5 voluntários participaram neste estudo, com idades compreendidas entre 22 e 25 anos. Os participantes receberam um total de 180 estímulos, que consistiam em tons puros de 1000 Hz, com 500 ms de plateau, 10 ms de subida e descida e apresentados a cada 2 segundos. A aquisição do EEG e os marcadores de evento foram concretizados através do Lab Streaming Layer, uma ferramenta que permite criar redes de conexões entre vários dispositivos e programas. O pré-processamento e o processamento dos dados foram executados no EEGLAB, uma extensão do MATLAB que oferece uma interface gráfica para realizar a análise do EEG. Os resultados obtidos foram satisfatórios: o complexo N1-P2 foi identificado em todos os sujeitos e também nas curvas de grande média, com uma melhor relação entre o sinal e o ruído comparativamente às curvas individuais. Relativamente à segunda parte desta tese, a experiência consiste em 2 grupos de sujeitos, 2 blocos de tarefas, cada um com 2 condições de estímulo (AB ou BB), concretizada durante 2 sessões, separadas por uma semana. Um total de 32 voluntários foram recrutados, com idades compreendidas entre 20 e 28 anos. Os sujeitos foram divididos em 2 grupos: grupo teta, que recebeu estimulação com BBs e ABs teta na frequência dos 6 Hz, criados a partir de tons puros de 247 Hz e 253 Hz; grupo beta, que foi estimulado com BBs e ABs beta na frequência dos 20 Hz, gerados a partir de tons puros de 240 Hz e 260 Hz. A primeira parte do primeiro bloco consistia numa tarefa passiva em que os sujeitos de cada grupo ouviam ABs durante 15 minutos, ao mesmo tempo em que aquisição do EEG era realizada. Seguiu-se uma tarefa de memória episódica, em que os participantes tinham que decorar uma sequência de 30 imagens de objetos, cada uma com a duração de 3 segundos. De seguida, uma tarefa de distração foi realizada consistindo numa contagem em voz alta de 20 até 0. Por fim, foi feito um teste de recordação livre em que os sujeitos apontavam num papel os objetos que se lembravam de ver, cujo número seria contabilizado como pontuações de memória. O segundo bloco de tarefas é idêntico ao primeiro, exceto que imagens de objetos diferentes foram usadas e a estimulação durante os 15 minutos iniciais foi feita com BBs. Na segunda sessão, os mesmos procedimentos foram repetidos, exceto o uso de imagens de objetos diferentes em cada bloco. Para quantificar a energia de cada banda de frequência do EEG, recorreu-se à Transformada de Wavelet Discreta, que decompõe o sinal em vários níveis, cada um correspondendo a uma banda de frequência de ritmos cerebrais, e à Energia de Wavelet Relativa (RWE, de Relative Wavelet Energy). Mudanças na RWE dum determinado nível de decomposição refletem mudanças na atividade cerebral na banda de frequências correspondente. Dois tipos de análise foram concretizados: um tendo conta a evolução temporal da RWE ao longo de 13 segmentos de 1 minuto; o segundo implicou calcular a RWE média ao longo de um único segmento de EEG, colapsando a dimensão temporal. Os testes t paramétricos e não paramétricos revelaram várias diferenças entre os valores de RWE durante a estimulação com ABs e a estimulação com BBs, ao longo de diferentes instantes de tempo, bandas de frequências, canais e sessões da experiência. Relativamente ao grupo teta, os testes revelaram que a RWE na banda de frequência alfa no canal AF8 durante a primeira sessão aumentou de AB para BB (t=2.2701, p=0.01919). Durante a segunda sessão, foi observado um aumento dos valores de RWE na banda de frequências teta no canal TP10 da condição AB para BB (t=2.4509, p=0.0135). Relativamente ao grupo beta, as seguintes observações correspondem à primeira sessão, da condição AB para BB: uma diminuição significativa de RWE na banda de frequências beta no canal TP10 (t=-2.3364, p=0.0181) e um aumento significativo de RWE na banda delta no canal TP10 (t=4.3193, p=0.0004164) e no canal TP9 (t=2.7144, p=0.00885). Quanto aos efeitos dos BBs na performance de memória episódica, os testes t revelaram diferenças significativas nas pontuações entre as condições AB e BB durante a primeira sessão (t=-2.48, p=0.0133) e segunda sessão (t=-2.67, p=0.00914) no grupo teta, com pontuações mais altas observadas após a estimulação com BB. No grupo beta, diferenças significativas nas pontuações foram observadas entre as condições AB e BB durante a primeira sessão (t=-2.40, p=0.0154), com pontuações mais elevadas registadoa na condição BB. A análise entre os grupos demonstrou que o grupo beta superou o grupo teta em ambas as condições AB (t=3.37, p=0.00244) e BB (t=3.58, p=0.00143) durante a segunda sessão. Uma análise fatorial ANOVA II demonstrou que o efeito principal da condição foi significativo, sendo que os participantes que foram submetidos à estimulação com batimentos binaurais tiveram resultados mais altos (F(1,115)=5.49, p=0.0208). O efeito principal da sessão também foi significativo, com pontuações mais altas obtidas durante a segunda sessão (F(1,115)=9.206, p=0.00298). Houve interação significativa entre grupo e sessão (F(1,115)=5.11, p=0.0256). Para além disso, regressões lineares demonstraram que o aumento das pontuações de memória está associado ao aumento de RWE na banda de frequências beta (F(5,114) = 5.876, p < 0.0001). Este estudo mostra que é possível quantificar os potenciais evocados auditivos corticais usando um dispositivo de EEG de grau de consumidor. Foi demonstrado que os batimentos binaurais teta de 6 Hz e beta de 20 Hz têm efeito positivo no desempenho da memória episódica, comparativamente aos respetivos acoustic beats. Os participantes que foram estimulados com BBs beta tiveram melhores resultados nos testes de memória comparativamente aos que receberam estimulação com BBs teta, o que pode ser explicado pelo facto da atividade teta, característica da memória episódica, ter sido despertada durante a estimulação BB beta. No entanto, foi demonstrado que o aumento nas pontuações de memória episódica é explicado pelo aumento da RWE no ritmo beta. A resposta pós-frequência foi observada durante a exposição aos BBs teta, porém o mesmo não se verifica relativamente aos BBs beta. Para concluir, este estudo prova que os batimentos binaurais são moduladores neuronais, com envolvimento de respostas dinâmicas. Este efeito modulador da atividade cerebral pode ser a razão por trás da influência destes batimentos na memória episódica

