When Dreams Talk Back: Rethinking Cognition Across Sleep and Wake

            Dr. Gabriella Torres-Plata's research this semester challenged long-held sleep science assumptions and presented evidence that contradicts them. The most significant assumption she challenged was that dreaming could only be studied after the fact. In place of that, Torres-Plata and colleagues have shown that some people who become aware while they are dreaming (lucid dreamers) can receive information and respond while still in REM sleep - they can answer yes/no questions, do basic arithmetic, and identify different sensory inputs based on coded eye movements and slight facial expressions. Torres-Plata and colleagues have opened the door for studying what happens in the mind while we dream, including memory creation, emotional processing and creative problem solving. The previous method of studying dreaming has been limited to the degree to which a person can remember what happened while they were asleep. This study has the potential to help us understand how the brain works at all times, and to make better use of our ability to dream. 

The concept that Torres-Plata explored has additional support in a recent paper published in the journal Neuron titled "Linking Memory and Imagination Across Sleep and Wake States" (Wamsley et al.), that came out in 2024. While Wamsley and his colleagues did not explore dream dialogue, they did find similar brain activity in REM states (where dreams occur), and in states of daydreaming. They were able to observe the way that the brain changes old experiences into something new, using areas of the brain such as the hippocampus and cortical networks. Both processes involve flexible, creative recombination of past experiences, guided by the hippocampus and association cortices. The Wamsley et al. study suggests that dreaming is not just “random noise,” but part of a broader system for simulating, reorganizing, and sometimes inventing mental content. 

Ultimately, the possibility of having a real-time conversation with someone while they are dreaming may provide the opportunity to study how the process of transforming memories occurs on a moment-by-moment basis. However, it also raises many important issues related to privacy, autonomy and the extent to which researchers should be allowed to intrude upon an individuals internal mental processes. Real-time dialogue might eventually allow researchers to probe how memory transformations unfold moment by moment. At the same time, these possibilities bring up important concerns about privacy, autonomy, and how much access researchers should have to an individual’s inner cognitive world. 

Both the seminar and the Neuron article highlight REM sleep as an active and dynamic state—not a pause in consciousness, but a unique mode of thinking. Together they suggest that dreams may be a window into how we imagine, problem-solve, and reshape our emotional experiences, both during sleep and while awake. 

References 

Konkoly, K. R., Appel, K., Chabani, E., Mangiaruga, A., Gott, J., Mallett, R., Caughran, B., Witkowski, S., Whitmore, N. W., Mazurek, C. Y., Berent, J. B., Weber, F. D., Türker, B., Leu-Semenescu, S., Maranci, J.-B., Pipa, G., Arnulf, I., Oudiette, D., Dresler, M., & Paller, K. A. (2021). Real-time dialogue between experimenters and dreamers during REM sleep. Current Biology, 31(7), 1417–1427.e6. https://doi.org/10.1016/j.cub.2021.01.026 

Wamsley, E. J., Elfassy, N. M., Ambo, L. K., Wangsness, H., Mughieda, N., Jensen, O., & Bhattacharya, M. (2024). Linking memory and imagination across sleep and wake states. Neuron, 112(9), 1501–1518. https://doi.org/10.1016/j.neuron.2024.02.012 

Dreaming Circuits and Directed Memories: How Selective REM Control Sheds Light on Sleep’s Hidden Functions

    From this semester, the one striking idea portrayed was the discovery that the lateral posterior nucleus (LPN), a higher-order thalamic visual nucleus that takes part of a specific role in REM sleep regulation. Guerrero and Cavanaugh’s conduct of this study demonstrates that silencing the LPN selectively leads to the reduction of REM sleep in mice. In a way, initiating this method leaves non-rapid eye movement (NREM) sleep almost intact. Going along the same idea, selective circuits lead to governing sleep function, which is applied to NREM sleep, the critical phase of deep memory consolidation. This proposes the fact that REM may rely on targeted support from sensory-related thalamic circuits instead of whole-brain sleep mechanisms. In another sense, REM isn’t just “dreaming turned on” but appears to be an adapted situation, in which the neural structures are working all around and stepping in at the right time needed. This finding raises the question of whether REM is supported by specialized neural circuits, and could altering REM change memory, emotion, or even dream content?

