Distinct Dendrites, Distinct Rules for Learning in a Single Neuron Mouse Study

How do we learn something new? How do tasks at a new job, lyrics to the latest hit song, or directions to a friend’s house become encoded in our brains? The broad answer is that our brains undergo adaptations to accommodate new information. To follow a new behavior or retain newly introduced information, the brain’s circuitry undergoes change.

Such modifications are orchestrated across trillions of synapses—the connections between individual neurons—where brain communication takes place. In an intricately coordinated process, new information causes certain synapses to get stronger with new data while others grow weaker. Neuroscientists closely studying these alterations, known as “synaptic plasticity,” have identified numerous molecular processes causing such plasticity. However, an understanding of the rules that determine the selection of which synapses undergo this process has remained unknown, representing a mystery that ultimately dictates how learned information is captured in the brain.

University of California, San Diego, neurobiologists William “Jake” Wright, PhD, Nathan Hedrick, PhD, and Takaki Komiyama, PhD, used a cutting-edge brain visualization methodology, including two-photon imaging, to zoom into the brain activity of mice and track the activities of synapses and neurons during learning activities. Shedding light on how the brain fine-tunes its wiring during learning, the team discovered that different dendritic segments of a single neuron follow distinct rules.

With the ability to see individual synapses like never before, the new images revealed that neurons don’t follow one set of rules during episodes of learning, as had been assumed under conventional thinking. Rather, the data revealed that individual neurons follow multiple rules, with synapses in different regions following different rules.

The new findings challenge the idea that neurons follow a single learning strategy and offer a new perspective on how the brain learns and adapts behavior. The results could support research leading to new development in areas including brain and behavior disorders, to artificial intelligence. The new insights could point to new therapeutic approaches targeting neurodegenerative and neurodevelopmental disorders, including Alzheimer’s disease or autism, as well as addiction and post-traumatic stress disorder.

“When people talk about synaptic plasticity, it’s typically regarded as uniform within the brain,” said Wright, a postdoctoral scholar in the School of Biological Sciences and first author of the study. “Our research provides a clearer understanding of how synapses are being modified during learning, with potentially important health implications since many diseases in the brain involve some form of synaptic dysfunction.”

The researchers reported on their findings in Science, in a paper titled, “Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning.”

The ability to acquire and adapt behavior through the process of learning is one of the most fundamental functions of the brain, the authors wrote. “Synaptic plasticity underlies learning by modifying specific synaptic inputs to reshape neural activity and behavior.” The brain’s remarkable ability to learn and adapt is rooted in its capacity to modify the connections within its neural circuits—synaptic plasticity—in which specific synapses are altered to reshape neural activity and support behavioral change. Neurons, unlike most other cell types, are characterized by their intricate, tree-like dendritic arbors, which extend from the cell body and serve as the primary site for receiving signals from other neurons via synaptic inputs. These dendrites are not uniform; instead, they are organized into distinct compartments with specialized anatomical and biophysical properties, which likely influence how various patterns of neural activity trigger the biochemical processes that underlie synaptic plasticity. “… it is possible that individual neurons use multiple activity-dependent plasticity rules in a compartment-specific manner, which may afford neurons with greater encoding capacity,” the researchers suggested.

How the brain determines which synapses should be modified during learning and whether individual neurons apply the same plasticity rules uniformly across their structurally and functionally distinct dendritic compartments remains unknown. Neuroscientists have carefully studied how synapses only have access to their own “local” information, yet collectively they help shape broad new learned behaviors, a conundrum labeled as the “credit assignment problem.” The issue is analogous to individual ants that work on specific tasks without knowledge of the goals of the entire colony. “Although the  molecular and cellular mechanisms underlying the induction and expression of synaptic plasticity have been extensively detailed,” the team further noted, “it remains unclear how specific synapses are selected to undergo different forms of plasticity during learning, often referred to as the credit assignment problem.”

To explore how synapses function and adapt during learning, Wright and colleagues used advanced imaging to observe single synapses in the motor cortex of mice as the animals learned new motor skills. The team trained mice on a motor task known to drive synaptic plasticity in layer 2/3 motor cortex neurons, observing clear behavioral signs of learning over two weeks. Then, to investigate how individual synapses adapt during this process, the investigators used in vivo two-photon imaging with molecular sensors that simultaneously tracked synaptic input (via glutamate release) and neuronal output (via calcium activity). The authors discovered that learning-related patterns of neural activity drive synaptic plasticity differently across dendritic compartments.

In apical dendrites, synapses were strengthened when they were coactive with nearby neighbors, suggesting that plasticity here is governed by local interactions between adjacent inputs. In contrast, plasticity in basal dendrites was linked to the neuron’s overall output, strengthening or weakening depending on how synapse activity aligned with global action potential firing. Suppressing a neuron’s activity selectively impaired plasticity in basal, but not apical, dendrites.

The finding that neurons follow multiple rules at once took the researchers by surprise. “This discovery fundamentally changes the way we understand how the brain solves the credit assignment problem, with the concept that individual neurons perform distinct computations in parallel in different subcellular compartments,” said study senior author Komiyama, a professor in the departments of neurobiology (School of Biological Sciences) and neurosciences (School of Medicine), with appointments in the Halıcıoğlu Data Science Institute and Kavli Institute for Brain and Mind.

The new information offers promising insights for the future of artificial intelligence and the brain-like neural networks upon which they operate. Typically, an entire neural network functions on a common set of plasticity rules, but this research infers possible new ways to design advanced AI systems using multiple rules across singular units.

For health and behavior, the findings could offer a new way to treat conditions including addiction, post-traumatic stress disorder, and Alzheimer’s disease, as well as neurodevelopmental disorders such as autism.

“This work is laying a potential foundation for trying to understand how the brain normally works to allow us to better understand what’s going wrong in these different diseases,” said Wright. The new findings are now leading the researchers on a course to dig deeper to understand how neurons are able to utilize different rules at once and what benefits using multiple rules gives them.