Group averages obscure how an individual’s brain controls behavior, Stanford Medicine study finds
Brain-scan averages miss the picture
Studying cognition by averaging data from many people’s brain scans hides how individuals use their brains, new Stanford Medicine research has shown.
In particular, children who struggle with goal-oriented tasks show distinct patterns of brain activity when their data is analyzed individually, rather than as part of a group of kids with mixed abilities. The findings, which have implications for understanding how the brain works in such conditions as attention-deficit/hyperactivity disorder, will be published April 27 in Nature Communications.
“Investigating how dynamics unfold within individual brains can provide significant insights into the neuroscience of individual differences and help us tackle questions that cannot be answered using conventional approaches,” said Percy Mistry, PhD, a research scholar in psychiatry and behavioral sciences, and a lead author of the study.
Mistry shares lead authorship with Nicholas Branigan, MS, a research data analyst in psychiatry and behavioral sciences. The senior author is Vinod Menon, PhD, a professor of psychiatry and behavioral sciences and the Rachael L. and Walter F. Nichols, MD, Professor.
The research evaluated inhibitory cognitive control — the process by which the brain suppresses distracting or irrelevant information while someone completes a task — in more than 4,000 children. The researchers compared results obtained by averaging brain-scan data of children against results obtained by analyzing the temporal dynamics in each child as they performed repetitions of the same task.
“Our study provides theoretical support for a growing movement toward personalization in human neuroscience, psychology and psychiatry,” Branigan said.
This approach was also able to identify subgroups of children with different levels of cognitive control and performance monitoring, or the ability to modify one’s strategy after making an error.
For example, children with good cognitive control and performance monitoring and those with poor cognitive control and performance monitoring showed quite different — and often opposite — brain dynamics.
Noting that studies connecting behavior to brain activity typically draw their conclusions from averaging groups’ data, Menon said, “Our study clearly shows that group averages can fundamentally mislead us about how the brain dynamically regulates behavior.”
A clue from the speed-accuracy trade-off
Psychologists have long known that behaviors that seem linked in a certain way when you study them in groups may not be related in the same way in individuals. The best example is the speed-accuracy trade-off: If you ask a group of people to do a task such as quickly solving arithmetic problems, the faster people tend to be more accurate. However, if you ask one individual to go faster, their accuracy will likely decline — or, if you ask one person to be more accurate, they’ll probably slow down.
Experts have wondered if a similar phenomenon plays out in hidden ways inside the brain.
The Stanford Medicine team looked at brain scan data from kids doing a task that measures their inhibitory control. To focus on a job or goal, a person must suppress the urge to pay attention to distractions and things that aren’t relevant while inhibiting actions or impulsive behaviors that are contradictory to reaching their goal.
Inhibitory control gets the job done. Poor inhibitory control is a hallmark of several psychiatric diagnoses, including ADHD, bipolar disorder and addiction. Understanding how inhibitory control normally works — and how it goes awry — could help guide the development of better behavioral therapies for these conditions.
Individual results going a different way
The research team analyzed data from more than 4,000 children, all 9 or 10 years old, that was collected as part of the baseline visit for the Adolescent Brain and Cognitive Development study, a long-term study tracking brain maturation into early adulthood.
The children’s brains were scanned via functional magnetic resonance imaging while they completed an activity designed to assess inhibitory control. Called the stop-signal task, the activity consists of pressing a button in response to prompts on a screen. Every time the child saw “Go” on the screen, they were asked to press the button as quickly as possible. Occasionally, the “Go” sign was immediately followed by an additional “Stop” sign. The children were supposed to avoid pressing the button when they saw this infrequent, unpredictable Stop cue.
The research team examined aspects of what the brain was doing during the task on every trial — both when comparing the children with one another and when analyzing several repetitions of the task by the same person.
The researchers found several brain-behavior links that were different within individuals than in the group as a whole.
For instance, when analyzing average trends in groups of children, slower reaction times to the “Go” signal were linked to increased activity in many brain regions, including the default mode network, which is involved in daydreaming, thoughts about oneself and mind-wandering.