    A 2021 study from Northwestern University was widely covered in news outlets such as NPR and Science Daily. They examined the occurrence called target memory reactivation (TMR), which is the process of activating the brain with keen sounds during sleep to either strengthen dreams or to modify them. With this study presented, the participants practiced a melody on a keyboard while also listening to a specific sound. The scientists replayed that cue during sleep, which led to the factor the participants performing the melody significantly better. The results acquired from these participants the next morning were better than allowing that cue to be replayed overnight. The key point of this research displayed how specifically REM and light NREM stage sleep are not submissive, therefore is considered an active state. That is because the specific brain circuits present selectively alter what we perceive and how well we remember it. This study resonates with Guerrero and Cavanaugh’s work. If REM sleep needs the LPN to maintain its normal structure,  then damaging that specific circuit could interfere with the neural cycle that TMR relies on. There could be an indication of an “entry point” for comprehending how sensory information, dreams, and memory consolidation could interact at a circuit level. 

    In the TMR study done at Northwestern, memories are reinforced by activating certain cortical pathways during sleep. Looking into the mouse in the REM study, by selectively silencing a visual thalamic structure, it weakened REM, which supports memory consolidation. There is the idea of distinct brain circuits that may play a role, determining what kinds of information get processed during sleep. These studies have opened the door to a new interpretation of sleep, how it's a series of regulated brain modes in which each is linked and supported by distinct neural structures with special functions. Sleep ultimately becomes less like a blanket covering for the brain but more like a series of subtly tuned spotlight beams that illuminate the different neural pathways, all at different times. As the continuation of learning proceeds, on how sleep interacts with memory and perception. The idea that one day we may influence how we dream seems to be realistic, not just being able to know whether we dream or not. The conclusion from the studies of Guerrero and Cavanagh suggests how these possibilities begin in the cortex but also how surprisingly powerful thalamic circuits can shape the landscape of our sleeping minds.

References

Guerrero, J.R., & Cavanaugh, J. (2025). Silencing the lateral posterior nucleus produced a highly selective reduction in mouse REM sleep. Neurobiology of Sleep and Circadian Rhythms. No DOI available. https://www.sciencedirect.com/science/article/pii/S2451994425000136  

Anthony, J. W., Cheng, L. Y., Brooks, P. P., Paller, K. A., & Norman, K. A. (2021). Sleep spindle refractoriness segregates periods of memory reactivation. eLife, 10, e70068. https://doi.org/10.7554/eLife.70068 

How People (& Values) Learn Like Machines by Gianna Eisen

Have you ever noticed yourself distancing yourself away from a person who has widely different opinions from you, or get tired of explaining yourself for your opinion? What about finding someone with whom you get along and who shares similar opinions to you? While catching up with friends or scrolling through comments on a social media post, it is easy to notice how clusters of opinions are formed and how individuals create a social group for themselves based on shared beliefs. But how does our brain perceive this polarization? Norberto Grzywacz, in his study Comparison of Distance and Reinforcement-Learning Rules in Social-Influence Models, studied how decision-making and social influence could follow the same learning rules that direct artificial intelligence. In past research, models of social influence automatically assume that individuals are swayed by those who already think like them, which is where the ‘distance-based’ rule, where influence takes precedence as opinions diverge. However, in Grzywacz’s research, we think about whether our brains use reinforcement learning, which is the same process used in AI systems. This allows people to learn which values or opinions ‘ pay off’ socially and show that behaviors that are rewarded (like by acceptance or appraisal) are then strengthened. Grzywacz’s simulation showed that both systems create polarization, but reinforcement learning produces realistic group patterns, like groups aligning or dividing suddenly due to unforeseeable shifts.

