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.