By: Kate Leinenweber Image: Dish of brain organoids sitting on a microscope I hold a memory in the back of my mind that reminds me of why I research what I do: my grandmother, lying prone on her hospice bed, her skin pale, her bones nearly visible beneath her skin. Her breathing continues, although I have to strain to hear it, before finally slowing down and stopping. At that point, she was long incapacitated by debilitating memory loss, and she could no longer speak or feed herself. She had been bedridden for 19 months after she forgot how to walk. I remember wondering what her brain might have looked like after degrading for that long. I know what took her life away from her, just as it has for six and a half million people across the United States.  The Struggle for Finding an Alzheimer’s Cure Nearly everyone has a story of a relative or loved one who suffered (or suffers) from Alzheimer’s disease; it’s not uncommon, yet over a century after the disease’s discovery, there are very few treatments that can help manage symptoms of the disease, let alone halt its prognosis. This is not just an issue when it comes to Alzheimer’s disease. Countless other neurodegenerative disorders suffer from the same prognosis: Parkinson’s disease, amyotrophic lateral sclerosis (ALS), progressive supranuclear palsy, Lewy body dementia, and more. Diagnosis is a question of how many years someone has left, not whether they’ve caught the disease early enough to cure it. And the family members of people with such disorders are forever plagued with the worry: what if this happens to me, too?    Many neurological diseases lack treatments and possible cures because of a lack of understanding (Jalink & Caiazzo, 2021). They do not progress like pathological diseases, and they do not tend to originate from a single gene mutation– this makes them hard to track genetically, and it means that there is no obvious target for potential drugs. In addition to this, brain research is difficult to conduct. Human brain samples can only be collected after a patient is deceased, not to mention that they must have previously elected to donate their brains to science, an option which many patients and families do not consider or even want to think about ‡ . Although mouse models are an effective way of modeling brain disease, they don’t always mirror human systems as well as needed, and there are many ethical considerations to be made when choosing to work with mice. Scientists have even developed single-layer cultures of specific cell types like neurons, which can help us look at very specific interactions between diseased cells. However, they only provide one dimension of clarity, and drugs tested in these models don’t always translate effectively to actual patients (Gerakis & Hentz, 2019). Many of the models we use in scientific research are effective, but not ideal, so continuing to improve older models and develop new ones is important to cover all of our bases. This is where a more recent research development comes into play: brain organoids.  What are Brain Organoids? Image: Brain organoids viewed under a microscope, 4x magnification. Brain organoids, lovingly coined ‘mini-brains’, are spherical models of brain tissue that can be used to model the brain’s structure and function. They are produced by culturing stem cells in a way that coaxes them to differentiate into the various cells of the brain, including neurons and glia. The early growth stages of organoids mimic human brain development, so brain organoids have widely been used to model disorders that arise during development, such as autism and psychiatric disorders like schizophrenia and depression (Jalink & Caiazzo, 2021). They have also been used to model neurodegenerative diseases like Alzheimer’s and Parkinson’s by allowing the organoids to mature for longer and represent later stages of brain development. Brain organoids are extremely useful for researching disorders of the brain for various reasons. For one, they are 3D models with multiple cell types representative of the entire brain, which can provide more complex architecture than single-layer cultures ( Corrò, et. al., 2020) . They also provide a way to compare genetic variations in a controlled environment and resemble human disease pathology more accurately than animal models. Finally, they make it possible to research disease stages that are hard to obtain samples for, such as the early stages of neurodegeneration. Modeling Neurodegeneration in Organoids There are multiple ways that neurodegenerative disease can be modeled in organoids. For example, skin tissue samples from patients with disorders such as Alzheimer’s can be induced to become stem cells, and then used to create organoids displaying Alzheimer’s pathology (Gonzalez, et. al., 2018). Models like these can be used to study the course of the disease and the interactions that cause it on a molecular level, such as why amyloid plaques (a hallmark of Alzheimer’s) start to accumulate in the brain or how the immune system responds to disease onset.  Another way that many labs generate brain organoids is by using stem cells that have been gene edited to have Alzheimer’s-associated mutations.  With this method, it is possible to research how much specific gene mutations affect the onset of Alzheimer’s, which can help with genetic testing for the disease in the future. This type of genetic testing is already available for a gene called  APOE , which is heavily connected to Alzheimer’s risk (Raulin, et. al., 2022). With the help of modeling technologies like organoids, efforts are already in progress to model how other gene mutations can contribute to the disease. Future Hopes: Why this Matters As research techniques continue to improve, scientists will be able to discover the mechanisms behind why Alzheimer’s occurs and what exactly happens in the body during disease onset. It’s extremely important with this in mind to support new technologies like organoid research and gene editing, which can often be met with skepticism due to their novelty and their media presentation as something out of science fiction, when in reality they are just a more complex type of cell culture. However, they should not be treated as the ‘best’ research model either– each type of research model has its own benefits, and the combination of multiple models and efforts (including brain donations, mouse models, and single-layer cultures) is necessary for finding disease treatments.  Together, these technologies have been invaluable in helping scientists discover more about neurological disease than was ever thought possible, including the genetic basis behind different diseases and drug testing for new treatments. In the future, recent leaps and bounds in Alzheimer’s research can help us create better and more precise disease treatments that don’t just buy patients time, but allow them to keep living high quality lives after diagnosis. Footnote ‡ I regret that I never asked my family to register my grandma as a brain donor. For all the pain that she and our family went through because of Alzheimer’s disease, her brain could have been used to further research a cure. If you or someone you love is interested in registering as a brain donor (which anyone over 18 can do), you can visit the NIH and Alzheimer’s Association sites below for more info: NIH: https://www.nia.nih.gov/health/brain-donation/brain-donation-gift-future-generations Alzheimer’s Assoc.: https://www.alz.org/alzheimers-dementia/research_progress/brain-donation Sources: Corrò, C., Novellasdemunt, L., Li, V.S.W. (2020).  A brief history of organoids. American Journal of Physiology - Cell Physiology 319(1), C151-C165. https://doi.org/10.1152/ajpcell.00120.2020 . Gerakis, Y., Hetz, C. (2019).Brain organoids: a next step for humanized Alzheimer’s disease models?. Mol Psychiatry  24, 474–478. https://doi.org/10.1038/s41380-018-0343-7 . Gonzalez, C., Armijo, E., Bravo-Alegria, J. et al.  (2018). Modeling amyloid beta and tau pathology in human cerebral organoids. Mol Psychiatry  23, 2363–2374. https://doi.org/10.1038/s41380-018-0229-8 . Gustavsson, A., Norton, N., et. al. (2022). Global estimates on the number of persons across the Alzheimer's disease continuum. Alzheimer’s and Dementia, 19(2), 650-670. https://doi.org/10.1002/alz.12694 . Jalink, P., & Caiazzo, M. (2021). Brain Organoids: Filling the Need for a Human Model of Neurological Disorder. Biology , 10 (8), 740. https://doi.org/10.3390/biology10080740 . Raulin, AC., Doss, S.V., Trottier, Z.A. et al.  (2022). ApoE in Alzheimer’s disease: pathophysiology and therapeutic strategies. Mol Neurodegeneration  17, 72. https://doi.org/10.1186/s13024-022-00574-4 .

Written by: Jacinda Taggett Edited by: Elena Bobric When choosing a field of study to go into for my research, I was immediately drawn to the neuroscience of human memory and had very little explanation as to why. That was over five years ago, and over time I have been dealt with the curse that psychologists and neuroscientists bear.  In my past experience talking to aspiring scientists in these disciplines, they always say that they were initially drawn to their research question because of their own experiences (or a loved ones’ experience) with their field of study. I did not necessarily have this same personal motivation, but I will admit that my memory has declined since then.  There are plenty of factors that can possibly explain my memory issues, from living with bipolar disorder to obsessing over short-form social media content to being on medications that alter my brain chemistry. I guess upon reflection of these personal attributes, the question is “how do these factors impact my cognition?” The most likely potential answer is the neuromodulators associated, dopamine and norepinephrine. Intro to neuromodulators Neuromodulators are a subset of neurotransmitters, or simply “brain chemicals”, that influence the conduction of signals throughout neurons, primarily in a scatter or spread out way. Two examples of neuromodulators that have been associated with memory impairment or improvement are dopamine and norepinephrine. Dopamine Known as the “pleasure chemical” of the brain, dopamine has been shown to affect multiple aspects of living and cognition. From movement to thinking to even symptoms of psychosis, this molecule has a wide variety of purposes in our brains. If you ever want a fun crash course on the various symptoms of minimal dopamine to extreme levels of dopamine, I recommend watching Awakenings  (1990) starring Robert De Niro and Robin Williams. If you were to watch this movie, you would see symptoms such as inability to move (minimal dopamine in the brain) and manic rambling (excess dopamine in the brain). On a similar note, it is worth mentioning that dopamine imbalances are associated with various disorders such as Parkinson’s Disease, schizophrenia, bipolar disorder, and ADHD… which all of these tend to have cognitive deficits as well. To better explain these cognitive deficits, dopamine’s role in memory has been studied for decades throughout differing clinical populations (Kourosh-Arami et al., 2023).  Norepinephrine Norepinephrine, also called “noradrenaline”, is a lesser known neuromodulator by the general public. This chemical is associated with the “fight-or-flight” response of individuals, leading to feelings of alertness or arousal. Imbalances of norepinephrine have been associated with disorders of depression or anxiety, as well as problems with memory. Therefore, sometimes patients with depression will be given SNRIs (serotonin-norepinephrine reuptake inhibitors) to increase norepinephrine in the brain. However, someone with anxiety is not advised to be given this same medication due to their susceptibility to already having too much norepinephrine release during anxiety episodes. However, the role of norepinephrine in cognitive deficits is harder to explain, leading neuroscientists to use various methods as described below. Utilizing Rodent Models for Reference Locus coeruleus (LC) and its projections of norepinephrine in the human brain. In order to determine neuromodulators’ role in memory, we have to look at rodent models as this is one of the few populations we can experimentally alter the activation of neurons in the brain. Throughout the research done on rodent models, we see that the part of the brain responsible for projecting norepinephrine and dopamine to other parts of the brain, the locus coeruleus (LC), can improve long-term memory. This enhancement of memory was seen when the neurons connecting the LC to the brain part responsible for memory, the hippocampus , are stimulated during learning (Wilmot et al., 2024) . Although we see these associations in rodents, the methods for studying norepinephrine and dopamine’s role on human memory can be more complex. Neuromodulators and Human Memory Dopaminergic Measures and Explanations When utilizing neuroimaging tools such as (f)MRI, researchers are able to determine that reward circuitry and the way it interacts with the hippocampus or the prefrontal cortex to improve memory. For example, when using Diffusion Tensor Imaging (an MRI-based measure of connectivity in the brain) during a value-directed remembering task, researchers had seen that the pathways depositing dopamine to the prefrontal cortex was associated with better memory performance for rewarding stimuli (Reggente et al., 2018). Popular theories for findings like this suggest that dopaminergic neurons enhance memory through providing internal reward value to memories, stabilizing memories, and identifying novelty in memories (Knowlton & Castel, 2022). Norepinephrinergic Measures and Explanations Tools to study norepinephrine and cognition in humans often rely on pupil dilation, therefore using eye tracking devices in order to assess how much of this neurotransmitter is being released. A pupil dilation, neuromelanin and fMRI study had concluded that goal-directed remembering, especially those that are from arousing situations, is better predicted by norepinephrine release (Clewett et al., 2018). In other words, when someone is told to remember a scene or else they would lose money, their pupils would dilate (biomarker for norepinephrine release) and the regions of the brain necessary for analyzing scenes were activated, leading to better memory for the scene compared to other parts of the moment. Many different models and theories have been proposed to explain why norepinephrine enhances memories, especially in emotional or salient contexts. Mainly, it is concluded that norepinephrine release increases long-term potentiation, a process in which connections between neurons that hold memories are strengthened, with every salient experience (Mather et al., 2016). Long-term potentiation is a process by which neuronal synapses are positively exciting each other frequently, allowing the memory associated with them to be easier to recall with every excitation. Since norepinephrine is an excitatory neuromodulator, then having the excess neurotransmitters during emotional or salient events can lead to stimulation of these neurons (Gelinas & Nguyen, 2007). How can we improve our memory? Once we consider how neuromodulators such as dopamine and norepinephrine improve memory in various contexts, the first question that comes to mind is “How is this useful for me?” Further research needs to be implemented to better understand whether these cognitive benefits can be used strategically (i.e., there are other cognitive processes that must occur in order for these benefits to happen) or pharmacologically (i.e., we can use dopaminergic and norepinephrinergic medications to improve memory). For a strategic approach, one can consider how their attention, curiosity, and motivation for learning information can have a positive influence on their long-term memory. Although this seems sound in concept, the actual practice of sustaining attention or piquing curiosity or feeling motivated can be hard to implement in practice. Those that instead want a more long-term treatment plan for their cognitive functioning might want to consider an intervention such as Wellbutrin, a norepinephrine-dopamine reuptake inhibitor (NDRI), which has been shown to improve cognitive functioning in clinical populations such as those with Major Depressive Disorder (Soczynska et al., 2014). Although, a caveat to this approach is that the main line of clinical diagnoses for this drug are Major Depressive Disorder and Seasonal Affective Disorder, indicating that baseline levels of these neuromodulators might be lower in these studies’ samples. Regardless of whichever approach becomes standardized practice in the years to come, we still need more research in this field of study. Without the basic science questions answered from cognitive neuroscientists and the pharmacological trials from clinical neuroscientists, we cannot truly understand how we will best improve human memory. References Clewett, D. V., Huang, R., Velasco, R., Lee, T.