Coherence in the Brain ― A Primer on Waves

July 24, 2026 Coherence No Comments

The picture of the brain as a network of neurons exchanging electrical signals is correct, but incomplete. Recent neuroscience increasingly shows that neural activity unfolds as dynamic waves that continuously travel across the cortex, organizing and reorganizing the brain as they go.

This is especially fascinating because these discoveries offer an unexpectedly concrete window into a deeper idea explored throughout the AURELIS blogs: that intelligence may emerge not from isolated components but from ongoing coherencing.

Looking beyond brain waves

For many people, brain waves evoke familiar images from an EEG: regular oscillations associated with sleep, relaxation, or concentration. These rhythms are only part of the story. Looking more closely, modern neuroscience reveals something much richer. Waves do not simply oscillate in place. They move. They spread across the cortex, interact with one another, merge, split, and continuously reshape the brain’s activity.

This changes how one looks at the brain itself. Instead of imagining countless neurons independently exchanging information, it becomes possible to see the brain as a living landscape of continuously evolving patterns. Activity is not merely transmitted; it is organized. What matters is increasingly not just which neurons are active, but how activity propagates through the entire system.

This blog asks a simple question: if coherence is indeed a fundamental principle of mind, would we expect the brain to behave in ways that reflect it? Remarkably, many recent discoveries suggest exactly that. As discussed in Coherence, Basically, coherence is understood here as the dynamic organization of mutually constraining elements into a meaningful whole. The present blog explores whether traveling cortical waves may be one observable expression of such ongoing organization.

Waves everywhere: the living cortex

One of the most striking discoveries of recent years is that traveling waves appear almost everywhere in the living brain. They are observed during perception, movement, memory, spontaneous thought, sleep, and wakefulness. They are not rare events produced under special circumstances but seem to be an intrinsic aspect of normal brain function.

These waves come in many forms. Some move almost like ripples across water. Others rotate in spiral-like patterns. Still others emerge from temporary sources, disappear into sinks, or change direction while interacting with neighboring waves. The brain resembles less a machine executing fixed programs than a sea whose currents are constantly changing while maintaining an overall organization.

Perhaps surprisingly, this apparent complexity is not a sign of disorder. On the contrary, the waves display recognizable patterns that repeatedly organize themselves across many spatial and temporal scales. They are dynamic rather than static, continuously adapting to changing circumstances while preserving an underlying coherence. As explored in Coherencing, the emphasis shifts from a fixed state toward an ongoing process of organization.

Thinking in terms of wave fields instead of isolated signals also changes how one approaches brain function. Rather than asking where a particular thought resides, it becomes more natural to ask how the brain organizes itself at each moment to make that thought possible.

The brain is not merely a collection of modules

For a long time, neuroscience largely searched for specialized brain regions responsible for particular mental functions. Some areas indeed contribute more strongly to language, others to vision or movement. Yet modern research increasingly shows that these regions rarely work in isolation. Their roles change continuously depending on the broader context within which they operate.

Traveling waves beautifully illustrate this principle. They ignore many of the anatomical boundaries that textbooks traditionally emphasize. Instead, they move across multiple regions, temporarily linking distant parts of the cortex into functional wholes. A region participating in one process at one moment may contribute to a very different process only moments later, depending on the evolving pattern of activity.

This fits remarkably well with ideas developed earlier in From Patterns to Meaning. Meaning is unlikely to reside inside individual neurons, just as the melody of an orchestra does not reside inside a single violin. Rather, meaning emerges through relationships among many interacting elements. The parts remain essential, yet the organization among them becomes equally important.

Seen from this perspective, the cortex is less like a collection of independent departments than like an orchestra continuously adjusting itself while playing. No conductor issues detailed commands at every instant. Instead, the music emerges from the ongoing coordination of many participants, each influencing and being influenced by the evolving whole.

