EEG Electrode Placement Options

EEG Electrode Placement Options

10 Min.
By The Bitbrain team
March 26, 2024

The market for neurotechnology devices is expanding, offering a plethora of new tools. However, selecting the appropriate EEG headset poses a challenge. Among the numerous features influencing this decision, the EEG montage or sensor layout stands out as crucial.

While some devices offer customizable layouts, providing flexibility for various research purposes, they often sacrifice ease of use. In contrast, fixed layouts offer simplicity but lack flexibility. Here, we delve into the pros and cons of each version.

Brain areas and function

The outer layer of the brain is known as the cerebral cortex, where numerous vital functions of the nervous system are performed. This cortex is divided into four lobes: the frontal lobe, parietal lobe, temporal lobe, and occipital lobe. Each lobe has further subdivisions and is linked to specific cerebral functions.

Brain Areas

These are the different parts 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 result in small electrical activity when neurons communicate with each other. While a single electric signal from neuron to neuron is too small to record, when millions of neurons synchronize, the generated electric field becomes measurable from the scalp. This electrical activity, known as electroencephalographic signals (EEG), traverses through tissue, bone, and hair before being recorded, resulting in significantly attenuated amplitude (Sörnmo & Laguna, 2005; Nunez & Srinivasan, 2006). 

EEG lead placement is crucial for ensuring reproducibility of experiments and facilitating comparison with recordings from different individuals. To address this, a committee was formed in 1947 to establish a standard that would unify EEG measurement procedures. This committee developed the EEG 10 20 system, which specifies the positioning and labeling of EEG channels and recommends a minimum of 21 electrodes for examining the adult brain (Jasper, 1958; Silverman, 1963).

The international system for EEG placement utilizes 4 universal cranial landmarks (nasion, inion, and both pre-auricular points) and proportionally distributes EEG electrodes across the surface of the head.

10 20 Eeg System

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 layout 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 eeg electrode placement.

The placement of EEG electrodes follows the International system, which labels them based on the areas of the cerebral cortex they cover. These labels correspond to the lobe or specific area of the brain being recorded: 

  • 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”.

This standardization allows for the association of EEG sensor locations with different brain functions, depending on their position within the sensor layout. The illustration below depicts the functions of various brain areas and their corresponding locations within the 10 20 EEG system.

Eeg Electrode Placement on Scalp

EEG montages are configurations of electrodes placed on the scalp. The selection and placement of electrodes depend on the research or clinical objectives. Common montages include:

  • Bipolar Montage: In this montage, adjacent electrodes are paired to measure the voltage difference between them. Bipolar montages are useful for detecting localized abnormalities or focusing on specific brain regions.
  • Referential Montage: In this configuration, one electrode serves as the reference while other electrodes measure the voltage relative to it. Referential montages are useful for capturing global brain activity patterns.
  • Laplacian Montage: Laplacian montages involve deriving scalp potentials using a weighted average of nearby electrodes. This montage emphasizes localized activity while reducing the influence of distant sources.

Customizable vs or fixed EEG placement

There are two types of EEG layouts:

  1. Customizable placement of EEG electrodes.
  2. Fixed placement of EEG electrodes.

Versatile EEG, Diadem EEG and Neuroheadset EEG

The sensor locations in systems like the 10-20, 10-10, or 10-5 are predetermined and fixed, meaning electrodes cannot be relocated. While EEG research traditionally adheres to these standardized systems, the trend in EEG applications, particularly in neurotechnology, is toward designing devices tailored to specific applications. These customized devices are designed to cover only the necessary brain areas relevant to the application, offering greater efficiency and precision for targeted use-case.

Bitbrain EEG Headset

Systems featuring customizable layouts enable interchangeable positions to adapt to various experiments. This flexibility is particularly beneficial in lab environments, especially during exploratory research phases. In these settings, prioritizing high head sensor coverage and flexibility over factors such as comfort or ergonomics allows researchers to conduct experiments with greater precision and versatility.

Versatile EEG Cap

Pros/Cons of customizable vs fixed montages

Here we outline the Pro y Cons of general customizable and fixed EEG montages.

Fixed Montages Pros:

  1. Ease of Use: Fixed montages are typically easier to set up and use since the electrode positions are predefined and standardized.
  2. Consistency: With fixed montages, electrode placement remains consistent across sessions, ensuring reproducibility of results and comparability between different recordings.
  3. Widely Accepted: Standard fixed montages, such as those based on the International 10-20 system, are widely accepted and commonly used in clinical and research settings.
  4. Suitable for Routine Applications: Fixed montages are well-suited for routine EEG recordings where consistency and simplicity are prioritized.