-H., & Mather, M. (2018). Locus Coeruleus Activity Strengthens Prioritized Memories Under Arousal. The Journal of Neuroscience, 38(6), 1558–1574. https://doi.org/10.1523/JNEUROSCI.2097-17.2017 Gelinas, J., & Nguyen, P. (2007). Neuromodulation of Hippocampal Synaptic Plasticity, Learning, and Memory by Noradrenaline. Central Nervous System Agents in Medicinal Chemistry, 7(1), 17–33. https://doi.org/10.2174/187152407780059196 Knowlton, B. J., & Castel, A. D. (2022). Memory and Reward-Based Learning: A Value-Directed Remembering Perspective. Annual Review of Psychology, 73(1), 25–52. https://doi.org/10.1146/annurev-psych-032921-050951 Kourosh-Arami, M., Komaki, A., & Zarrindast, M.-R. (2023). Dopamine as a Potential Target for Learning and Memory: Contributingto Related Neurological Disorders. CNS & Neurological Disorders - Drug Targets, 22(4), 558–576. https://doi.org/10.2174/1871527321666220418115503 Mather, M., Clewett, D., Sakaki, M., & Harley, C. W. (2016). Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory. Behavioral and Brain Sciences, 39, e200. https://doi.org/10.1017/S0140525X15000667 Reggente, N., Cohen, M. S., Zheng, Z. S., Castel, A. D., Knowlton, B. J., & Rissman, J. (2018). Memory Recall for High Reward Value Items Correlates With Individual Differences in White Matter Pathways Associated With Reward Processing and Fronto-Temporal Communication. Frontiers in Human Neuroscience, 12, 241. https://doi.org/10.3389/fnhum.2018.00241 Soczynska, J. K., Ravindran, L. N., Styra, R., McIntyre, R. S., Cyriac, A., Manierka, M. S., & Kennedy, S. H. (2014). The effect of bupropion XL and escitalopram on memory and functional outcomes in adults with major depressive disorder: Results from a randomized controlled trial. Psychiatry Research, 220(1–2), 245–250. https://doi.org/10.1016/j.psychres.2014.06.053 Wilmot, J. H., Diniz, C. R., Crestani, A. P., Puhger, K. R., Roshgadol, J., Tian, L., & Wiltgen, B. J. (2024). Phasic locus coeruleus activity enhances trace fear conditioning by increasing dopamine release in the hippocampus. eLife, 12, RP91465. https://doi.org/10.7554/eLife.91465.3

Written by: Sam Tyhonas Edited by: Jacinda Taggett, Samira Rodrigues Dantas Introduction Recently, I took an online class at my institution about medical marijuana. I took this course as a way to properly educate myself on how it can work as a medicine, since I was considering getting my own medical marijuana card at the time. After taking the course, I became hooked on what kind of impact it could have on those who struggle with neurodivergent or neurological disorders. Although medical marijuana is becoming popular throughout the United States, there is still a lack of research on this subject to prove just how helpful it can be. To understand how marijuana can be used as a medicine for neurological disorders, we need a general understanding of both of these topics. History of   marijuana Throughout history, cannabis was treated as any other plant. In early human societies, it was used to craft clothing, accessories, textiles, and more. Some cultures even include it in beverages such as bhang, which is a milkshake-like drink containing cannabis stems. According to research professional Meng Ren, wild cannabis plants have been discovered growing in areas around Central Asia, including countries such as China, Pakistan, and Afghanistan. This area is known as the Pamir Plateau, which is where the Jirzankal Cemetery is located. This cemetery has been shown to have biomarkers of cannabis on wooden braziers after gas chromatography was conducted. (Ren et al., 2019) Despite cannabis having a reputation for being used recreationally, there are records from India discussing medicinal usage prior to domestication in China. From the Sushruta Samhita (an ancient Sanskrit text written in 6th century BCE), it is claimed that cannabis was recommended for phlegm, catarrh and diarrhea. It has also been observed that the fumes of Cannabis Indica were used as an anesthetic prior to western medicine. (Russo, 2005). Although humanity’s relationship with cannabis has lasted thousands of years, within the last hundred of those years, the United States has turned this plant into an area of political discussion (Hudaks, 2016, p. 1). In the late 1920’s to 1930’s, many different political events occurred which eventually led to the illegalization of cannabis, such as the Marijuana Tax Act of 1937 . The controversy started around the time Harry Anslinger (the first commissioner of the Federal Bureau of Narcotics) was elected into office and thrusted the illegalization of cocaine and heroin into action. He knew that attacking such a small demographic would not benefit his department, so he instilled a fear of cannabis in the general public by stating, “Marijuana is the most violence-causing drug in the history of mankind", and used his confirmation bias to only showcase researchers that agreed with his point of view. The other tactic Anslinger used to criminalize cannabis was inherently racist. Although the term ‘cannabis’ was used frequently in the early 1900’s, he sensationalized the term ‘marijuana’ to associate the drug with Mexican immigrants. He claimed the use of marijuana would lead to interracial marriage or sexual relations, as this would strike fear into the hearts of white Americans. Despite this, there were a few influential figures who attempted to speak out in support of cannabis. Fiorello LaGuardia released the LaGuardia Report, and using scientific reasoning, the report concluded that marijuana did not cause any of the issues Anslinger claimed it was causing, including violence, mental illness, or sexual deviancy. Unfortunately, nothing much came of this report when it was released in 1944. Now, almost 100 years later, cannabis is classified a Schedule 1 drug. Within the drug scheduling guide in the United States, there are five distinct categories, where the number gets lower on a one through five scale if it is at higher risk for abuse and there is no accepted medicinal use. Recently, government officials attempted to change cannabis’ status as Schedule 1 due to the rise in medicinal use within the U.S., but these changes were nullified. Present day, scientists are conducting proper research studies on cannabis to disprove the racist agenda of corrupt politicians. THC and CBD One type of cannabis, known more formally as Cannabis sativa  or hemp, is very low in THC, which is the psychoactive substance within cannabis. Cannabis indica  is the type of cannabis we use today either recreationally or medicinally, as it has higher levels of THC. This molecule is what gives users the feeling of being “high”, but it has many other benefits than simply recreational use. Many of those who use THC medicinally report chronic pain significantly decreased, as well as more sleep and an increased appetite. If used improperly—such as using it too frequently, using unregulated cannabis, or using cannabis with high levels of THC without the advice of a medical professional—it can cause undesired effects, usually including deficiencies in areas such as working memory, decision making, and controlling impulses. (Petker et al., 2020) CBD is not known to cause any undesirable effects, but rather is used frequently to treat anxiety, stress, insomnia, and various symptoms associated with cancer and chemotherapy. Due to the limited research that has been performed on CBD alone, there is not much conclusive evidence supporting what the chemical can do on its own. Valuing THC as the more important compound or interesting research topic may lead to more users underestimating the effects CBD can have depending on your endocannabinoid system, as well as researchers failing to perform proper studies on cannabis.  When we inhale or ingest cannabis, both of these compounds attach to endocannabinoid receptors (referred to as CB1 and CB2 receptors in the diagram below), which are part of our natural endocannabinoid system. An endocannabinoid is a type of neurotransmitter throughout all vertebrates that assists in regulation regarding immune responses, inflammation, and many other physiological processes. If a patient uses a strain of cannabis that has higher levels of THC than CBD, more receptors will pick up on THC. For someone with a chronic pain disorder, this would be beneficial to help ease their pain; however, for someone with a mood disorder like bipolar 1, it may lead to their symptoms worsening. CBD ( cannabidiol)  is the other compound within marijuana, which is also known to help with pain relief. CBD is not psychoactive, but works as an antipsychotic, which means it can help treat conditions like schizophrenia, anxiety disorders, or depression by crossing the blood-brain barrier and binding to endocannabinoid receptors without binding to these receptors directly like THC would. When THC binds to these receptors, it allows for the complete activation of the receptor, which gives THC the term of an agonist . The alternative, antagonist , is used for chemicals that block a receptor. The issue comes in when someone uses too much THC than their endocannabinoid system is made for, which can result in more serious effects if used long-term as discussed previously. Since CBD does not function the same way, it is a partial agonist. Although current research regarding how THC and CBD function on their own, it is thought that CBD is able to reduce the strong binding of THC to alleviate negative side effects while using cannabis due to its biphasic nature (Seeman, 2016).  Medical professionals worldwide advocate for both compounds, but many treat THC as if it is unsafe to use due to the psychoactive effects it has. Although both compounds do different things, they have shown that they work better together than separate; this theory is referred to as the entourage effect. This theory may need some more testing, but there are other studies that may allude to this theory having some truth to it. For example, in a study testing how cannabis can be used to treat bipolar, there were some conflicting results. When studying CBD, scientists found that it has a similar pharmacological profile to other antipsychotics, but there were patients that reported worsening symptoms after using cannabis. This is likely due to the impact of high levels of THC. (Sagar et al., 2016) To make sense of why this could be, we need an understanding of what is happening internally. There still needs to be further research done on how it can work with mood disorders, since there are also some studies that claim it helps, but that may be due to a more equal amount of THC and CBD content in the strain a patient is given. Cannabis is a very complex substance, but this does not mean it is entirely unreliable. For example, an article by Alejandra Delgado-Sequera was written to determine the molecular and cellular effects cannabis can have on Bipolar disorder type-I (BD), including alterations such as inflammation, apoptosis (more commonly known as cell death), lipid metabolism, and much more. This study presents another article that indicates BD and Cannabis Use Disorder (CUD) share some of the highest comorbidities within psychiatric disorders (Lalli et al,. 2021). Despite this claim, the Delgado-Sequera later states that apoptosis significantly decreased in BD patients that use cannabis (Delgado-Sequera et al., 2021). This finding is incredibly exciting to pharmacological research, as patients with BD are shown to experience apoptosis more frequently when unmedicated. While those with BD may be more likely to use cannabis as a way to cope, there is always a risk of addiction when using it in an unregulated way. Such as any other drug, cannabis has risks, but it can be extremely helpful when treated like a pharmaceutical.  What does this mean?           In the neuroscience field, many professionals are still skeptical of the benefits of cannabis. In order to change the perception of it, more quality research needs to be performed to prove how useful cannabis can work as a medicine. Many individuals use cannabis as a way to ease their daily chronic pain, and others use it to ease the negative symptoms of mood disorders. Despite the fact that this plant has been used for thousands of years while avoiding government regulation, Harry Anslinger and other politicians corrupted the way Americans view drugs and drug addicts, which has influenced the opinions other countries have as well.           Humans are incredibly complicated organisms, and the way individuals react to certain drugs can have hundreds of possibilities, but we need to continue working to grow our current body of knowledge. While it is important to discuss the positives and negatives, it is equally as important to realize that allowing cannabis to remain federally illegal deprives thousands of people from access to life changing medicine. We must continue to evolve as a society and move on from this traditional way of thinking and become pioneers in the field of neurology. By reducing negative perceptions of cannabis and performing many large-scale studies, we can create a healthier and happier society, ensuring those with uncontrollable illnesses a more fruitful and extensive life. References Alejandra Delgado-Sequera, Clara Garcia-Mompo, Ana Gonzalez-Pinto, Maria Hidalgo-Figueroa, Esther Berrocoso, A Systematic Review of the Molecular and Cellular Alterations Induced by Cannabis That May Serve as Risk Factors for Bipolar Disorder, International Journal of Neuropsychopharmacology , Volume 27, Issue 2, February 2024, pyae002, https://doi.org/10.1093/ijnp/pyae002 Hudak, J. (2016). Marijuana: A Short History.  The Brookings Institution. Lalli M, Brouillette K, Kapczinski F, de Azevedo Cardoso T (2021) Substance use as a risk factor for bipolar disorder: a systematic review. J Psychiatr Res  144:285–295. Petker, T., DeJesus, J., Lee, A., Gillard, J., Owens, M. M., Balodis, I., Amlung, M., George, T., Oshri, A., Hall, G., Schmidt, L., & MacKillop, J. (2020). Cannabis use, cognitive performance, and symptoms of attention deficit/hyperactivity disorder in community adults. Experimental and Clinical Psychopharmacology , 28 (6), 638–648. https://doi.org/10.1037/pha0000354 Ren, M. (2019, June 12). The origins of Cannabis Smoking: Chemical Residue Evidence from the first millennium BCE in the pamirs . Science. https://www.science.org/doi/10.1126/sciadv.aaw1391   Russo, E. (2005). Cannabis in India: ancient lore and modern medicine. In: Mechoulam, R. (eds) Cannabinoids as Therapeutics. Milestones in Drug Therapy MDT. Birkhäuser Basel. https://doi.org/10.1007/3-7643-7358-X_1 Sagar KA, Dahlgren MK, Racine MT, Dreman MW, Olson DP, Gruber SA (2016) Joint Effects: A Pilot Investigation of the Impact of Bipolar Disorder and Marijuana Use on Cognitive Function and Mood. PLoS ONE 11(6): e0157060. https://doi.org/10.1371/journal.pone.0157060 Seeman, P. (2016). Cannabidiol is a partial agonist at dopamine D2High receptors, predicting its antipsychotic clinical dose. Transl Psychiatry  6, e920. https://doi.org/10.1038/tp.2016.195

