3rd International Winter BCI Conference - 49 Publications

All the links to the 49 publications from the 3rd International BCI Conference, presented in this blog some weeks ago, are available here or at IEEE Xplore Digital Library.

• Tutorial on multimodal neuroimaging for brain-computer interfacing
• Bayesian common spatial patterns
• Brain-computer interface for stroke rehabilitation with clinical studies
• Mobile real-time EEG imaging Bayesian inference with sparse, temporally smooth source priors
• Neuro-driving: Automatic perception technique for upcoming emergency situations
• Spatial projections of neural arrays: A short guide to classic and new signal analysis techniques
• Divergence estimation for machine learning and signal processing
• Progress toward a high-performance neural prosthetic
• Decoding cognitive brain states
• Eeg/sonication-based brain-brain interfacing
• Japanese SRPBS for BMI research: Decoded neurofeedback as a causal tool in systems neuroscience
• A Bayesian approach for spatio-spectral filter optimization in BCI
• A novel P300-based BCI system for words typing
• Non-homogeneous spatial filter optimization for EEG-based brain-computer interfaces
• A novel tactile stimulation system for BCI feedback
• A study on information transfer rate by brain-computer interface (BCI) using functional near-infrared spectroscopy (fNIRS)
• BMFLC with neural network and DE for better event classification
• Classifying ECoG signals prior to voluntary movement onset
• Common spatial patterns based on generalized norms
• Decoding three-dimensional arm movements for brain-machine interface
• Design of a robotic wheelchair with a motor imagery based brain-computer interface
• Detection of multi-class emergency situations during simulated driving from ERP
• Dry electrode design and performance evaluation for EEG based BCI systems
• EEG asymmetry and anxiety
• Eeg-based emotion recogntion during emotionally evocative films
• Eeg-based person authentication using face stimuli
• Effects of rest frames on cybersickness and oscillatory brain activity
• Efficient edge detection method for anatomic feature extraction of neuro-sensory tissue image based on optical coherence tomography
• Emotion classification in movie clips based on 3D fuzzy GIST and EEG signal analysis
• Estimation on the development of cerebral edema from computed tomography preliminary studies for pediatric traumatic brain injury patients
• Ethical and social issues behind brain-computer interface
• Evaluation of feature extraction methods for motor imagery-based bcis in terms of robustness to slight changes of electrode locations
• “Eyes-closed” SSVEP-based BCI for binary communication of individuals with impaired oculomotor function
• Implementation of a mental spelling system based on steady-state visual evoked potential (SSVEP)
• Learning Markov random field image prior for pixelation removal of fiber microscopy using sparse coding based on Bayesian framework
• Modified pattern-reversal visual checkerboard stimuli with dual alternating frequencies for multi-class ssvep-based brain-computer interfaces
• Motor trajectory decoding based on fMRI-based BCI — A simulation study
• Multimodal imaging technique for rapid response brain-computer interface feedback
• Optimal channel selection based on statistical analysis in high dimensional NIRS data
• P300 speller using a new stimulus presentation paradigm
• Power consumption of wireless EEG device for BCI application: Portable EEG system for BCI
• The beginning of neurohaptics: Controlling cognitive interaction via brain haptic interface
• The effectiveness of epidural ECoG on brain computer interface in primate
• Three-dimensional upper limb movement decoding from EEG signals

Shining light on Depression - Champalimaud Centre for the Unknown

Depression is a complicated and heterogeneous mood disorder. It affects a big part of the adult population and results in a significant financial and social liability for countries worldwide. But what really is depression and what are its causes? How can it be treated and prevented?

On January 22nd a group of neuroscience students and researchers from Champalimaud Neuroscience Programme will explore this subject and try to find some answers about it.
If tickets (free) are sold out live streaming will be available during the event. Don't miss!

Muse: the brain sensing headband.

Interaxon from Canada recently announced the launch of a new EEG reading device: MUSE (version 2). As the old version, it measures the electric activity produced by the brain searching for behavior patterns and identifying states of mind. Basically uses alpha waves (8-12Hz) to find if the person is calm and focused or when is wandering.

Muse is the mental equivalent of a treadmill, which helps you exercise your brain with focused attention training. It improves your attention by training you to become aware of your distractions quicker and react faster to regain focus on what you’re doing.

Connected to a Smartphone it will process the signals in real-time alerting you if get distracted and helping you catch to regain focus increasing the productive in your activity.

According to the company, the main advantages that this product offers are:

It motivates you to change your brain

Studies show that the focused-attention and mindfulness exercises upon which Muse is based can cause the brain to change itself, making it more resistant to distractions. Muse makes this process more motivating, fun and efficient.

It improves how you respond to stress

In the short-term, this training has been shown to trigger the natural relaxation response – a state of deep rest that changes the physiological and emotional responses to stress. Your metabolism decreases and your heartbeat slows. The muscles relax, breathing becomes slower, and blood pressure decreases.

