Predictability's aftermath: Downstream consequences of word predictability as revealed by repetition effects

Stimulus processing in language and beyond is shaped by context, with predictability having a particularly well-attested influence on the rapid processes that unfold during the presentation of a word. But does predictability also have downstream consequences for the quality of the constructed representations? On the one hand, the ease of processing predictablewordsmight free up time or cognitive resources, allowing for relatively thorough processing of the input. On the other hand, predictabilitymight allowthe systemto run in a top-down “verificationmode”, at the expense of thorough stimulus processing. This electroencephalogram (EEG) study manipulated word predictability, which reduced N400 amplitude and inter-trial phase clustering (ITPC), and then probed the fate of the (un)predictable words in memory by presenting them again. More thorough processing of predictable words should increase repetition effects, whereas less thorough processing should decrease them. Repetition was reflected in N400 decreases, late positive complex (LPC) enhancements, and late alpha/beta band power decreases. Critically, prior predictability tended to reduce the repetition effect on the N400, suggesting less priming, and eliminated the repetition effect on the LPC, suggesting a lack of episodic recollection. These findings converge on a top-down verification account, on which the brain processes more predictable input less thoroughly. More generally, the results demonstrate that predictability hasmultifaceted downstreamconsequences beyond processing in the momen

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Proof-of-concept of a single-point Time-of-Flight LiDAR system and guidelines towards integrated high-accuracy timing, advanced polarization sensing and scanning with a MEMS micromirror

Dissertação de mestrado integrado em Engenharia Física (área de especialização em Dispositivos, Microssistemas e Nanotecnologias)The core focus of the work reported herein is the fulfillment of a functional Light Detection and Ranging (LiDAR) sensor to validate the direct Time-of-Flight (ToF) ranging concept and the acquisition of critical knowledge regarding pivotal aspects jeopardizing the sensor’s performance, for forthcoming improvements aiming a realistic sensor targeted towards automotive applications. Hereupon, the ToF LiDAR system is implemented through an architecture encompassing both optical and electronical functions and is subsequently characterized under a sequence of test procedures usually applied in benchmarking of LiDAR sensors. The design employs a hybrid edge-emitting laser diode (pulsed at 6kHz, 46ns temporal FWHM, 7ns rise-time; 919nm wavelength with 5nm FWHM), a PIN photodiode to detect the back-reflected radiation, a transamplification stage and two Time-to-Digital Converters (TDCs), with leading-edge discrimination electronics to mark the transit time between emission and detection events. Furthermore, a flexible modular design is adopted using two separate Printed Circuit Boards (PCBs), comprising the transmitter (TX) and the receiver (RX), i.e. detection and signal processing. The overall output beam divergence is 0.4º×1º and an optical peak power of 60W (87% overall throughput) is realized. The sensor is tested indoors from 0.56 to 4.42 meters, and the distance is directly estimated from the pulses transit time. The precision within these working distances ranges from 4cm to 7cm, reflected in a Signal-to-Noise Ratio (SNR) between 12dB and 18dB. The design requires a calibration procedure to correct systematic errors in the range measurements, induced by two sources: the timing offset due to architecture-inherent differences in the optoelectronic paths and a supplementary bias resulting from the design, which renders an intensity dependence and is denoted time-walk. The calibrated system achieves a mean accuracy of 1cm. Two distinct target materials are used for characterization and performance evaluation: a metallic automotive paint and a diffuse material. This selection is representative of two extremes of actual LiDAR applications. The optical and electronic characterization is thoroughly detailed, including the recognition of a good agreement between empirical observations and simulations in ZEMAX, for optical design, and in a SPICE software, for the electrical subsystem. The foremost meaningful limitation of the implemented design is identified as an outcome of the leading-edge discrimination. A proposal for a Constant Fraction Discriminator addressing sub-millimetric accuracy is provided to replace the previous signal processing element. This modification is mandatory to virtually eliminate the aforementioned systematic bias in range sensing due to the intensity dependency. A further crucial addition is a scanning mechanism to supply the required Field-of-View (FOV) for automotive usage. The opto-electromechanical guidelines to interface a MEMS micromirror scanner, achieving a 46º×17º FOV, with the LiDAR sensor are furnished. Ultimately, a proof-of-principle to the use of polarization in material classification for advanced processing is carried out, aiming to complement the ToF measurements. The original design is modified to include a variable wave retarder, allowing the simultaneous detection of orthogonal linear polarization states using a single detector. The material classification with polarization sensing is tested with the previously referred materials culminating in an 87% and 11% degree of linear polarization retention from the metallic paint and the diffuse material, respectively, computed by Stokes parameters calculus. The procedure was independently validated under the same conditions with a micro-polarizer camera (92% and 13% polarization retention).O intuito primordial do trabalho reportado no presente documento é o desenvolvimento de um sensor LiDAR funcional, que permita validar o conceito de medição direta do tempo de voo de pulsos óticos para a estimativa de distância, e a aquisição de conhecimento crítico respeitante a aspetos fundamentais que prejudicam a performance do sensor, ambicionando melhorias futuras para um sensor endereçado para aplicações automóveis. Destarte, o sistema LiDAR é implementado através de uma arquitetura que engloba tanto funções óticas como eletrónicas, sendo posteriormente caracterizado através de uma sequência de testes experimentais comumente aplicáveis em benchmarking de sensores LiDAR. O design tira partido de um díodo de laser híbrido (pulsado a 6kHz, largura temporal de 46ns; comprimento de onda de pico de 919nm e largura espetral de 5nm), um fotodíodo PIN para detetar a radiação refletida, um andar de transamplificação e dois conversores tempo-digital, com discriminação temporal com threshold constante para marcar o tempo de trânsito entre emissão e receção. Ademais, um design modular flexível é adotado através de duas PCBs independentes, compondo o transmissor e o recetor (deteção e processamento de sinal). A divergência global do feixe emitido para o ambiente circundante é 0.4º×1º, apresentando uma potência ótica de pico de 60W (eficiência de 87% na transmissão). O sensor é testado em ambiente fechado, entre 0.56 e 4.42 metros. A precisão dentro das distâncias de trabalho varia entre 4cm e 7cm, o que se reflete numa razão sinal-ruído entre 12dB e 18dB. O design requer calibração para corrigir erros sistemáticos nas distâncias adquiridas devido a duas fontes: o desvio no ToF devido a diferenças nos percursos optoeletrónicos, inerentes à arquitetura, e uma dependência adicional da intensidade do sinal refletido, induzida pela técnica de discriminação implementada e denotada time-walk. A exatidão do sistema pós-calibração perfaz um valor médio de 1cm. Dois alvos distintos são utilizados durante a fase de caraterização e avaliação performativa: uma tinta metálica aplicada em revestimentos de automóveis e um material difusor. Esta seleção é representativa de dois cenários extremos em aplicações reais do LiDAR. A caraterização dos subsistemas ótico e eletrónico é minuciosamente detalhada, incluindo a constatação de uma boa concordância entre observações empíricas e simulações óticas em ZEMAX e elétricas num software SPICE. O principal elemento limitante do design implementado é identificado como sendo a técnica de discriminação adotada. Por conseguinte, é proposta a substituição do anterior bloco por uma técnica de discriminação a uma fração constante do pulso de retorno, com exatidões da ordem sub-milimétrica. Esta modificação é imperativa para eliminar o offset sistemático nas medidas de distância, decorrente da dependência da intensidade do sinal. Uma outra inclusão de extrema relevância é um mecanismo de varrimento que assegura o cumprimento dos requisitos de campo de visão para aplicações automóveis. As diretrizes para a integração de um micro-espelho no sensor concebido são providenciadas, permitindo atingir um campo de visão de 46º×17º. Conclusivamente, é feita uma prova de princípio para a utilização da polarização como complemento das medições do tempo de voo, de modo a suportar a classificação de materiais em processamento avançado. A arquitetura original é modificada para incluir uma lâmina de atraso variável, permitindo a deteção de estados de polarização ortogonais com um único fotodetetor. A classificação de materiais através da aferição do estado de polarização da luz refletida é testada para os materiais supramencionados, culminando numa retenção de polarização de 87% (tinta metálica) e 11% (difusor), calculados através dos parâmetros de Stokes. O procedimento é independentemente validado com uma câmara polarimétrica nas mesmas condições (retenção de 92% e 13%)

