More Than Just Tired- How Sleep Impacts Your Well Being

Sleep deprivation is normalized especially among adolescent years. The daily pressures of school, social life, extracurricular activities, etc. demand an obscene amount of time, leaving little to no time for restorative sleep. Not to mention, the emergence of the digital age has offered new barriers to the acquisition of adequate sleep. Digital technology serves as a constant distraction in daily life, especially around bedtime. Research suggests that the effects of minimal sleep go far beyond just feeling tired. In a recent talk, it became clear that lack of sleep has significant effects on brain function and overall health, especially during a critical period of development. 

In her recent talk, Stephanie Crowley emphasized that adolescents have a natural shift in their circadian rhythm. This notable biological shift causes individuals of adolescent age to feel increasingly awake at later hours. Crowley further described that sleep pressure builds more slowly in adolescence. Thus, allowing them to stay awake longer without feeling tired. Not to mention, the presence of external factors such as early school start times, academic demands, social interactions, and extracurricular activities demand them to wake up early. The combination of these internal biological changes and external pressures constitute what Crowley referred to as the perfect storm; an interplay between biological changes and external forces. This chronic lack of sleep, referred to as sleep deprivation, was described by Crowley as having a negative impact on emotional regulation. Thus, leading to increased levels of irritability, mood swings, and occurrences of risky/impulsive behavior. 

The ideas presented by Crowley closely connect with recent work conducted by Shah et al. (2025). Shah and colleagues (2025) facilitated an umbrella review that examined findings across a wide range of studies on sleep deprivation and health outcomes. The review found that insufficient sleep is correlated with high prevalence of mental health issues and disorders; including depression and anxiety. The study further identified that sleep deprivation was correlated with a notable decline in cognitive functioning. They further found that the effects of sleep deprivation extended far beyond the psychological domain, identifying several negative physical health outcomes. These included, but were not limited to, disruptions in metabolic processes and immune function. The analysis and integration of a wide range of results, using the umbrella review, provided strong and overwhelming evidence that the effects of sleep deprivation are widespread and potentially detrimental to both mental and physical health. 

Crowley and Shah et al. (2025) comprehensively demonstrate the negative effects that lack of sleep can have on the human. Crowley explained the brain regions affected by sleep deprivation and their involvement in emotional regulation. Thus, it is not surprising that Shah et al. (2025) found strong links between inadequate sleep and mental health issues. Likewise, they both highlight the impact that chronic sleep deprivation can have on cognitive functioning. Together they show that the effects extend far beyond cognitive or mental health. 

These inclusive findings, from both Crowley’s talk and the review conducted by Shah et al. (2025) incur the question; should our society focus more on attaining adequate sleep instead of productivity? Should the physical and mental toll that sleep deprivation has on both adolescents and adults be normalized? They beg to question if our society has centered life around the wrong things. Should society restructure its function, and especially focus on ensuring adequate sleep for teens? It is unsure if nascent evidence will encourage systemic change, however, the research has remained generally consistent and reliable. 

References 

‌Crowley, S.J., Wolfson, A.R., Tarokh, L. and Carskadon, M.A. (2018), An update on adolescent sleep: New evidence informing the perfect storm model☆. Journal of Adolescence, 67: 55-65. https://doi.org/10.1016/j.adolescence.2018.06.001

Shah, A. S., Pant, M. R., Tulasiram Bommasamudram, Nayak, K. R., Spencer, Gallagher, C., K. Vaishali, Edwards, B. J., Tod, D., Davis, F., & Pullinger, S. A. (2025). Effects of Sleep Deprivation on Physical and Mental Health Outcomes: An Umbrella Review. American Journal of Lifestyle Medicine. https://doi.org/10.1177/15598276251346752

