Summary: Researchers discovered the first definitive neural evidence of how the brain creates and reuses abstract symbols to think creatively. The research tracks the neural substrates of “compositional generalization”, the foundational cognitive ability to take familiar components and recombine them into entirely fresh ideas.
By observing brain cell activity in primate models during complex touchscreen tasks, investigators located this symbolic engine within the ventral premotor cortex. This discovery upends traditional views of the motor system, offering a mechanistic look at abstract thought while providing templates to optimize brain-computer interfaces (BCIs) and assess cognitive disorders.
Key Facts
- The Recombination Engine: Humans naturally possess the capacity to learn discrete symbolic units—like words, shapes, or musical notes—and envision how those symbols can be reused in novel contexts to fuel problem-solving and creative thinking.
- The Ventral Premotor Mediator: Neuroscientists located the neural substrates of this process inside the ventral premotor cortex, a section of the frontal lobe. The region serves as a crucial mediator, bridging the prefrontal cortex (responsible for high-level planning) and the motor cortex (responsible for executing physical movement).
- The “Action Symbol” Paradigm: Because human brain-imaging tech lacks the resolution to monitor individual nerve cells, researchers trained macaque monkeys to draw geometric shapes (lines, arcs, squares) on touchscreens, treating each shape as a discrete “action symbol”.
- Choosing Logic Over Tracing: When presented with complex, completely new shapes, the animals actively chose to strategically recombine their learned symbols to build the images rather than relying on a basic, unthinking tracing strategy. This proved they understood the actions as abstract symbolic building blocks.
- The Mental Typewriter: The study fundamentally redefines the ventral premotor cortex. Long mischaracterized as a basic motor-planning zone for finger movements, the data proves it acts as an abstract mental typewriter, specifying the symbolic “key” to press before instructing the motor cortex to execute the actual stroke.
- Upgrading BCIs and Diagnosis: Mechanistically decoding how symbols are assembled provides a framework to dramatically improve BCIs, allowing devices to translate neural intent into fluent speech or physical action. The paradigm also offers diagnostic pathways for action-planning disorders like constructional apraxia and psychiatric conditions like schizophrenia.
Source: Rockefeller University
If you ask a child to draw an animal that doesn’t exist, they’ll often cobble together components from real ones—say, the body of a seal with an elephant’s trunk, four octopus arms, and one lizard eye.
This imaginative ability is theorized to stem from our larger capacity to learn symbolic units—an arm or a leg in the aforementioned example, or perhaps a word—and then envision how those symbols could be reused in a new context. Neuroscientists call this facility for recombining familiar elements into fresh ideas compositional generalization, and it is hypothesized to be key to problem solving, making sense of new situations, and creative thinking.
In new research published in Nature, Rockefeller University’s Laboratory of Neural Systems has found the first evidence of the neural substrates that underlie this process. The team located it in the ventral premotor cortex, a section of the frontal lobe.
The region appears to act as a sort of mediator between the prefrontal cortex, where higher-level thinking such as planning occurs, and the motor cortex, which enables movement.
In their findings, the researchers not only illuminate fundamental properties of neural function but also see implications for improving computer-brain interfaces (BCIs) and studying brain disorders.
“The discovery solves a long-standing problem in cognitive neuroscience: Where do symbols—the basic units of thought—come from?” says Winrich Freiwald, head of the lab. “It also points to a future—a near future—in which we can understand thinking mechanistically.”
Action symbols
Compositional generalization is an influential hypothesis in neuroscience for explaining the wide variety of human abilities that use abstract thought to generate new ideas, including math, written and spoken language, drawing, dancing, handwriting, and musicianship. It may also characterize cognitive abilities we share with other animals, such as reasoning, object manipulation, and tool use.
However, there hasn’t been definitive neuroscientific evidence of symbols. “The idea behind our research was, if these reusable components exist, what would their neural activity look like?” says first author Lucas Tian, a postdoctoral fellow in the lab. “If there are units that are being reused in different situations, then you should be able to see that in the neural data.”
Designing an experiment to locate such neural mechanisms, however, was no mean feat. Only humans do math, use language, or draw, and the methods currently used for measuring brain activity in humans do not have the necessary resolution to monitor the activity of nerve cells in the brain.
To bypass that technical limitation, Tian worked with macaque monkeys. “We wanted to develop an animal model in which we can actually observe compositionality in action in the animals’ behavior while simultaneously doing neural recordings to understand how the brain might be doing this,” Tian describes.
But he still had to confront the problem of finding a behavioral paradigm for the animals that could uncover their compositional abilities. Tian’s idea was to teach them to trace simple geometric figures on touchscreens—lines, squares, arcs, circles, triangles—and then task them with re-creating new shapes, all while observing their brain activity through sensors. Each simple shape was considered its own discrete knowledge unit, or action symbol—action because they had to physically execute the drawing of each one.
Then he built novelty into the experiment by testing how the monkeys drew new, more complex shapes. “I gave them a lot of symbol variation rather than having them repeat one simple task over and over. They had to learn how to grapple with new and changing factors, which is the sort of environment you’d find compositional generalization useful for,” Tian describes.
