A Comprehensive Treatment of Brain Disorders with Neurotechnology
An analysis of novel tech that poises to change the way we view and treat mental health conditions and brain disorders
By: Twinkle Bansal
Edited by: Jack Thomson and Anirudh Murugesan
In a merging of the fields of neuroscience, clinical psychology, and computer science, novel research proposes new ways to utilize our current knowledge of neurological pathways to treat serious mental health and brain conditions. The computational modeling and understanding of the human brain through neuroimaging and other novel neurotechnology are consistently being proven to improve the diagnosis and treatment of brain disorders. This article will dive into the efficacy and development of a number of these treatments, as well as how they are poised to change society and modern medicine.
The Severity of Brain Disorders in Modern Society
According to Dr. Pedro A Valdes-Sosa from the National Center for Scientific Research, brain disorders such as anxiety, schizophrenia, depression, OCD, ADHD, various addictions, and cognitive issues account for “more than 34% of the global burden of disease, crippling developing nations’ ‘mental capital’”. The concept of mental capital describes the effects that brain disorders play on a nation’s development, economy, and disability-adjusted life years. Additionally, brain diseases cost the United States 1.4 trillion annually, and while current treatments prove helpful to some, millions more are left to suffer without sufficient help (World Economic Forum). Some of the largest roadblocks involving treating mental health and brain disorders are that treatment is often administered long after the onset of disease, such as when Alzheimer’s has already caused irreversible damage to the brain, or that current treatments involve prescriptions of drugs with many harmful side effects. However, this is starting to change as organizations across the world and clinical trials show a strong efficacy for clinical applications of early detection methods such as neuroimaging, and precise treatments that target the underlying mechanisms responsible for brain disorders.
Traditional Methods vs Newer Approaches
A common traditional method of assessing and treating many mental health and brain disorders is referred to as ‘functional assessment,’ which analyzes the behavior of a patient and devises a potential treatment plan. This plan usually consists of a prescription of medications that alter brain chemistry and physiology, along with some form of therapy to track progress and update the treatment (White). Functional assessment does indeed help a number of patients who struggle with mental ilness, especially in understanding the causes of problematic behavior and changing the environmental factors that lead to that behavior, but it also presents several limitations. Oftentimes clinicians are not able to identify phenomena that are not readily observable, such as having to actively interpret some perceived emotion, or the client may alter their behavior intentionally in the presence of a clinician, which reflects inconsistent behavioral responsivity and test validity (White). These difficulties can be alleviated by the rise in novel neurotechnology, which uses a more objective framework for diagnosis and treatment than functional assessment.
In addition, older ideas of a chemical imbalance being the main causal factor of brain disorders and mental illnesses are being revamped by newer data on the specific neural pathways involved in disorders such as depression and schizophrenia. If we approach mental disorders as circuit disorders and understand how to restimulate different pathways or identify precise biomarkers involved, we create the opportunity for precision neurotherapies that are far more effective than current functional assessment methods. This is explained by the fact that certain neural pathways and circuits are strengthened with use while others degenerate over time (a phenomenon called neuroplasticity), so those who struggle with brain disorders often suffer from an undesired level of stimulation on specific brain networks. Some therapies can both assess and treat neurological disorders, such as real-time f-MRI, which images the current cognitive and psychiatric state, enables brain-computer interface capabilities, and can be used in assisting neurofeedback-based therapies (White). Thus, applications with targeted stimulation can help us identify the regions needing treatment, and subsequently facilitate the brain’s ability to repair itself.
Treating Depression with DBS
For example, deep brain stimulation (DBS) is a form of neurotechnology that has proven to be extremely beneficial to those with treatment-resistant depression. Originally developed to treat motor symptoms in those with movement disorders such as Parkinson’s disease, DBS consists of small electrodes surgically implanted inside the brain and connected to a neurostimulator, which can be used to generate electrical signals to target the intended regions of the brain (Deck). This miniaturized brain pacemaker has not only been shown to stop tremors in patients with Parkinson’s disease but has used targeted stimulation to revamp the neural networks that, through brain mapping technologies, are associated with major depressive disorder. DBS has helped an astonishing 90% of patients in clinical trials for whom therapy and medication have not proven beneficial (Sullivan). Further research shows promising applications for DBS in treating obsessive-compulsive disorder (OCD), epilepsy, and more, affirming the growing idea that “psychiatric disorders arise from dysfunction in distributed brain networks” and can be alleviated through targeted stimulation of these networks (Sullivan). Thomas Knopfel, head of circuit neuroscience at Imperial College of London, says that neuropharmacology techniques are far better at targeting the direct source rather than taking pills, which he describes as wanting “to treat an organ, like your brain, but you also end up with receptors on your kidneys and liver, and a lot of side effects” (Deck). While it is important to acknowledge that current methods still have several positive effects, it can be extremely beneficial to pair them with neurotechnology in order to gain more clarity with the diagnosis and treatment of brain disorders.