However, when an individual had a slower reaction time to the “Go” signal, activity decreased in the default mode network — the opposite of the group-level pattern.
“Group-level associations substantially mischaracterize the neural dynamics governing processing speed at the individual level,” the research team wrote.
The researchers also developed a mathematical model that enabled them to study how the children adapted their reactions during several repetitions of the stop-signal task. Children with adaptive (good) regulation showed faster stopping reactions as they got further past the first “Stop” signal, correctly anticipating that each subsequent trial was more likely to be another “Stop.” Children with maladaptive reactions showed the opposite pattern, indicating decreasing expectancy of a second “Stop” signal. This difference shows up in the scans, manifesting as opposite reactions in activity in specific brain areas among the children with adaptive and maladaptive regulation.
The analysis also showed that some effects seen in the entire group of children were driven solely by children in one of the groups; in other words, the average results obscured what happened in many children’s brains.
Various pathways
The researchers also found that cognitive control has multiple components, which are orchestrated by different parts of the brain, including proactive control (preparing to stop) and reactive control (actually stopping). The brain regions used in these sub-processes are not always talking to each other in the same way in kids with stronger versus kids with weaker cognitive control.
“When children are weaker at cognitive control, they may be able to compensate for that with a more proactive approach or an alternate cognitive pathway,” Mistry said. “That’s interesting because it moves the dialogue away from cognitive control being a static capacity that children have, to something that can perhaps be regulated or driven in multiple ways.”
The findings may prove useful in designing new approaches to help children with ADHD improve in the types of behavior regulation that are hard for them, Mistry added. “If you’re looking at strategies in the classroom, this data points to the fact that inhibitory cognitive control is not a single capacity. There are multiple pathways involved, and perhaps students can learn to engage specific pathways to be more proactive about their inhibitory control approach,” he said.
Not only does the study open new possibilities for understanding human variability in brain function, but it should encourage neuroscientists to examine how each person reacts to specific situations, Menon added.
“We really have to pay attention to each person’s unique brain responses, because we’re trying to understand, and if necessary modify, behavior as it unfolds in real time for specific situations,” he said. “There is no such thing as an average brain. The real question is, ‘How is this child or this adult responding to the particular situations and changing contexts that demand attention and adaptive regulation of behavior?’ That’s what cognitive control is — knowing what response to take, at what time and under what circumstances.”
The data for the Adolescent Brain and Cognitive Development study is held in the National Institute of Mental Health Data Archive.
The ABCD study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123 and U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html.
At Stanford Medicine, this work was supported by the National Institutes of Health (grants MH121069 and MH124816), the National Science Foundation (grant 2024856), and the Stanford Maternal and Child Health Research Institute. In addition, Stanford University and Stanford Research Computing provided computational resources and support that contributed to the research results.
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About Stanford Medicine
Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu.
Journal
Nature Communications
Method of Research
Observational study
Subject of Research
People
Article Title
Nonergodicity and Simpson’s paradox in neurocognitive dynamics of cognitive control
Article Publication Date
27-Apr-2026
Do memories form on a blank slate?
ISTA researchers reveal how thought networks in the hippocampus develop after birth
image:
Neurons filled with biocytin—a tracer that labels them during recording—are fixed and stained to allow full reconstruction of their shapes. © Jose Guzman / Jonas group at ISTA
view moreCredit: © Jose Guzman / Jonas group at ISTA
The hippocampus is a key brain region involved in memory formation and spatial orientation. It transforms short-term memories into long-term ones, helping us retain and build upon our experiences. Researchers led by Magdalena Walz Professor for Life Sciences Peter Jonas at the Institute of Science and Technology Austria (ISTA) focus precisely on this area of the brain. Their latest study, published in Nature Communications, reveals how the central neural network in the hippocampus develops after birth.
Imagine a blank sheet of paper in front of you. There’s nothing on it so you start writing, adding more and more information. This is the principle of tabula rasa—the “blank slate.”
