Brain-mediated Transfer Learning of Convolutional Neural Networks

The human brain can effectively learn a new task from a small number of samples, which indicate that the brain can transfer its prior knowledge to solve tasks in different domains. This function is analogous to transfer learning (TL) in the field of machine learning. TL uses a well-trained feature space in a specific task domain to improve performance in new tasks with insufficient training data. TL with rich feature representations, such as features of convolutional neural networks (CNNs), shows high generalization ability across different task domains. However, such TL is still insufficient in making machine learning attain generalization ability comparable to that of the human brain. To examine if the internal representation of the brain could be used to achieve more efficient TL, we introduce a method for TL mediated by human brains. Our method transforms feature representations of audiovisual inputs in CNNs into those in activation patterns of individual brains via their association learned ahead using measured brain responses. Then, to estimate labels reflecting human cognition and behavior induced by the audiovisual inputs, the transformed representations are used for TL. We demonstrate that our brain-mediated TL (BTL) shows higher performance in the label estimation than the standard TL. In addition, we illustrate that the estimations mediated by different brains vary from brain to brain, and the variability reflects the individual variability in perception. Thus, our BTL provides a framework to improve the generalization ability of machine-learning feature representations and enable machine learning to estimate human-like cognition and behavior, including individual variability

Neuroscience and Education: The Importance of a Christian Understanding of Human Persons

The increased research in the neurosciences has affected the discipline of education in numerous ways, with publications translating this research into classroom practices. A caution is given to Christian educators to carefully reflect upon how this research influences our view of human persons and what difference this view makes in the teaching and learning process. The purpose of this paper is (1) to examine some of the ways that neuroscience is speaking into the discipline of education, particularly in understanding the capabilities and processes of the learner; (2) to develop an awareness of how this affects our understanding of persons; and (3) to establish the necessity for the preparation of future educators with a distinctly Christian perspective of the human constitution

Exploring students’ emotional state during a test-related task using wearable electroencephalogram

Using wireless sensors for brain activity, brain signals associated with the mood states of engineering students have been captured before and during the taking of a mathematics exam. The characterization of brain lobule activity related to arousal/valence states was analyzed from reports on the literature of the horizontal dimensions of pleasure-displeasure and vertical dimensions representing arousal-sleep. The results showed a direct relationship of the level of students’ arousal with the event of taking an exam as well as feelings of negative emotions during the exam presentation. The development of this research can lead to the implementation of controlled spaces for the presentation of students’ exams in which arousal/valence states can be controlled so that they do not affect their performance and the fulfillment of the goals, achievements or objectives established in a program or subject

The Role Of Individual Differences In Bilingual Language Processing

In this thesis, I investigated the neural correlates of bilingualism, and how individual differences in both brain and behaviour affect second language processing. To date, theories of bilingualism have tended to treat bilinguals as a uniform group, while in practice they vary greatly in both experience and ability. By examining how individual differences in proficiency and age of acquisition contribute to second language learning and processing, I sought to address this issue. In chapter two, I used event-related potentials to investigate how age of acquisition and proficiency modulate processing of a novel versus a grammatical rule that is similar across languages. I provided evidence that both age of acquisition and proficiency, in addition to bilingual status, modulate processing of a novel grammatical rule. In contrast, only proficiency predicted processing of a similar grammatical rule. Thus, while the similarities between languages affect second language processing, the degree of their influence is modulated by individual differences in second language experience. In chapter three, I used functional magnetic resonance imaging to investigate how bilinguals represent their shared, integrated lexicons in the brain. Several areas showed differing patterns of representation, while univariate analyses in these areas showed no differences in levels of activation. The separate representation of first and second languages in these regions provides a possible basis for the neurocognitive realization of a shared, integrated lexicon proposed by many theories of bilingualism. In chapter four, I used diffusion tensor imaging to investigate how AoA modulates white matter microstructure, examining white matter tracts in the left and right hemispheres that underlie language processing. Group statistics suggested that second language speakers as a whole may have lower fractional anisotropy, while the within-group analysis revealed that white matter integrity is sensitive to individual experience. Chapter five discusses the relevant findings of the previous chapters, and considers how individual differences arise. Next, I make recommendations for theories of bilingual language processing, and close with a discussion of future research directions

Reading skill related to left ventral occipitotemporal cortex during a phonological awareness task in 5–6-year old children