Predictability's aftermath : Downstream consequences of word predictability as revealed by repetition effects

Acknowledgments A James S. McDonnell Foundation Scholar Award and NIH grant AG026308 to K.D.F supported this work. J.R. is supported by the Netherlands Organisation for Scientific Research (NWO) grant 275-89-032. We thank Rami Alsaqri, Vivek Dave and Neha Vagadia for assistance with stimulus development and/or data collection, and Ryan J. Hubbard for sharing independent component analysis scripts.Peer reviewedPostprin

Validation in Fusion Research: Towards Guidelines and Best Practices

Because experiment/model comparisons in magnetic confinement fusion have not yet satisfied the requirements for validation as understood broadly, a set of approaches to validating mathematical models and numerical algorithms are recommended as good practices. Previously identified procedures, such as verification, qualification, and analysis of error and uncertainty, remain important. However, particular challenges intrinsic to fusion plasmas and physical measurement therein lead to identification of new or less familiar concepts that are also critical in validation. These include the primacy hierarchy, which tracks the integration of measurable quantities, and sensitivity analysis, which assesses how model output is apportioned to different sources of variation. The use of validation metrics for individual measurements is extended to multiple measurements, with provisions for the primacy hierarchy and sensitivity. This composite validation metric is essential for quantitatively evaluating comparisons with experiments. To mount successful and credible validation in magnetic fusion, a new culture of validation is envisaged.Comment: 27 pages, 1 table, 6 figure

The brain as a generative model: information-theoretic surprise in learning and action