Measurement of cognitive dynamics during video watching through event-related potentials (ERPs) and oscillations (EROs)

Event-related potentials (ERPs) and oscillations (EROs) are reliable measures of cognition, but they require time-locked electroencephalographic (EEG) data to repetitive triggers that are not available in continuous sensory input streams. However, such real-life-like stimulation by videos or virtual-reality environments may serve as powerful means of creating specific cognitive or affective states and help to investigate dysfunctions in psychiatric and neurological disorders more efficiently. This study aims to develop a method to generate ERPs and EROs during watching videos. Repeated luminance changes were introduced on short video segments, while EEGs of 10 subjects were recorded. The ERP/EROs time-locked to these distortions were analyzed in time and time-frequency domains and tested for their cognitive significance through a long term memory test that included frames from the watched videos. For each subject, ERPs and EROs corresponding to video segments of recalled images with 25% shortest and 25% longest reaction times were compared. ERPs produced by transient luminance changes displayed statistically significant fluctuations both in time and time-frequency domains. Statistical analyses showed that a positivity around 450 ms, a negativity around 500 ms and delta and theta EROs correlated with memory performance. Few studies mixed video streams with simultaneous ERP/ERO experiments with discrete task-relevant or passively presented auditory or somatosensory stimuli, while the present study, by obtaining ERPs and EROs to task-irrelevant events in the same sensory modality as that of the continuous sensory input, produces minimal interference with the main focus of attention on the video stream