It gives you a lasting feeling of self-control

Stress is thought of as a perceived lack of control or unpredictability, associated with impaired cognitive performance, higher blood pressure, lowered immunity, and many more negative effects. 

It can improve your emotional state

We often think of distraction as something external, like the sound of a nearby conversation. However, Muse’s feedback algorithms are tailored to respond to both external and internal distractions.

Extended use can have amazing and lasting results

A study showed that 20 minutes of focused attention training for 3 days in a row has been shown to reduce pain, reduce anxiety, improve mood, and reduce heart rate. 

It is designed to help you form the habit

Research has shown using an app and starting with 3-5 minutes can dramatically help you with mental exercises like meditation. Muse starts you with 3 minute sessions and rewards you for your achievements, making sure it’s easy and motivating to train with Muse.

Waitting to receive posts from people who have tested this new MUSE.

The Future of Brain/Neural Computer Interaction: Horizon 2020

The European Commission's Framework Programme 7 as created a Coordination and Support Action (CSA) called BNCI Horizon 2020. This project aims to foster communication and collaboration among stakeholders in the field of BCIs.

Brain-computer interfaces (BCIs) have become a popular topic for research in recent years. A BCI is a communication device which allows people to control applications through direct measures of their brain activity. A BNCI (brain/neuronal computer interaction) system extends a BCI by including other physiological measures such as muscle or eye movement signals. 

The number of BCI research groups around the world, peer-reviewed journal articles, conference abstracts, and attendance at relevant conferences are indicators of the rapid growth of this field. With dozens of companies and research groups actively participating in the development of BCIs and related technologies, collaboration, a common terminology, and a clear roadmap have become important topics.

For more informations visit the Horizon 2020 Web page.

3rd International Winter Workshop on Brain-Computer Interfaces

From 12 until 14 January, 2015, at Seoul - Korea, will be held the conference 3rd International Winter Workshop on Brain-Computer Interfaces.

Different approaches to Brain-Computer Interfaces have been developed, each one with specific solutions that range from understanding and explaining cognitive functions over communicating with real and virtual environments by thought alone to real-time monitoring of cognitive states. 
The 3rd International Winter Conference on Brain-Computer Interface aims to encourage overview, in-depth talks and discussions on the latest research at all levels of BCI research. 
Its devotion includes:

• invasive recording, 
• semi-invasive ECoG, 
• non-invasive EEG, 
• non-invasive NIRS and fMRI measurement and 
• potential combinations of the different methods furthermore advances in data analysis. 

The Path to Happiness - Peace or Pleasure?

Next December 4th, Champalimaud Center of the Unknown will discuss what bring us happiness. Dr. Morten Kringelbach and Scott Rennie will talk about meditative practices and their impact on how the brain works.

Is it the pleasure of good wine or great sex? 
The lasting pleasure of helping people in need? 
Or perhaps it is simply the quiet moments free from stress when we are truly relaxed? 

A very interesting event to assist!  I will be there!  :-)

How to reduce your required sleep time to just 2 hours a day

Intelclinic presents a new project called NeuroOn. Using EEG/EOG/EMG and with a sleep mask it will be possible to switch from two different sleep states: monophasic and polyphasic. The result is a solution that offers less and better sleep.

What is polyphasic sleep?
It is a term referring to alternate sleep patterns that can reduce the required sleep time to just 2-6 hours daily. It involves breaking up your sleep into smaller parts throughout the day, which allows you to sleep less but feel as refreshed as if you slept for 8 hours or more.
Simply put, it's a series of fine-tuned power naps that allow you to sleep effectively, rest better and perform at optimum energy levels during the day.
Additionally, NeuroOn monitored polyphasic sleep allows you to sync your body clock to very demanding schedules at whatever time is convenient or required.
In conclusion, through great sleep efficiency, Polyphasic sleep can give you an extra 4 hours of free time every day. That’s up to 28 hours (1 day+) a week, 1460 hours a year.

This project will be completed in July 2014. For more information press here.

iPhone Mobile App that Reads your Brain Activity

MELON company from USA created a headband, very simple to use, that reads your brain activity. This device uses the electroencephalography to measure your focus level and process it to show the results in your iPhone.

Gain insight into how your mind works by tracking your focus during any activity you choose. Understand yourself. Learn differently. Imagine if you could see and understand the invisible activity of your brain. Could you transform how you work? Improve the way you meditate? Find a new way to be creative? Melon is a headband and mobile app duo that tracks and helps you improve your focus in relation to your activity, your environment, your emotions, and any other behavior you want to track.

For the developer community there are a Software Development Kit for iOS and Android apps, where it is possible to access to raw data, list of algorithms for different mental states and connect to and control other Bluetooth devices

This project is undoubtedly one step further to the future of BCI.