It’s a different story when the sheet already contains marks: new information must be added to, or overwrite, what is already there. That describes tabula plena—the “full slate.”
At the heart of this philosophical concept lies a fundamental question: Is everything pre-set from the very beginning or do experiences shape who we become?
Biology reflects this controversy as well—between genes that provide the basic blueprint and environmental factors that sculpt the final organism.
Neuroscientists in the Jonas group at the Institute of Science and Technology Austria (ISTA) addressed precisely this question in the context of the hippocampus—the brain region that forms memories and guides spatial navigation. Specifically, they asked: How does the hippocampal network evolve after birth? Is it linked to tabula rasa or tabula plena?
First more, then less
The study focused on a central hippocampal network made up of interconnected CA3 pyramidal neurons. These cells store and recall memories through a process known as plasticity—the ability of neurons to constantly change, for example, by strengthening or weakening their connections or by reshaping their structure.
For his project, ISTA alum Victor Vargas-Barroso examined mouse brains at three developmental stages: early after birth (day 7–8), adolescence (day 18–25), and adulthood (day 45–50).
To analyze the networks, he applied the patch-clamp technique. This allows researchers to measure tiny electrical signals in specific parts of neurons—such as at their signal-sending ends (presynaptic terminals) or at the branching sites that receive signals (dendrites). In addition, advanced microscopy and laser-based techniques were used to observe processes inside the cells and to activate individual connections with high precision.
The results: Early on, the CA3 network is very dense, and the connections appear random. As the animals mature, however, the configuration shifts—the network becomes sparser but more structured and refined.
“This discovery was quite surprising,” says Jonas. “Intuitively, one might expect that a network grows and becomes denser over time. Here, we see the opposite. It follows what we call a pruning model: it starts out full, and then it becomes streamlined and optimized.”
An efficient network thanks to tabula plena?
Why this happens remains a matter of speculation. Jonas suspects that an initially widespread network allows neurons to connect quickly and efficiently—a crucial advantage in the hippocampus. This region does not just store visual, smell, or sound information—it links all these together.
“That’s a complex task for neurons,” Jonas explains. “An initially exuberant connectivity, followed by selective pruning, might be exactly what enables this integration.”
If, on the other hand, the network started as a true tabula rasa—with no preexisting connections—neurons would be too far apart and would need to ‘find’ one another first, making efficient communication nearly impossible.
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Information on animal studies
In order to better understand fundamental processes, for example in the fields of neuroscience, immunology, or genetics, the use of animals in research is indispensable. No other methods, such as in silico models, can serve as alternative. The animals are raised, kept, and treated according to the strict regulations of Austrian law. All animal procedures are approved by the Federal Ministry of Education, Science, and Research.
Journal
Nature Communications
Method of Research
Experimental study
Subject of Research
Animals
Article Title
Developmental emergence of sparse and structured synaptic connectivity in the hippocampal CA3 memory circuit
Article Publication Date
27-Apr-2026
Video screenshot: Network of interconnected CA3 pyramidal neurons in the mouse hippocampus. As the animals mature, the configuration shifts—the network becomes sparser but more structured and refined (blue).
Network of interconnected CA3 pyramidal neurons (mature mice) [VIDEO]
Network of interconnected CA3 pyramidal neurons in the mouse hippocampus. As the animals mature, the configuration shifts—the network becomes sparser but more structured and refined (blue).
Video screenshot: Network of interconnected CA3 pyramidal neurons in the mouse hippocampus: In young mice, the CA3 network is very dense, and the connections appear random (yellow).
Network of interconnected CA3 pyramidal neurons (young mice) [VIDEO]
Network of interconnected CA3 pyramidal neurons in the mouse hippocampus: In young mice, the CA3 network is very dense, and the connections appear random (yellow).
Credit
© Jake Watson / ISTA
We may be born with 2 complex cognitive functions already established
Study: Language, sensing others’ mental states have distinct brain origins
COLUMBUS, Ohio – A new study is the first to show that two of our most sophisticated cognitive functions, using and understanding language and being able to sense how other people feel, have distinct origins in the brain in young children – matching what we know about the adult brain.