Deep Convolutional Neural Networks in Medical Imaging

Dr. Baker’s article about Deep Convolutional Neural Networks (DCNNs) being unable to replicate the configural perception process utilized by humans made me think about what  DCNNs can do and what more they could someday be able to do. Potential uses of Deep Learning Models within neuroscience and biology are frequently related to disease pathology. Utilizing DCNNs has clear implications for recognizing biomarkers of various diseases. Matsuzaka and Iyoda discuss the many implications of convolutional neural networks within diagnostic medicine and pathology. They can analyze a wide range of medical images like x-rays, MRI scans, CT scans, and ultrasound images. They can be more accurate and more efficient than people if the models are trained correctly. Training these algorithms is however a current limitation. It is difficult to compile large and diverse sets of data to train DCNNs on, especially for rare pathology and disease. Dr. Baker and his colleague discussed this problem in their paper and argue that visual models like DCNNs need to be trained on a wide range of object tasks, not just simple category recognition to make them more robust tools. Could training DCNNs to utilize configural perception similarly to human perception help make for more accurate and efficient models when it comes to identifying pathology?

Dr. Baker’s research found that DCNNs are not as accurate as humans when it comes to the tasks that they tested for. However, research that Matsuzaka and Iyoda highlighted a finding of DCNNs performing better than radiologists when it comes to detecting breast cancer in mammograms, leading to fewer false negatives and false positives. If DCNNs were trained to use more configural perception, could they become worse at tasks like recognizing breast cancer in scans? Or would making them use more configural perception allow them to be better utilized across a wider variety of pathologies and could it help with the issue of small sets of data to train models on for less common pathologies?

            Other than the performance aspect of DCNNs in medical image analysis, practicality also has to be considered. There would be a significant price associated with using DCNNs, as data needs to be collected, models need to be trained, and technicians need to be hired to utilize it properly. However it could also lead to less work on the part of people, which would lead to a reduction in the amount of people needed. If they are able to prove more reliable and accurate at analyzing images, there would be less need to extra imaging which would reduce costs.

            Another large concern addressed by Matsuzaka and Iyoda is that of the “black box effect.” Results from DCNNs when it comes to recognition are generally not interpretable leads to the methodology of how the model got to its result not understandable and this lack of transparency leads to mistrust in the models. Research like Dr. Bakers that seeks to elucidate the mechanisms behind DCNNs can help to reduce this effect. By further studying DCNNs and comparing it to human perception, DCNNs usage for medical imaging can be optimized.   

- Sai Kanuru

Baker, N. E., & Elder, J. T. (2022). Deep learning models fail to capture the configural nature of human shape perception. IScience, 25(9), 104913–104913. https://doi.org/10.1016/j.isci.2022.104913

Yasunari Matsuzaka, & Masayuki Iyoda. (2026). Applications, image analysis, and interpretation of computer vision in medical imaging. Frontiers in Radiology, 5, 1733003–1733003. https://doi.org/10.3389/fradi.2025.1733003

When Words Don’t Do Enough: How Our Brains Connect the Gaps With Gestures

When Words Don’t Do Enough: How Our Brains Connect the Gaps With Gestures

People tend to think of language as the brain’s main form of communication. What if the brain doesn’t only rely on the auditory information it receives but just as much on visual stimulation, especially when understanding is hard?

In this course, we have learned that language is not processed as a single channel but as a dynamic, multimodal system by the brain. This becomes clearer when we look at how people comprehend communication in ordinary situations. The translation of words is but a small portion of the huge work of communicating. Effective communication requires attention, prediction, and integration of different brain systems. A recent research study of bilingual youngsters has demonstrated that the integration of different facets of communication is important. Researchers observed that children used more hand motions that accompany speech when they listened to stories in their weaker language. In fact, individuals were more likely to remember details of a story when the gestures (hands)  in their weaker language matched the verbal meaning, but not in their primary language.   

That implies something more profound about how the brain reacts to stress. When language becomes more difficult to understand, the brain doesn’t just try harder; it compensates. In reality, the young people in the study, after having processed their inferior language, shifted their visual attention and paid more attention to the speaker’s hands. The increased attention meant gestures had a greater effect on memory and understanding.

But not all gestures were that helpful. Sometimes, gestures can be detrimental to comprehension, in particular in the stronger language, when they provide redundant or incongruent information. This demonstrates a very important constraint: extra cues can benefit the brain, but only if they are in addition to the message. Otherwise, they interfere with processing and increase cognitive load.