Data fusion of complementary information from parietal and occipital event related potentials for early diagnosis of Alzheimer\u27s disease

The number of the elderly population affected by Alzheimer\u27s disease is rapidly rising. The need to find an accurate, inexpensive, and non-intrusive procedure that can be made available to community healthcare providers for the early diagnosis of Alzheimer\u27s disease is becoming an increasingly urgent public health concern. Several recent studies have looked at analyzing electroencephalogram signals through the use of many signal processing techniques. While their methods show great promise, the final outcome of these studies has been largely inconclusive. The inherent difficulty of the problem may be the cause of this outcome, but most likely it is due to the inefficient use of the available information, as many of these studies have used only a single EEG source for the analysis. In this contribution, data from the event related potentials of 19 available electrodes of the EEG are analyzed. These signals are decomposed into different frequency bands using multiresolution wavelet analysis. Two data fusion approaches are then investigated: i.) concatenating features before presenting them to a classification algorithm with the expectation of creating a more informative feature space, and ii.) generating multiple classifiers each trained with a different combination of features obtained from various stimuli, electrode, and frequency bands. The classifiers are then combined through the weighted majority vote, product and sum rule combination schemes. The results indicate that a correct diagnosis performance of over 80% can be obtained by combining data primarily from parietal and occipital lobe electrodes. The performance significantly exceeds that reported from community clinic physicians, despite their access to the outcomes of longitudinal monitoring of the patients

The Behavioral and Electrophysiological Effects of Discrimination and Inhibition Training on Visual Selective Attention: an ERP and Time-Frequency Analysis

Enhancement of task relevant information and the suppression of task irrelevant information are the two co-occurring mechanisms of selective attention. Studies have shown that ERP components (specifically N2, P3, and RP) and the alpha band (8-14 Hz) rhythm correspond to neural mechanisms and processes of visual selective attention, especially conflict resolution. Tested by a modified version of the visual flanker task, a conflict task employing inhibitory control, two groups of healthy adults were exposed to three weeks of cognitive training; either discrimination training (trained to discriminate target orientation) or inhibition training (trained to ignore interfering distractors) to investigate whether training impacts behavioral and neural correlates associated with stimuli processing. Behavioral analysis revealed a reduction in both Garner interference [F(1,33)=6.85, p=0.01] and Congruity effect [F(2,66)= 4.35, p=.02] after inhibition training, indicating better conflict resolution. Neural analyses revealed that the amplitude of N2 to target stimuli increased equally for both congruent and incongruent trials, albeit to a larger degree after inhibition training compared to discrimination training [F(1,32)= 5.18, pF(1,32)= 5.69, pF(1,32)= 4.87,

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

Joint time-frequency analysis and filtering of single trial event-related potentials.

The ongoing electrical activity of the brain is known as the electroencephalograph (EEG). Event related potentials (ERPs) are voltage deviations in the EEG elicited in association with stimuli. Their elicitation require cognitive processes such as response to a recognised stimulus. ERPs therefore provide clinical information by allowing an insight into neurological processes. The amplitude of an event-related potential is typically several times less than the background EEG. The background EEG has the effect of obscuring the ERP and therefore appropriate signal processing is required for its recovery. Traditionally ERPs are estimated using the synchronised averaging of several single trials or sweeps. This inhibits investigation of any trial-to-trial variation, which can prove valuable in understanding cognitive processes. An aim of this study was to develop wavelet-based techniques for the recovery of single trial ERPs from background EEG. A novel wavelet-based adaptive digital filtering method for ERPs has been developed. The method provides the ability to effectively estimate or recover single ERPs. The effectiveness of the method has been quantitatively evaluated and compared with other methods of ERP estimation.The ability to recover single sweep ERPs allowed the investigation of characteristics that are not possible using the conventional averaged estimation. The development of features of a cognitive ERP known as the contingent negative variation over a number of trials was investigated. The trend in variation enabled the identification of schizophrenic subjects using artificial intelligence methods.A new technique to investigate the phase dynamics of ERPs was developed. This was successfully applied, along with other techniques, to the investigation of independent component analysis (ICA) component activations in a visual spatial attention task. Two components with scalp projections that suggested that they may be sources within the visual cortex were investigated. The study showed that the two components were visual field selective and that their activation was both amplitude and phase modulated