Written by: Elizabeth Aliyeva; Edited by: Elena Have you ever found yourself sitting alone at midnight, heart racing, as an online quiz claims it can reveal the hidden truths of your mind in just ten questions? Imagine this: You’re scrolling late at night, the glow of your phone illuminating your face as you fall down the rabbit hole of mental health content. A TikTok therapist pops up, listing symptoms of anxiety you swear you’ve felt your whole life. Then another post appears–this one about ADHD. Suddenly, your mind races. Is this me?   You dive deeper, connecting dots you never even knew existed. It’s almost thrilling, uncovering layers of yourself you hadn’t examined before. But here’s the twist: by the time you close the app, you’re left with more questions than answers. Am I just stressed? Overthinking? Or is this a hidden truth about who I really am?  Now zoom out. What if this process of self-diagnosis–empowered by endless online information–becomes more than a tool for understanding? What if it starts shaping how we see ourselves, even redefining who we are? Is it a brave new frontier for personal growth–or a dangerous game of pinning labels where they might not belong? In a new world where “Google it” often replaces “see a doctor”, what does it mean to diagnose yourself? And more importantly, what are we gaining–or losing–in this pursuit of self discovery? As self-diagnosis becomes increasingly common in the digital age, it raises critical questions about the intersection of psychology, technology and identity–challenging us to navigate the fine line between empowering self-awareness and the potential risks of misinterpretation and labeling. The Science Behind Self-Diagnosis Self-diagnosis involves identifying psychological or medical conditions in oneself without professional input. While this practice has gained traction with the rise of online mental health resources, it comes with both benefits and risks. Why We’re Drawn to Self-Diagnosis Humans are naturally curious about their emotions and behaviours. This curiosity, paired with easy access to online information, creates a perfect storm for self-diagnosis. Cognitive biases, like confirmation bias, play a major role here. This bias causes us to focus on information that aligns with what we already suspect, potentially leading to overconfidence in our self-assessments. The Benefits of Self-Diagnosis (Farnood et al., 2020) Awareness and Accessibility:   Online resources can provide valuable insights and help people recognize symptoms they might have ignored, encouraging them to seek professional help.  Stigma Reduction:   Public discussions about mental health can normalize struggles, making it easier for people to acknowledge and address their concerns.  The Risks of Self-Diagnosis (Farnood et al., 2020) Overgeneralization :  Many mental health conditions share overlapping symptoms. For example, fatigue could stem from depression, anxiety, or simply poor sleep, making accurate self-diagnosis tricky.  Mislabeling : Attaching the wrong label to oneself can lead to unnecessary stress or prevent someone from seeking appropriate treatment. Undermining Expertise:   Relying too heavily on self-diagnosis can discourage people from consulting trained professionals, who use comprehensive tools like diagnostic interviews and standardized assessments. Research Surrounding Self-Diagnosis In 2020, Farnood et al. conducted a mixed-methods systematic review of the effects of online self-diagnosis and its influence on the patient-healthcare professional (HCP) relationship. In their research, they shed light on how the internet is transforming the way people approach their health, emphasizing both the benefits and potential pitfalls of this phenomenon.  Trust and Complementarity  Farnood et al. (2020) showed that despite the convenience of online health information, people still trust their HCP’s advice above all else. Online self-diagnosis serves as a complementary tool, not a replacement. Patients use the internet to bridge gaps in accessibility, affordability, and immediacy, especially when waiting for medical appointments (Farnood et al., 2020). Patients essentially demonstrated the adaptive way people use digital resources–not as a substitute for expertise, but as a way to enhance their understanding and engagement. Productivity in Consultations Farnood et al. (2020) point to how digital health resources empower patients to be better informed. By learning about their symptoms in advance, patients can ask more targeted questions during consultations. This preparatory step not only makes appointments more efficient, but also enables patients to play a more active role in their care, aligning with modern, patient-centered healthcare models (Farnood et al., 2020).  HCP-Patient Dynamics The relationship between patients and HCPs plays a critical role in the effectiveness of online self-diagnosis. Farnood et al. (2020) reveal that when HCPs respond positively to patients’ research, it strengthens trust and collaboration. However, negative reactions–such as dismissing the information outright–can create feelings of embarrassment or distrust. This dynamic underscores the importance of open communication and mutual respect in maintaining a healthy relationship between patients and providers. The Psychological Impact Online self-diagnosis has psychological implications for patients and HCPs. On one hand, accessing information can be reassuring, helping people feel proactive while awaiting professional health care (Farnod et al., 2020). On the other hand, misinformation or misinterpretation can lead to unnecessary anxiety and even “cyberchondria”, where excessive online health research worsens mental well-being (Starcevic, 2023). For HCPs, balancing patients’ online research with their own expertise can be challenging, particularly when the information is flawed or overvalued by the patient. In 2024, Underhill & Foulkes explored the contentious practice of self-diagnosing mental disorders, particularly as expressed in discussions on Reddit. They examined the diverse perspectives surrounding self-diagnosis, shedding light on the social, psychological, and moral dynamics at play. The Debate on Validity and Harms  Underhill & Foulkes (2024) highlight that self-diagnosis of mental disorders is often seen as inaccurate and potentially harmful. Critics argue that it devalues psychiatric terminology, creates skepticism about genuine mental health struggles, and can lead to self-fulfilling prophecies where individuals adopt the symptoms they identify with (Underhill & Foulkes, 2024). This reflects broader concerns about the reliability of online mental health resources. When people rely on social media or online tools for self-diagnosis, they risk misunderstanding their symptoms or trivializing serious conditions. The Role of Socioeconomic Barriers Proponents of self-diagnosis emphasize that financial constraints and long waitlists make professional diagnosis inaccessible for many (Underhill & Foulkes, 2024). Self-diagnosis then becomes a coping mechanism to label and manage one’s distress (Underhill & Foulkes, 2024). This underscores the intersection between healthcare accessibility and digital self-help. It highlights the necessity of making mental health resources more accessible while also guiding individuals toward accurate self-assessment.  Adolescents and Social Media Adolescents are particularly criticized in this dataset, as users claim that their self-diagnoses are driven by identity experimentation, peer pressure, or misinformation from social media (Underhill & Foulkes, 2024). The perceived immaturity of adolescents and the role of social media in shaping their mental health narratives create a unique tension. Adolescence is a period of heightened identity exploration and sensitivity to social cues, which can make teens more vulnerable to the influence of online mental health trends (Underhill & Foulkes, 2024). However, dismissing their experiences may exacerbate their distress and discourage them from seeking help. Diagnostic Possessiveness  The concept of “diagnostic possessiveness” emerges, where individuals feel protective over psychiatric labels and are wary of their misuse (Underhill & Foulkes, 2024). This possessiveness stems from the belief that these labels hold significant power and should not be diluted by misapplication (Underhill & Foulkes, 2024). This highlights a broader cultural reverence for professional diagnosis, even as online self-diagnosis becomes increasingly common. The tension between the need for accessible tools and the sanctity of clinical expertise lies at the heart of the online self-diagnosis debate. The Need for Validation Underhill & Foulkes (2024) notes that some users defend self-diagnosis by pointing out that mental health diagnoses often rely on self-reported symptoms. Thus, individuals may feel that they are the best authority on their own experiences (Underhill & Foulkes, 2024). This philosophical defense of self-diagnosis suggests that some people turn to diagnostic labels not to replace professional input, but to validate their feelings (Underhill & Foulkes, 2024). This mirrors why people turn to the internet for self-diagnosis–seeking validation and a sense of control over their mental health in a world where professional support is often inaccessible. In 2019, Brycz et al. explored the relationship between metacognitive self (MCS) and the desire for self-diagnostic information (SDMS), providing insights into how individuals seek to understand themselves better. Understanding Metacognitive Self (MCS) MCS refers to the capacity to monitor, evaluate and regulate one’s own thoughts, beliefs, and knowledge (Brycz et al., 2019). It forms the foundation for individuals to engage in self-reflection and self-assessment (Brycz et al., 2019). In the context of mental health self-diagnosis, individuals high in MCS may be more likely to seek diagnostic labels or explanations for their symptoms because they value understanding their internal states (Brycz et al., 2019). Link to Self-Diagnosis Brycz et al. (2019) showed that individuals with higher MCS consistently demonstrated a stronger desire for self-diagnostic information, including details that could help them interpret their mental states or performance. This aligns with why some people turn to self-diagnosis. They may seek to clarify their distress, trying to make sense of their experiences in the absence of professional guidance. This is particularly relevant for those who face barriers to accessing mental health care. Persistence and Intrinsic Motivation Brycz et al. (2019) suggest that those with high MCS are persistent in their pursuit of self-knowledge, even across time. This persistence could explain why some individuals are drawn to online communities (e.g. Reddit) or self-assessment tools to explore potential mental health diagnoses. Self-diagnosis, in this sense, may be seen as a form of self-regulation and self-motivation, driven by an intrinsic need to understand one’s psychological struggles.  Diagnostic Information and Cognitive Regulation Brycz et al. (2019) links MCS to improved learning and decision making, as individuals high in MCS use diagnostic information to refine their understanding of themselves. While the desire for self-diagnostic information can lead to greater self-awareness, it can also lead to reliance on inaccurate sources or mislabeling of normal distress as pathological (Brycz et al., 2019). Adolescents, in particular, may lack the cognitive maturity to critically evaluare the information they find online (Underhill & Foulkes, 2024).  What Needs to Be Done Next?  The topic of self-diagnosis, especially in relation to mental health, is critically important because it highlights the intersection of psychological self-awareness, information access and the potential risks of misdiagnosis. In today’s digital age, individuals are increasingly turning to the internet to seek out answers for their symptoms, which can lead to both positive and negative outcomes. On the one hand, greater self-awareness can encourage individuals to seek professional help or make changes to improve their mental well-being.  The goal is to foster a balanced approach to mental health self-awareness so that we can empower individuals to critically assess their symptoms, seek reliable information, and make informed decisions about their mental health. Education can help individuals between helpful self-reflection and potentially harmful over-diagnosis or reliance on unverified online sources. Ultimately, I hope to encourage a more informed, nuanced conversation about mental health that reduces stigma and promotes seeking professional support when necessary. The Role of Metacognition in Understanding One’s Mental State  Schools, workplaces, and public health organizations should implement programs to educate individuals on recognizing mental health issues and understanding the limits and benefits of self-diagnosis. This includes promoting mental health resources that are scientifically validated and professional led. Canada and the United States offer numerous mental health resources, from national programs such as CMHA and NMIH, to specific tools like the Mindshift app and Betterhelp. Integrating metacognitive practices into these resources empowers individuals to develop a deeper understanding of their mental health and improve emotional regulation.  Improve Access to Professional Mental Health Support Efforts should be made to remove barriers to accessing mental health care, such as cost, stigma and lack of availability. Providing more affordable and accessible counseling services can reduce the temptation for individuals to rely solely on self-diagnosis.   Encourage Critical Thinking and Media Literacy We need to empower individuals to critically evaluate online health information. Teaching media literacy and how to identify untrustworthy sources is crucial in ensuring that self-diagnosis does not turn into misinformation.  Promote Open Conversations about Mental Health Encouraging open, supportive dialogues about mental health can reduce stigma and create environments where individuals feel safe seeking professional help. This includes fostering an understanding that mental health is complex and that self diagnosis, while potentially helpful in some cases, is not a substitute for professional assessment. SUMMARY TOPIC KEY POINTS Importance of Self-Diagnosis Growing use of self-diagnosis, particularly among adolescents.  Many use diagnostic language to make sense of their distress.  Debate on the benefits and harms of self-diagnosis, particularly in mental health. Psychological Concepts Metacognitive Self (MCS): How people monitor and regulate their own cognitive processes.  Self-Diagnostic Motivational Scale (SMDS):  Desire to seek information about one’s mental state or symptoms.  MCS and SMDS are linked; MCS predicts increased desire for self-diagnosis. Social Media Influence Social media amplifies both positive and negative perceptions of self-diagnosis.  Adolescents are particularly vulnerable to misinformation and self-diagnosis trends.  Social comparisons and peer pressures influence diagnostic practices. Professional Perspectives Mental health professionals typically value official diagnoses but may recognize the role of self-diagnosis as the first step.  There’s tension between respecting self-diagnosis and maintaining diagnostic integrity. Ethical Concerns Moral Judgement: Self-diagnosis can be seen as harmful, both for the individual and society.   Diagnostic Possessiveness : Some believe psychiatric diagnoses should remain exclusive to those with clinical disorders. Implications for Support The stigma and criticism faced by those who self-diagnose can exacerbate their distress.  Support for individuals self-diagnosing should be grounded in validation and understanding.  Clinicians should collaborate with self-diagnosing individuals to guide appropriate care. Call to Action Encourage awareness and open dialogue about self-diagnoses.  Train professionals to work with patients using self-diagnosis.  Develop resources to help people, especially adolescents, make informed decisions about their mental health. References Brycz, H., Kleka, P., Fanslau, A., & Pilarska, A. (2019). Metacognitive Self and Motivation to Seek Diagnostic Information About the Self: A Longitudinal Study. Frontiers in Education , 4 . https://doi.org/10.3389/feduc.2019.00117 Farnood, A., Johnston, B., & Mair, F. S. (2020). A mixed methods systematic review of the effects of patient online self-diagnosing in the “smart-phone society” on the healthcare professional-patient relationship and medical authority. BMC Medical Informatics and Decision Making , 20 (1). https://doi.org/10.1186/s12911-020-01243-6 Starcevic, V. (2023). Keeping Dr. Google under control: how to prevent and manage cyberchondria. World Psychiatry , 22 (2), 233–234. https://doi.org/10.1002/wps.21076 Underhill, R., & Foulkes, L. (2024). Self-Diagnosis of Mental Disorders: A Qualitative Study of Attitudes on Reddit. Qualitative Health Research . https://doi.org/10.1177/10497323241288785