The findings suggest that these separate but related ways of processing complex concepts, both uniquely human skills, do not originate from overlapping brain areas and grow more distinct as the mind matures, which challenges prior theories. Instead, our brains appear to have evolved with discrete architecture and wiring enabling these different kinds of thinking.
Using fMRI to scan the brains of children while they listened to spoken language and watched a short movie, the researchers found that parts of the brain responsible for language and mentalizing, known as theory of mind, are separate and do not overlap. Additional analysis of how these regions communicate with other brain areas at rest reinforced the imaging data.
“It seems that these processors that help us mentalize and that help us speak and understand were dissociated very, very early in the evolutionary process, such that we can’t even see traces of overlap right now in human development,” said Zeynep Saygin, senior author of the study and an associate professor of psychology at The Ohio State University.
“It’s a fundamental question humans ask themselves: ‘What is it that makes us human? How does human cognition emerge?’ I think this sheds some light on that.”
Kelly Hiersche, a doctoral student in Saygin’s lab, led the study, published April 23 in Communications Biology. David Osher, assistant professor of psychology, was also a co-author and collaborator.
The two communication skills of focus originate from a region of the brain called the superior temporal lobe, located near each temple – with language based in the left hemisphere and theory of mind based in the right.
The researchers first confirmed with fMRI scans of the brain in 28 adults what has been found before – that separate and distinct regions associated with language and theory of mind did, indeed, respond strongly to stimuli intended to activate those areas.
The team then worked with 42 children between ages 3 and 9, scanning their brains with 2 fMRI scans, one while they listened to sentences and another while they watched a silent cartoon, observing which brain regions were activated for each task. Control conditions included nonsense words for the language assessment and, for the mentalization evaluation, signs of pain in cartoon characters – which elicits a pain response rather than theory of mind.
Results of the scans and additional analysis – imaging at the 2-3 millimeter, or 3D voxel, level of the brain across both hemispheres – showed that the regions responding to language stimuli and theory of mind stimuli were separate, with no overlap.
“That was our first question: Are these skills distinct in both their function and location? And we see really broadly, yes,” Hiersche said. “We demonstrate this for the first time in kids, extending an adult finding to development. They’re really distinct there, which is pretty cool.”
To tap further into the evolutionary question, the researchers took fMRI scans of the adults’ and children’s brains at rest – when the brain is still busy, but not being asked to respond to specific stimuli – to observe what other brain regions these separate language and mentalization regions were connecting with.
“If you observe a voxel’s connectivity, or how it talks to the rest of the brain, that’s going to give you an idea about how that voxel is going to function,” Hiersche said. This is the idea of a connectivity fingerprint: a unique connectivity pattern that determines the unique function of a brain region.
Using predictive modeling to characterize these connectivity fingerprints, the researchers found that there was more to the language and theory of mind distinctions than their locations on separate sides of the brain.
“Regions of the brain that are functionally specific should be communicating in a unique way,” Saygin said. “We knew these regions were localized in different parts of the brain, but also showed that there’s nothing in how they communicate with the rest of the brain that indicates that they were at any point overlapping.”
Looking for changes in the kids’ connectivity fingerprints over time further drove home the point that the regional and functional distinctions don’t change during childhood brain development.
“We were able to not just look across different kids, but look within the same child to see what happened over time,” Hiersche said. “And we showed that it’s not the case that when you’re 3 years old, you see a lot of overlap in these functions, but then when you get to 5 years old, they pull apart and become more separate.
“The connections we’re seeing that support these tasks – and that also separate them – are stable within the same person over time.”
In fact, comparing the differences in connectivity fingerprints between children and adults showed that while these functions and connectivity patterns are quite clearly separate and distinct in kids, there is some overlap across brain networks in adults – a sign of change in how we make use of the complementary skills.
“In adults, the mentalizing theory of mind network starts to talk to slightly similar regions as the language areas. In children, as those skills keep developing, maybe those networks are talking to each other more,” Saygin said.