Wakefulness means greater organized complexity

One might naturally assume that an alert brain is simply more synchronized than a sleeping or anesthetized one. Recent findings suggest something more subtle. During anesthesia, wave patterns often become larger, more regular, and more homogeneous. Sleep occupies an intermediate position. Especially during deep sleep, large synchronized waves dominate, reflecting a brain that remains highly organized but is temporarily less open to the outside world. In contrast, the awake brain displays a much richer diversity of interacting wave patterns, with many local and global processes unfolding simultaneously.

Wouldn’t greater complexity imply less organization? Not necessarily. A completely synchronized brain would leave little room for flexible thought. On the opposite extreme, completely random activity would prevent meaningful coordination. Healthy cognition appears to require something in between: a richly organized diversity in which many local processes remain coordinated without becoming identical.

This distinction is central. Coherence should not be confused with uniformity. A choir does not become better by singing one single note. Its beauty lies in many voices maintaining meaningful relationships while preserving their individual contributions. The same seems true of the brain. Intelligence flourishes not through rigid synchronization but through dynamic cooperation among diverse processes.

This idea echoes themes explored in Gestalt and A.I.: From Parts to Meaningful Wholes. A meaningful whole is neither the mere sum of isolated parts nor an undifferentiated unity. It is an organized pattern in which differentiation and integration continuously support one another.

Global and local coherence work together

One of the most intriguing aspects of cortical waves is that they operate simultaneously on many scales. Some remain relatively local, influencing neighboring populations of neurons. Others spread across much larger parts of the cortex, coordinating activity over considerable distances. Neither level appears sufficient on its own.

Local dynamics allow flexibility. They enable the brain to respond to specific circumstances, explore alternatives, and adapt rapidly to changing situations. Global dynamics, meanwhile, provide continuity. They integrate information across distant regions, allowing the brain to function as one coherent organism rather than as a loose collection of independent subsystems.

Modern neuroscience increasingly suggests that healthy cognition depends precisely on the ongoing interaction between these two tendencies. Local processes continually shape global organization, while the global state simultaneously influences local activity. Neither permanently dominates the other. Instead, both participate in a continuous dialogue.

This resonates strongly with Coherence Theory. Coherence does not emerge through centralized control. Nor does it arise from isolated local interactions alone. It develops through reciprocal influence, where larger patterns guide smaller ones while simultaneously growing out of them. As discussed in Coherence, Basically, the whole and the parts continually shape one another. Traveling cortical waves may be one of the most beautiful physiological demonstrations of that principle.

Waves compute by interacting

Perhaps the most remarkable aspect of cortical waves is that they do not simply carry signals from one place to another. They influence one another. As waves meet, they may reinforce, redirect, weaken, or reshape each other. New patterns emerge while others dissolve. Instead of resembling messages traveling along telephone wires, these interactions resemble conversations in which each contribution slightly changes the discussion.

Recent research even suggests that such interactions may perform genuine computation. Rather than relying exclusively on specialized circuits or fixed processing stages, the brain appears capable of transforming information through the evolving dynamics of wave interactions. Computation, in this view, is less about executing predefined instructions than about allowing coherent patterns to develop naturally through mutual influence.

This perspective fits well with ideas presented in From Patterns to Meaning. Meaning does not emerge because isolated components perform increasingly complex calculations. It emerges because many elements gradually organize themselves into a coherent whole. Traveling waves may therefore be viewed not as the computation itself but as one of its most visible physiological expressions.

One consequence is particularly intriguing. The brain no longer appears to contain a single place where ‘the thinking happens.’ Thinking becomes something the entire organized system continuously does. Individual neurons remain indispensable, yet we increasingly see that intelligence also resides in their evolving relationships.

From attractors to continuous coherencing

For many years, neuroscientists often described brain activity in terms of attractors: relatively stable states toward which neural activity naturally evolves. This remains an important idea, but contemporary research paints a more dynamic picture. Instead of settling into fixed states, the brain appears to move continuously through changing landscapes of temporary stability.

This ongoing movement is often described as metastability. The term may sound abstract, but the intuition is straightforward. Imagine walking across gently rolling hills rather than standing inside a single valley. One remains locally stable for a while, yet movement continues naturally toward new configurations as circumstances change. The brain seems to function in much the same way.