DBS has been approved for Parkinson's for over a decade and is sanctioned for OCD, and though clinical trials have proven to be promising, it still needs to go through FDA approval for widespread clinical applications towards major depressive disorder and PTSD. Much more research is still being done regarding methods similar to DBS, such as the option to target specific neurons (out of the 86 billion in the human brain) instead of larger brain regions for even greater effectiveness, a field called optogenetics (Deck). Currently, optogenetics is being researched as a potential method for treating Alzheimer’s disease, a severe and highly complex cognitive disease that causes dementia (Ning). However, optogenetics-based treatments are far more theoretical and still being studied, while DBS is further into clinical trials, approved for multiple applications, and has already been proven to be quite effective.
Neurofeedback in treating ADHD, ASD, and more
Another type of neurotechnology, referred to as neurofeedback or neurotherapy, is a non-invasive treatment that measures brain waves and provides a feedback signal that encourages the brain to develop healthier patterns of activity (Chandra). Unlike DBS, the real-time feedback provided in this technology is in the form of sounds and visuals at very specific frequencies, providing an immediate form of operant conditioning that trains the brain to reinforce healthier functioning. This way, the treatment targets the underlying biology in your brain responsible for the undesired behavior, such as anxiety, compulsions, or inattentiveness.
According to a meta-analysis done by various scientists on numerous randomized studies, it is evident that certain symptoms of ADHD are treatable with neurofeedback (Arns). Efficacy, which was defined as ES for ‘effect sizes’ in the meta-analysis, was observed to be larger for inattention and impulsivity than for hyperactivity. What this means is that treatment factors for hyperactivity are less specific and less effective, while the other two symptoms showed greater improvement during clinical trials using neurofeedback. Combined neurofeedback techniques such as cranio-electro stimulation and slow cortical potential training used in clinical trials with children aged 8–12 also indicated strong efficacy. These experiments had various measures put in place to ensure that trials involving children were conducted ethically, and could mean a future implementation of an ADHD treatment for children that is noninvasive and doesn’t involve prescription drugs such as Adderall.
Neurofeedback can also help improve symptoms of a variety of other disorders, such as ASD, PTSD, cognitive loss, anxiety and stress, and behavioral disorders (All-Points North). A good example of the efficacy of neurofeedback comes from a study on individuals with ASD, or autism spectrum disorder. For context, individuals with ASD have high theta activity in their anterior cingulate cortex, which is associated with the part of the brain responsible for social imitation, emotion modulation, and monitoring others' emotions (White). In this RCT (randomized control style) study, neurofeedback resulted in modified brain activity that led to reduced theta activity, which subsequently increased social interaction and communication in individuals with ASD. There is also potential for research on neurofeedback to target gamma waves, which are absent in the occipital lobe of individuals with ASD when viewing emotions on other people’s faces (White).
Some other applications of neurofeedback involve improvements in drug and alcohol addictions and stabilizing emotions to promote better sleep, mood, and attention/impulse control (even in those without ADHD). Neurofeedback doesn’t exactly deliver a ‘cure’ for brain disorders but instead takes advantage of the brain’s neuroplasticity in order to induce positive change and adaptation towards desired behaviors. It proves as a simple but effective type of neurotechnology that will likely be increasingly implemented in therapies and treatments for a variety of conditions.
Innovation in Industry
Precision medicine is another growing field of research that considers the role of genetics in psychiatric disorders. In March of 2020, a study was conducted on the human exome (the protein-coding part of DNA) in a large sample of subjects with schizophrenia (Northfield). While it is important to consider that genetics alone may not be enough to give us the precision to develop disease therapies, it can give us insights into biosignatures and subgroups of patients with biological similarities, which would in turn indicate which groups would respond to similar treatments more consistently. This field of research has the capability to revolutionize the way that we approach traditional medicine and psychiatry, and we can already see forward movement for its industrial applications through Brown University’s BRAINSTORM program.
This program at the Carney Institute for Brain Science at Brown University is a group of 10 teams that brings together researchers in computational neuroscience, AI, and physician-scientists. The program's goals are to have a lasting impact on the field of mental health through accelerating the translation of computational brain science to clinical applications and commercialization (Brown University). They are able to accomplish this by researching the underlying mechanisms for complex neurological disorders while also having the support and infrastructure typical for industrial settings. By getting neuroscientists in the same room as people who write business plans and do market research, novel computational neuroscience and its potential applications can easily be pitched to outside investors and commercialized to those who would otherwise not have access to these technologies. By addressing the acknowledged gap between academia’s novel research and current applications in industry, new computational modeling and machine learning technology could vastly improve the diagnosis and treatment of mental illnesses and psychiatric disorders. The BRAINSTORM program has already developed potential applications for target treatments of OCD and epilepsy, the discovery of biomarkers for functional deficits underlying psychiatric disorders, and using speech recognition to predict cognitive decline (Brown University).