BCI Technologies: BrainTech Israel 2013

Israel will host their 1st International Brain Technology Conference at October, 14-15, 2013.

This conference will be a unique and innovative event, showcasing the latest developments in the field in Israel and around the world,  and featuring top-tier speakers from the world of neurotechnology along with engaging panels and networking opportunities. The event will bring together companies, entrepreneurs, academics, investors and life science and technology multinationals to explore opportunities in brain technology and enhance collaboration.

For more information about this conference press here.

Israel invests heavily on the study of the brain and has recently created a research center at the Hebrew University of Jerusalem.
The 14,500 square-meter building include state-of-the-art labs, classrooms, an innovative imaging center and areas for biological and pre-clinical research. Significant emphasis were placed on constructing an environmentally friendly building with a focus on conserving energy and reducing carbon dioxide emissions.

Another concrete example of great investment in the study of the brain that is being done all over the world.

BCI State of the art: International BCI Meeting 2013

The Fifth International Brain-Computer Interface Meeting occurred at Asilomar Conference Center in Pacific Grove, California from June 3rd - 7th, 2013. It was an International BCI Meeting organized by a committee of BCI researchers from around the world. 

Here is the list of all the individual abstracts providing the most recent BCI state of the art:

• The effect of real-time positive and negative feedback on motor imagery performance
• Perceptual learning via decoded-EEG neurofeedback
• Investigation of the utility of mind-body awareness training in the early learning of a 1D sensorimotor 
• Training effects of multiple auditory BCI sessions
• Motivation and SMR-BCI: The Fear to Fail affects BCI Performance
• EEG Evaluation During Stress Emotional State Elicited by Unpleasant Sounds Applied in BCI
• The Effects of Motivation on Task Performance using the BCI
• Towards neurofeedback for improving visual attention
• Feel the BCI vibe - vibrotactile BCI feedback
• A tactile P300-based BCI
• On the Need for Both Internal and External Context Awareness for Reliable BCIs
• Classification of Auditory Steady-State Responses Incorporating Alpha Waves
• Self-paced BCI with NIRS based on speech activity
• Using Multiple Reward Related Signals in the Adaptation of Neuoprosthetic Decoders
• Temporal and Spatial Distribution of Workload-Induced Power Modulations of EEG Rhythms
• On Oscillatory EEG during Palm and Finger Movements
• Error Potentials for Brain-Computer Interfaces
• Unsupervised BCI calibration as possibility for communication in CLIS patients?
• Probabilistic Co-Adaptive Brain-Computer Interfacing
• Brain-Computer Interface Controlled Robotic Gait Orthosis
• Humanoid Robot Control with SSVEP on Embedded System
• Single Trial Classification of Imagined Hand Postures
• SSVEP based Brain-Computer Interface combined with video for robotic control
• High performance prediction of 3D-trajectory of hand from ECoG 
• 3D Trajectory Reconstruction of Upper Limb Based on EEG
• Muscular Activity Estimation from EEGs Using Component Analysis for B. Machine Interface
• On classifiying artifactual independent components: Generalization ability to different electrode setups
• Increasing the Spectral Signal-To-Noise Ratio of Common Spatial Patterns
• Bayesian Priors for Classifier Design in RSVP Keyboard
• A Stimulus-Free Brain-Computer Interface using Mental Tasks and Echo State Networks
• An Auditory Brain-computer Interface Based on Three-stimulus Oddball Paradigm 
• Implementation of a new independent SSVEP-based BCI
• Listen to the frog! An auditory P300 brain-computer interface with directional cues and natural sounds
• Auditory Brain Computer Interface Using Natural Sound
• A novel approach to auditory EEG based spelling
• Optimized ERP-based BCI using the stimulus of multi-familiar faces
• Fixing a Standard Matrix Size for BCI-360 Applications
• BCI using space-time-frequency coding protocol
• BCI-based operation of off-the-shelf software applications: Towards a General-Purpose Application 
• Investigation of Optimal Mental Task Combinations for EEG-based Brain-Computer Interface (BCI)
• A portable immersive virtual reality platform for motor-imagery guided rehabilitation 
• Comparison of Adaptive Symbol Presentation Methods for RSVP Keyboard
• A Motor Imagery Based Asynchronous BCI Speller
• Characterizing the SSVEP Spectrum using a Broadband Noise Stimulus
• Towards implicit control through steady-state somatosensory evoked potentials
• Cloud-Based Analysis of EEG Signals for BCI Applications
• Bringing Big Data to Neural Interfaces
• Predicting changes in neural tuning during BCI learning
• Proposing a Novel Feedback Provision Paradigm for Restorative Brain-Computer Interfaces
• Dynamic Stopping in a Calibration-less P300 Speller
• Simultaneous BCI operation and electrophysiological assessment to identify brain signal features
• EEG-predictors of covert vigilant attention
• The Effect of Task Based Motivation on BCI Performance: A Preliminary Outlook
• Multi-command Tactile and Auditory Brain Computer Interface based on Head Position Stimulation
• Using generic models to improve tactile ERP-BCI performance of low aptitude users
• Improving Dynamic Data Collection in P300 spellers with a Language Model
• The Use of Phonetic Similarity Cues in Auditory Spellers
• Predicting the performance of a MI-based BCI based on pre-cue EEG data
• Brain mapping as a tool for improving a physiologically based features selection for BCI applications
• Classification of Various Mental Task Combinations for NIRS-based Brain-Computer Interface
• ERPs in the P300 BCI: Sensitivity to Matrix Size and Task
• Electrocorticographic gamma band power correlates with the velocity of upper extremity movements
• Cortically-derived error-signals during BCI use
• Strategy for Reducing Calibration Time with Invariant Common Spatio-Spectral Patterns
• Self-Calibration in an asynchronous P300-based BCI
• Robotic Arm Control Using a Non-Invasive EEG-based BCI
• Eye to eye contact: controlling robot using P300 BCI
• Intelligent adaptive user interfaces for BCI based robotic control