Fixed Montages Cons:

  1. Limited Flexibility: Fixed montages offer limited flexibility in electrode placement and configuration, which may be restrictive for certain research or clinical applications targeting specific brain regions.
  2. Not Customizable: The positions and number of electrodes in fixed montages cannot be easily modified or customized to accommodate different experimental designs or research objectives.

Customizable Montages Pros:

  1. Flexibility: Customizable montages offer flexibility in electrode placement and configuration, allowing researchers or clinicians to tailor the setup to specific research questions or clinical needs.
  2. Adaptability: Customizable montages can be adjusted or modified to target specific brain regions or features of interest, enhancing the sensitivity and specificity of EEG recordings.
  3. Suitable for Specialized Applications: Customizable montages are well-suited for specialized research studies or clinical assessments that require precise electrode positioning or targeting of specific brain networks.
  4. Versatility: With customizable montages, users have the freedom to experiment with different electrode layouts and configurations to optimize signal quality and experimental outcomes.

Customizable Montages Cons:

  1. Complexity: Customizable montages may be more complex to set up and use compared to fixed montages, requiring additional time and expertise to configure the electrode layout properly.
  2. Learning Curve: Users may need training or expertise in EEG electrode placement and configuration to effectively utilize customizable montages.
  3. Potential for Error: The flexibility of customizable montages increases the risk of error in electrode placement or configuration, which could affect the quality and validity of EEG recordings.
  4. Cost: Customizable EEG systems may be more expensive than fixed systems due to their advanced features and capabilities.

In summary, the choice between fixed and customizable EEG layouts depends on the specific requirements of the research or application, balancing factors such as ease of use, flexibility, and precision in EEG electrode placement. Researchers or practitioners should carefully consider these factors when selecting an EEG headset to ensure it meets their needs effectively.

Bitbrain customizable vs fixed montages

We summarize in this table below the pros and cons of the different approaches. We assume that the sensors that use customizable layouts rely on Bitbrain Versatile EEG (semi-dry EEG) family, while the fixed layouts on the Bitbrain Minimal EEG (dry-EEG) family.

Eeg Electrode Placement Comparision

How to select an EEG with customizable or fixed sensor layout?

The use of EEG headsets with fixed or variable sensor layouts can be effectively integrated into a general research pipeline as follows:

  • Phase 1 - Exploratory Research Phase: During this phase, researchers employ in-lab research-grade technologies, such as EEG headsets with customizable sensor layouts and higher sampling rates. The primary objective here is to gain insights into human behavior in controlled environments. Therefore, priorities include obtaining EEG data with a large number of sensors, comprehensive coverage of the brain, and high resolution and accuracy.
  • Phase 2 - Optimization of the Application: In this phase, EEG artificial intelligence and signal processing techniques are applied to understand where and how the neural correlates underlying behavior can be measured. Researchers analyze the data collected in the exploratory phase to identify relevant brain regions and activity patterns.
  • Phase 3 - Application-Oriented Phase: During this phase, researchers transition to using out-of-lab research and application technologies, which may include EEG headsets with fixed sensor layouts. The focus shifts to understanding human behavior in natural settings. Here, the priority is to use easy-to-use and comfortable EEG recording technologies with sensors placed only over the relevant brain areas. These systems should offer mobility and resistance to artifacts to handle free movement effectively.

It's worth noting that this research pipeline has a clear analogy with the use of wet-EEG (wet electrodes that use saline or conductive gel) or dry-EEG headsets (without the need for saline or conductive gels), see tips for selection here. Wet-based EEG systems with variable layouts are typically complementary to dry-EEG systems with fixed layouts, as they serve different stages of the research pipeline.

How to Select A Eeg Headset

From Customizable to Fixed montages in neurotechnology

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

Project 1: Motor neurorehabilitation

The European research project MoreGrasp H2020 aimed to develop a brain-controlled motor neuroprosthesis to assist quadriplegics in performing daily tasks like grasping a glass, thereby enhancing their autonomy and quality of life. The project's objective was to decode grasping intention from EEG patterns generated by the user's motor cortex (mental states or commands), and then activate the relevant muscles using personalized electrical currents to achieve effective movement. The project comprised two phases, during which Bitbrain developed two EEG headsets with different design specifications.

  • Phases 1 and 2: In the initial phase, participants with spinal cord injuries underwent a 4- to 8-week training period to familiarize themselves with the technology. During this phase, the research team aimed to identify the minimum number of sensors required to decode intention and the type of movement/grasping in a natural manner. Bitbrain developed the Versatile EEG, a wireless EEG headset featuring 32 channels and a flexible layout with extensive coverage of the head.