NMDA Receptor Dysfunction and Development of Translational Biomarkers for Autism and Schizophrenia

Autism and schizophrenia are neurodevelopmental disorders which both have highly disabling negative and cognitive symptoms with few effective treatments. A challenge to developing effective therapeutics is a dearth of pre-clinical models. Part of the difficulty in developing predictive models is that the symptoms being treated are complex, and difficult to reduce to a simple behavioral task. Therefore, the use of endophenotypes from methods such as EEG presents a new promising avenue for a model of complex human behaviors pre-clinically. New evidence suggests that autism and schizophrenia have reliable electrophysiological endophenotypes, some of which have been correlated to negative and cognitive symptoms. These endophenotypes therefore represent a possible new pathway for understanding the disrupted circuits in both diseases and developing treatments. Evidence has been accumulating for glutamate disruption in both schizophrenia and autism; accordingly, pre-clinical models are being developed around NMDA receptor (NMDAR) disruption to examine both diseases. NMDA disruption models have been used for many behavioral tasks, but only a few possible electrophysiological endophenotypes such as ERP amplitudes have been investigated. Investigating pre-clinical models of established clinical endophenotypes could lead to better translational biomarkers of disease symptoms. This thesis\u27s unifying theme is the study of how glutamate disruption can recreate the electrophysiological endophenotypes present in autism and schizophrenia and develop their use as translational biomarkers in both diseases. The primary models of focus are acute NMDA antagonist administration and NMDAR knockdown of PV interneurons. I used these models to examine the relationship between dose and EEG changes, along with the perturbations present with NMDAR disruption in PV interneurons. I investigated the degree to which NMDAR antagonists recreate signal-to-noise ratio (SNR) and timing perturbations in schizophrenia, and found a dose-dependent decrease in SNR and timing consistency. I assessed the extent to which low dose NMDAR antagonism recreates latency and gamma synchrony perturbations present in autism and found latency was increased and gamma synchrony was decreased dose-dependently. I examined the extent to which Parvalbumin (PV) containing interneurons cell type selective NR1 KO mice recreate the clinical EEG profiles of autism and found selective deficits in social behavior and increases in N1 latency

Oscillatory delta and theta frequencies differentially support multiple items encoding to optimize memory performance during the digit span task

The human brain has limited storage capacity often challenging the encoding and recall of a long series of multiple items. Different encoding strategies are therefore employed to optimize performance in memory processes such as chunking where particular items are ‘grouped’ to reduce the number of items to store artificially. Additionally, related to the position of an item within a series, there is a tendency to remember the first and last items on the list better than the middle ones, which calls the “serial position effect”. Although relatively well-established in behavioral research, the neuronal mechanisms underlying such encoding strategies and memory effects remain poorly understood. Here, we used event-related EEG oscillation analyses to unravel the neuronal substrates of serial encoding strategies and effects during the behaviorally controlled execution of the digit span task. We recorded EEG in forty-four healthy young-adult participants during a backward digit span (ds) task with two difficulty levels (i.e., 3-ds and 5-ds). Participants were asked to recall the digits in reverse order after the presentation of each set. We analyzed the pattern of event-related delta and theta oscillatory power in the time-frequency domain over fronto-central and parieto-occipital areas during the item (digit) list encoding, focusing on how these oscillatory responses changed with each subsequent digit being encoded in the series. Results showed that the development of event-related delta power evoked by digits in each series matched the ‘serial position curve’, with higher delta power being present during the first, and especially last, digits as compared to digits presented in the middle of a set, for both difficulty levels. Event-related theta power, in contrast, rather resembled a neural correlate of a chunking pattern where, during the 5-ds encoding, a clear change in event-related theta occurred around the third/fourth positions, with decreasing power values for later digits. This suggests that different oscillatory mechanisms linked to different frequency bands may code for the different encoding strategies and effects in serial item presentation. Furthermore, recall-EEG correlations suggested that participants with higher fronto-central delta responses during digit encoding showed also higher recall scores. The here presented findings contribute to our understanding of the neural oscillatory mechanisms underlying multiple item encoding, directly informing recent efforts towards memory enhancement through targeted oscillation-based neuromodulation.Türkiye Bilimsel ve Teknolojik Araştırma Kurum

