Brain areas and function

The outer layer of the brain is called the cerebral cortex, where many of the key functions of the nervous system are executed. The cerebral cortex of the human brain is divided into four parts of the brain named lobes: the frontal lobe, parietal lobe, temporal lobe, and occipital lobe. Each region has been subdivided and is associated with specific cerebral functions. 

Regions of the cerebral cortex associated with brain functions. [online] Available at: https://human-memory.net/sensory-cortex/

These physiological areas are related to some main functions or behaviors:

Brain functions related to brain lobes:

These are the different areas of the brain (lobes of the brain), and their main functions: 

1. Frontal: Reasoning, speech and movement control, emotions, and problem-solving.
2. Central: Sensoriomotor.
3. Parietal: Attention, perception and processing of stimuli related to the senses (temperature, touch, pressure, pain…).
4. Occipital: Vision.
5. Temporal: Memory, meaning, and auditory stimuli interpretation and processing.

The 10-5, 10-10 and 10 20 EEG systems

Biochemical exchanges between cells produce small electrical activity when the neurons communicate with each other. A single electric signal from neuron to neuron is not recordable, but when millions of neurons synchronize, the electric field generated can be measured from the scalp. This electrical activity of the brain (or electroencephalographic signals, EEG) is transmitted through tissue, bone, and hair before it is recorded, and by then its amplitude is very attenuated (Sörnmo & Laguna, 2005; Nunez & Srinivasan, 2006). 

In EEG, the location of the sensors is critical if we want our experiments to be reproducible, or want to compare our recordings with data recorded by different people. This is the reason why, in 1947, a committee was designated to create a standard that unified all the procedures for electroencephalogram EEG measurement. This committee devised the 10 20 system EEG as a way to position and label the EEG channels, and proposed a minimum of 21 electrodes to examine the adult brain (Jasper, 1958; Silverman, 1963). 

The international system for EEG placement takes four universal cranial landmarks (nasion, onion, and both pre-auricular points), and proportionally distributes the EEG electrodes over the head surface.  

A-C: Placement of the standard electrodes of the 10–20-system. Modified from: Seeck, M., Koessler, L., Bast, T., Leijten, F., Michel, C., Baumgartner, C., ... & Beniczky, S. (2017). The standardized EEG electrode array of the IFCN. Clinical Neurophysiology, 128(10), 2070-2077.

The EEG electrode placement follows the International system that labels them according to the areas of the cerebral cortex beneath. The labels refer to the lobe or area of the brain that is being recorded by each sensor:

• The main areas are fronto-polar (Fp), frontal (F), central (C), temporal (T), parietal (P), and occipital (O).
• Regarding their lateralized location, odd numbers (1,3,5,7) refer to electrodes placed on the left hemisphere, even numbers (2,4,6,8) refer to those on the right hemisphere.
• Electrodes over the midline (zero line) are labeled with the letter “z”.

Depending on the percentage of the distance between sensors, we have the 10-20 layout with a total of 21 sensors if we start from a distribution of 10% and 20% distances of the sagittal and coronal central reference curves. If these midlines are divided into 10%, then we have the 10-10 layout with 81 sensors, and, finally, if we add resolution with distances of the 5%, then, we have the 10-5 EEG system with 320 electrodes (Jurcak, Tsuzuki, & Dan, 2007).

With this standard of EEG scalp electrode locations, one can easily associate the EEG of a given sensor with different brain functions, depending on their location on the sensor layout. The illustration below represents the functions of the brain per area and its equivalent with the 10-20 electrode system. 

All EEG systems follow this standard, not only because the results can be compared with others in the research literature, but also because it is straightforward to describe, in a unified way, the brain area/function that we can access with each sensor (or headset).

EEG layouts with variable or fix electrodes placement

There are two types of systems:

1. Those that have a variable layout of sensors (sensors can be placed into different positions). 
2. Those with fixed layouts (the EEG electrode placement can not be changed).

1. EEG headset with variable layout

These systems allow for moving their interchangeable positions to accommodate different experiments. This usually happens in lab environments, where during exploratory research phases, where high head sensor coverage and flexibility are prioritized over other aspects like confort or ergonomics.  

These EEG systems are usually composed of a fabric EEG cap that covers the whole head with a chin strap, a sensor array, and an amplifier. The cap preserves the 10-10 or 10-20 system EEG with labeled housings along with its pattern where electrodes can be inserted. There are usually several sizes to better fit everyone.

2. EEG headset with fixed layout

The sensor locations on these systems are predefined. Electrodes are fixed and cannot be moved from one position to another. These systems are designed to measure specific mental processes and they just cover the required brain areas for the application.

Defining an optimized electrode layout allows for a lighter and less invasive headset design. The ease of use, comfort, and fast setup are the characteristics that make a fixed layout valuable for an experiment. These systems have a simplified design that allows for self-placement.