  • Phase 3: 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. 

Dry Eeg Headset for Motor Rehabilitation

During Phase 3, the challenge was to transform a lab-based EEG device with extensive coverage into an intuitive, user-friendly, and comfortable headset suitable for daily use. The reduction in the number of sensors and their fixed positions led to several key features:

  1. Hidden Cables and Leads: The fixed layout enabled the design to conceal the cables and EEG leads inside covers, resulting in a more aesthetically pleasing device suitable for real-world applications. This departure from the typical appearance of laboratory technology contributed to a simpler and more intuitive product setup, making it easier for caregivers to use.
  2. Focused Sensor Placement: Sensors were positioned exclusively over the motor cortex, the only required electrodes for the specific brain-computer interface application. By leaving the face clear, this approach facilitated easier integration of the technology into daily interactions and increased acceptance of the perceived less invasive nature of the device.
  3. Optimized Weight: The optimized 12-sensor configuration of the mobile EEG headset reduced its weight, enhancing comfort during prolonged use. This lighter design contributed to a more comfortable user experience, further encouraging daily adoption of the device.

Project 2. Cognitive neurorehabilitation

Elevvo is a commercial brain-computer interface (BCI) neurotechnology solution designed to enhance working memory, processing speed, and sustained attention of users (Escolano, 2019a). The underlying concept of this technology involves utilizing modern neurofeedback stimulation techniques to induce neuroplastic changes in brain areas associated with cognitive processes. Elevvo is primarily utilized for cognitive rehabilitation purposes. Over 100 participants have undergone its use, experiencing improvements in cognitive capacities ranging between 10% and 30%, depending on the target population (Escolano, 2019b).  

An essential feature of this technology is its development with an EEG headset featuring an interchangeable sensor layout. Initially deployed during research phases and later in experimental studies, the objective was to ascertain whether this modern neurofeedback training effectively produced the desired cognitive effects (Escolano, 2011; Escolano, 2014a; Navarro-Gil, 2018; Escolano, 2014b).

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 instance, the Sanitas project integrated Elevvo into retirement homes to aid in the cognitive rehabilitation of elderly individuals. Bitbrain utilized Diadem, a wearable dry-EEG headset featuring 12 sensors strategically positioned over the brain areas targeted by Elevvo technology. The design of this product was influenced by the following key factors:

  • Predefined and Fixed Layout: The headset's layout was predetermined and fixed, resulting in a lighter and more minimalist design. This design approach ensured that the headset was non-intrusive and comfortable for the user. Additionally, the integration of sensor wires into a carefully designed case enhanced the overall aesthetics and usability of the device.
  • Optimized Sensor Placement: With a limited number of sensors strategically located, the design of the product was simplified. This simplicity facilitated EEG setup and more intuitive use, enabling setup by individuals with limited EEG expertise or even self-placement. The streamlined design also contributed to shorter setup times, enhancing the user experience.

Eeg Headset Cognitive Enhancement


If your studies require flexibility, an EEG monitoring system with a customizable layout would be preferable. These systems are particularly useful during exploratory research phases when high head coverage and interchangeability are necessary. However, for real-world applications, EEG technologies with fixed sensor layouts optimized for specific purposes should be considered.

Other important determinant factors are:

  1. Set Up and Placement Time: Fixed electrode systems typically have shorter preparation and placement times compared to customizable ones. This is because the positions of fixed electrodes are predefined, eliminating the need for manual placement by the operator.
  2. Usability and Design: Fixed electrode systems are lighter and more comfortable due to their optimized and fixed layout. They are less invasive and offer a more innovative design, making them suitable for situations where image and perception are crucial factors (e.g., integration into the environment, marketing events). Additionally, fixed electrode systems are easier to set up, even for individuals who are not EEG experts.

About Bitbrain solutions

Bitbrain specializes in developing innovative devices with excellent usability for multimodal monitoring, encompassing semi-dry EEG, dry-EEG, and textile-EEG systems, as well as biosignals (ExG, GSR, RESP, TEMP, IMUs, etc.), and eye-tracking solutions (screen-based and mobile platforms).

The software tools facilitate the design of experiments, effortless data gathering with over 35 synchronized sensor types, and extensive data analysis covering a broad spectrum of emotional and cognitive biometrics.

Bitbrain's platforms offer interconnectivity with other systems through LSL, ePrime, Matlab, or Python, providing flexibility and compatibility for diverse research and application needs.

Our systems are used by scientists in high-impact and peer-reviewed publications in a wide range of research applications, including neuroscience, psychology, education, human factors, market research and neuromarketing, and brain-computer interfacing


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  • 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).
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