Summary: A new study confirms the old adage “practice makes perfect.” Researchers used cutting-edge technology to observe 73,000 neurons in mice as they learned a task. They found that repetitive practice solidifies neural pathways, transforming unstable memory representations into stable representations, leading to improved performance and mastery.
Highlights:
- Repetitive practice strengthens and stabilizes the neural pathways in the brain.
- This “crystallization” of memory circuits improves the precision and automaticity of acquired skills.
- The study used innovative light bead microscopy to visualize neuronal activity in real time.pen_spark
Source: Rockefeller University
“Practice makes perfect” isn’t just a cliché, according to a new study by researchers at Rockefeller University and UCLA. Instead, it’s the recipe for mastering a task, because repeating an activity over and over solidifies the neural pathways in your brain.
As they describe in NatureThe scientists used cutting-edge technology developed by Rockefeller’s Alipasha Vaziri to simultaneously observe 73,000 cortical neurons in mice while the animals learned and repeated a given task for two weeks.
The study found that memory representations change from unstable to solid in working memory circuits, providing insight into why performance becomes more precise and automatic after repetitive practice.
“In this work, we show how working memory – the brain’s ability to retain and process information – improves through practice,” says Vaziri, director of Rockefeller’s Neurology and Biophysics Laboratory.
“We hope that this knowledge will not only advance our understanding of learning and memory, but also have implications in combating memory-related disorders.” »
Imagine challenges
Working memory is essential for various cognitive functions, and yet the mechanisms underlying memory formation, retention and recall, which allow us to perform a task we have already performed without having to relearn it , remain unclear over long periods.
For the current study, the researchers wanted to observe the stability of working memory representations over time and what role these representations played in the ability to skillfully perform the task at the right time.
To do this, they sought to record neuronal populations repeatedly in mice over a relatively long period of time, while the animals learned and became expert in a given task.
But they faced a significant challenge: technical limitations hampered the ability to image the activity of a large population of neurons in the brain in real time, over long periods of time, and at any depth. tissue in the cortex.
The UCLA researchers turned to Vaziri, who has developed brain imaging techniques that are among the only tools capable of capturing the majority of the mouse cortex in real time, at high resolution and speed.
Vaziri suggested using light bead microscopy (LBM), a high-speed volumetric imaging technology he developed that allows in vivo cellular resolution recording of the activity of neuronal populations up to 1 million neurons, i.e. a 100-fold increase in the number of neurons. which can be recorded simultaneously.
Neural transformations
In the current study, researchers used LBM to simultaneously image the cellular activity of 73,000 neurons in mice at different depths of the cortex and tracked the activity of the same neurons for two weeks while the animals identified, recalled, and repeated a sequence of odors. .
They found that working memory circuits transformed as the mice mastered the appropriate sequences. Initially, the circuits were unstable, but as the mice practiced the task repeatedly, the circuits began to stabilize and solidify.
“This is what we call ‘crystallization,’” Vaziri explains. “The results essentially illustrate that repetitive training not only improves skill mastery, but also leads to profound changes in the brain’s memory circuits, making performance more precise and automatic.”
“If we imagine that each neuron in the brain emits a different note, the melody that the brain generates as it completes the task changed from day to day, but then became more and more refined and similar as the animals continued to practice the melody task,” adds corresponding author and neurologist Peyman Golshani of UCLA Health.
Importantly, some aspects of these findings were only made possible by the deep tissue and large-scale imaging capabilities of LBM. Initially, the researchers used standard two-photon imaging of smaller neuronal populations in higher cortical layers, but they failed to find evidence of memory stabilization.
But once they used the LBM to record more than 70,000 neurons in deeper cortical regions, they were able to observe the crystallization of working memory representations that accompanied the mice’s increasing mastery of the task.
“In the future, we may address the role of different neuronal cell types involved in mediating this mechanism, and in particular the interaction of different interneuron types with excitatory cells,” says Vaziri.
“We also want to understand how learning is implemented and could be transferred to a new context, that is, how the brain could generalize a learned task to new, unknown problems.”
About this memory search news
Author: Catherine Fenz
Source: Rockefeller University
Contact: Katherine Fenz – Rockefeller University
Picture: Image is credited to Neuroscience News
Original research: Free access.
“Volatile representations of working memory crystallize with practice” by Alipasha Vaziri et al. Nature
Abstract
Volatile working memory representations crystallize with practice
Working memory, the process by which information is maintained and manipulated transiently over a brief period, is essential for most cognitive functions.
However, the mechanisms underlying the generation and evolution of neuronal working memory representations at the population level over long periods of time remain unclear.
Here, to identify these mechanisms, we trained head-fixed mice to perform a delayed olfactory association task in which mice made decisions based on the sequential identity of two odors separated by a 5-s delay.
Optogenetic inhibition of secondary motor neurons during late delay and choice epochs strongly impaired mouse performance.
Mesoscopic calcium imaging of large neuronal populations from the secondary motor cortex (M2), retrosplenial cortex (RSA), and primary motor cortex (M1) showed that many late epoch-selective neurons emerged in M2 as the mice learned the task.
Accuracy of late working memory decoding improved significantly in M2, but not in M1 or RSA, as mice became experts.
During the early expert phase, working memory representations during the late delay period drifted across days, while stimulus and choice representations stabilized.
In contrast to single-plane layer 2/3 (L2/3) imaging, simultaneous volumetric calcium imaging of up to 73,307 M2 neurons, which included superficial L5 neurons, also revealed stabilization of representations late effects of working memory with continued practice.
Thus, activities related to delays and choices, essential for working memory performance, drift during learning and only stabilize after several days of expert performance.