Traveling waves fit naturally into this picture. They do not merely pass through a fixed landscape; they help reshape the landscape itself. Each moment of organization influences the possibilities available during the next. In that sense, the brain continually prepares itself for what comes next without ever becoming completely fixed.

As explored more extensively in Coherencing, coherence is not simply something the brain possesses. It is something the brain continuously becomes. The waves make this ongoing becoming directly visible.

Long-range communication without central control

An especially interesting discovery concerns communication across distant brain regions. During wakefulness, long-range connections become remarkably effective. Yet this does not happen because a central controller suddenly takes charge. Instead, local wave dynamics appear to create favorable conditions that allow distant regions to cooperate more efficiently.

In other words, large-scale organization depends upon healthy local organization. The relationship is reciprocal. Local activity supports global coordination, while the evolving global state continuously shapes local responsiveness. Neither direction alone tells the full story.

This offers a refreshing alternative to older images of the brain as a hierarchy issuing commands from above. While hierarchical organization exists anatomically, functionally the picture is much richer. Influence flows in many directions simultaneously. Organization propagates rather than commands.

The result is a remarkably flexible system. Without sacrificing unity, it preserves the ability to adapt, reorganize, and discover new solutions. Such flexibility would be difficult to explain if intelligence depended primarily on rigid control. It becomes much more understandable if intelligence emerges through ongoing coherence.

The geometry of coherencing

Another recent development takes the discussion even further. Increasingly, neuroscientists describe the brain using ideas from topology — the mathematics of relationships and organization rather than simple distances.

Ordinary network diagrams connect pairs of nodes. Topological approaches ask a broader question: what larger patterns arise when many elements interact simultaneously? Rather than focusing on individual links, they examine the shapes created by many relationships taken together.

Interestingly, these approaches increasingly reveal that brain organization cannot be adequately understood through pairwise connections alone. Higher-order structures emerge that remain stable even while individual connections change. The precise mathematics need not concern us here. What matters is the growing realization that organization itself has a measurable geometry.

This again resonates with Coherence Theory. Coherence has never been proposed as a collection of isolated links but as an evolving organization among many mutually constraining elements. The conceptual direction is remarkably similar.

What neuroscience does – and does not – show

At this point, an important distinction deserves emphasis. None of the findings discussed here proves Coherence Theory. Scientific theories are not established by a single experiment, nor should different perspectives be forced into premature agreement.

What is striking, however, is the growing convergence. Traveling waves, metastability, recurrent processing, large-scale dynamics, neuronal assemblies, topological organization, and predictive processing all emerged from largely independent research traditions. Each developed its own methods and vocabulary. Yet they increasingly portray the brain as a continuously self-organizing dynamical system rather than as a collection of isolated computational modules.

That convergence is perhaps more interesting than any individual discovery. Independent lines of investigation often illuminate different aspects of the same underlying phenomenon long before a common conceptual language emerges. Coherence Theory is a possible candidate for such a language — not because it replaces neuroscience, but because it offers an organizational perspective that can bring many of these observations into meaningful relationship.

Readers interested in the broader concept of coherence itself may find it useful to return to Coherence, Basically, while this blog has deliberately remained close to one particularly illuminating physiological phenomena.

The brain as a continuously coherencing system

The accompanying addendum presents a table titled Core principles of Coherence Theory and their compatibility with cortical-wave dynamics. It compares a series of organizational principles with recent neuroscience findings on traveling waves.

The comparison is intentionally modest. It does not identify cortical waves with coherence itself. Nor does it suggest that one physiological mechanism explains the whole mind. Instead, it asks whether the observable behavior of cortical waves exhibits characteristics one would naturally expect if the brain were continuously coherencing.

Seen together, the correspondences are difficult to ignore. Whole-to-part modulation, distributed organization, history dependence, dynamic context, nested organization across scales, recursive self-organization, adaptive stability, and the reduction of combinatorial complexity all find meaningful counterparts in contemporary studies of cortical-wave dynamics. Together they form an increasingly coherent picture.