Our environment is rich with statistical regularities, such as a sudden cold gust of wind indicating a potential change in weather. A combination of theoretical work and empirical evidence suggests that humans embed this information in an internal representation of the world. This generative model is used to perform probabilistic inference, which may be approximated through surprise minimization. This process rests on current beliefs enabling predictions, with expectation violation amounting to surprise. Through repeated interaction with the world, beliefs become more accurate and grow more certain over time. Perception and learning may be accounted for by minimizing surprise of current observations, while action is proposed to minimize expected surprise of future events. This framework thus shows promise as a common formulation for different brain functions. The work presented here adopts information-theoretic quantities of surprise to investigate both perceptual learning and action. We recorded electroencephalography (EEG) of participants in a somatosensory roving-stimulus paradigm and performed trial-by-trial modeling of cortical dynamics. Bayesian model selection suggests early processing in somatosensory cortices to encode confidence-corrected surprise and subsequently Bayesian surprise. This suggests the somatosensory system to signal surprise of observations and update a probabilistic model learning transition probabilities. We also extended this framework to include audition and vision in a multi-modal roving-stimulus study. Next, we studied action by investigating a sensitivity to expected Bayesian surprise. Interestingly, this quantity is also known as information gain and arises as an incentive to reduce uncertainty in the active inference framework, which can correspond to surprise minimization. In comparing active inference to a classical reinforcement learning model on the two-step decision-making task, we provided initial evidence for active inference to better account for human model-based behaviour. This appeared to relate to participants’ sensitivity to expected Bayesian surprise and contributed to explaining exploration behaviour not accounted for by the reinforcement learning model. Overall, our findings provide evidence for information-theoretic surprise as a model for perceptual learning signals while also guiding human action.Unsere Umwelt ist reich an statistischen Regelmäßigkeiten, wie z. B. ein plötzlicher kalter Windstoß, der einen möglichen Wetterumschwung ankündigt. Eine Kombination aus theoretischen Arbeiten und empirischen Erkenntnissen legt nahe, dass der Mensch diese Informationen in eine interne Darstellung der Welt einbettet. Dieses generative Modell wird verwendet, um probabilistische Inferenz durchzuführen, die durch Minimierung von Überraschungen angenähert werden kann. Der Prozess beruht auf aktuellen Annahmen, die Vorhersagen ermöglichen, wobei eine Verletzung der Erwartungen einer Überraschung gleichkommt. Durch wiederholte Interaktion mit der Welt nehmen die Annahmen mit der Zeit an Genauigkeit und Gewissheit zu. Es wird angenommen, dass Wahrnehmung und Lernen durch die Minimierung von Überraschungen bei aktuellen Beobachtungen erklärt werden können, während Handlung erwartete Überraschungen für zukünftige Beobachtungen minimiert. Dieser Rahmen ist daher als gemeinsame Bezeichnung für verschiedene Gehirnfunktionen vielversprechend. In der hier vorgestellten Arbeit werden informationstheoretische Größen der Überraschung verwendet, um sowohl Wahrnehmungslernen als auch Handeln zu untersuchen. Wir haben die Elektroenzephalographie (EEG) von Teilnehmern in einem somatosensorischen Paradigma aufgezeichnet und eine trial-by-trial Modellierung der kortikalen Dynamik durchgeführt. Die Bayes'sche Modellauswahl deutet darauf hin, dass frühe Verarbeitung in den somatosensorischen Kortizes confidence corrected surprise und Bayesian surprise kodiert. Dies legt nahe, dass das somatosensorische System die Überraschung über Beobachtungen signalisiert und ein probabilistisches Modell aktualisiert, welches wiederum Wahrscheinlichkeiten in Bezug auf Übergänge zwischen Reizen lernt. In einer weiteren multimodalen Roving-Stimulus-Studie haben wir diesen Rahmen auch auf die auditorische und visuelle Modalität ausgeweitet. Als Nächstes untersuchten wir Handlungen, indem wir die Empfindlichkeit gegenüber der erwarteten Bayesian surprise betrachteten. Interessanterweise ist diese informationstheoretische Größe auch als Informationsgewinn bekannt und stellt, im Rahmen von active inference, einen Anreiz dar, Unsicherheit zu reduzieren. Dies wiederum kann einer Minimierung der Überraschung entsprechen. Durch den Vergleich von active inference mit einem klassischen Modell des Verstärkungslernens (reinforcement learning) bei der zweistufigen Entscheidungsaufgabe konnten wir erste Belege dafür liefern, dass active inference menschliches modellbasiertes Verhalten besser abbildet. Dies scheint mit der Sensibilität der Teilnehmer gegenüber der erwarteten Bayesian surprise zusammenzuhängen und trägt zur Erklärung des Explorationsverhaltens bei, das jedoch nicht vom reinforcement learning-Modell erklärt werden kann. Insgesamt liefern unsere Ergebnisse Hinweise für Formulierungen der informationstheoretischen Überraschung als Modell für Signale wahrnehmungsbasierten Lernens, die auch menschliches Handeln steuern