This finding is directly relevant to more general notions in neuroscience about resource allocation and attention. The brain's processing power is finite and thus is constantly making choices about what to focus on. Less capable systems (e.g., language understanding) recruit other systems (e.g., visual processing) to help them. In this case, gesture acts as a kind of “back-up system” for understanding.

This has implications for the real world, outside of the lab. Take into account classes in which the learners are learning a language other than their mother tongue. Teachers are natural users of gestures or movement, and research shows the importance of gestures for understanding. The barriers of language often pose problems in international communication. Even in ordinary conversations, gestures can be more significant than we realize in transmitting complex ideas.

This also raises interesting considerations about the evolution of communication. We live in a text-heavy world of emails, messages, and AI-generated replies, and in doing so, we are stripping away one of the brain’s most powerful processing tools: visual, embodied clues. If gestures help understanding when words become hard, what happens when these clues are entirely removed?

This study ultimately re-conceptualizes our idea of communication. It is more than knowing the right words to say or speaking in a clear voice. It’s about how the brain makes meaning out of various streams of information, particularly when it is challenged.

The crucial lesson is not just that gestures are helpful, but rather that the brain is continually changing and trying to make sense of the world with whatever information it has. So the real question is: are we communicating as well as we think we are? Or, since understanding depends on more than just words, are we shutting part of the brain out of the conversation?

Education Reform: The Need for a Change in Thinking Regarding Neurodivergent Learning

In recent years, the United States has experienced a surge in diagnoses of neurological disorders with the most prevalent being Autism Spectrum Disorder (ASD). ASD has seen as much as a 300% increase in diagnosis in the last 20 years.1 With such a substantial increase in such a short amount of time, it brings into question how our education systems need to adjust to suit the needs of everyone in our society.

In an article titled, “Our Nation’s Public Schools are Failing Neurodivergent Learners. That Needs to Change,” the director of the Education Collaboratory at Yale, Christina Cipriano, provides a personal insight regarding the changes that are needed in the United States’ public education system. Cipriano begins by explaining a personal experience of hers in which the teacher of her neurodivergent daughter expressed that her daughter was “taking instructional time away from other students” after receiving an official diagnosis, prompting the creation of an Individual Education Plan (IEP). This was a shock to Cipriano and caused a feeling that the school was “waiting for her daughter to fail instead of providing a way for her to succeed.” Cipriano’s daughter is one of many in this country not being provided this need. Cipriano continues by explaining that our public schools need to change the way they operate to better support neurodivergent learning. One criticism is that despite funding, states are still having trouble hiring suitable special education educators. This poses an issue as most educators have only taken one class on how to educate students with disabilities, putting into question if this is a good enough standard. A large point being made is that neurodivergent students should not need to learn how to learn differently, meaning closer to the general population. Doing so would decrease the effectiveness of the teaching and the understanding of the student. Education systems should adjust to the students they are teaching and incentivise better understanding of how to teach to more unconventional learners.2

There is a lot of reason for the necessity of these changes in the fact that those with neurodevelopmental disorders (NDDs) do in fact learn differently than others. Often it is not a lack in the ability to understand a concept, rather it is the way it is presented. In a study titled, “A single-session behavioral protocol for successful event-related potential recording in children with neurodevelopmental disorders,” Maggie W. Guy et al. explore the use of Event-Related Potentials (ERPs) and their use in data collection along with the effectiveness of a single-session protocol. ERPs are a type of brain measurement collected using EEG. They are a useful tool in measuring brain activity because they are able to track very fast responses to stimuli in the brain. Traditionally, individuals with neurodevelopmental disorders would be excluded from studies looking at ERPs, but not only individuals with NDDs but also children with anxiety, lower IQ, and more sensory sensitivity. This can become an issue when data excluding these individuals causes a skew toward higher functioning more compliant children, which isn’t representative of the general population. The idea behind this study is that by developing a single-session protocol in which individuals are desensitized and prepared for data collection beforehand, then a single-session could be used, prompting more inclusion of data from individuals with NDDs. This specific single-session protocol was designed to support behavior and help young children with ASD and fragile X syndrome (FXS) by preparing them before the lab visit, desensitizing them to the EEG cap, and personalizing their experience through gauging preferences. Results of the single-session protocol show that it was effective for 100% of the typically developing (TD) children and 73% successful for children with ASD. In children with FXS, however, it was only about 38% successful. Some other findings regarding the success of these groups are that higher cognitive maturity and less severity in autism symptoms led to more success in all groups. Surprisingly, slightly higher anxiety in children with FXS was linked to better performance and sensory sensitivity did not reduce success as expected. These findings show that in instances the protocol can work, but does not work equally for everyone. This is shown through the high success in TD and ASD children and low success in children with FXS. Inclusion of these individuals in studies depends a lot on how the study is designed; it must account for differences and have intentional adjustments. From this information a key takeaway is formed, that is, there isn’t a “one size fits all” solution.3 