By Davis Hobley Stress and anxiety levels in children are at an all-time high and continue to grow over the years (Lebrun-Harris et al., 2022). Among children aged 4-14, the prevalence level of anxiety continually increases, with approximately 5% of 14-year-old adolescents experiencing some form of anxiety (Steinsbekk et al., 2021). Anxiety during childhood is unarguably detrimental to normal development (Beesdo, et al., 2009). Not only does it often persist into adulthood, but it is also correlated with co-morbid disorders such as depression, substance misuse, and poor education and employment outcomes (Morales-Muñoz et al., 2023). Much of the increase in youth anxiety has been attributed to the COVID-19 pandemic, which came with a sharp increase in mental health disorders (Meherali et al., 2021). Additionally, technological advancements, such as social media, have been linked to negative mental health outcomes in children through a variety of causes (Saleem et al., 2024). One of these is increased anonymity online, specifically in the context of bullying (Kaloeti et al., 2021). The subsequent uptake in peer bullying has been correlated with the onset of anxiety. Social media also creates unrealistic life expectations for youth, particularly as their peers share only the positive aspects of their lives (Mohr et al., 2023). As a result, youth may feel as if they are the only ones struggling with difficult life circumstances, which can further worsen anxiety. Treatment options for childhood anxiety include both medication and behavioral treatments. Selective serotonin reuptake inhibitors (SSRIs), often prescribed as antidepressants, are effective in treating anxiety symptoms as well (Walter et al., 2020). Mood disorders like anxiety and depression are often linked to chemical imbalances of neurotransmitters in the brain, including serotonin. For example, mood disorders tend to come with a deficiency in serotonin. SSRIs primary mechanism, therefore, is linked to preventing serotonin in the synaptic gap (space between neurons) from being taken back up by the sending neuron. This leads to a higher concentration of serotonin in the synaptic gap, which helps correct the deficiency. Figure 1   Molecular mechanism of selective serotonin reuptake inhibitors (SSRIs) Note: The above figure demonstrates the molecular process by which serotonin—that is transmitted from the presynaptic neuron—is prevented from being reuptaken by that neuron. Through this process, more serotonin remains in the synapse, which leads to the rebalancing of chemical concentrations in the brain (Neurotorium). Healthcare providers typically will not spring to medication as the first treatment path for anxiety, especially in children (Walter et al., 2020). Alternative treatment options include cognitive behavior therapy (CBT) (Kaczkurkin & Edna, 2015). CBT integrates behavioral therapy and talk therapy to address issues the patient faces on multiple fronts. CBT can include any number of treatment strategies, such as exposure therapy, cognitive therapy, and eye-movement desensitization and reprocessing (EMDR). These treatment paths seek to provide the patient with methods/tools to control their anxiety while also exploring its underlying causes with the assistance of a skilled practitioner. The exact formulation of these treatment strategies depends on the patient's particular needs (see Table 1). Table 1 Treatment types and details for anxiety disorders Treatment Mechanism and Treatment Plan Use Cases Side Effects and Risks Selective Serotonin Reuptake Inhibitors (SSRIs) Reuptake transporters of the sending neuron are blocked by a reuptake inhibitor. This allows more of the serotonin that is sent from the sending neuron to remain in the synapse. This often corrects for serotonin deficiency which is seen in mood disorders (Walter et al., 2020). Depression Anxiety Other Mood Disorders Eating Disorders Bipolar Disorder OCD Panic Disorder PTSD Social Anxiety Disorder (Cleveland Clinic, “SSRIs”) Headache Sleep disturbances Weight change Worsened anxiety Dizziness Gastrointestinal issues Serotonin syndrome Risk of suicidal ideation  (Cleveland Clinic, “SSRIs”) Cognitive Behavioral Therapy (CBT) CBT is a combination of talk therapy and behavioral therapy that works to treat mental health disorders on multiple fronts. Exposure-based techniques are commonly used as a means for patients to better understand the problems driving their mental health symptoms.  Exposure-based therapy is especially useful for treating anxiety disorders where the patient may be strictly avoiding their triggers (or reminders of their trauma) to avoid reliving negative experiences. CBT allows the patient to process their experience safely and productively (Kaczkurkin & Edna, 2015). Depression Anxiety Phobias PTSD OCD Eating Disorders Sleep Disorders Substance Use Disorders Bipolar Disorder Schizophrenia (Mayo Clinic) Emotional discomfort Temporary stress and anxiety (Mayo Clinic) Eye Movement Desensitization and Reprocessing Therapy (EMDR) EMDR is a mental health treatment that treats PTSD and other disorders by focusing on traumatic events from the past. EMDR was founded based on adaptive information processing, which suggests that there is a different process for storing traumatic memories compared to normal ones. Traumatic events can often be disconnected from normal thought patterns and memories to reduce the pain of reliving that trauma, though this can inhibit the healing process. EMDR emphasizes tackling the root of this trauma (Kaczkurkin & Edna, 2015).  EMDR is typically an eight-phase treatment plan. For a full overview of the phases, see Cleveland Clinic , “EMDR Therapy.” PTSD Anxiety  Panic Disorder Depression Dissociative Disorders Eating Disorders OCD Acute Stress Disorder Stressful experience Temporary discomfort The proper treatment plan for any patient is going to be a collaborative decision between the patient and their clinicians. Often, a combination of therapy, behavioral changes, and medication can yield the best results. However, everyone’s personal situation will vary (Mayo Clinic).  As the new generation is ushered in, advancements in treatments and a deeper understanding of developmental contexts are necessary to reduce the stress culture currently affecting today’s youth. References Beesdo, K., Knappe, S., & Pine, D. S. (2009). Anxiety and Anxiety Disorders in Children and Adolescents: Developmental Issues and Implications for DSM-V. Psychiatric Clinics of North America , 32 (3), 483–524. https://doi.org/10.1016/j.psc.2009.06.002 Cleveland Clinic. “EMDR Therapy: What It Is, Procedure & Effectiveness.” Cleveland Clinic , 29 Mar. 2022, my.clevelandclinic.org/health/treatments/22641-emdr-therapy . Cleveland Clinic. “SSRIs.” Cleveland Clinic , 3 May 2023, my.clevelandclinic.org/health/treatments/24795-ssri . Kaczkurkin, A., & Foa, E. (2015). Cognitive-behavioral therapy for anxiety disorders: An update on the empirical evidence. Dialogues in Clinical Neuroscience , 17 (3), 337–346. https://doi.org/10.31887/dcns.2015.17.3/akaczkurkin Kaloeti, D. V. S., Manalu, R., Kristiana, I. F., & Bidzan, M. (2021). The Role of Social Media Use in Peer Bullying Victimization and Onset of Anxiety Among Indonesian Elementary School Children. Frontiers in Psychology , 12 . https://doi.org/10.3389/fpsyg.2021.635725 Lebrun-Harris, L. A., Ghandour, R. M., Kogan, M. D., & Warren, M. D. (2022). Five-Year trends in US children’s health and well-being, 2016-2020. JAMA Pediatrics , 176 (7), 1–11. https://doi.org/10.1001/jamapediatrics.2022.0056 Mayo Clinic. “Cognitive Behavioral Therapy.” Mayoclinic.org , Mayo Clinic, 16 Mar. 2019, www.mayoclinic.org/tests-procedures/cognitive-behavioral-therapy/about/pac-20384610 . Meherali, S., Punjani, N., Louie-Poon, S., Abdul Rahim, K., Das, J. K., Salam, R. A., & Lassi, Z. S. (2021). Mental Health of Children and Adolescents Amidst COVID-19 and Past Pandemics: A Rapid Systematic Review. International Journal of Environmental Research and Public Health , 18 (7), 3432. https://doi.org/10.3390/ijerph18073432 Mohr, M., Vár Honnudóttir, Mohr, M., & Annika Helgadóttir Davidsen. (2023). The paradox of endless options and unrealistic expectations: understanding the impact on youth mental health. International Journal of Adolescence and Youth , 28 (1). https://doi.org/10.1080/02673843.2023.2242475 Morales-Muñoz, I., Mallikarjun, P. K., Chandan, J. S., Thayakaran, R., Upthegrove, R., & Marwaha, S. (2023). Impact of anxiety and depression across childhood and adolescence on adverse outcomes in young adulthood: a UK birth cohort study. The British Journal of Psychiatry , 222 (5), 1–9. https://doi.org/10.1192/bjp.2023.23 Neurotorium. “Selective Serotonin Re-Uptake Inhibitors (SSRIs).” Neurotorium , 5 Oct. 2016, neurotorium.org/image/selective-serotonin-re-uptake-inhibitors-ssris-2/ . Saleem, N., Young, P., & Yousuf, S. (2024). Exploring the Relationship Between Social Media Use and Symptoms of Depression and Anxiety Among Children and Adolescents: A Systematic Narrative Review. Cyberpsychology Behavior and Social Networking . https://doi.org/10.1089/cyber.2023.0456 Steinsbekk, S., Ranum, B., & Wichstrøm, L. (2021). Prevalence and course of anxiety disorders and symptoms from preschool to adolescence: a 6‐wave community study. Journal of Child Psychology and Psychiatry , 63 (5). https://doi.org/10.1111/jcpp.13487 Walter, H. J., Bukstein, O. G., Abright, A. R., Keable, H., Ramtekkar, U., Suhler, J. R., & Rockhill, C. (2020). Clinical practice guideline for the assessment and treatment of children and adolescents with anxiety disorders. Journal of the American Academy of Child & Adolescent Psychiatry , 59 (10), 1107–1124. https://doi.org/10.1016/j.jaac.2020.05.005

Maggie Dochnal If you are neurodivergent (like me), then participating in cognitive neuroscience and psychology experiments can be a very unpleasant experience. In my first semester at George Washington University, I signed up for a study where I had to perform a distance perception task: I would be shown pairs of dots and judge whether they were farther apart than the last pair. I sat in a sterile room in my school’s psychology department building for what felt like hours, staring at the same stimuli over and over and over again. At some point, I zoned out and carelessly answered on autopilot until I finished the last trial. The experience was so negative that, two years later, I still have not participated in another experiment. My experience is by no means uncommon. The history of cognitive psychology is riddled with experiment designs that create a painfully dull and boring experience for participants (Chandler et al., 2020; Siritzky et al., 2023). However, if you are neurodivergent or score high on measures of attentional deficit, then you may feel this effect differently from neurotypical participants. It can almost feel as if the experiments are designed to weed you out. With roughly 6% of American adults being diagnosed with attention-deficit/hyperactivity disorder (ADHD; Staley et al., 2024) and 2% being diagnosed with autism spectrum disorder (ASD; Dietz et al., 2020), which factors of experiment design drive this exclusion of neurodivergent participants and how may these issues be amended? Neurodivergent exclusion in experiment design Cognitive psychology experiments tend to be long. While most studies break up their trials into multiple blocks to prevent fatigue from affecting outcomes, the sheer number of trials  can still negatively impact a participant’s concentration (Sirtizky et al., 2023). Disengaged participants can fall into the trap of carelessly completing trials to get the experience over with which significantly damages the quality of the data collected (Chandler et al., 2020). To remedy this issue, experiments often utilize data cleaning  to remove data from unattentive participants. Common data cleaning practices include removing trials where participants were too fast, removing participants whose accuracy fell below a given range, or removing participants who failed attention checks: trials or survey items meant to flag inattentive participants (Grady et al., 2022; Siritzky et al., 2023; Vaknin et al., 2023). Disengagement stemming from long study procedures may even cause participants to remove themselves from a study. Hoerger (2024) found that drop-out rates can be as high as 2% of participants per every 100 survey items. Neurodivergent participants, especially those with ADHD or ASD, are more likely to be negatively affected by experimental procedure length (Ptacek et al., 2019; Siritzky et al., 2023). This problem is made even worse when stimuli are repetitive and testing environments are dull and unstimulating. While there is little data about participant dropout specifically among neurodivergent participants, the presence of neurodivergent symptoms likely exacerbates the effects of an adverse experiment environment.  