Pros and Cons of variable and fixed electrode placement

We summarize in this table below the pros and cons of the different approaches. We assume that the sensors that use Variable layouts rely on wet-EEG sensors and can have a large number of electrodes, and those that use fixed layouts are composed of a lower number of dry electrodes.

Pros and cons of variable and fix technologies.

How to select an EEG with variable or fixed electrode placement

Although EEG headsets with fixed layouts can be used to record EEG in almost any setup, the main purpose of these technologies is to address real-world environments or professional products or services. An easy way to fit both EEG with variable or fixed sensors in a general research pipeline is:

• Phase 1 - Exploratory research phase: use in-lab research-grade technologies (EEG headsets with variable sensor layouts and higher sampling rates) to understand human behavior in controlled situations. At this step, the priorities are to obtain EEG data with a large number of sensors, with high coverture of the brain, and with very high resolution and accuracy. 
• Phase 2 - Optimization of the application: use EEG signal processing techniques to understand where and how the neural correlates underlying the behavior can be measured.
• Phase 3 - Application-oriented phase: use out-of-lab research and application technologies (EEG headsets with fixed sensor layouts) to understand human behavior in natural scenarios. In this case, the priority is to have an easy-to-use and comfortable EEG recording technologies, with sensors only over the relevant brain areas (measuring only the brain activities we need to measure), with mobility and resistance to artifacts (to handle free movement).

Notice that there is a clear analogy of this research pipeline with the use of wet-EEG (wet electrodes that use saline or conductive gel) or dry-EEG headsets (no use of saline or conductive gels), see how to select a wet vs dry EEG). The main application focus of wet-based EEG (with variable layouts) is usually complementary to dry-EEG (with fixed layouts), as they are used in different stages of this research pipeline. 

Figure 8: This figure displays several examples of the implementation of these research phases.

Examples of projects with the two types of EEG systems

The examples below detail two real examples and how the selection of a variable or fixed layout EEG evolved along with the project stages:

1. EEG headsets with variable and fixed layouts to improve mobility in quadriplegics

The research European project MoreGrasp H2020 developed a brain-controlled motor neuroprosthesis to enable quadriplegics to carry out daily tasks, such as grasping a glass, improving their autonomy and quality of life. The objective is to decode grasping intention from the EEG patterns produced by the user’s motor cortex (mental states or mental commands), and then to activate those muscles that involve the intended movement by.personalized electrical currents (effective movement). The project was composed of two phases where Bitbrain developed two EEG headsets with different design requirements. 

In the first stage, participants with spinal cord injury completed a 4- to 8- week training phase to get familiarized with the technology. During this phase, the research team had to locate the least number of sensors needed to decode intention and the type of movement/grasping in a natural manner. Bitbrain developed the Versatile EEG, a wireless EEG headset with 32 channels and a flexible layout with wide coverage of the head.

Use of a brain-controlled motor neuroprosthesis during MoreGrasp project.

In the second stage of the project, Bitbrain developed Hero, a customized dry EEG headset that the participant received to be utilized daily at home. This time, the caregiver of the participant sets up the technology. 

Using Hero device for grasping movements.

At this point, the challenge was to turn a wide coverage lab EEG device into an intuitive, simple, and comfortable headset for daily use. The reduced number of sensors and their fixed positions gave the following key features:

• The fixed layout allowed a design that hides the cables inside covers, providing a more friendly-looking device for real-world applications, and getting away from the image of a laboratory technology. Also, it resulted in a simpler and intuitive product that could be set up by a caregiver.
• The sensors were located only over the motor cortex, which were the only required electrodes for this specific brain-computer interface application. With the face clear, this would make it easier for the participant to integrate the technology into daily life interactions and to accept the perception of less invasive technology.
• The optimized 12 sensors of the mobile EEG headset make the product lighter and therefore more comfortable.

2. EEG headsets with variable and fixed layouts for cognitive neurorehabilitation

Elevvo is a commercial brain-computer interface neurotechnology solution for improving working memory, processing speed, and sustained attention of the users (Escolano, 2019a). The rationale behind this technology is to use modern neurofeedback stimulation procedures to produce neuroplastic changes in brain areas that mediate in cognitive processes. It is mainly used for cognitive rehabilitation or maintenance. More than 100 participants have used it so far, improving in these cognitive capacities between 10 and 30%, depending on the target population (Escolano, 2019b).  

One important aspect of this technology is that it was developed with an EEG headset with an interchangeable sensor layout. Initially in the research phases, and later in the experimental studies, the objective was to understand whether this modern neurofeedback training produced the desired effects [Escolano, 2011; Escolano, 2014a; Navarro-Gil, 2018; Escolano, 2014b]

Use of a versatile device for Elevvo researches.

