Decoding movement kinematics from EEG using an interpretable convolutional neural network

Continuous decoding of hand kinematics has been recently explored for the intuitive control of electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs). Deep neural networks (DNNs) are emerging as powerful decoders, for their ability to automatically learn features from lightly pre-processed signals. However, DNNs for kinematics decoding lack in the interpretability of the learned features and are only used to realize within-subject decoders without testing other training approaches potentially beneficial for reducing calibration time, such as transfer learning. Here, we aim to overcome these limitations by using an interpretable convolutional neural network (ICNN) to decode 2-D hand kinematics (position and velocity) from EEG in a pursuit tracking task performed by 13 participants. The ICNN is trained using both within-subject and cross-subject strategies, and also testing the feasibility of transferring the knowledge learned on other subjects on a new one. Moreover, the network eases the interpretation of learned spectral and spatial EEG features. Our ICNN outperformed most of the other state-of-the-art decoders, showing the best trade-off between performance, size, and training time. Furthermore, transfer learning improved kinematics prediction in the low data regime. The network attributed the highest relevance for decoding to the delta-band across all subjects, and to higher frequencies (alpha, beta, low-gamma) for a cluster of them; contralateral central and parieto-occipital sites were the most relevant, reflecting the involvement of sensorimotor, visual and visuo-motor processing. The approach improved the quality of kinematics prediction from the EEG, at the same time allowing interpretation of the most relevant spectral and spatial features

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

Toward a model-based predictive controller design in brain-computer interfaces

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.Grants K25NS061001 (MK) and K02MH01493 (SJS) from the National Institute of Neurological Disorders And Stroke (NINDS) and the National Institute of Mental Health (NIMH), the Portuguese Foundation for Science and Technology (FCT) Grant SFRH/BD/21529/2005 (NSD), the Pennsylvania Department of Community and Economic Development Keystone Innovation Zone Program Fund (SJS), and the Pennsylvania Department of Health using Tobacco Settlement Fund (SJS)

Use of Spatial Information and Search Strategies in a Water Maze Analog in Drosophila melanogaster

Learning the spatial organization of the environment is crucial to fitness in most animal species. Understanding proximate and ultimate factors underpinning spatial memory is thus a major goal in the study of animal behavior. Despite considerable interest in various aspects of its behavior and biology, the model species Drosophila melanogaster lacks a standardized apparatus to investigate spatial learning and memory. We propose here a novel apparatus, the heat maze, conceptually based on the Morris water maze used in rodents. Using the heat maze, we demonstrate that D. melanogaster flies are able to use either proximal or distal visual cues to increase their performance in navigating to a safe zone. We also show that flies are actively using the orientation of distal visual cues when relevant in targeting the safe zone, i.e., Drosophila display spatial learning. Parameter-based classification of search strategies demonstrated the progressive use of spatially precise search strategies during learning. We discuss the opportunity to unravel the mechanistic and evolutionary bases of spatial learning in Drosophila using the heat maze

Constraints on anomalous QGC's in e+e−e^{+}e^{-} interactions from 183 to 209 GeV

The acoplanar photon pairs produced in the reaction e(+) e(-) - → vvyy are analysed in the 700 pb(-1) of data collected by the ALEPH detector at centre-of-mass energies between 183 and 209 GeV. No deviation from the Standard Model predictions is seen in any of the distributions examined. The resulting 95% C.L. limits set on anomalous QGCs, a(0)(Z), a(c)(Z), a(0)(W) and a(c)(W), are -0.012 lt a(0)(Z)/Lambda(2) lt +0.019 GeV-2, -0.041 lt a(c)(Z)/Lambda(2) lt +0.044 GeV-2, -0.060 lt a(0)(W)/Lambda(2) lt +0.055 GeV-2, -0.099 lt a(c)(W)/Lambda(2) lt +0.093 GeV-2, where Lambda is the energy scale of the new physics responsible for the anomalous couplings

Measurement of W-pair production in e+e−e^+ e^- collisions at 189 GeV

The production of W-pairs is analysed in a data samplecollected by ALEPH at a mean centre-of-mass energy of 188.6 GeV,corresponding to an integrated luminosity of 174.2 pb^-1. Crosssections are given for different topologies of W decays intoleptons or hadrons. Combining all final states and assumingStandard Model branching fractions, the total W-pair cross sectionis measured to be 15.71 +- 0.34 (stat) +- 0.18 (syst) pb.Using also the W-pair data samples collected by ALEPH at lowercentre-of-mass energies, the decay branching fraction of the W bosoninto hadrons is measured to be BR (W hadrons) = 66.97+- 0.65 (stat) +- 0.32 (syst) %, allowing a determination of theCKM matrix element |V(cs)|= 0.951 +- 0.030 (stat) +- 0.015 (syst)

Tumor-specific expression of αvβ3 integrin promotes spontaneous metastasis of breast cancer to bone

