Cross-Subject Assistance: Inter-and Intra-Subject Maximal Correlation for Enhancing the Performance of SSVEP-Based BCIs

National Natural Science Foundation of Chin

A Hybrid Brain-Computer Interface Based on Electroencephalography and Functional Transcranial Doppler Ultrasound

Hybrid brain computer interfaces (BCIs) combining multiple brain imaging modalities have been proposed recently to boost the performance of single modality BCIs. We advance the state of hybrid BCIs by introducing a novel system that measures electrical brain activity as well as cerebral blood flow velocity using Electroencephalography (EEG) and functional transcranial Doppler ultrasound (fTCD), respectively. The system we developed employs two different paradigms to induce changes simultaneously in EEG and fTCD and to infer user intent. One of these paradigms includes visual stimuli to simultaneously induce steady state visually evoked potentials (SSVEPs) and instructs users to perform word generation (WG) and mental rotation (MR) tasks, while the other paradigm instructs users to perform left and right arm motor imagery (MI) tasks through visual stimuli. To improve accuracy and information transfer rate (ITR) of the proposed system compared to those obtained through our preliminary analysis, using classical feature extraction approaches, we mainly contribute to multi-modal fusion of EEG and fTCD features. Specifically, we proposed a probabilistic fusion of EEG and fTCD evidences instead of simple concatenation of EEG and fTCD feature vectors that we performed in our preliminary analysis. Experimental results showed that the MI paradigm outperformed the MR/WG one in terms of both accuracy and ITR. In particular, 93.85%, 93.71%, and 100% average accuracies and 19.89, 26.55, and 40.83 bits/min v average ITRs were achieved for right MI vs baseline, left MI versus baseline, and right MI versus left MI, respectively. Moreover, for both paradigms, the EEG-fTCD BCI with the proposed analysis techniques outperformed all EEG- fNIRS BCIs in terms of accuracy and ITR. In addition, to investigate the feasibility of increasing the possible number of BCI commands, we extended our approaches to solve the 3-class problems for both paradigms. It was found that the MI paradigm outperformed the MR/WG paradigm and achieved 96.58% average accuracy and 45 bits/min average ITR. Finally, we introduced a transfer learning approach to reduce the calibration requirements of the proposed BCI. This approach was found to be very efficient especially with the MI paradigm as it reduced the calibration requirements by at least 60.43%

Epilepsy

With the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well

Electronic Imaging & the Visual Arts. EVA 2017 Florence

The Publication is following the yearly Editions of EVA FLORENCE. The State of Art is presented regarding the Application of Technologies (in particular of digital type) to Cultural Heritage. The more recent results of the Researches in the considered Area are presented. Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Sciences and Culture Developments and Applications; New Technical Developments & Applications; Museums - Virtual Galleries and Related Initiatives; Art and Humanities Ecosystem & Applications; Access to the Culture Information. Two Workshops regard: Innovation and Enterprise; the Cloud Systems connected to the Culture (eCulture Cloud) in the Smart Cities context. The more recent results of the Researches at national and international are reported in the Area of Technologies and Culture Heritage, also with experimental demonstrations of developed Activities

