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HOW YOUR BRAIN CREATES NEW MEMORIES  
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William Wright and Takaki Komiyama
April 17, 2025
The Conversation
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_ New research reveals how, by following different rules in the
process of learning, neurons can perform multiple functions in
parallel. This may have implications for human health and society,
including new ways to design artificial neural networks. _

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Every day, people are constantly learning and forming new memories.
When you pick up a new hobby, try a recipe a friend recommended or
read the latest world news, your brain stores many of these memories
for years or decades
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But how does your brain achieve this incredible feat?

In our newly published research in the journal Science, we have
identified some of the “rules” the brain uses to learn
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Learning in the brain

The human brain is made up of billions of nerve cells
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neurons conduct electrical pulses that carry information, much like
how computers use binary code to carry data.

These electrical pulses are communicated with other neurons through
connections between them called synapses
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Individual neurons have branching extensions known as dendrites that
can receive thousands of electrical inputs from other cells. Dendrites
transmit these inputs to the main body of the neuron, where it then
integrates all these signals [[link removed]] to
generate its own electrical pulses.

It is the collective activity
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electrical pulses across specific groups of neurons that form the
representations of different information and experiences within the
brain.

[Diagram of neuron, featuring a relatively large cell body with a long
branching tail extending from it]
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Neurons are the basic units of the brain. OpenStax
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CC BY-SA [[link removed]]

For decades, neuroscientists have thought that the brain learns by
changing how neurons are connected to one another. As new information
and experiences alter how neurons communicate with each other and
change their collective activity patterns, some synaptic connections
are made stronger while others are made weaker. This process of
synaptic plasticity
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representations of new information and experiences within your brain.

In order for your brain to produce the correct representations during
learning, however, the right synaptic connections must undergo the
right changes at the right time. The “rules” that your brain uses
to select which synapses to change during learning – what
neuroscientists call the credit assignment problem
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unclear.

Defining the rules

We decided to monitor the activity of individual synaptic connections
within the brain during learning to see whether we could identify
activity patterns that determine which connections would get stronger
or weaker.

To do this, we genetically encoded biosensors in the neurons of mice
that would light up in response to synaptic and neural activity. We
monitored this activity in real time as the mice learned a task that
involved pressing a lever to a certain position after a sound cue in
order to receive water.

We were surprised to find that the synapses on a neuron don’t all
follow the same rule. For example, scientists have often thought that
neurons follow what are called Hebbian rules
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consistently fire together, wire together. Instead, we saw that
synapses on different locations of dendrites of the same neuron
followed different rules
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whether connections got stronger or weaker. Some synapses adhered to
the traditional Hebbian rule where neurons that consistently fire
together strengthen their connections. Other synapses did something
different and completely independent of the neuron’s activity.

Our findings suggest that neurons, by simultaneously using two
different sets of rules for learning across different groups of
synapses, rather than a single uniform rule, can more precisely tune
the different types of inputs they receive to appropriately represent
new information in the brain.

In other words, by following different rules in the process of
learning, neurons can multitask and perform multiple functions in
parallel.

Future applications

This discovery provides a clearer understanding of how the connections
between neurons change during learning. Given that most brain
disorders, including degenerative
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malfunctioning synapses, this has potentially important implications
for human health and society.

For example, depression may develop [[link removed]]
from an excessive weakening of the synaptic connections within certain
areas of the brain that make it harder to experience pleasure. By
understanding how synaptic plasticity normally operates, scientists
may be able to better understand what goes wrong in depression and
then develop therapies to more effectively treat it.

[Microscopy image of mouse brain cross-section with lower middle-half
dusted green]
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Changes to connections in the amygdala – colored green – are
implicated in depression. William J. Giardino/Luis de Lecea
Lab/Stanford University via NIH/Flickr
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These findings may also have implications for artificial intelligence.
The artificial neural networks underlying AI have largely been
inspired by how the brain works
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However, the learning rules researchers use to update the connections
within the networks and train the models are usually uniform and also
not biologically plausible
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insights into how to develop more biologically realistic AI models
that are more efficient, have better performance, or both.

There is still a long way to go before we can use this information to
develop new therapies for human brain disorders. While we found that
synaptic connections on different groups of dendrites use different
learning rules, we don’t know exactly why or how. In addition, while
the ability of neurons to simultaneously use multiple learning methods
increases their capacity to encode information, what other properties
this may give them isn’t yet clear.

Future research will hopefully answer these questions and further our
understanding of how the brain learns.[The Conversation]

William Wright
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Postdoctoral Scholar in Neurobiology, _University of California, San
Diego
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and Takaki Komiyama
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Professor of Neurobiology, _University of California, San Diego
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This article is republished from The Conversation
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the original article
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