This idea is closely connected to a 2020 study by Levorsen et al., Testing the Reinforcement Learning Hypothesis of Social Influence. By using fMRIs and computational modeling, researchers were able to assess if social conformity, the tendency to match others’ opinions, operates on the same neural mechanism as reinforcement learning. Participants received both social feedback, on how their opinions compared to others, and reward feedback, monetary gains or losses. According to the study, the brain didn’t treat these two forms of feedback the same way, showing that while reinforcement depends on reward-processing regions of the brain, like the striatum, social influence, on the other hand, engaged additional areas related to social reasoning and self-evaluation. These findings show that Grzywacz’s reinforcement-learning model captures many aspects of social polarization, but real-world influence could be even more complex. Our brains don't just chase rewards, but respond to social norms or identity. This idea confirms that polarization does not only occur because opinions are ‘rewarded’ but because it defines who a person is within a group. Both Grzywacz and Levorsen’s findings show how individuals learn from one another. Rules like reinforcement learning can help to explain why opinions spread and cluster, but the emotional and social context of the opinions themselves makes the process human. Understanding both sides, the algorithmic and the social, can help our machines, like AI, learn values using reinforcement like systems, that pick up our biases and polarization patterns. Designing systems that can distinguish between social learning and reward learning can help prevent the divisive act of polarization.

Works Cited:

Grzywacz, Norberto M. Comparison of Distance and Reinforcement-Learning Rules in Social-Influence Models, Neurocomputing, Volume 649, 2025. https://doi.org/10.1016/j.ne ucom.2025.130870

Levorsen, Marie et al. “Testing the reinforcement learning hypothesis of social conformity.” Human brain mapping vol. 42,5 (2021): 1328-1342. doi:10.1002/hbm.25296

Crossing the Line: How our Brain Keeps Vision Seamless and Why Symmetry is Key.

 Most of us have never thought about the center line of our vision or actively seek it out. You look to your left, you look to your right, and even so the world manages to keep is balance and stay in one piece. In a recent article by MIT News, “How the brain splits up vision without you even noticing”, tells us why. As something moves across your view, the brain quietly passes the information from one hemisphere to the other so there isn’t a noticeable glitch or gap. For example, if runners are running a relay race and one passes the baton to the next runner up, and they match their speed so the baton is handed off cleanly and the race will continue without a hitch. This speaks to how perception works in everyday life, such as walking down a crowded sidewalk, during a sporting event, or even while doom scrolling through reels. 

In our Neuroscience seminar, our reading “The role of vertical mirror symmetry in visual shape detection” by Machilsen et al. (2009) talk about how the left and right side of our vision matching isn’t a design for aesthetic purposes but rather helps our brain find shapes in clutter. In the experiment from the reading, participants were asked to spot outline of shapes made from tiny line fragments with slightly turned little lines that made the outline so the shape was harder to see. Through the multiple conditions, shapes that were symmetric were much easier for the participants to decipher compares to chapes that were symmetric. This shows that symmetry acts as shortcut for when scenes aren’t clear or messy for our brains to outright decipher, so our brains use the other half that is clear or more recognizable to fill in the other half. 

But how do these ideas work together? The article by MIT explains how features slide across our vertical midline and the two hemispheres of our brain work together to keep it a continuous scene. Since vertical symmetry is connected by the midline, our brains are able compute that this half should mirror the other half. Symmetry pops because our brain is designed to create one big picture even with many moving pieces. This also confirms what Dr. Baker, our guest speaker, mentioned in his talk. Our vision is built up of many little pieces that work together to create the big picture. 

