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Mind Control in the Name of Medicine?

We’ve all encountered the theme of mind reading and mind control in sci-fi novels and films. But with technological progress skyrocketing over the past decade, could these far-fetched, dystopian scenarios become our new reality? Scientists have already created systems that control brain waves and neurotransmitters to communicate with paralyzed patients, restore limb function, and even reduce depressive symptoms. However, new devices are currently being developed at an unimaginable speed and focus on overall human enhancement, such as IQ boosts, that extend beyond the therapeutic benefits of brain manipulation. While such a reality may sound appealing in theory, relinquishing human autonomy to artificial intelligence comes with a plethora of ethical concerns.

One revolutionary advancement that scientists have already developed includes brain-computer interface (BCI) technology, which is important for reading and translating brain wave signals to restore or replace functions of people with neuromuscular disorders. Scientists have been able to build sophisticated AI algorithms to translate information directly from brain activity into computer-generated speech. In one study conducted by Angrick et al. (2019), researchers used electrocorticography, a method of measuring brain waves by placing electrodes directly on the surface of the brain, to create neural recordings [1]. These recordings supplied the necessary information to decode the process of speech production in the individual to eventually reconstruct the intended speech audio. Such research aims to create new speech functions for those suffering from conditions like amyotrophic lateral sclerosis (ALS) and strokes. Other applications of BCI technology have involved utilizing brain signals to control cursors, robotic arms, prostheses, wheelchairs, and other devices [2]. Hong et al. (2020) successfully trained amputees and paralyzed individuals to use thought and visualization to control the movements of their prosthetic arms [3]. Studies like this showcase the ability to read and translate brain waves into commands for devices that facilitate human function.

While BCIs have led to substantial progress in the medical field, an important question remains: where do we draw the line when it comes to neural data collection? In one study by Haynes et al. (2007), when participants were asked to choose between two sets of tasks, decoding activity from the prefrontal cortex predicted their choices with a 71% accuracy rate [4]. Human thoughts and intentions become more accessible with the advancement of brain-reading technologies, and as a result, privacy concerns and the fear of non-consensual manipulation are on the rise.

Beyond simply reading and recording neural signals, could tools like BCIs actually be used to control experiences in the brain and human behavior at large? Scientists are exploring a number of new technologies and techniques to help patients control their brain waves and nerve cells to treat a variety of behavioral issues and mental illnesses. One such technique is the use of neurofeedback to retrain brain wave patterns as a treatment for sleep disorders and behavioral conditions like ADHD [5]. In one study, Lim et al. (2019) investigated the effectiveness of a BCI-based attention training program in helping patients identify and control ADHD-associated brain wave patterns [6]. The researchers collected EEG data to monitor the brain waves of participants as they played a computer game, and the speed of the game’s avatar would increase in response to the detection of waves associated with high attention levels. Through such positive reinforcement, participants successfully learned to identify and control their attention levels, and their ADHD symptoms were reported to have improved [6]. Moving beyond the use of reward-based reinforcement, another non-invasive technique known as transcranial magnetic stimulation (TMS) has been used to control the experience of emotions by releasing powerful pulses of electromagnetic radiation through a person's skull to directly excite particular brain circuits [7]. This technique can treat brain-related conditions like depression and obsessive-compulsive disorder. Along similar lines, yet another new tool called Opto-vTrap was recently developed to control the mind through the use of infrared radiation [8]. By using a single light source, researchers were able to control the release of neurotransmitters, allowing them to manipulate emotion and behavior at a chemical level. The technique successfully reduced fear memories in mice, and researchers believe that future applications could also aid in epilepsy treatment, muscle spasm treatment, and skin tissue expansion technologies [8].

Although new methods and devices designed to restore function for those that are disabled seem beneficial, they walk a fine line between therapeutics and enhancement. For example, a device known as Neuralink, which is an implantable brain chip currently being developed by Elon Musk, aims to counter the effects of neurological diseases like Parkinson’s disease and restore mobility to people with spinal cord injuries [9]. However, another major goal of Neuralink is to enhance human performance in terms of game experiences, telepathy, cognitive abilities, and symbiosis with artificial intelligence [10]. The neuronal activity collected by devices like Neuralink is the same activity that encodes our personalities, emotions, memories, decisions, actions, and the entire individual human experience. By surrendering this data to a separate entity, we run the risk of sacrificing human autonomy and simplifying our existence into pieces of recordable data that can be manipulated for profit-seeking purposes.

Could controlling social behavior with such devices help us achieve an ideal world and strengthen human potential, or would such a phenomenon create a dystopian future built upon an imbalance of power and unequal access to critical human data? How would we decipher between true human experience and neurologically manipulated thoughts and emotions? What types of “enhancement” would be prioritized, and who would ensure the ethical use of BCIs? Could these technologies actually be used to produce harmful effects on human behavior? While these questions enter speculative territory, it is critical to consider the future impacts of developing devices that read and control human behavior.


  1. Angrick, Herff, C., Mugler, E., Tate, M. C., Slutzky, M. W., Krusiensk, D. J., & Schultz, T. (2019). Speech synthesis from ECoG using densely connected 3D convolutional neural networks. Journal of Neural Engineering, 16(3).

  2. Shih, J. J., Krusienski, D. J., & Wolpaw, J. R. (2012). Brain-computer interfaces in medicine. Mayo Clinic proceedings, 87(3), 268–279.

  3. Hong L. Z., Zourmand, A., Patricks, J. V., & Thing G. T. (2020). EEG-based brain wave controlled intelligent prosthetic arm. IEEE, 52-57.

  4. Haynes, J. D., Sakai, K., Rees, G., Gilbert, S., Frith, C., & Passingham, R. E. (2007). Reading hidden intentions in the human brain. Current biology, 17(4), 323–328.

  5. Fischer, K. (2022). What is a brain-computer interface in medicine? WebMD.

  6. Lim, C. G, Poh, X. W. W., Fung, S. S. D, Guan, C., Bautista, D., Cheung, Y. B., Zhang, H., Yeo, S. N., Krishnan, R., & Lee T. S. (2019). A randomized controlled trial of a brain-computer interface based attention training program for ADHD. PLoS ONE, 14(5).

  7. Rizvi, S., & Khan, A. M. (2019). Use of transcranial magnetic stimulation for depression. Cureus, 11(5), e4736.

  8. Won, J., Pankratov, Y., Jang, M. W., Kim, S., Ju Y. H., Lee, S., Lee, S. E., Kim, A., Park, S., Lee, C. K., & Heo, W. D. (2022). Opto-vTrap, an optogenetic trap for reversible inhibition of vesicular release, synaptic transmission, and behavior, Neuron, 110(3), 423-435.

  9. Maynard, A. (2020). The ethics of Advanced Brain Machine Interfaces -- and why they matter. College of Global Futures.

  10. Maynard, A. D., & Scragg, M. (2019). The ethical and responsible development and application of advanced brain machine interfaces. Journal of medical Internet research, 21(10), e16321.

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