The left ventral occipitotemporal cortex (vOT) is important in visual word recognition. Studies have shown that the left vOT is generally observed to be involved in spoken language processing in skilled readers, suggesting automatic access to corresponding orthographic information. However, little is known about where and how the left vOT is involved in the spoken language processing of young children with emerging reading ability. In order to answer this question, we examined the relation of reading ability in 5–6-year-old kindergarteners to the activation of vOT during an auditory phonological awareness task. Two experimental conditions: onset word pairs that shared the first phoneme and rhyme word pairs that shared the final biphone/triphone, were compared to allow a measurement of vOT\u27s activation to small (i.e., onsets) and large grain sizes (i.e., rhymes). We found that higher reading ability was associated with better accuracy of the onset, but not the rhyme, condition. In addition, higher reading ability was only associated with greater sensitivity in the posterior left vOT for the contrast of the onset versus rhyme condition. These results suggest that acquisition of reading results in greater specialization of the posterior vOT to smaller rather than larger grain sizes in young children

Cognitive changes in conjunctive rule-based category learning: An ERP approach

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule (“easy” stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule (“difficult” stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning

The effect of leads on cognitive load and learning in a conceptually rich hypertext environment

The purpose of this experiment was to determine whether leads affect cognitive load and learning from conceptually rich hypertext. Measures of cognitive load included self-report of mental effort, reading time, and event-related desynchronization percentage of alpha, beta, and theta brain wave rhythms. Conceptual and structural knowledge tests, as well as a recall measure were used to determine learning performance. Measures of learners\u27 reading ability, prior knowledge, and metacognitive awareness were employed to establish the effect of individual differences on cognitive load and learning from traditional and lead-augmented hypertext. Results demonstrated that while leads appeared to reduce brain wave activity associated with split attention, processing of redundant information contained in hypertext nodes may have increased extraneous cognitive load, and decreased germane load that is required for learning to take place. Whereas the benefits of leads relative to cognitive load and learning may have been mediated by the redundancy effect, learners with better developed metacognitive skills tended to use leads as a tool to review information in the linked nodes while revisiting content in the primary text passage. Limitations of the currently available cognitive load measures are discussed as applied to direct assessment of this theoretical construct