This does not even account for neurodivergent prospective participants like me, who are dissuaded from participating in research because of uncomfortable environments. Neurodivergent exclusion in sampling Even when neurodivergent participants complete all of their trials and survey items attentively, their data may still be removed from the dataset  due to selective sampling  where members of a sample may be selected at the researcher’s discretion (McIntyre, 1952). This process  involves the removal of participants from a sample after data is collected. It is common for cognitive psychology studies to remove participants with traits that may disrupt data collection, such as having a native language other than English, having a visual or cognitive impairment, or even being left-handed (Stoianov et al., 2024). Sometimes included in this list are participants with ASD, as was the case with Stoianov et al. (2024), although it is less common for participants with ADHD or obsessive-compulsive disorder to be excluded at this stage. Significance This kind of bias is called systematic bias : the participants who are removed from a dataset because they failed an attention check, dropped out, or did not meet the researcher’s inclusion criteria are not evenly distributed across the population (Siritzky et al., 2023). Because of the nature of their symptoms, neurodivergent participants are disproportionately likely to be removed from the dataset, and the generalizability of many cognitive psychology studies suffers because of it (Chandler et al., 2020). The reason I am only able to say “likely” is that many researchers do not report neurodiversity demographic data, especially for participants who are excluded or who dropped out (Siritzky et al., 2023). It is for this reason that Siritzky et al. (2023) described this as a “shadow” bias underlying the field, one that researchers can make inferences about but cannot be understood in its full scope because of a lack of information. Toward more inclusive experiment design The first step toward a  more inclusive experiment design for neurodivergent participants is for researchers to report demographic data about participants who are removed from the dataset because of failed attention checks or poor performance. Even if selective sampling methods can be exclusive, researchers very consistently state for which characteristics they are selecting which allows for more grounded, accurate critique.  Another step researchers can take toward making their designs more inclusive is to utilize virtual data collection methods such as Amazon Mechanical Turk (Mturk) and Prolific for behavioral studies (Siritzky et al., 2023). While there are criticisms to be made about data quality when using these platforms with high rates of participant exclusion for Mturk workers relative to Prolific (Vaknin et al., 2023), participating in experiments remotely may give participants a greater sense of agency with regards to pacing and environment (Siritzky et al., 2023). Conclusion Traditional experimental designs and sampling practices in cognitive psychology create systematic biases  against neurodivergent participants, harming the generalizability of findings to a neurodiverse population. To help make designs more inclusive toward neurodivergent participants, researchers can report demographic data for excluded participants and diversify data collection methods to include remote data collection and self-paced trials. References Chandler, J., Sisso, I., & Shapiro, D. (2020). Participant carelessness and fraud: Consequences for clinical research and potential solutions.  Journal of Abnormal Psychology , 129 (1), 49–55.  https://doi.org/10.1037/abn0000479 Dietz, P. M., Rose, C. E., McArthur, D., & Maenner, M. (2020). National and state estimates of adults with autism spectrum disorder. Journal of Autism and Developmental Disorders , 50 (12), 4258–4266. https://doi.org/10.1007/s10803-020-04494-4 Grady, J. N., Cox, P. H., Nag, S., & Mitroff, S. R. (2022). Conscientiousness protects visual search performance from the impact of fatigue. Cognitive Research: Principles and Implications , 7 (1), 56. https://doi.org/10.1186/s41235-022-00410-9 McIntyre, G. (1952). A method for unbiased selective sampling, using ranked sets. Australian Journal of Agricultural Research , 3 (4), 385. https://doi.org/10.1071/AR9520385 Ptacek, R., Weissenberger, S., Braaten, E., Klicperova-Baker, M., Goetz, M., Raboch, J., Vnukova, M., & Stefano, G. B. (2019). Clinical implications of the perception of time in attention deficit hyperactivity disorder (ADHD): A review. Medical Science Monitor , 25 , 3918–3924. https://doi.org/10.12659/MSM.914225 Siritzky, E. M., Cox, P. H., Nadler, S. M., Grady, J. N., Kravitz, D. J., & Mitroff, S. R. (2023). Standard experimental paradigm designs and data exclusion practices in cognitive psychology can inadvertently introduce systematic “shadow” biases in participant samples. Cognitive Research: Principles and Implications , 8 (1), 66. https://doi.org/10.1186/s41235-023-00520-y Staley, B. S., Robinson, L. R., Claussen, A. H., Katz, S. M., Danielson, M. L., Summers, A. D., Farr, S. L., Blumberg, S. J., & Tinker, S. C. (2024). Attention-deficit/hyperactivity disorder diagnosis, treatment, and telehealth use in adults — National Center for Health Statistics Rapid Surveys System, United States, October–November 2023. MMWR. Morbidity and Mortality Weekly Report, 73 . https://doi.org/10.15585/mmwr.mm7340a1 Stoianov, D., Kemp, N., Wegener, S., & Beyersmann, E. (2024). Emojis and affective priming in visual word recognition. Cognition and Emotion , 1–15. https://doi.org/10.1080/02699931.2024.2402492 Vaknin, D., Raz-Groman, Z., Scheuer, A., & Sadeh, T. (2023). Contextual reinstatement affects semantic organization. Frontiers in Psychology , 14 , 1199039. https://doi.org/10.3389/fpsyg.2023.1199039

Bernd van Ruremonde Image created by ChatGPT-4o with the prompt: “Create an image of a realistic brain implant, used for treating neurodegenerative disorders” Introduction Neuralink , Elon Musk’s brain-computer interfacing company, has recently been gaining a lot of publicity with its seemingly incredible breakthroughs in the field of neuroscience. However, as with many scientific advancements, the product is also seeing a lot of controversy, both from the scientific community and from the general public (Singh and Kumar, 2023). Many people seem scared of brain implants, afraid that their thoughts will be listened to, or even influenced. While most of these fears may quickly be debunked, it is clear that the public still shows significant hesitation towards acceptance of brain implants. Neuralink: Implant or Interface?  Let’s first make an important distinction. The field of brain implants is massive, and Neuralink  and other similar products only occupy a tiny fraction of this field. These products are called ‘brain-computer interfaces’ (BCIs). As the name suggests, they allow humans to interact with computers using only their brain as an input device. While Neuralink  is an implantable BCI, many other BCIs are not implanted and rather sit on top of the head. The term ‘brain implants’ often refers to therapeutic devices that are surgically inserted into the brain, to treat neurodegenerative disorders such as Alzheimer’s or Parkinson’s, or other neurological disorders such as epilepsy or an essential tremor. Implants are mostly used in the later stages of a disorder, when medication can no longer provide an adequate effect (Fymat, 2020). When this stage is reached, brain implants can provide a powerful and attractive alternative. It is worth noting that, while there are still significant advancements being made, most of these devices treat, and don’t cure. There is no widely accepted cure for most neurodegenerative and aforementioned neurological disorders available at this time. Neurodegenerative Disorders  The most well-known function of brain implants is to treat neurodegenerative disorders. These are disorders that are primarily caused by the death or damage of nerve cells in the brain. One such disorder is Alzheimer’s Disease (AD), a form of dementia where a build-up of Beta-Amyloid (Aβ) peptide – also called ‘senile plaques’ – in the brain inhibits the regular functioning of the nervous system (Chen et al., 2017). Diagnosis and treatment of AD have seen large advancements in recent times, with machine learning showing increasingly accurate diagnoses (Chelladurai et al., 2023). The treatment of AD has taken many different routes. One emerging technique considers preventative immunotherapy (Lathuiliere et al., 2016). The treatment is based on a cellular implant that leads to the production of Aβ-antibodies, which has shown a significant reduction in plaque buildup in animal models. While this method is preventative and might not work retroactively, studies have shown that AD can be visible in a preclinical stage through biomarkers (Sperling et al., 2011). These two methods combined could mean a significant improvement in the treatment of AD. Another common neurodegenerative disorder is Parkinson’s Disease (PD). PD is a movement disorder, thought to be caused by impaired dopamine (DA) release in the body (Cramb et al., 2023). Dopamine is what modulates the basal ganglia, which in turn controls how energetic your motor control is. Common treatments for PD are what many people think about when the word ‘brain implant’ is mentioned: an actual device that is surgically implanted in the head to modulate certain parts of the brain. This is also called ‘Deep Brain Stimulation’, or DBS (Fymat, 2020). It allows DA release to return back to a more functional state. Ethical issues & Risks Brain implants carry some serious risks and ethical critiques. DBS, for one, requires brain surgery, and while generally safe, every surgery carries risks. Additionally, a long-term analysis of 82 PD patients who underwent DBS surgery showed that more than 20% experienced non-reversible adverse effects that were possibly related to DBS (Buhmann et al., 2017). These adverse effects included symptoms like impaired gait, depression, cognitive disturbances, or urinary incontinence. Another big concern is hacking. Implants like Neuralink, while allowing the user to control devices in their environment (Janarthanan et al., 2024), inevitably become a part of the vulnerable Internet-of-Things (IoT) network. This network has been shown to have significant weaknesses (AlSalem et al., 2023), leading to worries that these implants could act as a gateway for hackers into our mind and behavior. Finally, there have been questions about the psychological and mental influence of DBS implants. Numerous studies suggest that DBS can affect an individual’s personal identity, raising ethical and legal issues (Klaming and Haselager, 2013). For instance, if a patient is influenced by DBS to a point where they commit a crime, can they be held liable? Or could they ‘plead insanity’ similar to a patient with a severe mental illness? Would it make a difference if the influence could be reversed by turning off the DBS? These are all valid questions as to the legal and ethical liability of DBS patients. Conclusion While numerous treatment methods for neurodegenerative disorders currently exist on the market, brain implants present an attractive long-term solution for patients with disorders like AD and PD. Implants like Neuralink also seem promising, both for ‘recreational’ and clinical use. However, for both of these categories, numerous ethical issues should be addressed before moving further in the field. Bibliography AlSalem, T., Almaiah, M., & Lutfi, A. (2023). Cybersecurity Risk Analysis in the IoT: A Systematic Review. Electronics , 12 (18), 3958. https://doi.org/10.3390/electronics12183958 Buhmann, C., Huckhagel, T., Engel, K., Gulberti, A., Hidding, U., Poetter-Nerger, M., Goerendt, I., Ludewig, P., Braass, H., Choe, C., Krajewski, K., Oehlwein, C., Mittmann, K., Engel, A. K., Gerloff, C., Westphal, M., Köppen, J. A., Moll, C. K. E., & Hamel, W. (2017). Adverse events in deep brain stimulation: A retrospective long-term analysis of neurological, psychiatric and other occurrences. PLOS ONE , 12 (7), e0178984. https://doi.org/10.1371/journal.pone.0178984 Chelladurai, A., Narayan, D. L., Divakarachari, P. B., & Loganathan, U. (2023). fMRI-Based Alzheimer’s Disease Detection Using the SAS Method with Multi-Layer Perceptron Network. 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A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., Park, D. C., Reiman, E. M., Rowe, C. C., Siemers, E., Stern, Y., Yaffe, K., Carrillo, M. C., Thies, B., Morrison‐Bogorad, M., … Phelps, C. H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging‐Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia , 7 (3), 280–292. https://doi.org/10.1016/j.jalz.2011.03.003 Further Reading Amami, P., Dekker, I., Piacentini, S., Ferré, F., Romito, L. M., Franzini, A., Foncke, E. M. J., & Albanese, A. (2015). Impulse control behaviours in patients with Parkinson’s disease after subthalamic deep brain stimulation: De novo cases and 3-year follow-up. Journal of Neurology, Neurosurgery & Psychiatry , 86 (5), 562–564. https://doi.org/10.1136/jnnp-2013-307214 Buhmann, C., Kassubek, J., & Jost, W. H. (2020). Management of Pain in Parkinson’s Disease. Journal of Parkinson’s Disease , 10 (s1), S37–S48. https://doi.org/10.3233/JPD-202069 Chayasirisobhon, S. (2014). Efficacy of Neuromodulation Therapy with Vagus Nerve Stimulator in Patients with Drug-Resistant Epilepsy on Unchanged Antiepileptic Medication Regimen for 24 Months Following the Implant. Journal of Neurology & Neurophysiology , 06 (01). https://doi.org/10.4172/2155-9562.1000268 Di Costa, S., Barow, E., Hidding, U., Mainka, T., Pötter-Nerger, M., Buhmann, C., Moll, C. K. E., Haggard, P., & Ganos, C. (2020). Dopamine boosts intention and action awareness in Parkinson’s disease. Experimental Brain Research , 238 (9), 1989–1995. https://doi.org/10.1007/s00221-020-05847-2 During, M. J., Freese, A., Sabel, B. A., Saltzman, W. M., Deutch, A., Roth, R. H., & Langer, R. (1989). Controlled release of dopamine from a polymeric brain implant: In vivo characterization. Annals of Neurology , 25 (4), 351–356. https://doi.org/10.1002/ana.410250406 Heneka, M. T., Carson, M. J., Khoury, J. E., Landreth, G. E., Brosseron, F., Feinstein, D. L., Jacobs, A. H., Wyss-Coray, T., Vitorica, J., Ransohoff, R. M., Herrup, K., Frautschy, S. A., Finsen, B., Brown, G. C., Verkhratsky, A., Yamanaka, K., Koistinaho, J., Latz, E., Halle, A., … Kummer, M. P. (2015). Neuroinflammation in Alzheimer’s disease. The Lancet Neurology , 14 (4), 388–405. https://doi.org/10.1016/S1474-4422(15)70016-5 Pournoori, N., Wirdatmadja, S., Bjorninen, T., Sydanheimo, L., Voutilainen, M., & Ukkonen, L. (2022). Wireless Brain Implant for Dopamine Monitoring. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI) , 876–877. https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9887309 Reyes, K. D. L., Chandrasekhar, S. S., Tagliati, M., & Alterman, R. (2010). Successful Implantation of a Deep Brain Stimulator for Essential Tremor in a Patient With a Preexisting Cochlear Implant: Surgical Technique Technical Case Report. Operative Neurosurgery , 66 (6), onsE372. https://doi.org/10.1227/01.NEU.0000369646.01287.42 Russo, M., Santarelli, D. M., & Smith, U. (2018). Cervical spinal cord stimulation for the treatment of essential tremor. BMJ Case Reports , bcr-2018-224347. https://doi.org/10.1136/bcr-2018-224347 Sehar, U., Rawat, P., Reddy, A. P., Kopel, J., & Reddy, P. H. (2022). Amyloid Beta in Aging and Alzheimer’s Disease. International Journal of Molecular Sciences , 23 (21), 12924. https://doi.org/10.3390/ijms232112924 The amyloid hypothesis of Alzheimer’s disease at 25 years . (n.d.). https://doi.org/10.15252/emmm.201606210 Vuletic, V., Racki, V., Chudy, D., & Bogdanovic, N. (2020). Deep Brain Stimulation in Non-motor Symptoms of Neurodegenerative Diseases. In D. Larrivee & S. Mansoor Rayegani (Eds.), Neurostimulation and Neuromodulation in Contemporary Therapeutic Practice . IntechOpen. https://doi.org/10.5772/intechopen.88430 Xu, J., Chen, T.-Y., Tai, C.-H., & Hsu, S. (2023). Bioactive self-healing hydrogel based on tannic acid modified gold nano-crosslinker as an injectable brain implant for treating Parkinson’s disease. Biomaterials Research , 27 (1), 8. https://doi.org/10.1186/s40824-023-00347-0 Zhang, E. (n.d.). Mechanically Matched Silicone Brain Implants Reduce Brain Foreign Body Response .