• Task Identification Using Fluctuation Analysis
• Decoding grip types from premotor, parietal, and motor cortex
• Classifying speed and force from movement intentions using entropy and a support vector machine
• Individual selection of mental tasks and frequency bands boosts performance
• EEG Independent Component Polarity Normalization by Convex Relaxation 
• Performance Enhancement by Sparse Representation of EEG Signals for Motor Imagery 
• Performance prediction in motor imagery BCI
• Basis Selection for Increased Interclass Separability of EEG Signals
• Denoising and Time-window selection using Wavelet-based Semblance for improving ERP detection
• Efficient Adaptive Stimulus Sequencing for Improved P300 Speller Performance
• EEG Channel Optimization based on Differential Evolutionary Algorithm for BCI Application
• Frequency recognition of AM-SSVEP using modified CCA and PSDA
• Phase Information Enhanced SSVEP-BCI Using a Canonical Correlation Analysis Neural Network
• Comparison of P300 Responses in Auditory, Visual and Audiovisual Spatial Speller BCI Paradigms
• Motor Imagery BCI Feedback Presented as a 3D VBAP Auditory Asteroids Game
• A new stimulation method of virtual speller for simultanous P300 and SSVEP responses
• Error Analysis of the Region-based P300 Brain-Computer Interface Speller
• A hybrid control of a P300-based BCI: a solution to improve system usability?
• Design of Optimal Keyboard Layouts for a Mental Speller
• Effects of Varying Presentation Rate and Sequence Length on User Performance 
• BCILAB: A Toolbox for Rapid Development of Advanced BCI Designs
• SSVEP-based BCI Stimulation Frequency Selection Training and Detection approaches
• Towards a Free and Open Source BCI System Written in Python
• An Online SSVEP-based Brain-computer Interface for Freely Moving Humans
• Objective Indication of Fatigue in SSVEP-based BCI through EEG Spectral Analysis
• Auditory BCIs for Visually Impaired Users
• BCI Research at Inria Bordeaux: making BCI designs usable outside the lab
• Towards a Low Cost mu-rhythm Based BCI
• A Comparison of EEG Systems for use in P300 Spellers by Users with Motor Impairments
• Visual and Stereo Audio Sensorimotor Rhythm Feedback in the Minimally Conscious State 
• Selective enhancement of motor imagery features using transcranial direct current stimulation
• Different Uses of Non-invasive BCI for Controlling Neuroprostheses: Case Studies with End-Users
• Rapid prototyping for BNCI users with Cerebral palsy
• The N100 of Averaged ERPs Predicts LDA Classifier Success on an Individual Basis
• EEG Correlates of Performance during Long-term use of a P300 BCI 
• Decoding Individual Finger Movements using Noninvasive EEG
• Controlling an Avatar by Thought using Real-Time fMRI
• Development of an Intracortical Eye Movement-Based Brain-Computer Interface
• Pairwise Classification of Phoneme Imagery Using CSP
• Mouth Motor movement based BCI
• Using a Brain-Computer Interface to Assess Awareness after Brain Injury
• Classifying volition for comatose patients: a BCI perspective
• Cooperating Brains: Dual-BCI as a New Paradigm to Investigate Brain-to-Brain Coordination
• Cooperating Brains: Joint Control of a Dual-BCI
• An ambulatory BCI-driven orthosis for stroke rehabilitation
• A Scene-combined navigation method based on Newton's Rings Paradigm 
• Tactually-evoked event-related potentials for BCI-based wheelchair control
• Detection of Motor Imagery of Swallow With Model Adaptation: Swallow Or Tongue?
• Towards Biometric Person Identification using fNIRS
• Detecting cognitive states for enhancing driving experience
• Neuroresponsive Media: SSVEP-based Interactive Experiences
• Iterative EEG-based Natural Image Search under RSVP
• EEG-based Emotion Detection in Music Listening
• P300-based Brain Computer Interface for Internet Browsing, Blogging and Storytelling
• Real-Time Functional Brain Mapping
• Evaluating hold-release functionality in a P300 BCI
• Prediction of Multiple Upcoming Emergencies during Simulated Driving based on ERP
• Design of Dry Electrodes for EEG based BCI systems
• Dry and Wireless EEG-based Brain-Computer Interfaces for Real-World Applications
• Comparison of Invasive Chronic Electrodes for Brain-Computer Interface Applications
• Brain Computer Interface Using Chromatic Transient Visual Stimulus Array
• Modeling the Electroencephalogram using Intracranial Signals
• Real-Time Estimation and 3D Visualization of Source Dynamics and Connectivity 
• Long-Term Independent BCI Home-Use by a Locked-In End-User: An evaluation study 
• Evaluation of Four different BCI prototypes by severely motor-restricted End-Users
• Correctly Applying Performance Metrics to Neuroprosthetic Control Interfaces
• Preliminary design and performance standards for BCI desired by potential users 
• An Improved Auditory Streaming BCI with Voice Stimuli
• Limitations of NIRS-based BCI for Realistic Applications in Human-Computer Interaction
• Transfer Learning for Accelerated P300 Speller Training
• Transferring BCI skills to successful application controls
• Effects of workload on P300 BCI signals and accuracy
• Assessment of the P300 evoked potentials latency stability during c(o)vert attention BCI
• Stability of Local Field Potentials Over 11 Months of Brain-Machine Interface Use
• Are BCIs Coming of Age as AAC Systems?
• Assessing information processing in patients with long-term and severe disorders of consciousness
• Clinical Screening Protocol for RSVP Keyboard™ BCI Use
• Comparison of the Checkerboard P300 Speller vs. the Row-Column Speller  
• "Selection Strategies" for the RSVP Keyboard™ BCI: Different Strokes for Different Folks
• Enhancing Brain-Computer Interface Performance in an ALS population: Checkerboard paradigms
• Towards a novel control paradigm based on decoding imagined movements from EEG
• Decoding complex hand movements using high density ECoG and high field fMRI
• Using ECoG Gamma Activity to Model the Mel-Frequency Cepstral Coefficients of Speech
• Decoding Articulatory Properties of Overt Speech from Electrocorticography
• Detecting brain responsivity in disorders of consciousness: a BCI-based methodology
• A platform for the detection of brain activity changes in patients diagnosed with Disorders
• A General Framework for Implementing A Multi-Subject Brain-Computer Interface
• Brain-Computer Interface Supported Collaborative Work

