Skip to content
Tech News
← Back to articles

Behavioral timescale synaptic plasticity rewires the brain after an experience

read original get Neuroscience Brain Plasticity Kit → more articles
Why This Matters

This breakthrough in understanding dendritic activity and behavioral timescale synaptic plasticity (BTSP) highlights the brain's complex computational capabilities, revealing mechanisms that could inform the development of more sophisticated artificial intelligence systems. For consumers and the tech industry, these insights pave the way for advancements in neural-inspired computing, memory enhancement, and brain-machine interfaces, potentially transforming how we approach learning and cognition enhancement technologies.

Key Takeaways

In recent decades, neuroscientists have come to a “slow realization that dendritic activity is super important for plasticity and for neuronal computations in general,” said Antoine Madar, a postdoc at the University of Chicago, who led the 2025 review of a Society for Neuroscience symposium on BTSP in The Journal of Neuroscience.

There is a “zoo” of different events that take place at dendrites, he said. They can fire their own local or global electrical spikes. They can cover a larger or smaller area, and they can surge for longer or shorter periods of time. Neuroscientists have found that these events at dendrites can allow even single neurons to perform complex computations — meaning that dendrites are the reason why a single neuron can have the same amount of computational power as a deep artificial neural network.

Still, there was much unknown about dendrites’ behavior. Neuroscientists have mainly characterized them in brain slices, where neurons are alive and can be activated but aren’t attached to a living animal. “We were trying to take that into the actual behaving animal, or the actual behaving brain,” Magee said.

In 2014, they began to home in on the hippocampus, an especially plastic area of the brain where we form experiential memories. It’s also home to place cells, which fire when an animal moves through its environment. Each of these neurons learns to fire at specific locations; later, if the rodent reenters that place, the cell will fire, recalling relevant information stored in the network.

Jeffrey Magee, a neuroscientist at Baylor College of Medicine, led the team that first described behavioral timescale synaptic plasticity in 2017. Courtesy of Jeffrey Magee

As the rodents ran on a circular track, Magee and his team recorded what was happening in their hippocampal dendrites. That’s when they observed something interesting.

Neuroscientists had long known that dendrites can sometimes stay active, with a slightly higher charge than when they’re resting, for long periods of time without firing — creating what’s known as a plateau potential. Because a plateau potential increases the odds that the neuron will fire, the activity was considered important to neuroplasticity. But while examining the rodent data, Bittner saw that place cells whose dendrites had produced just a single plateau potential began to fire.

In other words, a single burst of activity at the dendrite had tuned that cell to fire in that location. It was previously thought that encoding a place cell would take multiple action potentials, via Hebbian learning, which would require the animal to explore the same spot multiple times.

“So we were like, ‘Wow, what’s going on here?’” Magee said. When they experimentally triggered these plateaus, the cells fired in that location 99.5% of the time after a single dendritic plateau.

We were going to be facing up to nearly 100 years’ worth of dogma. Jeffree Magee, Baylor College of Medicine

... continue reading