Our Technology

BrainQ’s device uses non-invasive, frequency-tuned extremely low frequency and low intensity electromagnetic fields (ELF-EMF) with the aim of promoting neurological recovery in the central nervous system (CNS). The artificial intelligence (AI)-powered device tailors the electromagnetic field characteristics to suit each patient. 

Read more to learn why we’re using EMF, the scientific basis behind it, and how AI is applied to optimize its potential. 

What are neural networks?

The brain is organized into neural networks1 which behave in synchrony when performing specific functions, creating measurable neural oscillations, or brain waves, in regular patterns2. These patterns can be detected and measured using electrophysiology tools (e.g., EEG, EMG, MEG). Scientists can now study these patterns and begin to distinguish specific neural networks3–5 and functions. In the case of stroke, or other trauma/disease states, damage to neural networks interferes with neural activity and connectivity6–9, resulting in disability such as impaired motor function. A successful treatment needs to both target a particular network as well as deliver the patterns and frequencies of EMF needed to facilitate its recovery.

An example of an electromagnetic field induced by electric current in a coil

Why we're using EMFs to target neural networks 

BrainQ utilizes electrophysiology measurements (EEG, EMG, MEG) to characterize neural oscillatory activity. A growing body of evidence indicates that neural oscillations at specific frequencies are linked to opening neuroplasticity periods10,11, suggesting that using non-invasive brain stimulation (NIBS) techniques to neuromodulate at specific frequencies can influence these oscillations and aid in neurorecovery12–14. These fields have long been studied for their role in disease and recovery, and are similar in both magnitude and frequency to magnetic fields generated about a neuron by the current flows associated with a firing axon16. While humans cannot feel EMF on a sensory level, these fields may have a role in mediating healthy neural dynamics and coordination, which are dependent on synchronous cell firing, and may be mimicked by exogenous exposure to such similar fields.

In the case of stroke, as well as other neurological disorders, the oscillatory patterns of unhealthy or impaired individuals are measurably different from those of healthy individuals. With evidence that exposure to specific EMFs can influence neural oscillations15, BrainQ operates on the premise that exposing such unhealthy individuals to specific EMF frequencies associated with healthy functioning may improve network plasticity and functional ability. Thus, BrainQ is developing a treatment to target specific networks in the CNS, utilizing an extremely-low-frequency and low intensity electromagnetic field (ELF-EMF) treatment tuned to specific frequencies, with the goal of repairing damaged neural networks. The diffuse nature of these fields allows for the exposure of the entire CNS and its neural networks. This is an advantage over other forms of NIBS, which typically focus on specific brain regions or segments of the nervous system, and neglect the larger network. BrainQ aims at providing a comprehensive, frequency-tuned treatment to entire networks.

The effect of EMFs on neuroplasticity

Treatments for neurological disorders seek to promote and support recovery processes17–19. A number of effects in physiological, behavioral, and functional outcomes have been identified in tissues and organisms exposed to EMF, and these changes are implicated as the mechanisms which likely underlie the observed recovery from BrainQ’s investigational treatment.A number of mechanisms distinguish themselves as candidates which are likely to be causal in mediating the beneficial effects of the field. There is experimental evidence supporting the effect of ELF-EMF on processes specific to recovery from neurological conditions. There is evidence of:

  • Changes in calcium signaling, which is known to influence and mediate nearly all cellular processes20,21.
  • Proliferation, as well as differentiation, of multiple cell types (including neurogenesis of neural stem cells)22–24.
  • Peripheral nerve regeneration25.
  •  Effects on polar molecules26,27, likely responsible for the development of the neural projections.
  • Changes in plasticity-related growth factor levels in humans.  
All of the above have been shown to be affected by ELF-EMF exposure28,29.
 
Beyond plasticity-related mechanisms mediated by ELF-EMF exposure, beneficial effects have been observed in a wide variety of phenomena; such as modulation of oxidative stress30–32, effects on the inflammatory process33–35, and reduction of apoptosis. These mechanisms are very much related to the secondary injury cascade, which is responsible for a chronic and persistent state of neurological injury and neurodegeneration beyond the acute primary injury (i.e., stroke or other trauma/disease state). The modulation of these shared mechanisms of neurotrauma are likely involved in a reduction of overall disability and dependence36,37.
 

An illustration of neuroplasticity

Our data science approach

The novelty of BrainQ’s investigational treatment lies in the data-driven method we have deployed in order to inform the ELF-EMF frequency parameters. In choosing these parameters, our aim is to select frequencies that characterize motor related neural networks in the CNS, and are related to the disability a person experiences following a stroke or other neurological trauma. To achieve this, we have analyzed a large-scale amount of healthy and non-healthy individuals’ brainwaves (electrophysiology data). Our technology uses explanatory machine learning algorithms to observe the natural spectral characteristics and derive unique therapeutic insights. These are used by BrainQ’s technology to target the recovery of impaired networks. 

Our clinical work

Currently, BrainQ is engaged in clinical trials in partnership with leading research centers worldwide in sub-acute ischemic stroke and spinal cord injury to continue to investigate the safety and efficacy of our therapy.
 