References: 
https://www.luc.edu/psychology/people/facultyandstaffdirectory/profiles/bakernicholas.shtml

David Orenstein  |  The Picower Institute for Learning and Memory. (n.d.). How the brain splits up vision without you even noticing. MIT News | Massachusetts Institute of Technology. https://news.mit.edu/2025/how-brain-splits-vision-without-you-even-noticing-0926

Machilsen, B., Pauwels, M., & Wagemans, J. (2009). The role of vertical mirror symmetry in visual shape detection. Journal of Vision, 9(12):11, 1–11, http://journalofvision.org/9/12/11/, doi:10.1167/9.12.11. 

Ultraprocessed Foods Linked to Early Symptoms of Parkinson’s

 In class, we had the opportunity of having Dr. Mary Makarious as one of our guest speakers to talk about a program where she takes participation in to have an explanation towards Parkinson’s. Some early symptoms to detect in suspicion of early Parkinson’s are shaking unexpectedly, unable to sleep, losing sense of smell, not being able to stand properly, slow movement, expressionless face, etc. Parkinson’s disease is a disorder centralized of the nervous system that affects movement which over time unfortunately only gets worse. In a more scientific explanation, the dopamine in your brain stops functioning as the cells stop making it.  Global Parkinson’s Genetics Program (GP2), is made from different researchers around the world that do different research to find a cause for Parkinson’s in a genetic aspect. They give us a broader look into how different populations from around the world come to face this disease differently. 

I have come across an article, “Ultraprocessed Foods Linked to Early Symptoms of Parkinsons’s” which center a recent study on the potential cause on how our food choices can have an impact on brain health. With studies, you are going to have successful and Non successful ones, and this one came out to not prove that foods can be cause of this disease but did help on giving us more insight towards food related to Parkinson’s. This involves refraining from consuming too much processed foods, as those who consume it most have been revealed to be at higher risk of developing symptoms than those who consume less. Not only does it affect Parkinson’s, but it can have other life-threatening health problems like cancer, diabetes, dementia, heart disease, etc. This research developed in China and the US and involved analyzing the diets of their participants over years to find that ultra processed food takes a big toll on neurological diseases.  

Although there is still a long way ahead to find a true cause and even a potential solution to this life-threatening disease, research like the one from Dr. Makarious and the one previously mentioned in the article, all contribute to an effort for answers. Many people living with this disease daily are fighting for their lives, and these researchers are putting in an effort to show that hope has not been lost. 

Reference:  

Callahan, Alic. Ultraprocessed Foods Linked to Early Symptoms of Parkinson’s. The New York Times (2025). https://www.nytimes.com/2025/05/07/well/eat/ultraprocessed-foods-linked-to-early-symptoms-of-parkinsons.html?smid=url-share 

Understanding the World of Silence

     In the beginning of the semester, Dr. Wei-Ming Yu presented the concepts of Hepsin- which is an important transmembrane serine protease, TMPRSS1, that is crucial for the proper functioning of the cochlea and tectorial membrane. To be better prepared for this presentation, we had to read the article "Critical role of hepsin/TMPRSS1 in hearing and tectorial membrane morphogenesis: Insights from transgenic mouse models" by Yang, Ting-Hua et al. This article first started by introducing that mutations in a type II membrane serine protease in family members are highly associated with a non-syndrome hearing loss although some of those mechanisms are still unclear to be understood.  

First and most importantly, Dr. Yu explained the different mechanisms of how sound is produced by vibrations that create particles in a surrounding medium such as air.  This in turn result in a wave of vibrations that travel through air to the eardrum. When sound enters the ear, a series of hair cells activate in which fluid waves bend hair cells called cilia inside the cochlea. Vibrations travel through the ear canal then press against the eardrum, causing it to oscillate, or move back and forth in a rhythm., The movement of fluid bends the cilia in the cochlea which converts mechanical energy into electrical signals that are processed as sound perception via the brain.

Dr. Yu explained in depth at the molecular level that the proper technique of the tectorial membrane is important for accurate the stimulation of these cilia. This reveals that hepsin/TMPRSS1 plays a key in how we hear sounds. In transgenic mouse models lacking hepsin, the tectorial membrane was abnormally shaped and detached from the hair cell leading to severe hearing impairment. This proved that hepsin is necessary for maintaining the correct composition and structure of the tectorial membrane through processing of some specific extracellular matrix proteins.