• Motor Recovery After Stroke by Means of BCI-Guided Functional Electrical Stimulation
• Brain Interface to Control a Tele-Operated Robot
• On-board Neural Processor on Vehicular BMI for Rat toward Long-term Operation
• Categorizing outdoor places using EEG signals 
• BCI games with motion capture and its possibilities in rehabilitation
• A Neurofeedback Approach to Supporting Characters in Virtual Stories
• Review: Movement related cortical potential based brain computer interface for rehabilitation
• Using BCI to play games with brain signals: an organic interaction process through NeuroBodyGame 
• Distinguishing between target and non-target fixations in a visual search task 
• Braib-activity-driven real.time music emotive control
• The Musical BCI: Control by Selective Listening
• Microneedle array integrated on a flexible substrate to fabricate dry electrode
• One-dimensional imaginary movement cursor control using disc and tripolar electrodes
• Simulation comparisons of the spatial resolution beteen disc and tripolar concentric ring electrodes

• Non-Invasive versus Invasive Brain-Computer Interfaces
• Impedance, histology, stability and longevity of the Neurotrophic Electrode in rats, and humans
• Design of a multichannel cortical stimulator prototype for future neuroprosthetic research
• Identification of Cortical Target Regions for Intracranial BCI Based on Covert Spatial Attention 
• Which Neural Signals are Optimal for Brain-Computer Interface Control?
• Transcranial Doppler Ultrasonography-Driven Online Augmentative and Alternative Communication 
• Tensor decomposition on EEG of music imagination
• Towards a broad-scale Usability Evaluation of Hybrid BCIs
• The Brindisys project: Brain Computer Interfaces as assistive technology for people with ALS
• Autonomy and Social Inclusion for the Severely Disabled: The BrainAble Prototype
• Measuring (limitations on) control precision in BCI

Obama Administration Encourages the Study of Human Brain

The run to invest in the discovery of the human brain began. Now it is the U.S. with the Administration of President Barack Obama that presents their project with an investment of billions of dollars.