Effects of EEG-neurofeedback training on brain functional connectivity

Tese de Mestrado Integrado, Engenharia Biomédica e Biofísica, 2022, Universidade de Lisboa, Faculdade de CiênciasO neurofeedback (NF) consiste em medir a atividade cerebral, usando técnicas como a eletroencefalografia (EEG) ou a imagem por ressonância magnética funcional (fMRI), e apresentar ao participante, em tempo real, uma representação de um padrão de atividade de interesse, enquanto lhe é pedido para manipular essa mesma representação através da autorregulação da atividade cerebral (Sitaram et al., 2017). As bases neurofisiológicas desta técnica ainda não são conhecidas na sua totalidade, apesar de vários estudos terem demonstrado que o treino através de NF tende a reorganizar as redes cerebrais. Posto isto, existem poucos estudos que tentam comparar a influência da utilização de diferentes modalidades sensoriais de apresentação do “feedback” nos resultados do treino por NF em EEG, e os poucos estudos existentes não investigam possíveis efeitos nas métricas de conectividade funcional do cérebro. Neste projeto, pretendemos avaliar o efeito da utilização de diferentes modalidades de “feedback” no treino de NF através EEG (EEG-NF) para o incremento da amplitude relativa da banda alfa superior no canal Cz, e investigar se existe um efeito significativo nos padrões de conectividade funcional do cérebro. Para esse fim, será efetuada a análise de dados previamente recolhidos em 20 participantes saudáveis que realizaram quatro sessões de treino por EEG-NF, que visava incrementar a densidade espectral na banda alfa superior, e que utilizaram diferentes modalidades de feedback (visual, realidade virtual (VR), e auditiva). Os dados de EEG foram pré-processados, com remoção de artefactos através de análise de componentes independentes. Adicionalmente, duas técnicas de re-referenciação do sinal EEG foram utilizadas para comparação posterior, sendo estas a re-referenciação para a média de todos os canais EEG, e a re-referenciação através da aplicação de um Laplaciano de Superfície com parâmetro de rigidez de valores 4 e 3, respetivamente. A avaliação dos resultados foi efetuada a diversos níveis, com a análise: i) das variações intra-sessão da amplitude relativa da banda alfa superior no canal Cz, ii) da distribuição topológica da banda alfa superior no decorrer do treino, iii) das variações intrasessão dos padrões de conectividade funcional da banda alfa superior, utilizando a parte imaginária da coerência como métrica de conectividade, e iv) por fim, em termos de uma análise de redes, que visava avaliar a importância de nodos de rede, verificada através das métricas como betweeness centrality e força, da atividade segregada, verificada através da métrica de transitividade, e da atividade integrada, verificada através de métricas como caminho característico e eficiência global da rede cerebral. Relativamente aos resultados para a análise espectral e topológica, encontram-se correlações estatisticamente significativas entre o valor da amplitude relativa da banda alfa superior e o número de set, em todos os grupos, principalmente nas duas primeiras sessões, sendo cada set composto por 6 trials com duração de 30 segundos Posto isto, não são registadas diferenças estatisticamente significativas intra-sessão, isto é, do set 1 para o set 5 de cada sessão. Para a análise topológica, não se realizaram testes de significância, mas é possível visualizar uma acentuação da amplitude relativa da banda alfa superior em zonas parietais/occipitais, e é também possível verificar que o treino realizado, não afetou somente a banda de interesse mas também a banda theta, cuja atividade não focal diminui, a banda alfa inferior, cuja amplitude relativa parece incrementar. Relativamente aos resultados da análise de conetividade, os mesmos sugerem que o treino de EEG-NF para o incremento da banda alfa superior resulta num incremento mais pronunciado nas fases iniciais do treino, isto é, nas duas primeiras sessões de treino. Este incremento é representado pelo do número de canais que apresentam conectividade funcional com a zona parietal central, com canais como o Pz, e com a zona parietal direita, CP6, P4, entre outros, independentemente da modalidade de feedback, ou seja, para a generalidade dos "Learners”. De facto, os próprios canais parietais direitos, P4, P8, CP6, TP10 aumentam de forma estatisticamente significativa a conectividade entre eles. Isto parece indiciar a criação de um complexo focado na zona parietal direita. Em todas as modalidades, à exceção da VR, verifica-se ainda um aumento significativo intra-sessão da transitividade e eficiência global enquanto uma diminuição estatisticamente significativa intra-sessão é observada para a métrica caminho característico. Posto isto, a metodologia de neurofeedback no contexto experimental que foi implementado, parece promover a atividade cerebral segregada, isto é, a atividade que resulta de uma atividade cerebral mais localizada, e também integrada, isto é, que resulta da integração da atividade de áreas cerebrais dispersas. A não existência de variações significativas na modalidade VR não parece estar relacionada com a modalidade em si, mas sim devido a uma menor amostra do respetivo grupo. Assim, futuramente será necessário aumentar a amostra, pelo menos para este grupo, por forma a poderem ser extraídos resultados significativos da análise do mesmo. Interessantemente, e independentemente do método de rereferenciação utilizado, enquanto para o grupo do treino NF para a modalidade visual se observa a partir da terceira sessão de treino a estabilização do número de conexões funcionais entre os diferentes elétrodos, ou seja deixa de haver um crescimento acentuado da transitividade e da eficiência global com diminuição simultânea do caminho característico, para o grupo do treino NF com a modalidade auditiva a generalidade dos incrementos verificados, estão presentes em todas as sessões, incluindo a última sessão. No referente ao estudo sobre o método de re-referenciação dos dados EEG, com interesse específico na utilização de um Laplaciano de superfície comparativamente à simples utilização da média dos sinais EEG, a análise topológica das diferentes bandas cerebrais confirma que a utilização do Laplaciano de superfície contribuiu para aumento da resolução espacial dos dados de EEG, uma vez que atenuou para as diferentes bandas a amplitude relativa da atividade periférica, ou seja não focal, que estará relacionada com frequências espaciais mais baixas. Relativamente à análise da conectividade funcional intra-sessão, verifica-se que a aplicação do Laplaciano se reflete na mudança das configurações de variações de conexões funcionais no cérebro, nomeadamente eliminando determinados aumentos estatisticamente significativos, por exemplo para a sessão 1 dos “Learners”, após a aplicação do Laplaciano de superfície, o incremento da conectividade funcional entre Pz e O2 deixa de ser estatisticamente significativo. Possivelmente, isto poderá estar relacionado com uma eliminação de conexões espúrias. Também na análise de redes, a aplicação do Laplaciano afeta a configuração dos dados e outputs embora não se consiga precisar uma relação causa efeito. Posto isto, a variação da própria configuração do Laplaciano, no que se refere à rigidez do mesmo, de parâmetro m=4 para m=3, não se traduz em resultados tão diferentes, pese embora algumas alterações notadas na análise de redes. De facto, para análise de conectividade funcional, os heatmaps resultantes da aplicação de Laplaciano de superfície com m=4, são exatamente iguais aos heatmaps resultantes da aplicação de Laplaciano de superfície com m=3. Quanto à análise de redes, nomeadamente nas métricas de transitividade, caminho característico e eficiência global, se verificarmos os gráficos e tabelas apresentadas, apesar de serem notados ligeiros desvios quer nas curvas quer em valores de correlação ou variação intra-sessão, o nível de significância é quase sempre atingido, independentemente da rigidez do Laplaciano aplicado, para a mesma sessão. Posto isto, não é possível reportar claramente uma relação causa-efeito vantajosa decorrente da aplicação do Laplaciano de superfície nos dados aqui tratados. De facto, reitera-se que, pela análise topológica se confirma que este possa estar associado a um filtro espacial, mas nas restantes análises não se consegue confirmar se este “melhorou ou não” os nossos dados.Neurofeedback (NF) consists in measuring brain activity and presenting a real-time representation of a brain activity pattern of interest to an individual, while instructing him to manipulate the feedback representation through self-regulation. The neurophysiological basis for NF remains to be fully elucidated, whereas several studies support that NF training tends to reorganize the brain networks. Only a handful of studies compare how different feedback sensory modalities affect the outcomes of EEG-based NF training, and none of them analyzes such effect on the functional connectivity or network metrics. In this project, we evaluate how using different feedback modalities on the EEG-based NFtraining will affect the brain’s functional connectivity, by analyzing previously collected data from a total of 20 healthy subjects, who underwent four sessions of upper-alpha (UA) band EEG-based NF training, with different feedback modalities (visual, auditory, or virtual reality (VR)). The EEG data was preprocessed and re-referenced with three different methods for posterior comparison, the common average reference (avgREF), and spline lines Surface Laplacian with stiffness parameters equals 4 and 3. The data were evaluated in terms of: i) the within-sessions’ variations of the relative amplitude of the UA at the Cz channel, ii) relative band amplitude topological distribution across sets and sessions, iii) the within-sessions’ variations of the UA functional connectivity patterns, computed with the imaginary part of coherency, and iv) an UA band network analysis of the metrics betweenness centrality, strength, transitivity, charpath and global efficiency. Our results suggest that the UA EEG-based NF-training is associated with an early increment of functional connections with channels over parietal areas (e.g. Pz), independently of the feedback sensory modality. All the modalities, except the VR, which had a reduced sample, verify statistically significant intra-session increases in the transitivity and global efficiency, while showing statistically significant intra-session decreases of the charpath, suggesting that this protocol promotes both clustered and integrated brain activity. While for the visual NF-training group the third session seems to be a breakthrough point, where the number of functional connections stabilize, for the auditory NF-training group longer lasting “variations” are reported. Through the topological analysis we confirm that the application of Laplacian leads to higher spatial resolutions on the EEG data. Regarding the connectivity analysis and network analysis, we note that the application of the Surface Laplacian creates different values when compared to the avgREF data, yet no advantageous outcome can be reported