In the article “Noise Exposures Causing Hearing Loss Generate Proteotoxic Stress and Activate the Proteostasis Network” by Ramirez et al. describes how exposure to loud sounds damage to the inner ear and imbalances the cochlea. They experienced on rats by exposing them to different levels of sound: moderate, loud and very loud studying the biological effects of noise induced hearing loss. The results were that they found loud levels of sound causes protein in the cochlea to unfold and become damaged. 

Even though both articles are different from one another, they explain concepts at the molecular level of hearing loss providing evidence of how environmental and genetic factors produce sound. 

 

1.     Noise Exposures Causing Hearing Loss Generate Proteotoxic Stress and Activate the Proteostasis Network

Jongkamonwiwat, Nopporn et al. Cell Reports, Volume 33, Issue 8, 108431

2.     Yang, T. H., Hsu, Y. C., Yeh, P., Hung, C. J., Tsai, Y. F., Fang, M. C., Yen, A. C. C., Chen, L. F., Pan, J. Y., Wu, C. C., Liu, T. C., Chung, F. L., Yu, W. M., & Lin, S. W. (2024). Critical role of hepsin/TMPRSS1 in hearing and tectorial membrane morphogenesis: Insights from transgenic mouse models. Hearing research, 453, 109134. https://doi.org/10.1016/j.heares.2024.109134

Parkinson's Disease: The Umbrella of All

Parkinson's disease, also abbreviated to (PD),  is a neurodegenerative disorder that involves genetics and mutations found in a gene, which affects an individual's motor skills, balance, and nervous system, eventually leading to impairments of everyday life. PD is a disease that affects people from all over the world if they have at a concerning rate of increase in cases. There is a lot of research that is being done to try to find out what increases the likelihood of developing PD in the future, allowing people to get the care that they need from rehabilitation to medicine.   

Within the neuroscience seminar class, we had a guest speaker, Mary Makarious, who discussed the Global Parkinson’s Genetics Program that she works with. The point of this program is to collect data information from all over the world to understand PD on a whole new level. This is done by teaching institutions, medical locations, and many more how to look at genetic information from patients and volunteers and break down the data. In doing this, the data that is being collected is revealing specific key factors that lead to this complex disease. With the work that is being done, they have found that there are different key genes in different places that are specific to different groups of people, widely ranging across different demographics. This connects to the question of why there are so many different key gene variations that lead to the one disease, PD.  

In the article that I found, “α-Synuclein Deposition in Sympathetic Nerve Fibers in Genetic Forms of Parkinson's Disease”, which was published in 2021, goes on a deep dive into why there are so many different genes that are linked to PD. To learn this, they looked at a common denominator, which is α-synuclein, a protein that collects to form Lewy bodies within the brain and nerve cells, which happens in PD, to see how this interacts with the varying genes that lead to parkinsons. To create an experiment to show this, they colled skin biopsies samples from 65 participants; 30 of the participants with PD gene mutations, 19 participants that has no inherit gene or family that has had PD before them but yet still have PD, and lastly 16 participants who did not have PD or any signs of developing the disease. In these samples, it has the sympathetic nerves, which were then put through immunofluorescence microscopy to tag the α-synuclei and nerve fibers marked with tyrosine hydroxylase. Once calculated,d they were able to see how much the other overlapped using the colocalization index.  The results from this experiment showed that the participants who had the mutation gene SNCA, LRRK2, and GBA, and those who did not have a previous mutation, showed high amounts of α-synuclein that collected in the nerve fibers.  What was interesting was that the participants with PD with the mutation of PRKN had very small to practically no amount of α-synuclein. This then leads to the conclusion that the reason for this even happening is because PD is not just one specific disease, but instead it is an umbrella for all the different issues that happen within the body within the nerves and brain, leading to the symptoms that are known as PD. 