The New York Times, from 13 February 2013, explains in more detail the objectives of this program:

The Obama administration is planning a decade-long scientific effort to examine the workings of the human brain and build a comprehensive map of its activity, seeking to do for the brain what the Human Genome Project did for genetics. The project, which the administration has been looking to unveil as early as March, will include federal agencies, private foundations and teams of neuroscientists and nanoscientists in a concerted effort to advance the knowledge of the brain’s billions of neurons and gain greater insights into perception, actions and, ultimately, consciousness.

More information available at http://www.nytimes.com/2013/02/18/science/project-seeks-to-build-map-of-human-brain.html

Toyota Prius Concept Bike with a BCI

In the beginning of 2011 Toyota and Parlee announced the "Toyota Prius concept bike". This new bike has a large part of the materials in carbon fiber which keep it light and easy to move. "Its brakes were molded into the fork and bottom bracket to increase aerodynamics, along with countless other tweaks that were tested and validated in the wind tunnels at MIT. A built-in dock for a smartphone enables riders to view information about their speed, cadence and heart rate." There were also some more innovations but the most interesting was the use of BCI using EPOC equipment to read EEG. The next video shows Toyota's presentation.

In January 2013, after a large number of months of development, this bike was present in the Detroit Auto Show with their all innovations. All but except one: The helmet with neurotransmitters to enable the cyclist to shift gears just by thinking was not part of the presentation.

The question is: Why? Well, it is totally different to use this equipment in a testing room comparing to use outside in a bad floor. Probably the large number of artifacts created with the street vibration can produce in real-time serious problems to this system. Let's wait some more time to see if this BCI project can have the imagined success.

JORTEC 2013

In the last week of 18 to 23 February was held in the Faculty of Science and Technology of Lisbon - Portugal the JORTEC (TEChnological JOuRneys) 2013. The organizing commission of the biomedical’s JORTEC had some lectures and workshops very interesting during this days. 

Listing some we have:

• "The Biomedical Engineer in the Health Industry", Engineer Ana Raquel Reis
• "The present and future of devices for neural recording", Dr. Adam Kampff
• "The cerebellar circuit: from synapse to behavior", Dr. Megan Carey
• "Integrity in Science", Dr. João Lobo Antunes

More information can be obtained in the JORTEC2013 webpage.

OpenViBE 0.15.0 and Mensia Technologies

After almost 6 months with less activity the open-source OpenViBE BCI application has begun a new project and it has now the software version 0.15.0. With this upgrade, for now, it is possible the Acquisition-Server (AS) receive simulations from external applications that must run at the same computer where the AS is installed.

New features are expected as well as professional use. The french company Mensia Technologies located in Paris is an example with their core business centered in OpenViBE.

Hopefully this project will continue his development offering new features and keeping based in user-friend technology!

Brain Interactive Map

University of California at Berkeley did an interesting study called "Interactive map: how the brain sorts what we see". It shows how the brain is wired to put the categories of objects and actions we see daily and it organizes these groupings. 

Using fMRI they record the patients brain activity while showing 2 hours of movie trailers where each object and action of the movies were identified before. Measuring the blood flow in about 30.000 of Voxels (Volumetric Pixels), covering the entire cortex, it was possible to determine how each object and action affects those areas.

The final result was to formulate models that describe how the brain encodes visual information and responds during natural vision. 

Here it is a small video which I've made using the BrainViewer. 

If you have an old PC probably it will not be possible to use the online "BrainViewer" because some of the WebGL functions don’t exist in the video board.

For more informations about BCI/EEG press here.

OpenVibe 3D Voxel and Topographic Map

Voxel is an OpenVibe 3D plugin that shows how to display reconstructed brain activity through inverse model and voxel visualizer. It can be tested using demo file voxel-display.xml. 

Another scenario is the 3D topographic map that uses the interpolating potentials at the surface of the scalp, converting them to colours using a colour scale and mapping them over the surface of the scalp.

Here is an example created with raw data from EPOC. It shows in real-time 2D and 3D Topographic maps, Spectrum, Signal and Matrix Display, and also a Time-frequency map.

For more informations about BCI/EEG press here.

Biomedical Engineering Salary and Jobs

Biomedical Engineering is one of the highest offer/paid jobs in the world. The CNN Money based in PayScale.com it says that a median pay for an experienced worker in the field is around $6.500 (5.000€) / month and it can be $10.000 (7.500€) at the top career.

The sites SimplyHire and Job Search Money CNN show some of the supply jobs around the world. In the last 30 days 3.000 jobs were found in SimplyHire (an average of 100 jobs offer per day).

