Traveling Waves and Neural Gates: My Theory on How Our Brain Quickly Adapts to New Situations

Connecting Two Fascinating Ideas About the Brain

While I’m not a neuroscientist or deep AI expert, I’ve been fascinated by two separate brain theories that seem to fit together like missing puzzle pieces. My theory connects research on traveling waves in the visual cortex with Danko Nikolic’s concept of neural gates (which he discusses through his work at gating.ai). By bringing these ideas together, I believe we can better understand how our brains so effectively adapt to changing situations.

This article shares my personal understanding of how these concepts might work together, offering everyday examples to illustrate this fascinating connection. While I’m approaching this as an interested observer rather than an expert, I hope these connections might spark further conversation about how our brains achieve their remarkable flexibility.

What Are Traveling Waves in the Brain?

From what I understand about the research by Sato, Nauhaus, and Carandini, when we see something, our brain doesn’t just process it at a single fixed location. Instead, waves of neural activity spread outward from the initial activation point, similar to ripples expanding across a pond after dropping a stone.

These traveling waves move across our brain at speeds of about 0.1-0.4 meters per second. They appear to follow specific pathways, preferring to travel through brain regions with similar functions (like areas that process similar orientations in the visual field).

What I find particularly interesting is that these waves aren’t constant—they change based on what we’re looking at:

They’re strongest when we look at isolated objects (like a single letter or shape)
They’re very noticeable during spontaneous activity (when our mind is wandering)
They almost disappear when we’re looking at high-contrast scenes that fill our visual field

This context-dependence suggests to me that these waves aren’t just a side effect of neural activity but serve an important purpose in how our brain processes information.

What Are Neural Gates?

The other piece of this puzzle comes from Danko Nikolic’s theory of neural gates. As I understand it, these gates are like switches in our brain that can quickly reconfigure neural pathways. Rather than permanently rewiring our brain (which would take much longer), these gates can temporarily change how information flows through our neural circuits.

According to Nikolic’s theory, our brain contains countless such gates that:

Can open or close rapidly (within milliseconds to seconds)
Have default states that they return to after being temporarily activated
Learn when they should activate based on patterns they detect
Need a brief “recovery period” after activation before they can be used again

These gates might be implemented through specialized proteins called metabotropic receptors and G-protein-gated ion channels. Unlike the faster-acting mechanisms usually emphasized in neuroscience, these can change a neuron’s behavior for several hundred milliseconds or even minutes.

My Theory: Waves and Gates Working Together as a Dynamic System

Here’s where my personal theory comes in: I believe traveling waves and neural gates work together as a unified system to give our brain its remarkable flexibility and efficiency. In this combined view:

Waves as Information Carriers

The traveling waves serve as carriers of contextual information, propagating outward from points of initial activation. They don’t merely spread neural excitation—they carry complex signals that inform processing across different brain regions.

Gates as Contextual Interpreters

As waves traverse the brain, they encounter neural gates that “read” the contextual information contained in the wave patterns. Based on this information, gates dynamically reconfigure local neural circuits to optimize processing for the current situation.

Dynamic Processing Networks

I imagine the brain as containing multiple processing regions separated by gated boundaries. Traveling waves propagate through these regions, with gates determining whether and how the waves pass between regions.

When a wave encounters a gate, several things might happen:

The gate might remain closed, preventing the wave from affecting downstream regions
The gate might open partially, allowing specific aspects of the wave to propagate
The gate might open fully, facilitating complete transmission of the wave
The gate might transform the wave, altering its properties before propagation

These decisions would be made based on the contextual information encoded in the wave itself, allowing for rapid, context-specific reconfiguration of processing pathways.

How This Might Work in Everyday Situations

Let me illustrate my theory with some everyday examples that show how waves and gates might work together:

Reading Different Words

When you read the word “apple,” your brain first activates the visual regions that recognize those specific letter shapes. Then, a traveling wave of activity spreads from this initial activation to related brain areas. As this wave propagates, it encounters various neural gates that control which brain regions will process this information next.

Some gates open, allowing the wave to activate areas associated with:

The concept of fruit
The color red
Perhaps memories of eating apples
Maybe even the smell and taste of apples

When you then read “automobile,” a different pattern of gates opens, directing the traveling wave to activate areas associated with:

Vehicles
Driving experiences
The sound of engines
Different shapes and colors

The remarkable thing is how quickly your brain switches between these different processing modes. The gates reconfigure your neural pathways in milliseconds, allowing you to effortlessly transition from processing fruit-related concepts to vehicle-related concepts.