That is how science often progresses. Not through one decisive observation, but through many independent discoveries gradually fitting together until a broader understanding begins to emerge.

Conclusion

Traveling waves are fascinating. Their greatest significance lies in making visible something fundamental: the brain’s continuous process of organizing itself into ever-changing coherent patterns.

Instead of picturing intelligence as residing within particular neurons or specialized modules, modern neuroscience increasingly invites a different image. The brain resembles a living landscape in which countless local interactions continually give rise to larger patterns, while those larger patterns simultaneously guide local activity. Intelligence appears less like a stored object than like an ongoing process.

This brings neuroscience closer to everyday experience. Human understanding rarely feels like assembling disconnected pieces. More often it feels like something gradually falling into place. Meaning emerges, relationships become clearer, and what first seemed fragmented acquires an unexpected unity.

Perhaps the greatest contribution of recent research on cortical waves is therefore not simply that it has revealed new forms of neural activity. It has begun to show that the living brain is never merely active. It is continuously coherencing.

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Bibliography

Aggarwal, Adeeti, Jennifer Luo, Helen Chung, Diego Contreras, Max B. Kelz, and Alex Proekt. 2024. “Neural Assemblies Coordinated by Cortical Waves Are Associated with Waking and Hallucinatory Brain States.” Cell Reports 43 (4): 114017. https://doi.org/10.1016/j.celrep.2024.114017.

Bassett, Danielle S., and Olaf Sporns. 2017. “Network Neuroscience.” Nature Neuroscience 20 (3): 353–64. https://doi.org/10.1038/nn.4502.

Bassett, Danielle, and Edward Bullmore. 2006. “Small-World Brain Networks.” The Neuroscientist 12 (December): 512–23. https://doi.org/10.1177/1073858406293182.

Breakspear, Michael. 2017. “Dynamic Models of Large-Scale Brain Activity.” Nature Neuroscience 20 (3): 340–52. https://doi.org/10.1038/nn.4497.

Deco, Gustavo, and Morten L. Kringelbach. 2020. “Turbulent-like Dynamics in the Human Brain.” Cell Reports 33 (10): 108471. https://doi.org/10.1016/j.celrep.2020.108471.

Keller, T. Anderson, Lyle Muller, Terrence Sejnowski, and Max Welling. 2024. “Traveling Waves Encode the Recent Past and Enhance Sequence Learning.” International Conference on Learning Representations 2024: 12763–89. https://proceedings.iclr.cc/paper_files/paper/2024/hash/374fc6371864f800f213bf8a248f1117-Abstract-Conference.html.

Liang, Yuqi, Junhao Liang, Chenchen Song, et al. 2023. “Complexity of Cortical Wave Patterns of the Wake Mouse Cortex.” Nature Communications 14 (March): 1434. https://doi.org/10.1038/s41467-023-37088-6.

Margulies, Daniel S., Satrajit S. Ghosh, Alexandros Goulas, et al. 2016. “Situating the Default-Mode Network along a Principal Gradient of Macroscale Cortical Organization.” Proceedings of the National Academy of Sciences of the United States of America 113 (44): 12574–79. https://doi.org/10.1073/pnas.1608282113.

Muller, Lyle, Patricia S. Churchland, and Terrence J. Sejnowski. 2024. “Transformers and Cortical Waves: Encoders for Pulling in Context across Time.” Trends in Neurosciences 47 (10): 788–802. https://doi.org/10.1016/j.tins.2024.08.006.

Sporns, Olaf, Giulio Tononi, and Rolf Kötter. 2005. “The Human Connectome: A Structural Description of the Human Brain.” PLoS Computational Biology 1 (4): e42. https://doi.org/10.1371/journal.pcbi.0010042.

Sporns, Olaf. 2013a. “Structure and Function of Complex Brain Networks.” Dialogues in Clinical Neuroscience 15 (3): 247–62. https://doi.org/10.31887/DCNS.2013.15.3/osporns.

