1,720,983 research outputs found
SEEDS, simultaneous recordings of high-density EMG and finger joint angles during multiple hand movements
Get PDFWe present the SurfacE Electromyographic with hanD kinematicS (SEEDS) database. It contains electromyographic (EMG) signals and hand kinematics recorded from the forearm muscles of 25 non-disabled subjects while performing 13 different movements at normal and slow-paced speeds. EMG signals were recorded with a high-density 126-channel array centered on the extrinsic flexors of the fingers and 8 further electrodes placed on the extrinsic extensor muscles. A data-glove was used to record 18 angles from the joints of the wrist and fingers. The correct synchronisation of the data-glove and the EMG was ascertained and the resulting data were further validated by implementing a simple classification of the movements. These data can be used to test experimental hypotheses regarding EMG and hand kinematics. Our database allows for the extraction of the neural drive as well as performing electrode selection from the high-density EMG signals. Moreover, the hand kinematic signals allow the development of proportional methods of control of the hand in addition to the more traditional movement classification approaches
Collaborative Brain-Computer Interfaces in Rapid Image Presentation and Motion Pictures
Get PDFThe last few years have seen an increase in brain-computer interface (BCI) research for the able-bodied population. One of these new branches involves collaborative BCIs (cBCIs), in which information from several users is combined to improve the performance of a BCI system. This thesis is focused on cBCIs with the aim of increasing understanding of how they can be used to improve performance of single-user BCIs based on event-related potentials (ERPs). The objectives are: (1) to study and compare different methods of creating groups using exclusively electroencephalography (EEG) signals, (2) to develop a theoretical model to establish where the highest gains may be expected from creating groups, and (3) to analyse the information that can be extracted by merging signals from multiple users. For this, two scenarios involving real-world stimuli (images presented at high rates and movies) were studied. The first scenario consisted of a visual search task in which images were presented at high frequencies. Three modes of combining EEG recordings from different users were tested to improve the detection of different ERPs, namely the P300 (associated with the presence of events of interest) and the N2pc (associated with shifts of attention). We showed that the detection and localisation of targets can improve significantly when information from multiple viewers is combined. In the second scenario, feature movies were introduced to study variations in ERPs in response to cuts through cBCI techniques. A distinct, previously unreported, ERP appears in relation to such cuts, the amplitude of which is not modulated by visual effects such as the low-level properties of the frames surrounding the discontinuity. However, significant variations that depended on the movie were found. We hypothesise that these techniques can be used to build on the attentional theory of cinematic continuity by providing an extra source of information: the brain
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Past and Future of Multi-Mind Brain-Computer Interfaces
Get PDFThe great improvements in brain–computer interface (BCI) performance that are brought upon by merging brain activity from multiple users have made this a popular strategy that allows even for human augmentation. These multi-mind BCIs have contributed in changing the role of BCIs from assistive technologies for people with disabilities into tools for human enhancement. This chapter reviews the history of multi-mind BCIs that have their root in the hyperscanning technique; the collaborative and competitive approaches; and the different ways that exist to integrate the brain signals from multiple people and optimally form groups to maximize performance. The main applications of multi-mind BCIs, including control of external devices, entertainment, and decision making, are also surveyed and discussed, in order to help the reader understand what are the most promising avenues and find the gaps that are worthy of future exploration. The chapter also provides a step-by-step tutorial to the design and implementation of a multi-mind BCI, with theoretical guidelines and a sample application
An EEG dataset to study neural correlates of audiovisual long-term memory retrieval.
Get PDFMemory retrieval is a fundamental cognitive process that plays a critical role in our lives. Studying the neural correlates of this process has significant implications for numerous fields, such as education and health care. Advances in neuroimaging technologies have facilitated the use of neural data, such as electroencephalography (EEG), to decode cognitive states associated with memory tasks. However, most memory research is still conducted using simple stimuli, such as lists of words, and it is unclear how much the discoveries made with such stimuli generalise to more naturalistic scenarios. We introduce a dataset of EEG signals from 27 participants acquired while they watched 10-second long clips of movies (some of which they had previously seen), together with annotations that reflect whether they recognised or remembered the scenes and the time points of recognition. This dataset allows the study of neural correlates of long-term memory recall in a naturalistic task
Data-driven detection of memory encoding from EEG in an audiovisual task
Get PDFReliably detecting memory encoding can help diagnose memory impairments and provide insights into neural correlates of memory formation from electroencephalogram (EEG).
However, there is little prior literature that can be used to drive feature extraction to detect encoding in audiovisual memory tasks.
Our objective is to explore the use of an explainable neural network to detect memory encoding from EEG while participants watch videos. We use EEG-ITNet in single- and multi-user scenarios and show that detecting successful memory encoding from EEG data using audiovisual stimuli is possible, particularly when recordings from multiple participants are used to train the models. In the future we will explore the features identified by EEG-ITNet to detect a neural signature of memory encoding. Our framework can also be utilized for data-driven feature discovery in tasks where there is little prior knowledge
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Brain-Computer Interfaces for Detection and Localization of Targets in Aerial Images
Get PDFObjective. The N2pc event-related potential (ERP) appears on the opposite side of the scalp with respect to the visual hemisphere where an object of interest is located. We explored the feasibility of using it to extract information on the spatial location of targets in aerial images shown by means of a rapid serial visual presentation (RSVP) protocol using single-Trial classification. Methods. Images were shown to 11 participants at a presentation rate of 5 Hz while recording electroencephalographic signals. With the resulting ERPs, we trained linear classifiers for single-Trial detection of target presence and location. We analyzed the classifiers' decisions and their raw output scores on independent test sets as well as the averages and voltage distributions of the ERPs. Results. The N2pc is elicited in RSVP presentation of complex images and can be recognized in single trials (the median area under the receiver operating characteristic curve was 0.76 for left versus right classification). Moreover, the peak amplitude of this ERP correlates with the horizontal position of the target within an image. The N2pc varies significantly depending on handedness, and these differences can be used for discriminating participants in terms of their preferred hand. Conclusion and Significance. The N2pc is elicited during RSVP presentation of real complex images and contains analogue information that can be used to roughly infer the horizontal position of targets. Furthermore, differences in the N2pc due to handedness should be taken into account when creating collaborative brain-computer interfaces
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