Noor Amina It’s a Saturday morning and you are humming to yourself as you pick out a sweater for an outing with your friends. Suddenly, your vision starts to black out. A dull ache creeps along your neck and head, suffocating your thoughts and halting your movement. Your temples begin throbbing with pain making all lights and sounds unbearable. You cancel your plans and retreat into a dark room, hoping the pain will subside. For many individuals suffering from chronic migraines, this scenario is not uncommon. However, chronic migraines may not simply involve getting struck with random headaches; they may be rooted in something profound -an extension of your childhood experiences. Researchers are beginning to uncover an unexpected connection between adverse childhood experiences such as trauma or household dysfunction and the likelihood of chronic migraines in adulthood. Could understanding the link between negative childhood experiences aid individuals in treating or even preventing migraines? Migraines Migraines are distinct from headaches, typically characterized by severe throbbing pain on one or both sides of the head. In addition, the symptomatology of migraines varies in individuals as some report burning, pulsing, and flashing pain along with nausea, dizziness, and blurry vision. Additionally, many individuals experience migraine triggers, where exposure to light or sound may trigger an episode (“Migraine” 2023). Although the symptom's intensity and frequency differ per individual, one common factor that most individuals with chronic migraines experience is the duration of the migraine, which can last from 4 to 72 hours, often accompanied by a range of sensitives and symptoms. 60% of individuals experiencing migraines report symptoms such as fatigue, lack of appetite, digestive issues, and mood swings (“What is Migraine” 2014). Chronic migraines are even more debilitating and are defined as having migraines at least 15 days per month (“Migraine” 2023 ). The headache and symptoms become a companion for chronic migraine sufferers, which impacts their physical and mental health, along with their social relations. Adverse Childhood Experiences Adverse Childhood Experiences (ACEs) can broadly be defined as any physical, sexual, emotional, and mental abuse an individual undergoes during their formative early years (under the age of 18). The Substance Abuse and Mental Health Services Administration (SAMHSA) reported that 1 in 7 children have experienced childhood abuse/neglect (2024). Childhood maltreatment can impact brain development and influence the course of physiological development, affecting various aspects of health. Generally, children who are exposed to abuse during their childhood are at risk for developing chronic diseases, poor mental health, and mood disorders in adulthood (Monnat & Chandler, 2015). All these negative outcomes impact the quality of life for these individuals as childhood is a salient stage of development. One of the impacts ACEs can have on a physiological level is the disruption in the neuroendocrine system and immune functioning due to the recurrent release of stress hormones (Shonkoff et al., 2009). Relation of ACEs and Migraines Previous research has shown compelling evidence showing an association between inflammatory biomarkers and oxidative stress in women with migraines. Tietjen et al. conducted a study in which premenopausal women with and without migraines were studied to examine their endothelial functioning. The results found that women with migraines had endothelial dysfunction (2009). Further investigation on the relation of endothelial dysfunction biomarkers, childhood adversity, and migraines in female subjects. Results showed an association between an increase in ACE score and migraine onset, specifically in individuals with high emotional abuse. Additionally, clinical evidence demonstrated that early life stress results in physiological changes including the sympathetic nervous system and hypothalamopituitary-adrenocortical (HPA) axis, which are the primary pathways that respond to stress response and migraine development. (Tietjen et al., 2012). This aligns with previous studies on the understanding that childhood maltreatment or parental care has an effect on an individual's epigenetic memory that results in unrestrained inflammation and the malfunctioning of the reduction in the expression of genes such as the glucocorticoid receptor ( McGowan et al., 2009) . Importance Though the average individual may not necessarily be affected by chronic migraines, the rise in the number of adverse childhood experiences raises concerns about the long-term impacts of this trauma on individuals. Recognizing the widespread influence of childhood trauma is crucial for not only the average individual to understand but also to prevent the potential perpetuation of trauma across future generations. Furthermore, there needs to be an assessment of clinical interventions for individuals impacted by adverse experiences during childhood to ensure that healthy habits are instilled to prevent long-term health disorders. Although for individuals already impacted by abuse in their youth and chronic migraines in their adulthood, methods of prevention are overdue, understanding the background to their current suffering may aid in taking steps to address and heal their traumas. References Mayo Foundation for Medical Education and Research. (2023, July 7). Migraine . Mayo Clinic. https://www.mayoclinic.org/diseases-conditions/migraine-headache/symptoms-causes/syc-20360201  WebMD. (2014, March 14). What is Migraine? . WebMD. https://www.webmd.com/migraines-headaches/migraines-headaches-migraines  Chronic migraine . The Migraine Trust. (2024, June 7). https://migrainetrust.org/understand-migraine/types-of-migraine/chronic-migraine/#:~:text=Chronic%20migraine%20is%20defined%20as,frequent%20headache  Understanding Child Trauma . SAMHSA. (2024, May 24). https://www.samhsa.gov/child-trauma/understanding-child-trauma  Monnat, S. M., & Chandler, R. F. (2015). Long-Term Physical Health Consequences of Adverse Childhood Experiences . The Sociological Quarterly, 56(4), 723–752. https://doi.org/10.1111/tsq.12107 Shonkoff, J. P., Boyce, T. W., & McEwen, B. S. (2009, June 3). Neuroscience, molecular biology, and the childhood roots of Health Disparities: Building a new framework for Health Promotion and Disease Prevention . PubMed. https://pubmed.ncbi.nlm.nih.gov/19491187/  Tietjen, G. E., Herial, N. A., White, L., Utley, C., Kosmyna, J. M., & Khuder, S. A. (2009). Migraine and biomarkers of endothelial activation in young women. Stroke, 40(9), 2977–2982. https://doi.org/10.1161/STROKEAHA.109.547901 Tietjen, G. E., Khubchandani, J., Herial, N. A., & Shah, K. (2012). Adverse childhood experiences are associated with migraine and vascular biomarkers. Headache, 52(6), 920–929. https://doi.org/10.1111/j.1526-4610.2012.02165.x McGowan, Patrick O, et al. “Epigenetic Regulation of the Glucocorticoid Receptor in Human Brain Associates with Childhood Abuse.” Nature News, Nature Neuroscience Publishing Group, 22 Feb. 2009, www.nature.com/articles/nn.2270 .

By: Kate Leinenweber Image credit: The Hartman Center for Functional Neurology This past September, I attended a thought-provoking talk at Arizona State University featuring Dr. James Dennert and Dr. Jason Robert. The two of them spent the time debating and engaging the audience on a central topic: what is the difference between a neurological and psychiatric disorder? Where can we actually draw that line? How do we determine what issues we send people to a neurologist for, and what issues we send people to a psychiatrist or therapist for? When did we decide which diseases belonged where? “Mental Illnesses are Illnesses Like Any Other” Dr. Dennert, one of the speakers, spent 40 years as a psychiatrist before pursuing his doctorate. His thesis investigated the common saying in psychiatry that “mental illnesses are illnesses like any other.” The phrase asserts that mental disorders are physical disorders of the brain and should be treated in the same way as any other physical illness. This saying promotes the idea that there is a neurobiological base behind mental disorders, which could help reduce the social stigma surrounding them (Malla, 2015). If psychological and psychiatric disorders were considered as physical disorders of the brain, the same way that neurological disorders are, then they would be less likely to be stigmatized as issues people can simply “get over” by focusing better, worrying less, or being less sad. This perspective is meant to promote the social acceptance of psychiatric disorders, helping patients and their families be more open to diagnosis and treatment. Surprisingly, there are arguments both for and against this perception, whereas I had originally assumed most therapists would support this idea as a way to reduce social stigma surrounding mental illness. Dr. Dennert challenged my assumption by arguing that mental illnesses are not illnesses like any other. He emphasized that mental illnesses possess unique pathologies, modes of symptom production, and treatment methods that distinguish them from other physical disorders. Physical vs. Mental Illness Dr. Dennert’s reasoning for this conclusion follows the path from the “cause” of a disease – a specific bodily or cellular dysfunction – to the symptoms that you would observe in a person. For instance, diabetes is a result of the body’s inability to produce enough insulin, impairing its ability to regulate blood glucose levels. The disease stems from a clear abnormal pathology in a specific organ, the pancreas, and the symptoms are direct consequences of that dysfunction (Dennert, 2024, p. 25). In contrast, Dr. Dennert argued that the link between cause and symptoms in mental illness is far less concrete. While dysfunctional neural activity or imbalances in neurotransmitters lead to changes in behavior, it is hard to determine exactly why and how that process occurs. Unlike physical illnesses, mental disorders lack a definitive connection between the brain’s physical state and the contents of our thoughts, emotions, or behaviors. As someone who primarily researches molecular biology and neuroscience, hearing Dr. Dennert’s argument sparked my curiosity. Why do we define neurological and psychiatric disorders the way we do, and why do we sometimes struggle to draw the line between them? Current research on the origins of these disorders tends to focus a lot on the genetic basis of disease, while others focus on our environment, or tracing the path from cause to symptom. However, the way our bodies work is a combination of all these approaches, and possibly more that we haven’t discovered yet. So, what is the best way to go about characterizing them? I initially believed that psychiatric disorders should be observed on the same basis that neurological disorders are: as conditions stemming from some protein neurotransmitter dysfunction in the brain, something that can be characterized by a physical marker or a dysfunctional gene variant. The saying that “mental illnesses are illnesses like any other” is common for a reason – we want to strive for parity in how we address neurological and psychiatric disorders. Not to mention, the human body doesn’t just divide diseases into neat categories. We can try to box things into categories to make disorders easier to understand, but nothing about our evolution and the different disorders that have come from it is naturally ordered or easy to understand. And yet, Dr. Dennert’s point still stands: there is a difference. At the very least, this difference is prominent enough that we created these two broad categories for brain diseases to fall into – diseases that affect our psyche, and diseases that affect our nervous system. If we are going to continue to differentiate between them, however, we need to have a good reason besides tradition behind it. We need to think critically about common beliefs, and reassess what frameworks we use in psychology and medicine. It might then lead us to develop new therapeutic and physical treatments, and allow for a better characterization of these diseases. This question prompted me to examine more closely how and why we categorize neurological and psychiatric conditions the way we do. So What is the Difference? In the medical field, there is a relatively clear consensus on where we draw the line between neurological and psychiatric disorders, rooted in whether the dysfunction primarily affects the nervous system or whether it affects mood and behavior. Neurological disorders are primarily defined by dysfunction in the nervous system, which includes the brain, spinal cord, and nerves (Galinato, 2018). Conditions like Alzheimer’s disease and Parkinson’s disease fall under this category because the diseases are primarily characterized by neuronal degeneration and death. Similarly, epilepsy is classified as neurological because its symptoms arise from abnormal electrical signaling between neurons. Psychiatric disorders, on the other hand, are primarily defined by abnormalities in mood, behavior, and emotional state. For instance, depression is characterized by changes in emotions, feelings of emptiness, and unusual sleeping and eating patterns. Anxiety is characterized by restlessness, persistent anxious thoughts, and difficulty with decision making. While many psychiatric disorders may present with physical symptoms, their hallmark is their impact on mental states, thus it is harder to trace their neurology. Of course, the way we categorize these disorders is not the end all be all, and neurological and psychiatric disorders tend to overlap greatly. Many neurological disorders  affect mood and behavior, and there are often higher rates of psychiatric issues in people with other neurological disorders. For example, Alzheimer’s disease is characterized by the accumulation of amyloid plaques and tau tangles in the brain, but it is also primarily recognized when people with the disorder experience unexpected changes in memory and emotional regulation. People with Alzheimer’s, Parkinson’s, and epilepsy, which are all defined as neurological disorders, are often impacted by depression, exemplifying how suffering from a neurological disorder can affect a person’s mental health. In recent years, neuropsychiatry has gained prominence as a field that bridges the gap between neurology and psychiatry. This approach is based on the approach that neurological and psychiatric disorders, though intrinsically different, overlap in many significant ways. Many disorders can benefit from a combination of treatments from both areas. For example, many medications traditionally used for psychiatric disorders, like SSRIs and antipsychotics, can also affect neurotransmitters, and have demonstrated effectiveness in reducing symptoms of neurological disorders such as epilepsy or Huntington’s disease (Taslim, 2024). Additionally, ongoing research into the genetic basis of psychiatric disorders is uncovering physical mechanisms that could lead to improved treatments. The brain is a unique and complex organ which serves as the center of our behavior and thought while still being a physical organ that is susceptible to dysfunction like any other. While debates about the conceptual distinctions between neurological and psychiatric disorders are useful, it’s important to realize that our categorization of these disorders are just our way of making sense of the complicated system that is the human body. Our knowledge will continue to evolve as we make advances in our research and understanding of the brain and mind. As the boundaries between neurological and psychiatric conditions continue to blur, we can learn to view disorders of the brain on a spectrum rather than boxing them into discrete categories. By viewing brain disorders as interconnected rather than separate, we can develop more effective, holistic treatments for a wide range of conditions, ensuring that patients receive comprehensive care regardless of the traditional classification of their disorder. References:  Baker, M. G., Kale, R., & Menken, M. (2002). The wall between neurology and psychiatry. BMJ (Clinical research ed.) , 324 (7352), 1468–1469. https://doi.org/10.1136/bmj.324.7352.1468 Brain and Spine Specialists. (2024, March 21). Neurological vs Psychological - A Closer Look | Brain And Spine Specialists . https://brainandspinecenterllc.com/2024/03/21/neurological-vs-psychological-a-closer-look/ . David, A. S., & Nicholson, T. (2015). Are neurological and psychiatric disorders different?. The British journal of psychiatry : the journal of mental science , 207 (5), 373–374. https://doi.org/10.1192/bjp.bp.114.158550 Dennert, J.W. (2024). "Mental Illnesses Are Illnesses Like Any Other": An Inquiry and Critique. ASU Electronic Theses and Dissertations. https://hdl.handle.net/2286/R.2.N.193427 . Hartman, J. (2023, August 28). What Are the Common Therapies Used in Brain Injury Treatment? . The Hartman Center for Functional Neurology. https://thehartmancenter.com/what-are-the-common-therapies-used-in-brain-injury-treatment/ . Malla, A., Joober, R., & Garcia, A. (2015). "Mental illness is like any other medical illness": a critical examination of the statement and its impact on patient care and society. Journal of psychiatry & neuroscience : JPN , 40 (3), 147–150. https://doi.org/10.1503/jpn.150099 Galinato, M. (2018). What Is the Difference Between Neurological and Psychiatric Disorders?   Brainfacts.org . https://www.brainfacts.org/diseases-and-disorders/mental-health/2018/what-is-the-difference-between-neurological-and-psychiatric-disorders-070618 . Pescosolido, B. A., Martin, J. K., Long, J. S., Medina, T. R., Phelan, J. C., & Link, B. G. (2010). “A Disease Like Any Other”? A Decade of Change in Public Reactions to Schizophrenia, Depression, and Alcohol Dependence. American Journal of Psychiatry , 167 (11), 1321–1330. https://doi.org/10.1176/appi.ajp.2010.09121743 Taslim, S., Shadmani, S., Saleem, A. R., Kumar, A., Brahma, F., Blank, N., Bashir, M. A., Ansari, D., Kumari, K., Tanveer, M., Varrassi, G., Kumar, S., & Raj, A. (2024). Neuropsychiatric Disorders: Bridging the Gap Between Neurology and Psychiatry. Cureus , 16 (1), e51655. https://doi.org/10.7759/cureus.51655 .