This takeaway can be applied when looking at the argument for reform in education in the US. As in the study by Guy et al., success of the individuals may depend on how the system has been designed to account for the differences of the individuals. The single-session protocol worked with some groups but wasn’t as effective with the FXS group; this is similar to the way that standardized teaching methods have worked with a majority but have failed to support individuals in a broader range of neurodivergent learners. These examples highlight that there is a need to create environments where all students are given a chance to succeed. Expecting students to adapt to rigid systems is exclusive to those who learn more effectively using different methods. Incentivising more development for teachers to learn and understand how to create more personalized approaches that meet diverse learning needs would be beneficial to the students and families. 

References:

1. Is there an autism epidemic? | johns hopkins | Bloomberg School of Public Health. June 6, 2025. Accessed April 29, 2026. https://publichealth.jhu.edu/2025/is-there-an-autism-epidemic. 

2. Cipriano C. Our nation’s public schools are failing neurodivergent learners. that needs to change. - edsurge news. EdSurge. April 20, 2026. Accessed April 28, 2026. https://www.edsurge.com/news/2024-02-14-our-nation-s-public-schools-are-failing-neurodivergent-learners-that-needs-to-change. 

3. Guy MW, Black CJ, Hogan AL, Coyle RE, Richards JE, Roberts JE. A single‐session behavioral protocol for successful event‐related potential recording in children with Neurodevelopmental Disorders. Developmental Psychobiology. 2021;63(7). doi:10.1002/dev.22194 

Do I really need 8 hours?

During the second half of the semester, I had the pleasure of listening to Dr. Stephanie Crowley’s research presentation titled “An Update on Adolescent Sleep: New Evidence Informing the Perfect Storm Model,”centering around the effect of sleep on young adolescents and how it can alter their circadian rhythm. This research highlighted how sleep and biological clocks affect how an adolescent interacts during hours of sleep as well as waking hours. This made me more interested in the research of how sleep can not only affect young adolescents throughout their week, but also, how their regulation and cognitive function can be altered as well due to irregular sleep patterns.

In a study done in 2011, the research described the two biological systems that go through modifications during maturation: sleep and regulation of the homeostatic process and the circadian rhythm. In Dr. Crowley’s research, the study focused on summarizing current progression and understanding how new progress affects and benefits our understanding of sleep modification and regulation and how behavior regarding sleep during the maturation phase has altered. 

In a study titled “Cognitive Performance, Sleepiness, and Mood in Partially Sleep Deprived Adolescents: The Need for Sleep Study”, published in 2016, researchers found their participants demonstrating “incremental deterioration in sustained attention, working memory and executive function, increase in subjective sleepiness and decrease in positive mood” (Lo et a., 2016). This highlights how even just a week of sleep deprivation affects young adolescents’ executive cognitive functions as well as mental health, impacting their mood and alertness. They discovered that the sleep missed over the week-long sleep deprivation was not recovered even after 2 full nights of dedicated sleep recovery time. This demonstrates that in order for young adolescents to improve in many aspects of their daily functioning, appropriate sleep is demanded.