The Champalimaud Neuroscience Programme

The Champalimaud Neuroscience community is a research group from over 20 different countries to try to understand how the brain works. The "Ar" group using interactive projects wants to show to the people why science is important. 

Society, Adventures in illegal art, Mind Invaders, Think of a Numb3r, Food for Thought, Human 2.0, Creativity and Suspicious Coincidences in the Brain - are some of their very active scientific events.

The Champalimaud Centre for the Unknown is located in Portugal near Belém.

Human Brain Project

The human brain has extraordinary functions and it is the most powerful computer imaginable. The Human Brain Project wants to start building a computer model of the brain and simulate its functions. It consists of a large international number of neuroscientists, physicists and other groups from the scientific community that aims to recreate the human brain inside a supercomputer with a budget of 1 Billion Euro.

As modern computers exploit ever-higher numbers of parallel computing elements, they face a power wall: power consumption rises with the number of processors, potentially to unsustainable levels. By contrast, the brain manages billions of processing units connected via kilometers of fibres and trillions of synapses, while consuming no more power than a light bulb. Understanding how it does this can provide the key not only to a completely new category of hardware but to a paradigm shift for computing as a whole, moving away from current models of “bit precise” computing towards new techniques that exploit the stochastic behavior of simple, very fast, low-power computing devices embedded in intensely recursive architectures. 

In short, the goal of the Human Brain Project is to build an infrastructure for future neuroscience, future medicine and future computing that will catalyze a global collaborative effort to understand the human brain and its diseases and ultimately to emulate its computational capabilities. The economic and industrial impact is potentially enormous.

BCI European Projects

Here are probably the 6 bigger BCI EU projects for systems that include spelling devices, computer games, functional electrical stimulation and navigation in virtual environments.

TOBI (2008-2012)

TOBI will design non-invasive BCI prototypes that will be combined with existing assistive technologies and rehabilitation protocols. In such a hybrid approach users can couple brain interaction with muscle-based interaction or can naturally switch between the different ways of interacting. Non-invasive BCI are based on electroencephalogram (EEG) signals. The EEG is recorded through electrodes placed on the user's head. This technology is not invasive and only records the electrical activity of the brain without interfering with it. TOBI is expected to have an impact by broadening the appropriate use of BCI assistive technology, by incorporating adaptive capabilities that augment those other assistive technologies they are combined with.

DECODER (2010-2012)

DECODER is a European collaborative project that will deploy Brain-Computer-Interfaces (BCI) for the detection of consciousness in non-responsive patients. The DECODER team develops an assessment battery that sup­ports an exact diagnosis of the state of consciousness by a variety of auditory, visual, tactile and mental stimulation paradigms. Through the deployment of Brain-Computer Interfaces (BCI) for non-responsive patients DECODER will provide access to modern information and communication technology such as internet, personal computer or home appliances when only a single response of a person is available.

BETTER (2010-2012)

The principal goal of BETTER is to improve physical rehabilitation therapies of gait disorders in stroke patients based on BNCI assistive technologies, producing improved systems, providing guidelines for improving future systems, and developing benchmarking and evaluation tools. The project will validate, technically, functionally and clinically, the concept of improving stroke rehabilitation with wearable exoskeletons and robotic gait trainers based on a TOP-DOWN approach: The robot exerts physical stimulation -at the periphery- as a function of targeted neural activation patterns (related to user involvement). This intervention is expected to result in reorganizations in the cortex. Such Top-Down therapeutic treatment would aim to encourage plasticity of the affected brain structures to improve motor function.

BrainAble (2010-2012)

The BrainAble project is about empowering them and pursues to mitigate the limitations of the everyday life to which they are confronted to. Our initiative is to research, design, implement and validate an ICT-based HCI (Human Computer Interface) composed of BNCI (Brain Neural Computer Interface) sensors combined with affective computing and virtual environments. Motor disabilities of people from any origin have a dramatic effect on their quality of life. Some examples of neurologic nature include a person suffering from a severe brain injury resulting from a car collision or individuals who have suffered a brain stroke. For years, the severely disabled have learned to cope with their restricted autonomy, impacting on their daily activities like moving around or turning on the lights and ability for social interaction.

ABC (2011-2014)

ABC aims at increasing human capabilities by means of Brain/Neural Computer Interfaces (BNCI). The project will develop applications addressed primarily to persons with Dyskinetic Cerebral Palsy (DCP). Due to DCP particular conditions, BNCI-based systems present a huge potential for the improvement of the quality life and the promotion the independent living of this target group. In particular, project outcomes will specifically focus the augmentation of capabilities related to communication, learning, social participation and control of devices. ABC system will be composed by four independent modules based on the latest advancements in BNCI signal processing, Affective Computing, Augmented Communication and Biosignal Monitoring. The reference European Research Institutions in each field will lead the R&D work.