As a result of all the studies that were carried out, people saw clear improvements in cognitive capacities (with variability depending on the user and their brain capabilities). Once this concept was proven, the next step was to apply this technology to real world applications.

For example, The Sanitas project implemented Elevvo in retirement homes for the cognitive rehabilitation of elderly people. For that purpose, Bitbrain used Diadem, a wearable dry-EEG headset with 12 sensors over the brain areas used by Elevvo technology. The design of this product was the result of the following key determinants:

• Predefined and fixed layout allowed a lighter and more minimalistic headset design that was non-intrusive and more comfortable for the user. Sensor wires are integrated in a carefully designed case.
• The limited number of sensors in optimized locations made it possible to design a simple product with an easier and more intuitive use, enabling setup by a non-EEG expert, or even self-placement, with short setup times. 

Diadem from Bitbrain being used for the Sanitas project.

Conclusions

• If flexibility is required for your studies, then an EEG monitoring system with a variable layout should be the preferred option. They are very useful in exploratory research phases when a high head coverage and interchangeability are required characteristics. Otherwise, if you need your device for real-world applications, consider EEG technologies with fixed sensor layouts that are optimized for specific applications. 

Other important determinant factors are:

• Set up and placement time: usually preparation and placement time for fixed electrodes is much lower than for variable ones, since their positions are predefined and the operator does not need to place them. 

• Usability and design: due to an optimized and fixed electrode layout, these systems are lighter and more comfortable than variable EEGs. Their design is less invasive and more innovative, so they are more suitable in those situations where image and perception are important factors (integration of the user into the environment, marketing events, etc.) or when the person who will set up the system is not an EEG expert. 

About the Authors

• Alexandra Alda, Product Design Engineer at Bitbrain - Linkedin

Alexandra Alda obtained her degree in industrial design and product development engineering (2006) and a MSc in industrial management (2013) by the University of Zaragoza (Spain). After her 6 year of experience as a product designer in three design studios of Madrid and Zaragoza, from 2013 to the present she works as a product designer and the chief of the product design department for Bitbrain. Her main design expertise is in the field of design and development of biometrics recording devices mainly centered on wearable electroencephalogram products. Her interests are focused on ergonomics as well as user-centered design.

• Natalia Torreblanca, Product Design Engineer at Bitbrain - Linkedin

Natalia Torreblanca holds an Industrial Design and Product Development Engineer degree (2017) by the University of Zaragoza (Spain). Since then to date she works as a product designer focused in wearable EEG and biometrics hardware development with a multidisciplinary team. These projects usually include aspects like usability, ergonomics, 3D print prototyping or product manufacturing.

References

• Silverman, D. (1963). The Rationale and History of the 10-20 System of the International Federation. American Journal of EEG Technology, 3(1), 17–22. https://doi.org/10.1080/00029238.1963.11080602
• Jasper, H. H. (1958). The ten-twenty electrode system of the International Federation. Electroencephalogr. Clin. Neurophysiol., 10, 370-375.
• Jurcak, V., Tsuzuki, D., & Dan, I. (2007). 10/20, 10/10, and 10/5 systems revisited: their validity as relative head-surface-based positioning systems. Neuroimage, 34(4), 1600-1611.
• Escolano, C., Montesano, L. & Minguez, J. (2019a). On Modern Neurofeedback Solutions based on Brain-Computer Interfaces in Uncontrolled Real-World Settings. In IEEE International Conference on Systems, Man, and Cybernetics (SMC). Bari (Italy).
• Escolano, C., Montesano, L. & Minguez, J. (2019b). A  Business Proof-of-Concept of a Brain-Computer Interface for Cognitive Enhancement. In IEEE International Conference on Systems, Man, and Cybernetics (SMC). Bari (Italy).
• Escolano, C., Navarro-Gil, M., Garcia-Campayo, J., Congedo, M., De Ridder, D., & Minguez, J. (2014a). A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder. Frontiers in Behavioral Neuroscience, 8(296).
• Navarro-Gil, M., Escolano, C., Montero-Marín, J., Minguez, J., Shonin, E., & Garcia-Campayo, J. (2018). Efficacy of neurofeedback on the increase of mindfulness-related capacities in healthy individuals: a controlled trial. Mindfulness, 9, 303-311.
• Escolano, C., Aguilar, M., & Minguez, J. (2011). EEG-based upper alpha neurofeedback training improves working memory performance. In International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (p. 2327-2330). Boston (USA).
• Escolano, C., Navarro-Gil, M., Garcia-Campayo, J., Congedo, M., & Minguez, J. (2014b). The effects of individual upper alpha neurofeedback in ADHD: An open-label pilot study. Applied Psychophysiology and Biofeedback, 39(3-4), 193-202.

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