Neuroscience Research at Numenta: Cortical Theory
Through our focus on cortical theory, we seek to understand the complex circuitry of a cortical column. We want to understand the function and operation of the laminar circuits in the brain, including what the neurons are doing, what the layers are doing, how they interact, and how a cortical column works.
Vernon Mountcastle proposed that because every part of the neocortex has the same complex circuitry, then every part is doing the same thing. Therefore, if we can understand a cortical column, we will understand the neocortex.
We are often asked how we do neuroscience research at Numenta and what it means to focus on cortical theory. We read many neuroscience papers and published results to get a deep understanding of neuroanatomy, neurophysiology, and cortical function. We propose theories about how the detailed architecture of the neocortex implements these functions. We ensure our work satisfies biological constraints and test our theories via simulation. Since we do not do any wet lab work, we collaborate with experimentalists that run investigations and give us feedback. We also host scientists through our Visiting Scholar Program.
We document our research in several ways, including peer-reviewed journal papers, conference proceedings, research reports, and invited talks. In addition, we place our daily research commits in an open source project and answer questions about our research posted on our forums. We strive to be completely open in everything we do.
Although there is much to do, we have made significant progress on several key aspects of cortical theory. We are filling in the pieces of the common cortical circuit that underlines all of intelligence. We have made discoveries on how neurons make predictions, the role of dendritic spikes in cortical processing, how cortical layers learn sequences, and how cortical columns learn to model objects through movement.
Our Research Focus Areas
Building on Mountcastle’s proposal that the neocortex is made up of identical cortical columns, we are working on filling in the pieces of the cortical circuit – understanding each layer, what the neurons are doing, and how a cortical column works. As part of this research, we have proposed a detailed model, consistent with anatomical and physiological evidence, that shows how cortical columns learn sensorimotor models of the world by combining sensory inputs with a movement-updated allocentric location signal.
Find more information on cortical columns.
Memory and recall of sequences is an essential component of inference and behavior. We believe that sequence memory is occurring in multiple layers of the neocortex. We’ve shown how a layer of pyramidal neurons with active dendrites, arranged in mini-columns, will learn transitions of patterns and form a robust sequence memory.
Find more information on sequence learning and prediction in cortex.
Sparse distributed representations
Sparse Distributed Representations (SDRs) are a foundational aspect of all of our theories. Everywhere in the neocortex, information is represented by distributed and sparsely active sets of neurons. We have shown through mathematical analysis and simulation that SDRs enable semantic generalization and robustness.
Find more information on sparse distributed representations.