Similarly, in the study titled “The intersection between sleep science and policy: introduction to the special issue on school start times,” published in 2017, researchers addressed the issue surrounding delay in school start time and its positive effects on not only performance in their students but also cognitive alertness. The research study represented a large cross-section of many diverse students, all across the world. Additionally, with the use of meta-analysis, it was concluded that “later start times were associated with less daytime sleepiness and tardiness to school, all of which have important implications for students’ academic performance” (Troxel and Wolfson, 2017). This demonstrates how not only do students themselves wish for a later start time, but also, how it is substantially better for their cognitive function and mental health as well. This allows the student to stay more attentive during school hours as well as benefiting their circadian rhythmic clock. The study also provided information regarding research done within the last three decades, stating that even though there has been a hugely beneficial jump in understanding circadian rhythms and bioregulatory processes, not much has been done to effectively benefit those who need it. This social awareness and acceptance is the first step to understanding and addressing a large problem that has been affecting many young adolescents for many decades.

Together, the research explores the topic of sleep and the understanding of circadian rhythms and how it centers around how young adolescents behave, sleep and score in their academics. In particular, when it comes to students who get poor sleep or are forced to wake up at much earlier hours than their circadian rhythm agrees to, it can take a toll on their mental health, academics, as well as bioregulatory systems, encouraging an environment of mood swings, irritation as well as even sleeping during classes. In many ways, it would be incredibly beneficial to understand and address the data surrounding the benefits of delayed school starting hours, as it could be incredibly significant for the students as well as the school districts.

References:

Crowley, Stephanie J., et al. “An update on adolescent sleep: New evidence informing 

The perfect storm model☆.” Journal of Adolescence, vol. 67, no. 1, 13 June 

2018, pp. 55–65, https://doi.org/10.1016/j.adolescence.2018.06.001.

Lo, June C., et al. “Cognitive Performance, Sleepiness, and Mood in Partially Sleep 

Deprived Adolescents: The Need for Sleep Study.” Sleep, vol. 39, no. 3, 1 Mar. 2016, pp. 687–698, https://doi.org/10.5665/sleep.5552.

Troxel, Wendy M., and Amy R. Wolfson. “The Intersection between Sleep Science and 

Policy: Introduction to the Special Issue on School Start Times.” Sleep Health, 

vol. 3, no. 6, Dec. 2017, pp. 419–422, https://doi.org/10.1016/j.sleh.2017.10.001.

Sleep Deprivation: Why Sleep in Teenagers is the 'Perfect Storm'

In our neuroscience seminar class at Loyola University Chicago, we discussed how biological and social factors interact to shape teenage sleep patterns. Our guest speaker, Stephanie Crowley, presented research on the “Perfect Storm” model of teenage sleep. This explains why teens often experience short and poorly timed sleep. This research focused on two biological systems, sleep homeostasis and the circadian rhythm. As a teenager, sleep pressure builds more slowly, causing teens to stay awake longer. Additionally, their circadian rhythm shifts, making them feel more awake and alert at night and less in the morning. The speaker emphasized the role of light exposure in influencing sleep timing and circadian rhythm. She discussed that while teenagers are not more sensitive to light than adults, increased exposure to evening light pushes sleep later. Psychosocial factors, like early school start times, social activities, and screen use at night delay sleep, but still require an early wake-up time. Despite needing nine hours of sleep a night, teenagers often get only around seven hours on school nights. These biological and psychosocial factors create the “Perfect Storm” that leads to chronic sleep deprivation in teenagers. 

A study by the University of Surrey, “Math Reveals Why Sleep Patterns Shift With Age, Light, and Routine”, connects to this idea. The study expands on the same “Perfect Storm” model described by Crowley by discussing the effects of light exposure in a mathematical model. Researchers used mathematical modeling to show how sleep is regulated by the interaction between sleep pressure, the body’s internal clock, and light exposure. Their findings suggest that late-night light exposure can disrupt the balance between these factors and create later sleep schedules, similar to Crowley’s findings. These results help explain why teenagers have a later sleep schedule, going to bed and falling asleep later, when exposed to bright light at night. 