These results challenge the idea that language and mentalizing have similar origins and instead support distinct mechanisms for these communicative skills, she said.
This work was supported by the U.S. National Science Foundation, the Alfred P. Sloan Foundation, the National Institutes of Health, and Ohio State’s College of Arts and Sciences, Center for Brain Injury Recovery and Discovery, and Women in Philanthropy award.
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Contact: Zeynep Saygin, Saygin.3@osu.edu
Written by Emily Caldwell, Caldwell.151@osu.edu; 614-292-8152
Journal
Communications Biology
Method of Research
Imaging analysis
Subject of Research
People
Article Title
Functional dissociation of language and theory of mind in the developing superior temporal lobe
Article Publication Date
23-Apr-2026
MIT researchers find self-organizing “pencil beam” laser could help scientists design brain-targeted therapies
They leveraged a surprise discovery to devise a faster and more precise biomedical imaging technique
image:
Under the right conditions, a chaotic mess of laser light can spontaneously self-organize into a highly focused “pencil beam.” This schematic shows the pencil beam formation mechanism.
view moreCredit: MIT
CAMBRIDGE, MA -- MIT researchers discovered a paradoxical phenomenon in optical physics that could enable a new bioimaging method that’s faster and higher-resolution than existing technology.
They discovered that, under the right conditions, a chaotic mess of laser light can spontaneously self-organize into a highly focused “pencil beam.”
Using this self-organized pencil beam, the researchers captured 3D images of the human blood-brain barrier 25 times faster than the gold-standard method, while maintaining comparable resolution.
By showing individual cells absorbing drugs in real-time, this technology could help scientists test whether new drugs for neurodegenerative disease like Alzheimer’s or ALS reach their targets in the brain, with greater speed and resolution.
“The common belief in the field is that if you crank up the power in this type of laser, the light will inevitably become chaotic. But we proved that this is not the case. We followed the evidence, embraced the uncertainty, and found a way to let the light organize itself into a novel solution for bioimaging,” says Sixian You, assistant professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the Research Laboratory for Electronics, and senior author of a paper on this imaging technique.
She is joined on the paper by lead author Honghao Cao, an EECS graduate student; EECS graduate students Li-Yu Yu and Kunzan Liu; postdocs Sarah Spitz, Francesca Michela Pramotton, and Federico Presutti; Zhengyu Zhang PhD ’24; Subhash Kulkarni, an assistant professor at Harvard University and the Beth Israel Deaconess Medical Center; and Roger Kamm, the Cecil and Ida Green Distinguished Professor of Biological and Mechanical Engineering at MIT. The paper appears today in Nature Methods.
A surprising finding
The discovery began with an observation that initially puzzled the researchers.
The team previously developed a precise fiber shaper, a device that enables them to carefully tune the laser light shining through a multimode optical fiber. This type of optical fiber can carry a significant amount of power.
Cao was pushing the multimode fiber toward its limit to see how much power it could take.
Typically, the more power one pumps into the laser, the more disordered and scattered the beam of light becomes due to imperfections in the fiber.
But Cao observed that, as he increased the power almost to the point where it would burn the fiber, the light did the opposite of what was expected: It collapsed into a single, needle-sharp beam.
“Disorder is intrinsic to these fibers. The light engineering you typically need to do to overcome that disorder, especially at high power, is a longstanding hassle. But with this self-organization, you can get a stable, ultrafast pencil beam without the need for custom beam-shaping components,” You says.
To replicate this phenomenon, the researchers found they had to satisfy two simple, but precise conditions.
First, the laser must enter the fiber at a perfect, zero-degree angle. This is a more rigorous requirement than is usually used for these types of fibers. Second, the power must be dialed up until the light begins to interact with the glass of the fiber itself.
“At this critical power, the nonlinearity can counter the intrinsic disorder, creating a balance that transforms the input beam into a self-organized pencil beam,” Cao explains.