by Omegan Wright The world has an $818 billion problem on its hands and, with no solution in sight the problem is projected to grow to two trillion dollars in the next six years. The issue at hand is Alzheimer's disease, a neurodegenerative condition characterized by irreversible, progressive neurological degeneration resulting in memory loss, impaired thinking and reasoning, as well as personality and behavioral changes (Liu et al., 2019). Aging is the primary risk factor in the progression of the disease. For individuals over the age of 65 their chances of developing Alzheimer's doubles every 5 years (Liu et al., 2019). The trend is already being observed globally, as every 20 years, the number of individuals diagnosed with Alzheimer's doubles (Liu et al., 2019). The widespread impact of Alzheimer's disease extends beyond financial costs, creating a significant socio-cultural burden. Families will need to make sacrifices to take care of ailing elderly family members as they can no longer take care of themselves. Alzheimer's disease is an illness that robs people of their autonomy, their past, and their sense of self. Yet, we may have been examining it all wrong. This article is the first in a series focusing on the different theories of Alzheimer's disease pathogenesis. In this installment, we will examine the prevailing theories of the pathogenesis of Alzheimer's disease, their historical and current significance, and the reasons these theories have faced increasing criticism from the broader medical community since 2014. The Amyloid Cascade Hypothesis: An Issue with Hyperfixation? The amyloid cascade hypothesis is the second major hypothesis to gain traction in the scientific community regarding Alzheimer’s Disease (AD). In 1991, John Hardy and David Allsop proposed that the rapid deposition in the brain of a protein fragment called Amyloid-β (Aβ) causes the buildup of plaques, which they suspected to be the primary driver of Alzheimer's disease (Liu et al., 2019). These initial findings were based on previous studies regarding AD symptoms observed in individuals with Down's Syndrome who have an extra copy of chromosome 21 leading to overproduction of proteins encoded on that chromosome. Researchers identified a connection between specific genetic mutations in three key genes located on chromosome 21 and the overproduction of amyloid precursor protein (APP), which generates Aβ. As the theory and science evolved, more pathways and mechanisms were included until the amyloid cascade hypothesis outlined a detailed pathway: Aβ deposition leads to the phosphorylation of Tau oligomers, causing plaques and neurofibrillary tangles, as well as resulting in cognitive impairment and degeneration due to neuronal death (Liu et al., 2019). The key feature of this theory is that amyloid accumulation is the initiating event that causes Alzheimer’s disease (Frisoni et al., 2022). This proposed mechanistic pathway is supported by extensive evidence and research, including studies examining the relationship between Aβ presence and AD progression, the temporal associations between Tau and Aβ presenting Aβ as the proceeding factor, and findings that certain forms and quantities of Aβ are toxic (Frisoni et al., 2022). Conversely, alternative evidence gathered over the past few decades has challenged the linearity of this hypothesis.. The first cracks in the hypothesis was the conclusion that accumulation Aβ occurs over a long period of time and isn't indicative of cognitive impairment in some individuals. In autopsies of cognitively normal adults, Aβ dispersion through the liquid environment of the brain matter was fairly common (Yadollahikhales & Rojas, 2023). Although, not at the acute levels observed in AD (Yadollahikhales & Rojas, 2023). It has been determined that approximately 30% of adults with normal cognition have signs of Aβ accumulation or plaque formation implicated as the source of AD pathology (Liu et al., 2019). Additionally, the distribution of Aβ deposition is not consistent with the features of neurodegeneration in Alzheimer’s disease (Roda et al., 2022). The amyloid cascade hypothesis also struggles to explain the 95% of Alzheimer's cases that are sporadic rather than familial AD. Sporadic AD is a multifactorial disease with multiple modulating environmental and genetic variables, with the ε4 allele of apolipoprotein E (APOE) being the most significant genetic risk factor (Liu et al., 2019). Most critically, the clinical trials based on the amyloid cascade hypothesis are, at most, mildly effective, even as they treat the plaque build-up extremely well (Kepp et al., 2023). For instance, Solanezumab, a monoclonal antibody treatment targeted toward the clearance of Monomeric and soluble Aβ, was extremely effective in reducing free plasma Aβ concentrations by more than 90%, but did not lead to significant cognitive improvement (Frisoni et al., 2021; Liu et al., 2019). It also failed stage 3 clinical trials due to significant adverse side effects, and is not currently on the market (Frisoni et al., 2021). Other antibody treatments, such as Aducanumab, Lencecumab, and Donanemab, have been approved recently, but controversy has already arisen. Aducanumab was approved in June 2021 under an accelerated approval protocol based on its ability to remove plaques. It was the first drug approved for AD in 18 years, yet the efficacy of its treatment is questionable (Imbimbo et al., 2023). Since plaque removal only slows the progression of the disease mildly, or rather 22% in this case, and there was a high incidence of side effects, it was recently removed from the market and replaced with Lecanemab (Frisoni et al., 2021; Liu et al., 2019). Lecanemab targeted Aβ protofibrils and showed promising clinical results but did not meet primary endpoints, such as a positive change in dementia related cognitive impairment, in phase two clinical trials; however it did slow cognitive decline with a highest success of all other approved therapies at 47% (Frisoni et al., 2022). Similarly, Donanemab, approved under the FDA’s breakthrough therapy designation, aimed to reduce plaque burden by targeting the Aβ peptides directly (Yadollahikhales & Rojas, 2023). While it reduced plaque levels by 80%, it did not significantly improve outcomes in the four cognitive scales used as the study’s primary endpoint; the best this expensive therapy could do was slow the progression of the disease (Yadollahikhales & Rojas, 2023). The limited success of these therapies has prompted growing skepticism of the amyloid cascade hypothesis. While the hypothesis has undoubtedly contributed to understanding Alzheimer’s disease, its central role as the primary driver of the condition is increasingly questioned. The Tau Propagation Hypothesis: The Actual Toxin? The Tau hypothesis posits that the abnormal accumulation of tau protein tangles, known as neurofibrillary tangles (NFTs), disrupts the structural integrity and function of neurons in the central nervous system (CNS), ultimately leading to cell death (Kapoor & Chinnathambi, 2023). The Tau propagation hypothesis was proposed by Frost et al. in 2009 with a study that demonstrated how misfolded Tau could be taken up into cells and propagate in a prion-like manner (Liu et al., 2019; Takeda, 2019). Tau is a very soluble protein commonly found in both the peripheral and central nervous systems, and crucial in stabilizing the microtubules and facilitating cellular transport (Kapoor & Chinnathambi, 2023). However, Tau can also spread in a prion-like manner. Neurons already hosting dysfunctional tau can spread then to healthy neurons releasing tau "seeds", oligomers of misfolded Tau, that can be taken up by neighboring cells. When the dysfunctional Tau comes into contact with functional Tau in the typical neuron, it confers this dysfunction (Pascoal et al., 2021). Dysregulated Tau is often caused by genetic mutations or post-translational modifications such as phosphorylation after assembly, which alters the protein's structure, making it more prone to aggregation and NFT formation. (Roda et al., 2022). Hyperphosphorylated Tau aggregates into paired helical filaments that clump together into NFTs, also called tangles. NFTs are problematic as they cause disruptions in critical components of normal neuronal function, including axonal transport, synaptic transmission, and neuronal signaling. The breakdown of these processes can kill the neuron, contributing significantly to the cognitive decline observed in individuals with AD (Kapoor & Chinnathambi, 2023). What makes the Tau hypothesis particularly compelling is its alignment with the progression of Alzheimer’s disease unlike the AB deposition hypothesis. The spread of Tau tangles closely correlates with disease stages, as reflected in Braak staging (I-VI), a model consistently validated across studies (Kapoor & Chinnathambi, 2023; Pascoal et al., 2021). This temporal and spatial alignment strengthens the argument that Tau is a primary driver of neurodegeneration in Alzheimer’s disease. Despite its appeal, the Tau propagation hypothesis is not without limitations. There are some gaps to be explored and difficulty in executing clinical treatments based on these observations. The mechanism doesn’t exactly mediate the connection between tau and Aβ plaques, In the mesial temporal regions of the brain—where Tau dysregulation often begins—low levels of Aβ are present and are believed by some to initiate the dysfunction (Pascoal et al., 2021). Additionally, the microglial cells of the CNS have been implicated in the initiation of tau propagation. This suggests that while Tau plays a critical role in disease progression, it may not be the initiating factor (Pascoal et al., 2021). Also, tau-target therapies are hard to develop because they exist in six isoforms in the human brain, and their levels become dysregulated during Alzheimer’s progression, lowering targeting efficacy (Roda et al., 2022,). Furthermore, the precise mechanisms behind Tau hyperphosphorylation and subsequent aggregation into NFTs remain mostly unknown, so highly specific treatments cannot be developed at this time (Roda et al., 2022). Another concern is that by the time Alzheimer’s disease is diagnosed, the damage may be too advanced for monotherapies targeting Tau to reverse its progression, and treatment of a singular contributing factor might not be enough to salvage the situation. Still, the Tau propagation hypothesis provides a compelling alternative to the amyloid cascade hypothesis, especially given its closer alignment with Alzheimer’s disease progression. However, the theory faces significant scientific and therapeutic challenges that must be addressed. Figure 1. Depicts the location of Tau (red dots) relative to the anatomical damage associated with Alzhimer’s disease progression. The darker the region of the brain the more damaged the area. The darker the dot the higher concentration of deposits there are in the area. Figure 2. Depicts the location of Aβ (red dots) relative to the anatomical damage associated with Alzheimer’s disease progression. The darker the region of the brain the more damaged the area. The darker the dot the higher concentration of deposits there are in the area.   The Neuroinflammation Hypothesis: A Slippery Slope Inflammation is an essential physiological process, enabling the body to combat injury and infection; the surrounding tissue fills with fluid medium, like cerebrospinal fluid, to facilitate the transport of healing metabolites and immune cells that can fight off potential infections. However, prolonged inflammation can be detrimental and cause the death of the cells in that area (Wang et al., 2023). This effect is especially pronounced in the brain, where each neuron plays a vital role in overall function. Microglia and astrocytes are responsible for inflammatory responses in the brain. More specifically, microglial cells are integral to brain health at all stages, and, in the case of non-injury, they primarily scan the surrounding area waiting to be activated (Wang et al., 2023). However, once activated, microglia can polarize into two distinct states: the mobile, pro-inflammatory M1 state and the anti-inflammatory M2 state (Wang et al., 2023). In AD, the M1 form predominates, spreading inflammation-promoting metabolites like cytokines, chemokines, etc. (Wang et al., 2023). When it comes to the relationship between microglia and the progression of AD, the temporal lines between hallmarks of the disease get complex. Activated microglia not only promote the aggregation of Aβ and Tau but are also influenced by these proteins, creating a vicious cycle. Evidence suggests that microglial activation and the resulting neuroinflammatory response may precede Aβ and Tau pathologies in some cases (Calsolaro & Edison, 2016). For example, mutations in the TREM2 gene, which encodes a receptor on microglia that regulates inflammation, are more prevalent in AD patients. These mutations impair TREM2’s ability to suppress cytokine production and mediate inflammatory responses, allowing unchecked inflammation even in the absence of significant Aβ or Tau changes (Calsolaro & Edison, 2016). The mutation triples the risk of development of late-onset AD (Calsolaro & Edison, 2016). Dark or dystrophic microglia are also a newly discovered phenotype of glial, characterized by aberrations in the chromatin, tightly wound DNA (Wang et al., 2023). Dark microglia have been observed to precede the spread of Tau pathology, indicating an interesting and novel temporal landmark (Wang et al., 2023). Epidemiological data supports clinical systemic inflammation as a risk factor which is strongly associated with the development of AD as well as correlated conditions like obesity, diabetes, cardiovascular disease, and metabolic syndrome (Calsolaro & Edison, 2016). Interestingly, prolonged use of non-steroidal anti-inflammatory drugs (NSAIDs) appears to provide some protection against AD, although clinical trials have yielded mixed results (Calsolaro & Edison, 2016). Though, in the literature review, the authors still attempted to characterize Aβ as the precursor to most mechanisms, which could be due to an adherence to upheld dogma or a lack of concrete clinical evidence allowing them to shift their hypothesis effectively. Potential treatments in this vector may be more effective than the previously mentioned Tau targeted and Aβ as it might mitigate damage being proliferated. Prospective medical interventions could include suppressing microglial priming in the pre-clinical phase of the disease, modulating microglia polarization to a more anti-inflammatory phenotype, and limiting the pro-inflammatory response of the microglia (Wang et al., 2023). These options include novel or well-researched targets and treatments, like statins, antioxidant supplementation (folic acid, omega-3 fatty acids), NF-kB, etc. (Wang et al., 2023). It bypasses the targeting issue seen in Tau and the miscorrelation between cognitive decline and Aβ plaques. However, these approaches are not without risks. Using agents that would inhibit the natural immune progress of the brain, such as microglia modulation or limiting the proinflammatory response, could leave individuals vulnerable to infections, and infections in the brain are particularly devastating for the same reasons cell death in the brain is devastating. Trying to See the Bigger Picture The Amyloid cascade, tau progression, and neuroinflammation hypotheses each highlight vital aspects of Alzheimer’s disease (AD) progression but fall short of crafting a definitive antithesis to the development of AD. To truly understand AD, we must widen the scope of inquiry, integrate diverse theories, examine interwoven mechanisms, and challenge entrenched perspectives. A unified understanding of all the factors at play in this disease is going to prove necessary for the comprehension and development of an effective treatment and, eventually, a cure. In the next article in this series, we will explore new hypotheses as well as up-and-coming ideas, aiming to build a more comprehensive understanding of this increasingly prevalent disease. Stay tuned! References Calsolaro, V., & Edison, P. (2016). Neuroinflammation in Alzheimer's disease: Current evidence and future directions. ALZHEIMERS & DEMENTIA, 12, 719-732. https://doi.org/10.1016/j.jalz.2016.02.010 Frisoni, G., Altomare, D., Thal, D., Ribaldi, F., van der Kant, R., Ossenkoppele, R.,…Dubois, B. (2022). The probabilistic model of Alzheimer disease: the amyloid hypothesis revised. NATURE REVIEWS NEUROSCIENCE, 23, 53-66. https://doi.org/10.1038/s41583-021-00533-w Imbimbo, B., Ippati, S., Watling, M., & Imbimbo, C. (2023). Role of monomeric amyloid-β in cognitive performance in Alzheimer's disease: Insights from clinical trials with secretase inhibitors and monoclonal antibodies. PHARMACOLOGICAL RESEARCH, 187, Article 106631. https://doi.org/10.1016/j.phrs.2022.106631 Kapoor, M., & Chinnathambi, S. (2023). TGF-β1 signalling in Alzheimer's pathology and cytoskeletal reorganization: a specialized Tau perspective. JOURNAL OF NEUROINFLAMMATION, 20, Article 72. https://doi.org/10.1186/s12974-023-02751-8 Kepp, K., Robakis, N., Hoilund-Carlsen, P., Sensi, S., & Vissel, B. (2023). The amyloid cascade hypothesis: an updated critical review. BRAIN, 146, 3969-3990. https://doi.org/10.1093/brain/awad159 Liu, P., Xie, Y., Meng, X., & Kang, J. (2019). History and progress of hypotheses and clinical trials  for Alzheimer's disease. SIGNAL TRANSDUCTION AND TARGETED THERAPY, 4, Article 29. https://doi.org/10.1038/s41392-019-0063-8 Pascoal, T., Benedet, A., Ashton, N., Kang, M., Therriault, J., Chamoun, M.,…Rosa-Neto, P. (2021). Microglial activation and tau propagate jointly across Braak stages. NATURE MEDICINE, 27, 1592-+. https://doi.org/10.1038/s41591-021-01456-w Roda, A., Serra-Mir, G., Montoliu-Gaya, L., Tiessler, L., & Villegas, S. (2022). Amyloid-beta peptide and tau protein crosstalk in Alzheimer's disease. NEURAL REGENERATION RESEARCH, 17, 1666-1674. https://doi.org/10.4103/1673-5374.332127 Takeda, S. (2019). Tau Propagation as a Diagnostic and Therapeutic Target for Dementia: Potentials and Unanswered Questions. Front Neurosci ,  13 , 1274. https://doi.org/10.3389/fnins.2019.01274 Wang, C., Zong, S., Cui, X., Wang, X., Wu, S., Wang, L.,…Lu, Z. (2023). The effects of microglia-associated neuroinflammation on Alzheimer's disease. FRONTIERS IN IMMUNOLOGY, 14, Article 1117172. https://doi.org/10.3389/fimmu.2023.1117172 Yadollahikhales, G., & Rojas, J. (2023). Anti-Amyloid Immunotherapies for Alzheimer's Disease: A 2023 Clinical Update. NEUROTHERAPEUTICS, 20, 914-931. https://doi.org/10.1007/s13311-023-01405-0