The role of the HCN2 channel in the mouse septohippocampal circuit

Hyperpolarization-activated cyclic nucleotide-gated (HCN) cation channels be-long to the superfamily of voltage gated ion channels. They are activated by hyperpolarization and modulated by cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) binding to the cyclic nucleotide-binding domain (CNBD). There are four isoforms of HCN channels, HCN1-4, that convey a depolarizing inward current, termed Ih, which is essential for a variety of physiological processes in the brain, such as the stabilization of the resting membrane potential, the regulation of firing properties, and the genera-tion of theta oscillations. In the central nervous system, HCN channels are ex-pressed for example in the hippocampus and in the medial septum (MS). The hippocampus and the MS are interconnected via GABAergic (gamma-aminobutyric acid), cholinergic, and glutamatergic projection neurons and form the septo-hippocampal system. This system is crucial for the generation and modulation of the theta rhythm, which is one of the most prominent synchro-nous rhythms in the brain and is characterized by a frequency of 4-12 Hz. Functionally, the theta rhythm is critically involved in information processing, rapid-eye-movement sleep (REM), and organization of cognitive processes like learning and memory. In this study, I knocked out HCN2 in distinct subsets of MS neurons by a lenti-viral-based system with the help of a Cre-dependent approach. Investigating GABAergic neurons, electrophysiological recordings showed that in Cre-injected animals Ih and the theta power of REM sleep in electroencephalogram (EEG) recordings were reduced. Hippocampal spatial behavior was unaltered, while the object recognition memory was impaired. The examination of an HCN2 knockdown pan-neuronal of the MS resulted in a significantly reduction of Ih current and theta power of REM sleep. Additionally, HCN2 knockdown led to an impairment in hippocampal-dependent reversal learning in the Water Cross Maze (WCM). These findings implicate an important influence of HCN2 in the MS on septo-hippocampal neurons and the generation of theta oscilla-tions in the hippocampus