Typically, researchers conduct these experiments at much lower power levels for fear of destroying the fiber, in which case they wouldn’t see this self-organization. In addition, such precise on-axis alignment isn’t typically necessary since a multimode fiber can carry so much power.
But taken together, these two techniques can generate a stable pencil-beam without any complicated light engineering methods.
“That is the charm of this method — you could do this with a normal, optical setup and without much domain expertise,” You says.
A better beam
When the researchers performed characterization experiments of this pencil beam, it was more stable and high-resolution than many similar beams. Other beams often suffer from “sidelobes” — blurry halos of light that can distort images.
Their beam was more pristine and tightly focused.
Building on those experiments, the researchers demonstrated the use of this pencil-beam in biomedical imaging of the human blood-brain barrier.
This barrier is a tightly packed layer of cells that protects the brain from toxins, but it also blocks many medicines. Scientists and clinicians often want to see how drugs flow inside the vasculature of the blood-brain barrier and whether they reach their targets within the brain.
But with standard optical settings, the best one can do is capture one 2D section of the vasculature at a time, and then repeat the process multiple times to generate a fuller image, You explains.
Using this new technique, the researchers created an ultrafast, high-precision pencil beam that enabled them to dynamically track how cells absorb proteins in real-time.
“The pharmaceutical industry is especially interested in using human-based models to screen for drugs that effectively cross the barrier, as animal models often fail to predict what happens in humans. That this new method doesn’t require the cells to have a fluorescent tag is a game-changer. For the first time, we can now visualize the time-dependent entry of drugs into the brain and even identify the rate at which specific cell types internalize the drug,” says Kamm.
“Importantly, however, this approach is not limited to the blood-brain barrier but enables time-resolved tracking of diverse compounds and molecular targets across engineered tissue models, providing a powerful tool for biological engineering,” Spitz adds.
The team captured cellular-level 3D images that were higher quality than with other methods, and generated these images about 25 times faster.
“Usually, you have a tradeoff between image resolution and depth of focus — you can only probe so far at a time. But with our method, we can overcome this tradeoff by creating a pencil-beam with both high resolution and a large depth of focus,” You says.
In the future, the researchers want to better understand the fundamental physics of the pencil-beam and the mechanisms behind its self-organization. They also plan to apply the technique to other scenarios, such as imaging neurons in the brain, and work toward commercializing the technology.
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This work was funded, in part, by MIT startup funds, the National Science Foundation (NSF), the Silicon Valley Community Foundation, Diacomp Foundation, the Harvard Digestive Disease Core, a MathWorks Fellowship, and the Claude E. Shannon Award.
This comparison shows imaging of a blood-brain barrier model using a common Gaussian beam (top) versus the new Pencil beam method (bottom) which captures the entire volume and 3D information in a single scan.
Credit
MIT
Journal
Nature Methods
Article Title
Self-localized ultrafast pencil beam for volumetric multiphoton imaging
Article Publication Date
27-Apr-2026
Hydraulic brain: Body motion linked to fluid movement in the brain
Abdominal contractions are tightly linked to gentle brain movements that help circulate cerebrospinal fluid, researchers find in mouse study
Penn State
image:
Using microCT scanning, which allows for high-resolution imaging of an organism's internal structures, and other imaging techniques, researchers found that a network of veins serve as a mechanical connection between the abdominal cavity and the brain. Here, the veins in red run through the interior of a vertebrae and around the spine.
view moreCredit: Penn State
UNIVERSITY PARK, Pa. — The brain is more mechanically connected to the body than previously appreciated, scientists reported today (April 27) in Nature Neuroscience. Through a study using mice and simulations, the team found a potential biological mechanism underlying why exercise is thought to benefit brain health: abdominal contractions compress blood vessels connected to the spinal cord and the brain, enabling the organ to gently move within the skull. This swaying facilitates the surrounding cerebrospinal fluid to flow over the brain, potentially washing away neural waste that could cause problems for brain function.
According to Patrick Drew, professor of engineering science and mechanics, of neurosurgery, of biology and of biomedical engineering at Penn State, the work builds on previous studies detailing how sleep and neuron loss can influence how and when cerebrospinal fluid flushes through the brain.