BackHome (2012-2015)

BACKHOME will conceive, research, design, implement and validate person-centred solutions to end users with functional diversity. Knowing the person’s needs will be a core part of the pro­ject focus. Social research techniques will be conducted in order to provide a continuous flow of user-based knowled­ge that will be crucial to ensure the alignment between the project outputs and the requirements of people.

BackHome will provide Assistive Technology (AT) so­lutions to research and develop systems for assisting people with severe disabilities. The AT embedded within BackHome will include BNCIs, environmental control systems and a range of other te­chnologies which are usually classified as ambient inte­lligence and which can provide a considerable support to make BNCI solutions really work in environments with a lack of human support.

EEG with Dry Electrodes

Enobio is a wearable and wireless electrophysiology sensor system for the recording of EEG using dry electrodes. It is not necessary to use gel or saline water so it takes just one minute to start reading EEG signals.

This system has a user friendly software (NIC) for real time visualization (including spectrum and spectrogram), filtering, streaming and feature extraction. It as 8 or 20 channels and is wireless using Bluetooth.

Neuroelectrics from Spain (Barcelona) provides this solution. The price is supplied by completing a questionnaire and depending on the type of activity for which it will be used.

Cognitive Control Machines by FESTO

A software solution for controlling devices with thoughts was developed by FESTO using the EPOC BCI device from EMOTIV. 

CogniGame is a reinterpretation of the 1970s game with two players, a ball and two linear axes which move the bats to clear the ball and keep it in play. One player controls his bat with a joystick, and the other controls the linear axis alone by the power of thought via a brain-computer interface (BCI).

This system uses the brainwave pattern mu rhythm. The mu rhythm is generated in the motor-sensory cortex and occurs as a result of physical movement, or even the mere thought of such movement. Consequently, it’s sufficient to simply imagine the left hand moving in order to move the axis to the left. 

More information in the PDF article "New operational concepts for human-machine interaction".

Samsung BCI patent

Samsung recently patent its product to US patent and Trademark office. The patent application which covers Samsung’s initial work on a possible future headset that will utilize a brain computer interface.

Getting to the heart of the patent, Samsung states that “The neural activity is tracked on a neural activity detecting device. The electrical signals representative of the neural activity are transmitted via wired or wireless to the control unit.

If a predetermined signal is sensed by a detecting device, the same EEG readings may be monitored. For example, the Alpha waves (8-13 Hz) could be affected if the user concentrates on some actions. If the concentration pattern is detected, the system is responsive to the signal and issue an instruction to take action to “open file”, “close file”, “copy file”, “clicking”, “paste”, “delete”, “space”, or “inputting characteristics” etc. 

It should be noted that the state patterns of potential users may be monitored before the system is used.

3D Brain Atlas

The Brain Explorer 3-D viewer is a dynamic tool associated with the Allen Human Brain Atlas that allows you to visualize human brain anatomy and gene expression information from the Atlas database.

A growing collection of online public resources integrating extensive gene expression and neuroanatomical data, complete with a novel suite of search and viewing tools.

The Brain Explorer 2 software is a desktop application for viewing the human brain anatomy and gene expression data in 3-D. Using the Brain Explorer 2 software, you can:

• View a fully interactive version of the Allen Human Brain Atlas in 3-D;
• View gene expression data in 3-D: inflated cortical surfaces are colored by gene expression values of nearby samples;
• View expression data from different donors side-by-side;
• Explore anatomically-labeled MRI images and cortical surfaces.

This video provides a brief walkthrough of the interactive 3-D viewer, demonstrating its basic features for exploring human brain anatomy and gene expression.

MUSE headband controler

MUSE is a flexible, adjustable, lightweight headband with 4 sensors - including two on the forehead and two behind the ears. It communicates over Bluetooth and is compatible with iPhone, iPad, Android, Mac OS, Windows and Linux. This is a new competitor to Emotiv or NeuroSky companies.

The Canadian startup InteraXon says that it's specially designed to work with a family of applications with exercises for brain health, fitness training, stress management, studying and many more. MUSE is expected to launch in 2013 and retail for around $200. 

Main features:

• Open communication standard to allow people to write their own device drivers;
• Rechargeable battery that lasts for 10 hours of use;
• The headband produces bipolar readings using AFz as the reference for AF3, AF4, TP9, TP10;  
• The 4-electrode montage enables estimation of hemispheric asymmetries;
• EEG signals are oversampled and bandpass filtered for noise reduction then downsampled to yield a selectable output sampling rate from 100 Hz to 600 Hz with 2uV (RMS) noise;
• Active noise suppression is achieved with a DRL - REF feedback configuration using centrally positioned frontal electrodes. 

In my opinion, using an equipment that reads EEG in real-time, when you are running or walking, will have a lots of "noise". I am very curious to see if InteraXon is able to overcome this big challenge.