Driving a Car

While driving, your visual system constantly processes a complex, changing environment. Here’s how waves and gates might work together during this activity:

Seeing the road ahead: Traveling waves of neural activity spread from your visual cortex to areas that help you maintain your lane position and assess road conditions. Gates along these pathways are open, allowing this information to flow freely.
Noticing a pedestrian about to cross: The traveling wave encounters gates that immediately reconfigure your neural processing to focus attention on the pedestrian. Gates open to pathways leading to regions that prepare motor responses (like slowing down) while temporarily closing gates to less important information.
Glancing at your speedometer: Gates temporarily redirect the traveling waves to activate regions processing numbers and comparing them to speed limits. Meanwhile, gates partially close pathways related to processing the road scene, though keeping critical safety monitoring active.
Looking back at the road: The gates reset, closing pathways to speedometer processing and reopening the full pathways to road scene processing.

All of these transitions happen seamlessly within fractions of a second. Without gates directing these traveling waves, I believe your brain would need much more time and energy to reconfigure its processing for each different focus of attention.

Why This Matters: Shallow But Smart

One of the most fascinating implications of this unified theory is that it explains how our brains can be so computationally powerful despite having a relatively shallow architecture.

Modern artificial intelligence systems often use “deep learning” with hundreds of layers of artificial neurons. Yet your brain’s cortex is only about 2-4 mm thick with far fewer “layers.” How does it accomplish so much with so little depth?

The answer may lie in this dynamic combination of traveling waves and neural gates. Rather than needing hundreds of layers stacked on top of each other, your brain can use the same neural tissue for many different functions by:

Using traveling waves to spread information horizontally across the brain
Employing gates to dynamically reconfigure how that information is processed
Reusing the same neural circuits for different tasks by changing which gates are open or closed

This is far more efficient than having dedicated, separate circuits for every possible task. It’s like having a single piece of multi-purpose workshop equipment that can be quickly reconfigured to serve as a drill, a saw, a sander, or a lathe, rather than needing separate machines for each function.

Evidence That Supports This Combined Theory

While I’m not a neuroscientist, several observations seem to support this unified view of traveling waves and neural gates:

Context-Dependent Wave Behavior

The traveling waves observed in the brain don’t behave the same way in all situations. They’re strongest with isolated stimuli and almost disappear with high-contrast, full-field stimulation. This variable behavior suggests they’re under the control of some gating mechanism that adapts to different contexts.

Speed of Adaptation

Our brain can adapt to new situations faster than would be possible if it needed to physically rewire its connections each time. The timeframes of traveling waves (hundreds of milliseconds) and the operation of neural gates match perfectly with the speed at which we can switch attention or adapt to new situations.

Selective Propagation Pathways

Traveling waves don’t spread uniformly in all directions—they show preference for regions with similar functions (like similar orientation preferences in visual cortex). This selective propagation suggests they follow pathways determined by gates that control which connections are currently active.

Fading Memory Experiments

From what I’ve read, experiments on fading memory in neural responses have revealed complex temporal dynamics, including periods of suppression followed by reemergence of activity. These patterns are difficult to explain with traditional models but align well with the temporal properties of gates, which can transiently suppress activity before returning to default states.

What This Might Mean for Brain Science and AI

If my theory about the connection between traveling waves and neural gates is on the right track, it could have interesting implications:

For Understanding Our Brain

This combined theory provides a framework for understanding many aspects of brain function, from attention and working memory to why we can switch so quickly between different cognitive tasks. It might help explain how a relatively shallow structure like our cortex can perform such complex computations.

For Artificial Intelligence

Current AI systems might benefit from incorporating similar principles, creating shallower but more dynamically reconfigurable networks rather than just adding more and more layers. This could lead to AI systems that:

Are more energy-efficient
Can adapt more quickly to new situations
Don’t need as much training data
Better mimic human-like flexibility in thinking

A Personal Perspective on a Dynamic, Adaptive Brain

As someone fascinated by how the brain works, I find this connection between traveling waves and neural gates compelling because it gives us a new way to understand how our brain achieves its remarkable flexibility and efficiency. Rather than being a static, hardwired system, our brain appears to be in constant flux—waves of activity travel across its surface, encountering gates that dynamically reconfigure neural circuits based on current needs.

This dynamic, adaptable architecture may be the secret to the brain’s remarkable ability to perform so many complex tasks with relatively limited neural resources. Instead of needing deep, specialized circuits for each possible task, our brain uses the same neural tissue in different configurations, dynamically routing information through changing patterns of gates opened by traveling waves.

As we go about our day—reading different words, driving our car, recognizing faces, or solving problems—our brain is constantly reconfiguring itself through this elegant interplay of traveling waves and neural gates, allowing us to seamlessly navigate a complex, ever-changing world.

While I offer this theory as an interested observer rather than an expert, I believe the research on traveling waves in visual cortex provides a missing puzzle piece that helps explain how Nikolic’s neural gating theory might be implemented in practice across the brain. Together, they create a unified picture of how our minds can so effortlessly adapt to new situations moment by moment.

I hope this perspective might encourage further exploration of how these fascinating brain mechanisms might work together, potentially leading to new insights in neuroscience or inspiring more brain-like approaches to artificial intelligence.