By Barbara Bocanegra Fueling the Brain Think about the last thing you ate. Recall its taste, smell, and how it felt as it settled in your stomach. We assume most of our food ends up there, right? But what you may not realize is that what you consume each day does more than just satisfy your hunger—it fuels you! And that fuel powers your brain. Imagine it this way: we are like cars that need fuel to run. Just as gas powers an engine, the food we eat fuels our brain, driving its performance. But how exactly does this work? What is the real connection between what we eat and how it affects our brain functions? To understand this, we need to dive deeper into the link between nutrition and its effects on our cognitive brain. What’s Really Happening? When we eat, our body breaks down food into nutrients, one of the most important being glucose. Glucose is often called the brain’s primary fuel because neurons, the cells responsible for thinking and memory, rely heavily on it to function. Once glucose enters the bloodstream, it needs help getting into the brain. This is where glucose transporters—special proteins in the blood-brain barrier—play a crucial role. They act like “gatekeepers,” ensuring glucose reaches the brain, even during times of low blood sugar. Research shows that glucose transporter proteins, particularly GLUT1, are essential for maintaining healthy brain function. A deficiency in these transporters has been linked to serious neurological disorders like seizures and cognitive impairments (De Vivo et al., 1999). This underscores how critical a steady supply of glucose is for brain performance. However, not all diets support optimal glucose transport. Studies have found that consuming a high-sugar diet can overwhelm these systems, leading to erratic glucose levels and potential damage to brain cells (Parihar & Hemnani, 2007).Over time, this may impair memory and reduce attention span, showing just how closely diet quality impacts brain health. Pump the Brakes Let’s return to our earlier analogy: every car needs fuel to run, but not all fuel is suited for every vehicle. Imagine you have a diesel car and mistakenly fill it with regular gasoline. It’s safe to say it wouldn't run properly. Similarly, consuming highly processed foods or those high in sugar may not provide the essential nutrients our bodies need to function optimally and can affect our glucose levels. According to the Texas Institute for Neurological Disorders (n.d.), a high-sugar diet can lead to an excess of glucose in the brain. Studies have linked this overconsumption to memory and cognitive deficiencies. For instance, elevated glucose levels can harm the hippocampus, the brain region responsible for forming and retrieving memories. This impairment happens through mechanisms such as inflammation caused by excess sugar, oxidative stress, and insulin resistance. Insulin is vital as it provides energy to brain cells, and when the brain becomes resistant to insulin, it struggles to function efficiently. Over time, this can cause difficulties with learning and memory. All of this makes it harder for the hippocampus to work properly (Machado et al., 2023). The implications are clear: the quality of our food matters. Diets rich in processed, sugary foods can create an overload of glucose, leading to spikes and crashes that leave us feeling fatigued, unfocused, or even irritable. Over time, this pattern can harm brain health, affecting areas such as memory retention and attention span. Does This Mean I Should Eat Less? Not necessarily! While it’s important to limit excessive sugar intake, cutting food from your diet altogether is not the solution. Malnourishment, or not consuming enough calories and nutrients, can also harm brain health. When the brain is deprived of fuel, its ability to perform essential tasks such as decision-making, problem-solving, and emotional regulation can suffer significantly (National Eating Disorders Collaboration, n.d.). For example, individuals with eating disorders or severe food insecurity often experience "brain fog," difficulty concentrating, or trouble with executive functioning. This underscores the delicate balance needed to nourish the brain effectively without overloading it with harmful substances. What Can I Do? The solution is to balance and make mindful choices about the food you eat. Focus on consuming a variety of nutrient-rich foods that provide your brain with the energy it needs to function at its best. Include whole grains, fruits, vegetables, lean proteins, and healthy fats in your diet, as these foods contain the essential nutrients that support cognitive performance. Limit highly processed foods and those loaded with added sugars, as they can cause spikes and crashes in energy levels and may negatively impact your memory and focus. Additionally, staying hydrated is just as important. Your brain relies on water to maintain its functions, and even mild dehydration can affect your concentration and mood. (Very Big Brain, n.d.; Continental Hospitals, 2024) Water supports cognitive processes by ensuring that nutrients are transported to brain cells and helping maintain proper neurotransmitter function. Inadequate hydration can lead to cognitive slowdowns, decreased attention, and irritability.  (Very Big Brain, n.d.; Continental Hospitals, 2024) By fueling your body and brain properly with a good diet, you set yourself up for better mental clarity, stronger memory, and improved emotional well-being. Remember, the food you eat isn’t just fuel—it’s the building block of your health and happiness. References Cavezza, S. (n.d.). Brain health and functional medicine . Dr. Shelley Cavezza. Retrieved November 26, 2024, from   https://www.drshelleycavezza.com.au/brain-health-functional-medicine De Vivo, D. C., Trifiletti, R. R., Jacobson, R. I., Ronen, G. M., Behmand, R. A., & Harik, S. I. (1999). Defective glucose transport across the blood-brain barrier as a cause of persistent hypoglycorrhachia, seizures, and developmental delay. Annals of Neurology, 45 (1), 8–15. https://doi.org/10.1002/1531-8249(199901)45:1<8::AID-ART4>3.0.CO;2-V Ding, Y., Liu, Y., & Wang, J. (2020). Glucose transporters in the brain in health and disease. Frontiers in Aging Neuroscience, 12 , Article 82.   https://doi.org/10.3389/fnagi.2020.00082 National Center for Biotechnology Information. (n.d.). Glucose. Bookshelf . Retrieved from   https://www.ncbi.nlm.nih.gov/books/NBK453140/ National Eating Disorders Collaboration. (n.d.). The starved brain: Can what we eat determine how we think?  Retrieved from   https://nedc.com.au/eating-disorder-resources/find-resources/show/issue-59-i-the-starved-brain-can-what-we-eat-determine-how-we-think/ Parihar, M. S., & Hemnani, T. (2007). Alzheimer’s disease pathogenesis and therapeutic interventions. Physiology & Behavior, 92 (1–2), 1–16. https://doi.org/10.1016/j.physbeh.2007.05.016 Texas Institute for Neurological Disorders. (n.d.). The effects of a high sugar diet on the brain.  Retrieved October 23, 2024, from   https://www.texasinstituteforneurologicaldisorders.com/uncategorized/effects-high-sugar-diet-brain/ Machado, U. F., Saad, M. J. A., & Moreira, T. S. (2023). Glucose transport and utilization in the hippocampus: From neurophysiology to diabetes-related development of dementia. International Journal of Molecular Sciences, 24 (22), 16480.   https://doi.org/10.3390/ijms242216480 Very Big Brain. (n.d.). Water intake and neuroplasticity: The hydration-brain link.  Retrieved from https://verybigbrain.com/body-brain-connection/water-intake-and-neuroplasticity-the-hydration-brain-link/

Alexa Kightlinger “Sorry, I’ve got the memory of a goldfish” has been a common adage to express one’s extreme forgetfulness. It has been a longtime myth that goldfish only have a memory that lasts for approximately seven seconds. Since then, a plethora of studies have disproved this misconception. One of the most notable studies was conducted by Oxford researchers who trained goldfish to swim across a tank for a food reward while changing the starting position and strip pattern of the tank. Researchers concluded that goldfish used optic flow, the motion of objects in a scene caused by the observer moving, to aid in navigation and remember visual cues (Sibeaux et al., 2022). Many land-bound species are known to use optic flow, but goldfish process the information differently, instead relying on contrast changes to make it to their destination (Sibeaux et al., 2022). Many other researchers have also shown that goldfish are not the simple-minded creatures we once thought them to be (Davis & Agranoff, 1966 & Givon et al., 2023).  Goldfish aside, imagine how your life would be impacted if you were only capable of living within a seven-second window. That would not be living, merely surviving as you constantly place “catch-up” in regards to your own life. While memory exists on a spectrum of sorts, the function it provides us with is insurmountable.  Learning : Through the encoding of new memories when experiencing novel situations, we can store and retrieve information later to learn new information and skills. Language and Communication : Memory helps us use the proper vocabulary, grammar, and syntax allowing for more effective communication.  Social Interaction:  Remembering past interactions, faces, and names of others allows us to build and maintain relationships. Problem Solving : Drawing on our past experiences or failures can help us approach issues from a new and different perspective. These are just a few key skills one may lose when memory is impacted. There are several types of memory, all of which come together to help us perform everyday tasks. I’ve briefly summarized them below so that we can better understand how memory is far more complex than most people think. Sensory:  Short-term storage of sensory information gained from the five senses. Echoic:  Information from auditory senses. Iconic:  Information from visual senses. Haptic: Information from touch. Short-Term: Retains information for about 30 seconds. Working: Deals with the storage, maintenance, and manipulation of information and is used in processes such as learning and reasoning. Long-Term: Technically has no limit as to how long this memory can last. Implicit (Non-Declarative):  Memories that cannot be expressed in words. Procedural:  Involves memory for actions. Explicit (Declarative):  Memories that can be put into words. Episodic: Memories of events; autobiographical. Semantic:  General facts and knowledge. (Camina & Güell, 2017) I’m sure by now it wouldn’t be surprising to know this is just a consolidated list of the general categories of memory. However, if I were to go into every single type we would be here quite a while. Losing any single one would certainly impact the way you went about your normal life. The idea that memory, an aspect so important and closely tied to one’s identity can be tampered with is certainly a frightening idea. Imagine experiencing a memory lapse more severe than simply forgetting to submit a homework assignment during a busy workweek or misplacing your keys for a few minutes. Now imagine losing, not just one type of memory, but almost every type of memory and being confined to only remembering life in a a seven to thirty second window. That’s the life of Clive Wearing. A talented musician and brilliant scholar who became infected with herpes simplex encephalitis, causing damage to his medial temporal lobe (Cavaco et. al., 2014) as well as decimating his hippocampus (Suddendorf et. al., 2009). This damage resulted in him developing chronic forms of anterograde and retrograde amnesia. Despite this, his procedural memory remains intact as his ability to sight-read music and play the piano continues to remain strong (Cavaco et. al., 2014). While he can still at large  communicate effectively and recognize his life, much of his life is lived in the present (Suddendorf et. al., 2009). Continually, Wearing is under the impression he has just woken up or recovered from being dead which his wife, Deborah Wearing, captures in her book, Forever Today. While his case is inherently unique, the damage he sustained to his hippocampus which resulted in episodic memory deficiency but a retention in semantic memory tracks with other cases and implies that these types of memories have distinct mechanisms, making them double dissociates (Suddendorf et. al., 2009). Damage to the bilateral hippocampus suggests that it plays a critical role in the retrieval of details used to aid in episodic memory which can play roles in both real and imaged scenarios (Suddendorf et. al., 2009).  Wearing’s case has been an important source of information for researchers studying the role the hippocampus plays in memory formation as well as showing the distinction between short and long term memory. Not only has it shined a light on a neuropsychological perspective, but also forces us to think about our own sense of identity and perception. Wearing is forced to experience every moment as if it is the first time he has experienced it. Not only has this been a challenge for him, but for his family and loved ones who he has forgotten. Those who have lost or are currently experiencing a loved one suffering from Alzheimer's or dementia can state first hand how daily life changes and the frustration that comes with it. And yet, despite these challenges, Clive Wearing still finds joy in music and connecting with his loved ones, even if the memory only lasts for seconds. His story should serve as a reminder to cherish and nurture the relationships between our loved ones.  References  Cavaco, S., Feinstein, J. S., van Twillert, H., & Tranel, D. (2014). Musical memory in a patient with severe anterograde amnesia. Journal of Clinical and Experimental Neuropsychology. 34 (10), 1089-1100. https://doi.org/10.1080/13803395.2012.728568 .  Davis, R. E. & Agranoff, B. W. (1966). Stages of memory formation in goldfish: evidence for an environmental trigger. Proceedings of the National Academy of Sciences of the United States of America 55 (3), 555-559. https://doi.org/10.1073/pnas.55.3.555 .  Givon, S., Altsuler-Nagar, R., Oring, N., Vinepinksy, E., & Segev, R. (2023). Lateral and medial telencephalic pallium lesions impair spatial memory in goldfish. Brain Research Bulletin, 204( 1 ) , 110802. https://doi.org/10.1016/j.brainresbull.2023.110802 . Sibeaux, A., Karlsson, C., Newport, C., & Burt de Perera, T. (2022). Distance estimation in the goldfish ( Carassius auratus ). Proceedings of the Royal Society B: Biological Sciences. 12 :289. https://doi.org/10.1098/rspb.2022.1220 . Suddendorf T., Addis, D. R., & Corballis, M. C. (2009). Mental time travel and the shaping of the human mind. Philosophical Transactions of the Royal Society B 364, 1317-1324. https://doi.org/10.1098/rstb.2008.0301 .