Characterization of dynamical neural activity by means of EEG data: application to schizophrenia

Schizophrenia is a disabling, chronic and severe mental illness characterized by disintegration of the process of thinking, contact with reality and emotional responsiveness. Schizophrenia has been related to an aberrant assignment of salience to external objects and internal representations. In addition, schizophrenia has been identified as a dysconnection syndrome, which is associated with a reduced capacity to integrate information among different brain regions. Relevance attribution likely involves diverse cerebral regions and their interconnections. As a consequence, many efforts have been devoted to identifying abnormalities in the cortical connections and their relation to schizophrenia symptoms and cognitive performance. Neural oscillations are one of the largest contributing mechanism for enabling coordinated activity during normal brain functioning. Alterations in neural oscillations and cognitive processing in schizophrenia have long been assessed using electroencephalographic (EEG) recordings (i.e. time-varying voltages on the human scalp generated by the electrical activity on the cerebral cortex). Event-related potentials (ERP) depict EEG data as a response to a cognitive task. ERP analyses are used to gain further insights into the neural mechanisms underlying cognitive dysfunctions. In this Doctoral Thesis, a 3-stimulus auditory-oddball paradigm was used for examining cognitive processing as response to both relevant and irrelevant stimuli. A total of 69 ERP recordings were analyzed in the research papers included in the Thesis, which comprises 20 chronic schizophrenia patients, 11 first episode patients and 38 healthy controls. This Doctoral Thesis is focused on the study, design and application of biomedical signal processing methodologies in order to facilitate the understanding of cognitive processes altered by the schizophrenia. EEG data were examined using a two-level analysis: (I) local activation studies to quantify functional segregation of the brain network, by means of spectral analysis and by assessing neural source generators of P3a and P3b components; and (II) EEG interactions studies to explore functional integration across brain regions, including pair-wise couplings and exploring hierarchical organization of neural rhythms.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Characterization of Neural Activity using Complex Network Theory. Application to the Identification of the Altered Neural Substrates in Schizophrenia

La esquizofrenia es un desorden psiquiátrico caracterizado por alteraciones en el pensamiento y en la capacidad de respuesta emocional. Comprende una gran variedad de síntomas, sin embargo, no está claro que todos compartan un sustrato neurológico común. Por ello, el objetivo de esta Tesis Doctoral es desarrollar un marco de referencia desde la perspectiva de la Teoría de Redes Complejas para investigar las interacciones neurales alteradas de la esquizofrenia haciendo uso de la señal electroencefalográfica. Así, dos bases de datos independientes de registros electroencefalográficos fueron registras durante una tarea cognitiva. Nuestros hallazgos son consistentes con estudios previos al tiempo que muestran una hiperactivación del intervalo de estímulo previa a una reorganización neural disminuida durante la cognición, principalmente asociado a caminos neurales secundarios. Los hallazgos de esta Tesis ponen de manifiesto la gran heterogeneidad de la esquizofrenia, posiblemente asociada a la existencia de subgrupos dentro de la misma.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione