The Science



As we think and process information, our brain produces voltage fluctuations resulting from the ionic currents within billions of neuronal cells (1). These large-scale, synchronized voltage fluctuations are the electrical basis of thought, and are commonly referred to as brainwaves.

Brainwaves can be measured via electroencephalography (EEG), which quantifies the electrical activity on the surface of the scalp. EEG was discovered in 1924, and quickly became a prominent research and diagnostic tool that has been used to produce data for over five hundred thousand research publications (2,3).

EEG is a non-invasive and painless test because it is recorded by placing electrodes on your scalp. Just as a microphone passively captures pressure variations caused by sound, EEG electrodes passively capture brainwaves caused by thought.

Due to the large body of literature around EEG, and the fact that it is a direct measure of brain activity, it continues to be one of the most well-established assessments of brain function.


(Event-Related Potentials)

When our brains perceive specific sensory, cognitive, or motor events, they produce an electrophysiological response called an event-related potential (ERP) (4). ERPs are easily-identifiable and repeatable changes in your brainwaves following a perceived stimulus. ERPs have been extensively studied since 1964 to help us understand the physiological correlates of sensory, perceptual and cognitive activity associated with information processing (5,6).

ERPs have a number of components that allow researchers and clinicians to accurately assess your brain performance and health. One of the most well-studied components is called the P300, which is understood to reflect a higher cognitive response to salient stimuli.


We measure your P300 response as one of the indicators of your information processing capacity and neural processing speed (7).

Information Processing is the term neuroscientists use to describe your brain’s ability to process the information your senses collect about your environment, and refine it into a consciously meaningful experience of reality. Information processing is calculated from the amplitude of your P300 waveform.

Information processing is sensitive to cognitive fatigue, burnout, brain fog, cognitive impairment, mild cognitive impairment, dementia, concussion, mild traumatic brain injury, traumatic brain injury, post-traumatic stress disorder, and many other factors related to deficits in cognitive performance (12, 13, 14, 15, 16, 17, 18, 19). Therefore, understanding how your ability to process information is changing over time is one of the clearest benchmarks into your cognitive performance.

Peak human performance can also be measured by the P300 component of an ERP (20). As you improve your P300 amplitude and latency, you are able to tap into your smartest and best-performing self.

Neural processing speed is a measure of how quickly your brain is responding to stimuli and how fast it is able to process information. As we age, it is normal for our neural processing speed, measured by the P300 latency, to slow down. Neural processing is an important component of measuring brain performance as it is sensitive to a host of neurological deficits, such as concussion, mild traumatic brain injury, traumatic brain injury, mild cognitive impairment, and dementia (14, 15, 16).

For both information processing and neural processing speed, it is scientifically unknown what humans are biologically capable of in terms of their peak cognitive ability.


The Oddball task is used to elicit a visually-evoked, neural potential that is measurable via EEG. Our companion mobile application guides you through an Oddball task to provide you with frequent and infrequent visual stimuli in the form of coloured circles. Your EEG response to the circles is recorded, allowing us to calculate and identify the amplitude and latency of your P300 (cognitive performance and neural processing speed respectively) (8). Predecessors to this technology have been used in a NASA Mars Training mission (9).

Mobile EEG

Mobile EEG (mEEG) has blossomed within the last decade as recent technological advances in electronic devices allow us to capture your brainwaves accurately (10). Mobile EEG headsets have been shown to capture ERPs with accuracy comparable to instrumentation used in neuroscientific laboratories, and have led to novel advances in brain research (11,12).

The Circl headset captures your parietal brainwaves by measuring microvolt changes on your scalp at millisecond time intervals. Since the headset is so sensitive, it also requires sophisticated signal processing software to make sure your brainwaves are selectively identified, amplified, and recorded, while minimizing background electromagnetic noise from the electrified environment within your home or office.


  1. Niedermeyer E.; da Silva F.L. (2004). Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. Lippincott Williams & Wilkins. ISBN 978-0-7817-5126-1.
  2. Haas, L F (2003). "Hans Berger (1873-1941), Richard Caton (1842-1926), and electroencephalography". Journal of Neurology, Neurosurgery & Psychiatry. 74 (1): 9.
  3. As of June 2022, 522,000 research publications reference EEG.
  4. Luck SJ (2005). An Introduction to the Event-Related Potential Technique. The MIT Press. ISBN 978-0-262-12277-1.
  5. Walter WG, Cooper R, Aldridge VJ, Mccallum WC, Winter AL (July 1964). "Contingent Negative Variation: An Electric Sign of Sensori-Motor Association and Expectancy in the Human Brain". Nature. 203 (4943): 380–4. Bibcode:1964Natur.203..380W. doi:10.1038/203380a0. PMID 14197376. S2CID 26808780.
  6. Handy, T. C. (2005). Event Related Potentials: A Methods Handbook. Cambridge, Massachusetts: Bradford/MIT Press.
  7. McCormick B (2006). "Your Thoughts May Deceive You: The Constitutional Implications of Brain Fingerprinting Technology and How It May Be Used to Secure Our Skies". Law & Psychology Review. 30: 171–84.
  8. Polich, J. (2007). "Updating P300: An integrative theory of P3a and P3b". Clinical Neurophysiology. 118 (10): 2128–2148. doi:10.1016/j.clinph.2007.04.019. PMC 2715154. PMID 17573239.
  9. Brain Burnout.
  10. Lin CT, Ko LW, Chang CJ, Wang YT, Chung CH, Yang FS, et al. (2009). "Wearable and Wireless Brain-Computer Interface and Its Applications", Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, Lecture Notes in Computer Science, Springer Berlin Heidelberg, vol. 5638, pp. 741–748, doi:10.1007/978-3-642-02812-0_84, ISBN 978-3-642-02811-3, S2CID 14515754.
  11. Krigolson, O. E., Williams, C. C., Norton, A., Hassall, C. D., & Colino, F. L. (2017). Choosing MUSE: Validation of a low-cost, portable EEG system for ERP research. Frontiers in Neuroscience: Brain Imaging Methods, 109(11).
  12. Krigolson, O. E., Hammerstrom, M. R., Abimbola, W., Trska, R., Hecker, K.G., Wright, B. W., & Binsted, B. (2021). Using Muse: Rapid Mobile Assessment of Brain Performance. Frontiers in Neuroscience. 
  13. Luijtelaar, G. V., Verbraak, M., Bunt, M. V. D., Keijsers, G., & Arns, M. (2010). EEG findings in burnout patients. The Journal of neuropsychiatry and clinical neurosciences, 22(2), 208-217.
  14. Frodl, T., Hampel, H., Juckel, G., Bürger, K., Padberg, F., Engel, R. R., ... & Hegerl, U. (2002). Value of event-related P300 subcomponents in the clinical diagnosis of mild cognitive impairment and Alzheimer's Disease. Psychophysiology, 39(2), 175-181.
  15. Bonanni, L., Franciotti, R., Onofrj, V., Anzellotti, F., Mancino, E., Monaco, D., ... & Onofrj, M. (2010). Revisiting P300 cognitive studies for dementia diagnosis: early dementia with Lewy bodies (DLB) and Alzheimer disease (AD). Neurophysiologie Clinique/Clinical Neurophysiology, 40(5-6), 255-265.
  16. Lavoie, M. E., Dupuis, F., Johnston, K. M., Leclerc, S., & Lassonde, M. (2004). Visual p300 effects beyond symptoms in concussed college athletes. Journal of Clinical and Experimental Neuropsychology, 26(1), 55-73.
  17. Faruque Reza, M., Ikoma, K., Ito, T., Ogawa, T., & Mano, Y. (2007). N200 latency and P300 amplitude in depressed mood post-traumatic brain injury patients. Neuropsychological rehabilitation, 17(6), 723-734.
  18. Araki, T., Kasai, K., Yamasue, H., Kato, N., Kudo, N., Ohtani, T., ... & Iwanami, A. (2005). Association between lower P300 amplitude and smaller anterior cingulate cortex volume in patients with posttraumatic stress disorder: a study of victims of Tokyo subway sarin attack. Neuroimage, 25(1), 43-50.
  19. Wang, H., Chang, W., & Zhang, C. (2016). Functional brain network and multichannel analysis for the P300-based brain computer interface system of lying detection. Expert Systems with Applications, 53, 117-128.
  20. Park, J. L., Fairweather, M. M., & Donaldson, D. I. (2015). Making the case for mobile cognition: EEG and sports performance. Neuroscience & Biobehavioral Reviews, 52, 117-130.