He found that even though they could have drawn these new images by using a simple tracing strategy—moving their fingers along the edges of the shapes—they instead chose to recombine the symbols they had learned to create new complex combinations. This revealed that they had understood these actions as symbols—building blocks for creating novel drawings.
Surprising activity
Tian used an array of electrodes to observe hundreds of neurons across eight brain regions simultaneously throughout these activities.
“It was important for us to cast a wide net,” he notes, “because no one knew whether—or where —compositional generalization might be occurring in the brain.”
The study found that one particular region activated as the monkeys drew: the ventral premotor cortex, an area of the frontal lobe traditionally associated with the planning and execution of movement—especially hand movements. Tian and his colleagues found that the activity was not simply involved in motor execution but represented a high-level cognitive representation of the action itself.
“What Lucas found forces us to re-think the role of this part of the brain,” Freiwald says. “It is not simply a part of the motor system one step removed from the control of the finger, but an area that generates a sort of mental typewriter. It specifies in an abstract format the ‘key’ to press when you want to express yourself in writing, and then instructs another area to turn that key into a stroke.”
Insights into disorders of the human brain
The researchers believe their novel approach could develop into a foundational experimental paradigm that could be used in humans as well. Drawing is a widely used tool for diagnosing cognitive disorders; specific disorders result in specific drawing impairments.
“One possibility is that the things we learn could lead to new insights into psychiatric disorders such as schizophrenia or action-planning disorders like constructional apraxia, where people have trouble creating complex action sequences even though they understand the task at hand and retain basic motor abilities,” says Tian.
To that end, they plan to collaborate with neurosurgeons and their patients to gather brain activity data from people who have had a procedure involving brain implants, such as for epilepsy.
They also see possibilities for the improvement of BCIs. “Knowing how thinking works mechanistically will improve our ability to read the activity of the human brain and express it into speech or action through brain-machine interfaces, where such expression is not otherwise possible,” Freiwald says.
Moreover, there are essential questions about cognition at play, he adds. “This is basic research on a fundamental quality of human nature—thinking, which is altered in many psychiatric disorders. We conduct this work with the goal of improving the human condition.”
Key Questions Answered:
A: When a child draws a creature that doesn’t exist, they instinctively grab a seal’s body, an elephant’s trunk, and an octopus’s arms. This ability to take familiar, separate components and recombine them to handle a brand-new situation is called compositional generalization. It is the biological framework behind language, math, art, and everything we define as human creative thinking.
A: For decades, scientists thought this region was just a basic cog in the motor system meant to move your fingers. This study forces a complete rewrite of that theory. The area is actually a high-level cognitive powerhouse that holds abstract symbols. It picks out the conceptual “key” you want to type to express yourself, and then passes that abstract blueprint down to the muscles to create a stroke.
A: Modern Brain-Computer Interfaces (BCIs) try to read a patient’s brain activity and turn it into speech or machine movement. Up until now, we didn’t know the exact mechanism of how the brain structures abstract units of thought. By revealing how the brain builds and combines these symbolic building blocks in real time, engineers can design BCIs that read intent mechanistically, allowing paralyzed individuals to express themselves with unprecedented speed and fluid accuracy.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this neuroscience and abstract thought research news
Author: Katherine Fenz
Source: Rockefeller University
Contact: Katherine Fenz – Rockefeller University
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Neural representation of action symbols in primate frontal cortex” by Lucas Y. Tian, Kedar Garzón Gupta, Daniel J. Hanuska, Adam G. Rouse, Mark A. G. Eldridge, Marc H. Schieber, Xiao-Jing Wang, Joshua B. Tenenbaum & Winrich A. Freiwald. Nature
DOI:10.1038/s41586-026-10297-x
Abstract
Neural representation of action symbols in primate frontal cortex
A hallmark of intelligence is proficiency in solving new problems, including those that substantially differ from previously seen problems. Problem solving in turn depends on the goal-directed generation of novel ideas and behaviours, which has been proposed to involve internal representations of discrete units (or symbols) that can be recombined into numerous possible composite representations.
Although this view has been influential in cognitive-level explanations of behaviour, definitive evidence for a neuronal substrate of symbols has remained elusive.
Here we identify a neural population that encodes action symbols—recombinable representations of discrete units of motor behaviour—in a specific area of the frontal cortex.
In macaque monkeys performing a drawing-like task, we found behavioural evidence that action elements (strokes) exhibit three crucial features that indicate an underlying symbolic representation: (1) invariance over low-level motor parameters; (2) categorical structure, which reflects discrete action types; and (3) recombination into novel sequences.
Based on simultaneous neural recordings across eight regions of the motor, premotor and prefrontal cortex, we identified population activity specifically in the ventral premotor cortex that encodes planned actions in a manner that also reflects invariance, categorical structure and recombination.
These findings reveal a neural representation of action symbols localized to the ventral premotor cortex and a putative neural substrate for symbolic operations.