For more information, please visit clinicaltrials.gov
 

Footnotes

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2.      van Drongelen, W. et al. Oscillation in a network model of neocortex. in ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning 425–430 (2009).

3.      Schirrmeister, R. T. et al. Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. Hum. Brain Mapp. 38, 5391–5420 (2017).

4.      Betzel, R. F. et al. Synchronization dynamics and evidence for a repertoire of network states in resting EEG. Front. Comput. Neurosci. (2012). doi:10.3389/fncom.2012.00074

5.      Yu, M. et al. Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer’s disease: An EEG study. Neurobiol. Aging 42, 150–162 (2016).

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11.    Iaccarino, H. F. et al. Gamma frequency entrainment attenuates amyloid load and modifies microglia Hannah. 540, 230–235 (2016).

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21.    Ben Yakir-Blumkin, M., Loboda, Y., Schächter, L. & Finberg, J. P. M. Neuroprotective effect of weak static magnetic fields in primary neuronal cultures. Neuroscience 278, 313–326 (2014).

22.    Cuccurazzu, B. et al. Exposure to extremely low-frequency (50Hz) electromagnetic fields enhances adult hippocampal neurogenesis in C57BL/6 mice. Exp. Neurol. 226, 173–182 (2010).

23.    Komaki, A., Khalili, A., Salehi, I., Shahidi, S. & Sarihi, A. Effects of exposure to an extremely low frequency electromagnetic field on hippocampal long-term potentiation in rat. Brain Res. 1564, 1–8 (2014).

24.    Gaetani, R. et al. Differentiation of human adult cardiac stem cells exposed to extremely low-frequency electromagnetic fields. Cardiovasc. Res. 82, 411–420 (2009).

25.    Hei, W. H. et al. Effects of electromagnetic field (PEMF) exposure at different frequency and duration on the peripheral nerve regeneration: in vitro and in vivo study. Int. J. Neurosci. 126, 739–748 (2016).

26.    Wu, X. et al. Weak power frequency magnetic fields induce microtubule cytoskeleton reorganization depending on the epidermal growth factor receptor and the calcium related signaling. PLoS One 13, 1–27 (2018).

27.    Gholami, D., Riazi, G., Fathi, R., Sharafi, M. & Shahverdi, A. Comparison of polymerization and structural behavior of microtubules in rat brain and sperm affected by the extremely low-frequency electromagnetic field. BMC Mol. Cell Biol. 20, 1–11 (2019).

28.    Longo, F. M. et al. Electromagnetic fields influence NGF activity and levels following sciatic nerve transection. J. Neurosci. Res. 55, 230–237 (1999).

29.    Cichoń, N. et al. Increase in blood levels of growth factors involved in the neuroplasticity process by using an extremely low frequency electromagnetic field in post-stroke patients. Front. Aging Neurosci. 10, 1–11 (2018).

30.    Ladak, A. A., Enam, S. A. & Ibrahim, M. T. A Review of the Molecular Mechanisms of Traumatic Brain Injury. World Neurosurg. 131, 126–132 (2019).

31.    Elhalel, G., Price, C., Fixler, D. & Shainberg, A. Cardioprotection from stress conditions by weak magnetic fields in the Schumann Resonance band. Sci. Rep. 9, (2019).

32.    Selvam, R. et al. Low frequency and low intensity pulsed electromagnetic field exerts its antiinflammatory effect through restoration of plasma membrane calcium ATPase activity. Life Sci. 80, 2403–2410 (2007).

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35.    Vianale, G. et al. Extremely low frequency electromagnetic field enhances human keratinocyte cell growth and decreases proinflammatory chemokine production. Br. J. Dermatol. 158, 1189–1196 (2008).

36.    Park, E., Velumian, A. A. & Fehlings, M. G. The role of excitotoxicity in secondary mechanisms of spinal cord injury: A review with an emphasis on the implications for white matter degeneration. J. Neurotrauma 21, 754–774 (2004).

37.    Liu, N. K. & Xu, X. M. Neuroprotection and its molecular mechanism following spinal cord injury. Neural Regen. Res. 7, 2051–2062 (2012).

38.    Whissell, P. & Persinger, M. Emerging Synergisms Between Drugs and Physiologically-Patterned Weak Magnetic Fields: Implications for Neuropharmacology and the Human Population in the Twenty-First Century. Curr. Neuropharmacol. 5, 278–288 (2007).

39.    Musienko, P., van den Brand, R., Maerzendorfer, O., Larmagnac, A. & Courtine, G. Combinatory Electrical and Pharmacological Neuroprosthetic Interfaces to Regain Motor Function After Spinal Cord Injury. IEEE Trans. Biomed. Eng. 56, 2707–2711 (2009).

40.    Kostoff, R. N. & Lau, C. G. Y. Combined biological and health effects of electromagnetic fields and other agents in the published literature. Technol. Forecast. Soc. Change  80, 1331–1349 (2013).

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