INTRODUCTION: Studies in xenograft models and experimental models of metastasis have implicated several β3 integrin-expressing cell populations, including endothelium, platelets and osteoclasts, in breast tumor progression. Since orthotopic human xenograft models of breast cancer are poorly metastatic to bone and experimental models bypass the formation of a primary tumor, however, the precise contribution of tumor-specific αvβ3 to the spontaneous metastasis of breast tumors from the mammary gland to bone remains unclear. METHODS: We used a syngeneic orthotopic model of spontaneous breast cancer metastasis to test whether exogenous expression of αvβ3 in a mammary carcinoma line (66cl4) that metastasizes to the lung, but not to bone, was sufficient to promote its spontaneous metastasis to bone from the mammary gland. The tumor burden in the spine and the lung following inoculation of αvβ3-expressing 66cl4 (66cl4beta3) tumor cells or control 66cl4pBabe into the mammary gland was analyzed by real-time quantitative PCR. The ability of these cells to grow and form osteolytic lesions in bone was determined by histology and tartrate-resistant acid phosphatase staining of bone sections following intratibial injection of tumor cells. The adhesive, migratory and invasive properties of 66cl4pBabe and 66cl4beta3 cells were evaluated in standard in vitro assays. RESULTS: The 66cl4beta3 tumors showed a 20-fold increase in metastatic burden in the spine compared with 66cl4pBabe. A similar trend in lung metastasis was observed. αvβ3 did not increase the proliferation of 66cl4 cells in vitro or in the mammary gland in vivo. Similarly, αvβ3 is not required for the proliferation of 66cl4 cells in bone as both 66cl4pBabe and 66cl4beta3 proliferated to the same extent when injected directly into the tibia. 66cl4beta3 tumor growth in the tibia, however, increased osteoclast recruitment and bone resorption compared with 66cl4 tumors. Moreover, αvβ3 increased 66cl4 tumor cell adhesion and αvβ3-dependent haptotactic migration towards bone matrix proteins, as well as their chemotactic response to bone-derived soluble factors in vitro. CONCLUSION: These results demonstrate for the first time that tumor-specific αvβ3 contributes to spontaneous metastasis of breast tumors to bone and suggest a critical role for this receptor in mediating chemotactic and haptotactic migration towards bone factors

Searches for neutral Higgs bosons in e+e−e^{+}e^{-} collisions at centre-of-mass energies from 192 to 202 GeV

Searches for neutral Higgs bosons are performed with the 237 pb^-1 of data collected in 1999 by the ALEPH detector at LEP, for centre-of-mass energies between 191.6 and 201.6 GeV. These searches apply to Higgs bosons within the context of the Standard Model and its minimal supersymmetric extension (MSSM) as well as to invisibly decaying Higgs bosons. No evidence of a signal is seen. A lower limit on the mass of the Standard Model Higgs boson of 107.7 GeV/c^2 at 95% confidence level is set. In the MSSM, lower limits of 91.2 and 91.6 GeV/c^2 are derived for the masses of the neutral Higgs bosons h and A, respectively. For a Higgs boson decaying invisibly and produced with the Standard Model cross section, masses below 106.4 GeV/c^2 are excluded

Second asymptomatic carotid surgery trial (ACST-2): a randomised comparison of carotid artery stenting versus carotid endarterectomy

Background: Among asymptomatic patients with severe carotid artery stenosis but no recent stroke or transient cerebral ischaemia, either carotid artery stenting (CAS) or carotid endarterectomy (CEA) can restore patency and reduce long-term stroke risks. However, from recent national registry data, each option causes about 1% procedural risk of disabling stroke or death. Comparison of their long-term protective effects requires large-scale randomised evidence. Methods: ACST-2 is an international multicentre randomised trial of CAS versus CEA among asymptomatic patients with severe stenosis thought to require intervention, interpreted with all other relevant trials. Patients were eligible if they had severe unilateral or bilateral carotid artery stenosis and both doctor and patient agreed that a carotid procedure should be undertaken, but they were substantially uncertain which one to choose. Patients were randomly allocated to CAS or CEA and followed up at 1 month and then annually, for a mean 5 years. Procedural events were those within 30 days of the intervention. Intention-to-treat analyses are provided. Analyses including procedural hazards use tabular methods. Analyses and meta-analyses of non-procedural strokes use Kaplan-Meier and log-rank methods. The trial is registered with the ISRCTN registry, ISRCTN21144362. Findings: Between Jan 15, 2008, and Dec 31, 2020, 3625 patients in 130 centres were randomly allocated, 1811 to CAS and 1814 to CEA, with good compliance, good medical therapy and a mean 5 years of follow-up. Overall, 1% had disabling stroke or death procedurally (15 allocated to CAS and 18 to CEA) and 2% had non-disabling procedural stroke (48 allocated to CAS and 29 to CEA). Kaplan-Meier estimates of 5-year non-procedural stroke were 2·5% in each group for fatal or disabling stroke, and 5·3% with CAS versus 4·5% with CEA for any stroke (rate ratio [RR] 1·16, 95% CI 0·86–1·57; p=0·33). Combining RRs for any non-procedural stroke in all CAS versus CEA trials, the RR was similar in symptomatic and asymptomatic patients (overall RR 1·11, 95% CI 0·91–1·32; p=0·21). Interpretation: Serious complications are similarly uncommon after competent CAS and CEA, and the long-term effects of these two carotid artery procedures on fatal or disabling stroke are comparable. Funding: UK Medical Research Council and Health Technology Assessment Programme