Why do we have traveling brain waves?
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Neuroscientist John Reynolds synthesized years of research about neural brain waves to propose they are a computational powerhouse that allow the brain to predict, reconstruct, and perceive the world.
view moreCredit: Salk Institute
LA JOLLA (July 21, 2026)—Your brain has something surprising in common with the ocean: waves! Electrical activity washes over the brain’s surface, creating what are called traveling brain waves or neural traveling waves. These waves cause real differences in your behavior and attention, and—again, like ocean waves—can have variable causes, from intrinsic to environmental inputs.
A new review article written by Salk Institute neuroscientists synthesizes the physiological and computational information about these neural traveling waves and draws a new conclusion: Neural traveling waves are a computational engine in the visual cortex. These waves allow the visual cortex (and likely other areas of the brain) to build representations of the external world, enabling our capacity to predict, reconstruct, and perceive the world around us.
The piece was published in Neuron on July 21, 2026.
What are traveling brain waves, and why do they exist?
Salk neuroscientist John Reynolds, PhD, was the first to identify traveling brain waves in the visual systems of awake animals back in 2020. What’s more, his lab found that these traveling brain waves directly correlated with whether those animals were able to perceive an object right in front of them—helping explain the classic conundrum of searching for something, like a pair of keys, that evidently was right in front of you the whole time.
After finding that traveling brain waves exist in awake animals, and that they alter animals’ ability to perceive stimuli at a given moment, Reynolds had a new question: Why?
“This paper lays out, for the first time in a single integrated framework, what the brain can actually compute by virtue of having this recurrent wave-generating circuitry,” says Reynolds, senior and co-corresponding author of the paper.
The researchers focused on the visual cortex, proposing neural traveling waves allow the visual cortex to: 1) modulate perception moment to moment, 2) turn recent sensory inputs into an internal representation of those inputs, 3) generate short-term predictions about the external world, and 4) store and replay patterns that represent memories of events unfolding in time.
What does this new framework mean?
The paper suggests that neural brain waves are much more than just electrical noise. The neural connections that generate these waves aren’t simply relaying signals; rather, they change their physiology (“synaptic weights”) to reflect the outside world.
Each sight, smell, sound, and action of an animal alters the connections that generate these waves, building the neural circuitry that the brain uses to construct an internal representation of the external world.
“This is, in a meaningful sense, analogous to what large language models like ChatGPT do,” explains Reynolds. “They learn statistical structure from language and use that knowledge to generate meaningful and appropriately structured text that reflects the patterns of language. The brain may be doing something functionally similar—a biological generative model built from the ground up by experience.”
Each time the brain receives sensory input, it must decide, what am I most likely sensing right now? Though the world is rich and complex, it is also somewhat predictable; objects around you exist in 3D space, you see the world in retinal images that change with your eye and body movements, and the laws of physics and physiology overlay this all.
Reynolds’ paper proposes that the brain internalizes these regularities by encoding them in networks of synapses, which can then generate waves that allow the brain to infer the likely causes of sensory input and construct an internal model of the world. This framing brings us one step closer to understanding how our brains compute the busy, messy world around us, turning a complicated sensory onslaught into behaviors and experiences.
Other authors and funding
Other authors of this study include Lyle Muller of UT Dallas and Fields Institute, Alexandra Busch of Fields Institute and Western University, and Zachary Davis of University of Utah.
This study was funded by the National Institutes of Health (R01 EY028723, U01 NS131914, and U01 NS139877, EY014800), Research to Prevent Blindness, Natural Sciences and Engineering Research Council of Canada, Western University, Compute Ontario, and Digital Research Alliance of Canada.
This press release was written by Isabella Davis.
About the Salk Institute for Biological Studies
The Salk Institute is an independent, nonprofit research institute founded in 1960 by Jonas Salk, developer of the first safe and effective polio vaccine. The Institute’s mission is to drive foundational, collaborative, risk-taking research that addresses society’s most pressing challenges, including cancer, Alzheimer’s, and agricultural vulnerability. This foundational science underpins all translational efforts, generating insights that enable new medicines and innovations worldwide. Learn more at www.salk.edu.
Journal
Neuron
Article Title
Neural traveling waves in cortex: network mechanisms and potential roles in neural computation
Article Publication Date
21-Jul-2026
Why brains lose their flexibility in
psychiatric conditions
Rutgers researchers find that dynamic brain function better explains individual mental health experiences than conventional diagnostic labels
Individuals with psychiatric conditions show reduced flexibility in their brain network dynamics, according to a new Rutgers study.
The human brain is organized into networks that can adaptively shift and reorganize to meet ever-changing cognitive and emotional demands. This flexible reconfiguration of brain networks over time supports our ability to regulate our thoughts and behavior. Disruptions in the brain’s dynamic processes are thought to play an important role in psychiatric illness. However, it remains unclear how differences in brain network dynamics relate to the wide range of symptoms seen across mental health conditions.
The study, published in Nature Communications, was led by Carrisa Cocuzza, a postdoctoral fellow, and Avram Holmes, an associate professor of psychiatry at Robert Wood Johnson Medical School and core faculty member of the Center for Advanced Human Brain Imaging Research within the Rutgers Brain Health Institute.
The researchers used a large, transdiagnostic dataset of 219 people that included individuals with 11 psychiatric diagnoses, alongside extensive behavioral, cognitive and clinical assessments. Participants underwent magnetic resonance imaging scans both at rest and while performing tasks, allowing the researchers to examine how brain connectivity patterns changed across six cognitive states.
Using these data, team members characterized how brain networks reconfigure over time and identified individual “symptom fingerprints” by grouping behavioral and clinical measures into personalized profiles.
The researchers found individuals with psychiatric conditions showed reduced flexibility in their brain network dynamics.
“Their brain networks were less able to shift between different configurations across cognitive states compared to healthy individuals,” Cocuzza said.
These flattened dynamics were useful for distinguishing between patients and healthy participants as well as for identifying specific diagnostic categories.
“This work addresses a central challenge in clinical neuroscience, linking changes in brain function to the diverse symptoms experienced across psychiatric disorders,” Holmes said
Critically, patterns of brain network dynamics were more strongly related to individuals’ symptom fingerprints than to traditional diagnostic labels, suggesting that dynamic features of brain function may provide a more precise way of understanding mental illness, capturing how symptoms manifest in each individual rather than simply whether a diagnosis is present.
“The findings indicate that impairments in time-varying brain processes may underlie differences in cognitive and behavioral functioning across individuals,” Holmes added. “By showing that brain network dynamics track symptom variation across diagnostic boundaries, the study supports a shift toward more personalized, biology-informed models of mental health.”
Future research will build on these findings to further explore how brain network dynamics change over time and with intervention, to develop more precise, individualized approaches for assessing and supporting mental health.
Journal
Nature Communications
Method of Research
Data/statistical analysis
Subject of Research
People
Article Publication Date
21-Jul-2026
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