Together, these studies highlight how teenage sleep patterns are a result of a combination of biology, psychosocial, and environmental factors. The speaker’s research explains how developmental changes in the brain, psychosocial factors, and exposure to light make teens naturally inclined to stay up later. The study by the University of Surrey builds on this by showing how light and biological systems interact mathematically to delay sleep. These findings, together, suggest that improving sleep in teenagers isn’t related to only changing individual behaviors as previously thought. It will require changes like later school times in order to account for the biological changes that cause later sleep schedules. Understanding how the interaction between biological, social, and environmental factors causes teenagers to struggle with sleep helps to create more effective solutions.

References:

Crowley, Stephanie J., et al. "An update on adolescent sleep: New evidence informing the perfect storm model." Journal of Adolescence, vol. 67, no. 1, 13 June 2018, pp. 55-65, https://doi.org/10.1016/j.adolescence.2018.06.001.

Njolinjo, D. (2025, July 22). Math reveals why sleep patterns shift with age, light, and routine. Neuroscience News. https://neurosciencenews.com/math-sleep-regulation-29512/

Event related potentials: How do they work in different developmental disorders?

        Children are diagnosed with neurodevelopmental disorders every day, including autism spectrum disorder (ASD), Fragile X syndrome (FXS) and ADHD. One of the ways scientists have found to measure these children's neural responses is event-related potentials (ERPs). There are multiple ERPs that are talked about within the two studies done, reporting potential effects of working memory, conflict monitoring, and face processing. 

    In a recent neuroscience seminar, Dr. Maggie Guy came and talked about what ERPs are and how they can be used to see how the brain works in different stages of processing. Dr. guy measured ERPs using voltage oscillations using an EEG to measure the brief stimulus presentation. The study used children with ASD, FXS and siblings of kids with autism to study the responses to faces between the 3 groups. The two ERPs measured were N290 and Nc, where N290 had a peak about 290-350 milliseconds after onset while Nc had a peak around 350-750 milliseconds after the stimulus onset (Guy et al., 2021). 

    Guy was able to show that N290 may have reflected some automatic face recognition, and that the engagement with the task was increased in infants with FXS rather than the siblings of kids with autism. However, a question I have is what is the difference between FXS and autism compared to a different disorder like ADHD? A study done by scientists in the Xinjiang region in China focuses more on ERPS in children diagnosed with ADHD.

    These scientists define ADHD as a common developmental disorder with a core symptom of response inhibition (Gao et al., 2026). Gao and others tested the P300 component and N200 component, testing index of working memory and conflict monitoring respectively. There were 2 separate experiments done and revealed some pretty interesting results. Experiment 1 showed that the combined paradigm of N-back and Nogo indicated both working memory and response inhibition as cognitive processes that are separate but also engaged simultaneously. Experiment 2 showed that children with ADHD responded less accurately compared to typical children, supporting the hypothesis of core executive dysfunction. It was shown that Nogo-N200 components were prolonged with children with ADHD, and the amplitudes of the N-backP300 components were lower in the ADHD than the normal group (Gao et al., 2026).

    Dr Guy and the researchers showed that children with FXS and ASD had more problems recognizing faces, using the ERPs. Dr. Gao was able to show that ERPs are important in children with ADHD as well, noting that those ERPs are possibly responsible for executive dysfunction. ERPs are seen as an important step into more information for those with developmental disorders.

    I am curious to see what Dr. Guy does next. It was noted that it is incredibly hard to get the information they did, and I wonder if it would be easier or harder with different disorders. I have a younger sibling with autism, and I wonder if there are other things that affect her that I cannot see. Autism can be something difficult to have, especially in social situations, and I wonder if more information on the disorder can make it easier for children with autism to live with the disorder socially. 

References

Gao, X., Zhong, L., He, H., Zhang, J., & Yang, W. (2026, April). Response inhibition and working memory in children with attention deficit hyperactivity disorders: An event-related potential study. Science Direct. https://www.sciencedirect.com/science/article/pii/S0387760426000185

            Guy, M. W., Black, C. J., Hogan, A. L., Coyle, R. E., Richards, J. E., & Roberts, J. E. (2021,             November). A single-session behavioral protocol for successful event-related potential recording in      children with Neurodevelopmental Disorders. Developmental psychobiology.                                    https://pmc.ncbi.nlm.nih.gov/articles/PMC9523962/