Direction-Dependent Responses To Traumatic Brain Injury In Pediatric Pigs

Traumatic brain injury (TBI) in children is a costly and alarmingly prevalent public health concern. Children (4-11 years of age) in the US have the highest rate of TBI-related emergency department visits. The plane of head rotation significantly affects neurocognitive deficits and pathophysiological responses such as axonal injury, but is largely ignored in TBI literature. In Chapter 1, an outline of existing research is provided, including the lack of attention to diagnosis, treatment, and prevention in children, who exhibit distinct biomechanical and neuropathological responses to TBI. Additionally, we hypothesize that the plane of head rotation in TBI induces a) region-specific changes in axonal injury, which lead to acute and chronic changes in electrophysiological responses; b) changes to event-related potentials and resting state electroencephalography (EEG) and c) tract-oriented strain and strain rate alterations in the white matter. All work in this dissertation is based on a well-established piglet model of TBI. In Chapter 2, we assess a novel rotational head kinematic metric, rotational work (RotWork), which incorporates head rotation rate, direction, and brain shape, as a predictor of acute axonal injury. This metric provides an improvement over existing metrics and could be useful in the development of effective child safety equipment used in recreation or transportation. In Chapter 3, we generate functional networks from auditory event-related potentials and use the patterns of change to distinguish injured brains from non-injured; the resulting algorithm showed an 82% predictive accuracy. In Chapter 4, we find elevations in network nodal strength, modularity and clustering coefficient after TBI across all frequency bands relative to baseline, whereas both metrics were reduced in shams. We report the first study using resting state EEG to create functional networks in relation to pediatric TBI, noting that this work may assist in the development of TBI biomarkers. In Chapter 5, we use a high-resolution finite element model to examine the effects of head rotation plane on the distribution of regional strains and strain rates. Sagittal rapid head rotations induced significantly larger volume fraction of damaged brainstem than axial and coronal rotations. We also found that local tissue deformation and histopathology were head direction- and region- dependent but poorly correlated at a local scale. Finally, in Chapter 6, we conclude that the work presented in this dissertation is novel and contributes valuable knowledge to the study of pediatric TBI, and that consideration of the plane of head rotation is critical to the understanding and accurate prediction of pediatric functional and region-dependent responses to TBI

A cortical model of object perception based on Bayesian networks and belief propagation.

Evidence suggests that high-level feedback plays an important role in visual perception by shaping the response in lower cortical levels (Sillito et al. 2006, Angelucci and Bullier 2003, Bullier 2001, Harrison et al. 2007). A notable example of this is reflected by the retinotopic activation of V1 and V2 neurons in response to illusory contours, such as Kanizsa figures, which has been reported in numerous studies (Maertens et al. 2008, Seghier and Vuilleumier 2006, Halgren et al. 2003, Lee 2003, Lee and Nguyen 2001). The illusory contour activity emerges first in lateral occipital cortex (LOC), then in V2 and finally in V1, strongly suggesting that the response is driven by feedback connections. Generative models and Bayesian belief propagation have been suggested to provide a theoretical framework that can account for feedback connectivity, explain psychophysical and physiological results, and map well onto the hierarchical distributed cortical connectivity (Friston and Kiebel 2009, Dayan et al. 1995, Knill and Richards 1996, Geisler and Kersten 2002, Yuille and Kersten 2006, Deneve 2008a, George and Hawkins 2009, Lee and Mumford 2003, Rao 2006, Litvak and Ullman 2009, Steimer et al. 2009). The present study explores the role of feedback in object perception, taking as a starting point the HMAX model, a biologically inspired hierarchical model of object recognition (Riesenhuber and Poggio 1999, Serre et al. 2007b), and extending it to include feedback connectivity. A Bayesian network that captures the structure and properties of the HMAX model is developed, replacing the classical deterministic view with a probabilistic interpretation. The proposed model approximates the selectivity and invariance operations of the HMAX model using the belief propagation algorithm. Hence, the model not only achieves successful feedforward recognition invariant to position and size, but is also able to reproduce modulatory effects of higher-level feedback, such as illusory contour completion, attention and mental imagery. Overall, the model provides a biophysiologically plausible interpretation, based on state-of-theart probabilistic approaches and supported by current experimental evidence, of the interaction between top-down global feedback and bottom-up local evidence in the context of hierarchical object perception

XXV Congreso Argentino de Ciencias de la Computación - CACIC 2019: libro de actas

Trabajos presentados en el XXV Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de Río Cuarto los días 14 al 18 de octubre de 2019 organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y Facultad de Ciencias Exactas, Físico-Químicas y Naturales - Universidad Nacional de Río CuartoRed de Universidades con Carreras en Informátic