How The Innovator’s Brain Works

How does the human brain learn to innovate? The Thousand Brain theory, proposed by Silicon Valley innovator-turned-scientist Jeff Hawkins, is the first proposal to explain how the brain functions at the cellular level. This theory has direct, important, unexpected implications for how people learn to innovate, and therefore for how teachers, coaches, managers, and other professionals teach innovation.

This article provides a summary of Jeff’s conclusions. A longer, more detailed and informative video where I interview Jeff is available here or click the graphic below.

Key Idea

Based on new research in neuroscience, the Thousand Brain theory proposes that the cells in your brain make models of objects and concepts called reference frames. When new information arrives into the brain, these cells “vote” in order to determine if the new information fits the existing model or requires a new model. In this session, the theory’s author, Jeff Hawkins, will explain how the brain processes concepts like “opportunity” and “innovation”. These explanations have surprising implications for the way that educators teach students to innovate so that our pedagogy aligns with the way that our students’ brains function. During the session, Jeff will apply his theory of the brain to his own history as the inventor of the PalmPilot and the Treo, the world’s first handheld computer and first smartphone.

The theory begins with the supposition – supported with evidence – that each person’s brain creates models, called reference frames, inside the neocortex that approximate the world outside of the brain. These collect inputs from touch, sight, sound, smell, and taste. Each sensory experience creates its own model. These slowly converge towards a single consensus model of the world. For example, your brain has a full three-dimensional model of your coffee cup, along with estimates for where the cup is in space and where you are in comparison to the cup.

When an adult encounters a new object for the first time, the person’s brain first attempts to fit the object into reference frames that already exist in their mind. When you first saw a coffee cup, you might have thought that it was a solid stone. As the actor continues to interact with the object, the person’s cells vote to determine if the object fits in an existing frame or if a new model is required. (This vote is why this theory is called Thousand Brains. There are thousands of individual cells that participate in this vote.) The person’s brain will start to create a new model, using as many pieces from the old model as possible.

Once a person has developed a model of an object, they can make predictions about when they next see portions of the object. If you see only one side of your cup on a shelf, you can guess that it is the full, whole, complete cup even though you cannot see or touch all of it. The subset of information that you can collect agrees with the model that is already in the brain. The vote by the brain’s cells quickly achieve consensus.

The brain goes through this same process with more complex concepts like “democracy” or “trust.” It creates a rough model from other concepts that it already knows, and then refines the model to fit the new experiences. In other words, the brain starts with analogies. If new evidence contradicts predictions from the analogy, then the brain creates a new model that fits with the evidence, which in turn can become the basis for new prediction.

The Innovating Brain

Applying this theory to innovation is particularly challenging because, unlike a coffee cup or democracy, an innovator knows that a concept like “opportunity” does not necessary exist. And even if it does exist, it might be fleeting. And even if it does exist and is durable, it might not be large enough or lucrative enough to support an innovative product.

In addition to discovering this Thousand Brains theory, Jeff Hawkins was also the inventor of the PalmPilot, the world’s first handheld computer, and the Treo, the world’s first smart phone. A few years after the successful IPO of Palm, Jeff left technology to recommence his pursuit of brain science. This history allows Jeff to explain his own theory based on its activity while he himself was innovating.

He developed several different reference frames for how the PalmPilot could evolve as a product and as a business in the marketplace, which he and his co-founders drew from analogies of prior products. For example, he concluded that the company should follow the model set by Apple – one company making both the core software and the hardware devices for an integrated, cohesive product – and not the model set by Microsoft – one company making software with many companies competing against each other to create Windows computers for sale in various different segments. As he collected more evidence, his reference frame incrementally evolved into a new model.

How should educators teach students to be innovative? The Thousand Brain Theory suggests that neither recipes for innovation (i.e. the Lean Startup Method) nor practice in innovating (i.e. experiential experimentation) are sufficient to train an innovator’s brain to create new reference frames.

Jeff concludes that innovators need hundreds of existing reference frames in their brain already to help the brain’s cells recombine models during their voting process. Moreover, innovators need to protect this voting process in the neocortex from deeper feelings of fear, pressure, anxiety, adventure, or excitement that can emerge from older portions of the brain.

Artificial Intelligence and Popular Inaccuracies

In the latter portion of Jeff’s book, he explains the current popular method for helping computers mimic the brain to create artificial intelligence are larger on the wrong track because they do not attempt to imitate how the brain’s cells are creating and choosing reference frames. This fault, he opines, limits the progress that these contemporary approaches will make.

Jeff also describes how some false ideas – for example, willful and intentional belief that humans are not altering the Earth’s climate – can spread as a popular albeit inaccurate reference frame.

Every discipline – business strategy, childhood education, football training – rests on assumptions about how the human brain works. Jeff Hawkins asserts that every professional in these disciplines will be more effective if they more explicitly leverage this realization based on hard evidence for brain function.

References

Hawkins, J. (2021). A Thousand Brains: A New Theory of Intelligence. New York: Basic Books.

Lewis, M., Purdy, S., Ahmad, S., & Hawkins, J. (2019). Locations in the neocortex: a theory of sensorimotor object recognition using cortical grid cells. Frontiers in neural circuits, 13, 22.

Hawkins, J., Lewis, M., Klukas, M., Purdy, S., & Ahmad, S. (2019). A framework for intelligence and cortical function based on grid cells in the neocortex. Frontiers in neural circuits, 12, 121.

Hawkins, J., Ahmad, S., & Cui, Y. (2017). A theory of how columns in the neocortex enable learning the structure of the world. Frontiers in neural circuits, 11, 81.

Hawkins, J. (2017). Special report: Can we copy the brain?-What intelligent machines need to learn from the Neocortex. IEEE spectrum, 54(6), 34-71.

Hawkins, J., & Ahmad, S. (2016). Why neurons have thousands of synapses, a theory of sequence memory in neocortex. Frontiers in neural circuits, 10, 23.

Ahmad, S., & Hawkins, J. (2016). How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites. arXiv preprint arXiv:1601.00720.

George, D., & Hawkins, J. (2009). Towards a mathematical theory of cortical micro-circuits. PLoS computational biology, 5(10), e1000532.

Hawkins, J. (2007). Why Can’t a Computer be more Like a Brain? IEEE spectrum, 44(4), 21-26.

Hawkins, J., & Blakeslee, S. (2004). On intelligence: Macmillan.