“Our research explains how just moving around might serve as an important physiological mechanism promoting brain health,” said Drew, corresponding author on the paper. “In this study, we found that when the abdominal muscles contract, they push blood from the abdomen into the spinal cord, just like in a hydraulic system, applying pressure to the brain and making it move. Simulations show that this gentle brain movement will drive fluid flow in and around the brain. It is thought the movement of fluid in the brain is important for removing waste and preventing neurodegenerative disorders. Our research shows that a little bit of motion is good, and it could be another reason why exercise is good for our brain health.”
Drew, who also holds the title of associate director of the Huck Institutes of the Life Sciences, explained how in a hydraulic system, a pump creates pressure that drives fluid flow. In this case, the pump is the abdominal contraction — which can be as light as the tensing prior to sitting up or taking a step. The contraction puts pressure on the vertebral venous plexus, a network of veins that connect the abdominal cavity to the spinal cavity, causing the brain to move.
The researchers visualized the process in moving mice with two advanced imaging technologies: two-photon microscopy — which allows for high-definition imaging of living tissue — and microcomputed tomography — which enables high-resolution 3D examination of whole organs. They observed the brain shifting in the moments before the mouse moved, but right after the tightening of the abdominal muscles needed to spur the body into further movement.
To confirm that it was abdominal contractions rather than other movement that acted as the pump, the researchers applied gentle and controlled pressure to the abdomens of lightly anesthetized mice. With no other movement other than a localized mechanical pressure less than a human would experience with a blood pressure cuff, the mice’s brains shifted.
“Importantly, the brain began moving back to its baseline position immediately upon relief of the abdominal pressure,” Drew said. “This suggests that abdominal pressure can rapidly and significantly alter the position of the brain within the skull.”
With the abdominal contraction-brain movement link confirmed, Drew said the next step was to understand the fluid’s movement in the brain and if the brain’s movement could induce fluid flow. However, there previously were no existing imaging techniques to visualize the rapid, nuanced dynamics of such fluid flows.
“Luckily, our interdisciplinary team at Penn State was able to develop these techniques, including conducting the imaging experiments of living mice and creating computer simulations of fluid motion,” Drew said. “That combination of expertise is so important for understanding these types of complicated systems and how they impact health.”
Francesco Costanzo, professor of engineering science and mechanics, of biomedical engineering, of mechanical engineering and of mathematics, led the computational modeling.
“Modeling fluid flow in and around the brain offers unique challenges because there are simultaneous, independent movements, as well as time-dependent, coupled movements. Accounting for all of them requires accounting for the special physics that happens every time a fluid particle crosses one of the many membranes in the brain,” Costanzo said. “So, we simplified it. The brain has a structure similar to a sponge, in the sense that you have a soft skeleton and fluid can move through it.”
By simplifying the geometry of the brain to that of a sponge, Costanzo explained that the team could model how fluid flows through a structure with varied spaces, like wrinkles in the brain, or pores in the sponge.
“Keeping with the idea of the brain as a sponge, we also thought of it as a dirty sponge — how do you clean a dirty sponge?” Costanzo asked. “You run it under a tap and squeeze it out. In our simulations, we were able to get a sense of how the brain moving from an abdominal contraction can help induce fluid flow over the brain to help clear waste products.”
Drew emphasized that while more work is needed to understand the full implications in humans, this study suggests that body movement may help to cycle cerebrospinal fluid around and in the brain, removing waste and helping to protect against neurodegenerative disorders associated with waste buildup.
“This kind of motion is so small. It’s what’s generated when you walk or just contract your abdominal muscles, which you do when you engage in any physical behavior. It could make such a difference for your brain health,” Drew said.