Wagemans, Johan, Jacob Feldman, Sergei Gepshtein, et al. 2012. “A Century of Gestalt Psychology in Visual Perception: II. Conceptual and Theoretical Foundations.” Psychological Bulletin (US) 138 (6): 1218–52. https://doi.org/10.1037/a0029334.

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Addendum

Table: Core principles of Coherence Theory and their compatibility with cortical-wave dynamics

Core principle of Coherence Theory	Organizational meaning	Compatibility with cortical-wave dynamics	Why the convergence matters
Whole-to-part modulation	The organization as a whole continuously influences the behavior of its constituent parts.	Cortical waves modulate local neuronal excitability, influencing when and how individual neurons respond according to the current global dynamical state.	The larger organization becomes causally relevant through modulation rather than centralized control.
Distributed organization	Meaning emerges from interactions among many elements rather than from isolated units.	Traveling waves propagate through distributed neural populations, overlap, interfere, and interact across space, time, frequency, and scale.	Brain function appears fundamentally distributed rather than localized.
History-dependent coherence	The present continuously incorporates the recent past.	Earlier neural activity generates evolving wave states into which later stimuli arrive.	The past remains active by shaping the organization that receives the present.
Dynamic context	Every event is interpreted within an already existing organization.	The same stimulus can evoke different responses depending on the phase and state of ongoing cortical-wave dynamics.	Context becomes an intrinsic property of the evolving brain rather than an external addition.
Nested coherence across scales	Coherence develops simultaneously at multiple interacting organizational levels.	Cortical waves occur across spatial and temporal scales, from local circuits to large-scale cortical dynamics.	No single privileged processing level is required; coherent organizations can be nested.
Differentiation within integration	Unity does not require uniformity; coherent systems preserve functional diversity.	Effective brain coordination combines differentiated activity with selective synchronization; excessive synchrony is often pathological.	Coherence is organized diversity, not uniform behavior.
Recursive self-organization	Emerging organization continually reshapes the conditions for further organization.	Traveling waves alter the neural landscape, thereby changing subsequent wave propagation and local responses.	The brain continually reorganizes itself through its own activity.
Prospective organization	Present coherence constrains future possibilities without rigidly determining them.	Cortical-wave dynamics bias future processing and contribute to short-term prediction and anticipatory modulation.	Prediction naturally emerges from ongoing organization rather than from separate predictive modules.
Reduction of combinatorial complexity	Coherent organization narrows the space of meaningful possibilities before explicit computation becomes necessary.	The current wave state modulates which neuronal responses become more probable and which incoming signals gain influence.	Organization simplifies processing by shaping the landscape of possibilities rather than by exhaustive search.
Resonant completion	Partial organization can recruit a larger coherent whole.	Distributed wave dynamics preserve previous activity, allowing partial input to interact with an already structured population state.	Suggests a physiological basis for retrieval through resonance and pattern completion rather than explicit address lookup.
Adaptive stability	Coherence possesses degrees of robustness rather than simple all-or-none existence.	Neural dynamical patterns vary in persistence, stability, and susceptibility to perturbation.	Coherent organizations can strengthen, weaken, or dissolve while maintaining continuity.
Multiple realizability (degeneracy)	Similar coherent functions may arise through different physical pathways.	Different neural pathways and dynamically changing configurations can produce comparable functional outcomes.	Functional coherence need not depend on one unique anatomical implementation.
Self-reinforcing coherence	Organization may increasingly sustain itself, adaptively or maladaptively.	Recurrent neural dynamics can stabilize persistent wave patterns; pathological states may likewise become self-maintaining.	Not every coherence is beneficial; coherent organization may become rigid or dysfunctional.

Note

This table does not claim that cortical waves are coherence, nor that they prove Coherence Theory. Rather, it shows that one of the brain’s most extensively studied dynamical phenomena exhibits striking, systematic compatibility with the core organizational principles proposed by Coherence Theory. The convergence is strongest at the level of organization rather than at the level of specific physiological mechanisms.

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