In Conclusion
A rise in the research, design, and marketing of neurotechnological applications within the last two decades has helped scientists better understand, assess, and treat numerous brain disorders and psychopathological issues. The most revolutionary aspect of these technologies is that they allow for a direct way to manipulate the functioning of the brain by facilitating its ability to repair itself. While some disorders, such as schizophrenia, depression, anxiety, and autism spectrum disorder involve socioemotional difficulties that make initial assessments challenging, neurotechnology is extremely helpful in conducting initial evaluations, which will improve assessment tools as well as treatment interventions. Regarding those for whom current methods fail to alleviate symptoms, modern applications of neurotechnology can be life-changing.
Various neurotechnologies all retain different drawbacks or gaps of information, such as the poor spatial resolution of EEG and the poor temporal resolution of fMRI, but computational modeling and AI technology are capable of merging conclusions from various methods, allowing us to better assess the underlying mechanisms that are responsible for a patient’s behaviors. While some treatments are more invasive and expensive than others, the availability of a broader range of effective treatments that are slowly merging with the medical industry can revolutionize the mental health crisis that plagues us today. Ideally, neurotechnologies will be used in the coming decades, not to replace, but to complement current pharmacological and psychosocial approaches, acting as a third leg in the set of methods we currently have for treating those who seek viable alternatives to alleviating their mental health.
Arns M, de Ridder S, Strehl U, Breteler M, Coenen A. Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci. 2009 Jul;40(3):180–9. doi: 10.1177/155005940904000311. PMID: 19715181.
Chandra, Suruchi. “What Is Neurofeedback? A Psychiatrist’s Perspective.” Suruchi Chandra M.D. Integrative Psychiatry and Medicine, 24 Aug. 2021, https://chandramd.com /what-is-neurofeedback/#:~:text=What%20is%20neurofeedback%20therapy%3F,biological%20level%20for%20better%20functioning.
“Deep Brain Stimulation.” Deep Brain Stimulation, Johns Hopkins Medicine, 8 Aug. 2021, https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/deep-brain- stimulation#:~:text=Deep%20brain%20stimulation%20(DBS)%20is,dystonia%20and%20other%20neurological%20conditions.
“Improving Mental Health through Computational Neuroscience.” Alumni & Friends | Brown University, Brown University, 8 Nov. 2021, https://alumni-friends.brown.edu/news/2021 -1 1–08/brainstorm.
“Mind Hunters: How Neurotech Can Solve Our Brain-Health Crisis.” World Economic Forum, 12 Dec. 207AD, https://www.weforum.org/agenda/2017/12/how-neurotech-can -solve-our-brain-health-crisis/.
Ning S, Jorfi M, Patel SR, Kim DY, Tanzi RE. Neurotechnological Approaches to the Diagnosis and Treatment of Alzheimer’s Disease. Front Neurosci. 2022 Mar 24;16:854992. doi: 10.3389/fnins.2022.854992. PMID: 35401082; PMCID: PMC8989850.
Northfield, Rebecca. “Technology Takes on Mental Illness.” E&T, Institute of Engineering and Technology, 21 Apr. 2020, https://eandt.theiet.org/content/articles/2020 /04/technology-takes-on-mental-illness/.
Pedro A VS. Coping with Brain Disorders using Neurotechnology. Malays J Med Sci. 2012 Jan;19(1):1–3. PMID: 22977368; PMCID: PMC3436487.
“Rewire Your Brain with Neurotechnology.” All Points North, https://apn.com/blog/2023 /01/05/neurotechnology/.
Sullivan CRP, Olsen S, Widge AS. Deep brain stimulation for psychiatric disorders: From focal brain targets to cognitive networks. Neuroimage. 2021 Jan 15;225:117515. doi: 10.1016/j.neuroimage.2020.117515. Epub 2020 Nov 1. PMID: 33137473; PMCID: PMC7802517.
White SW, Richey JA, Gracanin D, Bell MA, LaConte S, Coffman M, Trubanova A, Kim I. The Promise of Neurotechnology in Clinical Translational Science. Clin Psychol Sci. 2015 Sep;3(5):797–815. doi: 10.1177/2167702614549801. Epub 2014 Oct 17. PMID: 26504676; PMCID: PMC4615684.