Co-authors include C. Spencer Garborg, postdoctoral researcher in Drew’s lab; Beatrice Ghitti, who was a postdoctoral researcher supervised by both Costanzo and Drew at the time of the research and is now a research fellow at the University of Auckland; Qingguang Zhang, who was an assistant research professor in Drew’s lab and is now an assistant professor of physiology at Michigan State University; Joseph M. Ricotta, who was a postdoctoral researcher in Drew’s lab; Noah Frank, who earned his bachelor’s degree in mechanical engineering from Penn State; Sara J. Mueller, who led the Penn State Center for Quantitative Imaging at the time of the research and is now executive director of the Wildlife Leadership Academy; Denver L. Greenawalt and Hyunseok Lee, graduate students at Penn State; Kevin L. Turner and Ravi T. Kedarasetti, who earned their doctorates from Penn State under co-supervision by Drew and Costanzo; and Marceline Mostafa, an undergraduate student who earned a degree in biology. Microcomputed tomography imaging for this project was performed at the Penn State Center for Quantitative Imaging, an Institute of the Energy and the Environment core research facility.
The National Institutes of Health, the Pennsylvania Department of Health and the American Heart Association supported this research.
The researchers used two-photon microscopy — which allows for high-definition imaging of living tissue — to observe the brain shifting in the moments before the mouse moved, but right after the tightening of the abdominal muscles needed to spur the body into further movement. On the left, the brain, in green, sits during a stationary moment, while the image on the right shows the brain during movement.
Credit
Penn State
Journal
Nature Neuroscience
Article Title
Brain motion is driven by mechanical coupling with the abdomen
Article Publication Date
27-Apr-2026
Optimizing a powerful tool for measuring brain activity
Sleep and age influence various measures of brain signals collected from awake individuals via electroencephalography, a tool for measuring brain activity both clinically and in human research.
Society for Neuroscience
Clinicians use electroencephalography (EEG) to assess brain activity in epilepsy and sleep pathologies, and this powerful tool has shown promise for other conditions. Emerging evidence suggests that brain development, age, and the time of day affect EEG signals measured during sleep. In a new eNeuro paper, researchers at the University Children’s Hospital of Zurich explored how differences in brain development, age, and sleep affect measures of EEG signals recorded from awake individuals. Elaborates lead author Sophia Snipes, “EEG studies have typically relied on summary measures when comparing patients or experimental conditions, but we picked apart the EEG signal with more detail to better understand the meaning behind the differences we were observing.”
First, supporting previous findings, the researchers found that four measures of EEG signals from 163 awake people aged 3–25 were differentially affected by sleep history and age. One measure showed an interaction between sleep history and age that could potentially reflect how children experience more brain changes during learning and memory compared to adults—a new finding, according to the researchers. Another measure displayed a surprising developmental shift, with opposite results in children and adults after a night of sleep. These findings ultimately demonstrate that brain signals during wakefulness depend on prior sleep, and that this effect differs between children and adults.
Because ADHD patients have developmental differences to neurotypical people and because previous work identified brain activity differences in EEG recordings taken from sleeping ADHD patients, the researchers further assessed their specific measures from the data of 58 awake ADHD children. No differences in the measures were observed based on ADHD diagnosis alone, suggesting to the researchers that sleep quality, more than symptoms of ADHD itself, may explain previously observed EEG data variability, though more work is needed.
Expanding on how this work may improve research and clinical use of EEG, says Snipes, “[Researchers and clinicians] have used this tool for a while, but more elaborate forms of data analysis can improve interpretations of EEG recordings. Even though we know certain variables change the EEG signal, we can’t assume what these changes mean if we don’t know what parts of the signal are changing.”
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About eNeuro
eNeuro is an online, open-access journal published by the Society for Neuroscience. Established in 2014, eNeuro publishes a wide variety of content, including research articles, short reports, reviews, commentaries and opinions.
About The Society for Neuroscience
The Society for Neuroscience is the world's largest organization of scientists and physicians devoted to understanding the brain and nervous system. The nonprofit organization, founded in 1969, now has nearly 35,000 members in more than 95 countries.
Journal
eNeuro
Subject of Research
People
Article Title
The Interaction Between Sleep and Development on Wake EEG Oscillations
Article Publication Date
27-Apr-2026
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