The mammalian cerebral cortex is structured into six layers. It needs to be clarified whether a corresponding pattern of neuronal activity aligns with these layers across the entire cortex.
A group of neuroscientists from MIT and Vanderbilt University has discovered that the six layers of the mammalian cerebral cortex exhibit distinctive patterns of electrical activity. These patterns are consistent across various brain regions and animal species, including humans.
The top layers of the cortex primarily show rapid gamma wave oscillations in neuron activity, while the deeper layers exhibit slower alpha and beta wave oscillations. The universality of these patterns suggests that these oscillations play a significant role throughout the brain.
The consistent and widespread presence of these electrical activity patterns across the cortex suggests that they play a fundamental role in the functioning of the cortex. Imbalances in the interactions of these oscillations may be implicated in brain disorders, such as attention deficit hyperactivity disorder (ADHD). Understanding the role of these oscillations in normal brain function could provide insights into the mechanisms underlying neurological disorders.
Robert Desimone, director of MIT’s McGovern Institute for Brain Research and one of the senior authors of the study, said, “Overly synchronous neural activity is known to play a role in epilepsy, and now we suspect that different pathologies of synchrony may contribute to many brain disorders, including disorders of perception, attention, memory, and motor control. In an orchestra, one instrument played out of synchrony with the rest can disrupt the coherence of the entire piece of music.”
In their recent study, the researchers aimed to investigate whether the observed layered oscillation pattern in the prefrontal cortex is widespread, occurring in various parts of the cortex and across different species.
They used data from multiple sources, including Miller’s lab, Desimone’s lab, and collaborating labs from Vanderbilt, the Netherlands Institute for Neuroscience, and the University of Western Ontario. The dataset included recordings of electrical activity from 14 different areas of the cortex, spanning four mammalian species. Additionally, they analyzed data from three human patients with electrodes inserted into their brains during surgery.
Recording from individual cortical layers is challenging due to their thinness. For this study, special electrodes were used to record from all layers simultaneously. The recorded data was then processed using a novel computational algorithm developed by the researchers, FLIP (frequency-based layer identification procedure). FLIP can identify the specific layer from which each signal originates.
MIT postdoc Alex Major said, “More recent technology allows recording of all layers of cortex simultaneously. This paints a broader perspective of microcircuitry and allows us to observe this layered pattern. This work is exciting because it is informative of a fundamental microcircuit pattern and provides a robust new technique for studying the brain. It doesn’t matter if the brain performs a task or at rest and can be observed in as little as five to 10 seconds.”
The researchers found a consistent layered activity pattern across all species and in every region of the cortex they studied. A comprehensive data analysis identified the same way in all areas of the cortex, indicating that the observed phenomenon is a fundamental mechanism present throughout the cortex. This widespread occurrence across different species and brain regions suggests the importance and universality of these layered oscillation patterns in cortical functioning.
The discovered layered activity patterns align with a model previously proposed by Miller’s lab. This model suggests that the brain’s spatial organization facilitates the integration of new information, carried by high-frequency oscillations, into existing memories and brain processes maintained by low-frequency oscillations. As data flows through different layers, it can be incorporated to assist the brain in specific tasks, like learning a new recipe or recalling a phone number.
André Bastos, an assistant professor of psychology at Vanderbilt University, is also a senior author of the open-access paper, said, “The consequence of a laminar separation of these frequencies, as we observed, may allow superficial layers to represent external sensory information with faster frequencies, and for deep layers to represent internal cognitive states with slower frequencies. The high-level implication is that the cortex has multiple mechanisms involving anatomy and oscillations to separate ‘external’ from ‘internal’ information.”
According to the proposed theory, an imbalance between the brain’s high- and low-frequency oscillations could lead to attention deficits like ADHD when higher frequencies dominate, allowing excessive sensory information in. Conversely, delusional disorders such as schizophrenia might arise when low-frequency oscillations are too strong, limiting the intake of sensory information.
Properly balancing top-down control signals and bottom-up sensory signals is crucial for various cortex functions. When this balance is disrupted, a range of neuropsychiatric disorders may occur.
Researchers are now exploring the possibility of using these oscillation measurements to diagnose such disorders. Additionally, they are investigating whether restoring the balance of these oscillations could alter behavior, offering a potential avenue for treating conditions like attention deficits or other neurological disorders.
Researchers are now looking forward to characterizing the layered oscillation patterns in more detail across different brain regions.
- Major, A. J., Lee, N., Lichtenfeld, M. J., Carlson, B., Mitchell, B., Meng, P. D., Xiong, Y., Westerberg, J. A., Jia, X., Johnston, K. D., Selvanayagam, J., Everling, S., Maier, A., Desimone, R., Miller, E. K., & Bastos, A. M. (2024). A ubiquitous spectrolaminar motif of local field potential power across the primate cortex. Nature Neuroscience, 1-14. DOI: 10.1038/s41593-023-01554-7