The research that took place for the articles really shows the importance of how research can further our understanding of PD. With the knowledge that is gained, it will allow people all over the world to get a proper diagnosis of the disease early on. Another important key to note is the fact that with continuing research on PD, we will be able to better create solutions, such as care and treatment for all of the different symptoms of PD. 

 

References: 

Tackling a Disease on a Global Scale, the Global Parkinson’s Genetics Program, GP2: A New Generation of Opportunities: The American Journal of Human Genetics, www.cell.com/ajhg/fulltext/S0002-9297(25)00284-8 . Accessed 11 Oct. 2025. 

 α-Synuclein Deposition in Sympathetic Nerve Fibers in Genetic Forms of Parkinson’s Disease. Movement Disorders, vol. 36, no. 10, 2021, pp. 2346–2357, https://doi.org/10.1002/mds.28667. Accessed 11 Oct. 2025.https://movementdisorders.onlinelibrary.wiley.com/doi/epdf/10.1002/mds.28667

Fighting Back: Silent Engrams and Alzheimer's Disease Research

Memory is a very widely known and recognized cognitive function. Despite this common knowledge of its existence, how memory actually works behind the scenes has been widely debated for decades. Dr. Stephanie Grella presented a talk at Loyola University Chicago about engrams, a theory gaining more traction in recent years that suggests the physicality of a memory in the brain. Something that particularly struck me was the discussion of silent engrams. Silent engrams are memories that are no longer retrievable by natural means (Josselyn & Tonegawa). Scientists have experimented with this concept by messing around with optogenetics and disrupting the normal consolidation process using protein inhibitors (commonly known to cause amnesia). They found that administering anisomycin, a protein inhibitor, would block the formation of memories. In this context, scientists were fear-conditioning mice and after administering anisomycin, mice would show little fear response. However, reactivating the associated neurons using optogenetics was sufficient to bring back the memory. 

This concept has been used in the study of Alzheimer's Disease (AD). AD is a neurodegenerative disease that mainly affects the elderly by slowly eating away at their brain. Studies have been surrounding this disease for years, desperate to find a cure or specific causes. Silent engrams have been used to study AD, with it being used as a possible explanation for the early stages of AD. Transgenic mice used for studying AD and expressed genes that were associated with the onset of the disease underwent an optogenetic treatment to reactivate an area of the brain associated with memory (Josselyn & Tonegawa). Miraculously, these mice essentially got their memories back. This has been compared to reports of humans in early-stage AD having enhanced memory retrieval if specific retrieval cues are used. This is a very promising step in figuring out how to combat AD, and with more research on engrams, perhaps a medicinal solution is not entirely out of reach.

Other research surrounding AD has also been undertaken. Another focus besides engrams is hippocampal neurogenesis and how to maximize it. Studies have shown that neurogenesis occurs into adulthood, however it is difficult to study specifically in humans. However, in rodents and primates, hippocampal neurogenesis tends to decrease with age, along with cognition (Lazarov et. al). Scientists have found that growing within an enriched environment and partaking in physical activity is able to retain these levels of neurogenesis from young mice to old mice. Despite this being somewhat difficult to fully apply to human subjects in a scientific setting, it shows promise in how we can potentially make certain lifestyle choices to avoid AD. In the future, more work surrounding this will hopefully allow us to bring a scientific backing for ways on how people can fight back against AD.

References:

Lazarov, O., Gupta, M., Kumar, P., Morrissey, Z., & Phan, T. (2024). Memory circuits in dementia: The engram, hippocampal neurogenesis and Alzheimer's disease. Progress in neurobiology, 236, 102601. https://doi.org/10.1016/j.pneurobio.2024.102601

Josselyn, S. A., & Tonegawa, S. (2020). Memory engrams: Recalling the past and imagining the future. Science (New York, N.Y.), 367(6473), eaaw4325. https://doi.org/10.1126/science.aaw4325