Imagining the world from a mouse’s
perspective is essential for International Brain Laboratory scientists when
picking a lab task that mimics a real-world decision. Credit: Elena
Nikanorovna, CC BY-ND
Decisions
span a vast range of complexity. There are really simple ones: Do I want an
apple or a piece of cake with my lunch? Then there are much more complicated
ones: Which car should I buy, or which career should I choose?
Neuroscientists like me have identified some of the individual
parts of the brainthat contribute to making decisions like
these. Different areas process sounds, sights or
pertinent prior knowledge. But understanding how
these individual players work together as a team is still a challenge, not only
in understanding decision-making, but for the whole field of neuroscience.
Part of the reason is that until now, neuroscience has operated in
a traditional science research model: Individual labs work on their own,
usually focusing on one or a few brain areas. That makes it challenging for any
researcher to interpret data collected by another lab, because we all have
slight differences in how we run experiments.
Neuroscientists who study decision-making set up all kinds of
different games for animals to play, for example, and we collect data on what
goes on in the brain when the animal makes a move. When everyone has a
different experimental setup and methodology, we can't determine whether the
results from another lab are a clue about something interesting that's actually
going on in the brain or merely a byproduct of equipment differences.
The BRAIN Initiative, which the Obama
administration launched in 2013, started to encourage the kind of collaboration
that neuroscience needs. I just think it hasn't gone far enough. So I co-founded
a project called the International Brain Laboratory – a virtual mega-laboratory composed
of many labs at different institutions – to show that the proverb "alone
we go fast, together we go far" holds true for neuroscience. The first
question the collaboration is tackling focuses on decision-making by the brain.
The brain's decision team
Individual neuroscience labs have already uncovered a lot about
how particular brain areas contribute to decision-making.
Say you're choosing between an apple or a piece of cake to go with
lunch. First, you need to know that apples and cake are the two options. That
requires action from brain areas that process sensory information – your eyes
see the apple's bright red skin, while your nose takes in the sweet smell of
cake.
Those sensory areas often connect to what we call association
areas. Researchers have traditionally thought they play a role in putting different pieces of information together. By collating information
from the eyes, the ears and so on, the association areas may give a more
coherent, big-picture view of what's happening in the world.
And why choose one action over another? That's a question for the
brain's reward circuitry, which is critical in weighing the value of different options.
You know that the cake will taste sweetly delicious now, but you might regret
it when you're heading to the gym later.
Then, there's the frontal cortex, which is believed to play a role in controlling voluntary action.
Research suggests it's involved in committing to a particular action once
enough incoming information has arrived. It's the part of the brain that might
tell you the piece of cake smells so good that it's worth all of the calories.
Understanding how these different brain areas typically work
together to make decisions could help with understanding what happens in
diseased brains. Patients with disorders such as autism, schizophrenia and
Parkinson's disease often use sensory information in an unusual way, especially if it's
complex and uncertain. Research on decision-making may also inform treatment of
patients with other disorders, such as substance abuse and addiction. Indeed, addiction is perhaps a
prime example of
how decision-making can go very wrong.
A lab collaborative spread around the world
Right now, neuroscientists are taking lots of closeup snapshots of
what happens in particular areas of the brain when it makes a decision. But
they aren't coordinating with each other much, so these closeup pieces don't
fit together to give us the big picture of decision-making that we need.
That's why a team of us joined up to form the International Brain
Laboratory. With support from the International Neuroinformatics Coordinating
Facility, the Wellcome Trust, and the Simons Foundation (also a funder of The
Conversation US), we aim to create that big picture by designing one
large-scale experiment that uses the exact same approach to study many
different brain areas. Because the brain is so complex, we need the expertise
of many different labs that each specialize in particular brain areas. But we need them to coordinate
and use the same approach so that we can put all of their different pieces of
the picture together.
We're bringing together a team of 21 scientists who will work very
closely to understand how billions of neurons work together in a single brain
to make decisions. About a dozen different labs will each do part of one big
experiment by measuring neuron activity in animals engaged in exactly the same
game. Our team members will record activity from hundreds of neurons in each
animal's brain. We'll collect tens of thousands of neuronal recordings that we
can analyze together.
Keep it simple
In real-world decisions, you're combining lots of different pieces
of information – your sensory signals, your internal knowledge about
what's rewarding, what's risky. But implementing that in a laboratory context
is pretty hard.
We're hoping to recreate a mouse's natural foraging experience. In
real life, there are many different paths an animal can take as it navigates
the world looking for something to eat. It wants to find food, because food is
rewarding. It uses incoming sensory cues, like, "Oh, I see a cricket over
there!" An animal might combine that with a memory of reward, like,
"I know this area has lush berry bushes, I remember that from yesterday,
so I'll go there." Or, "I know over here there was a cat last time,
so I'd better avoid that area."
At first pass, the setup we're using for the International Brain
Laboratory doesn't look very natural at all. The mouse has a little device that
it uses to report decisions – it's actually a wheel from a Lego set. For
example, it might learn that when it sees an image of a vertical grating and
turns the wheel until the image is centered, it gets a reward. If you think
about what foraging is – exploring the environment, trying to find rewards,
making use of sensory signals and prior knowledge – this simple Lego wheel
activity does capture its essence.
We really had to think about the trade-off between having a
behavior that was complex enough to give us insight into interesting neural
computations, and one that was simple enough that it could be implemented in
the same way in many different experimental laboratories. The balance we struck
was a decision-making task that starts simple and becomes more and more complex
as an individual animal achieves different stages of training.
Even in the simplest, very earliest stage we're looking at, where
the animals are just making voluntary movements, they're deciding when to make
a movement to harvest a reward. I'm sure we can go much further, but even if
that's as far as we get, having neural measurements from all over the brain
during a simple behavior like this will be very interesting. We don't know how
it happens in the brain that you decide when to take a particular action and
how to execute that action. Having neural measurements from all over the brain
of what happened just before the animal spontaneously decided to go and get a
reward will be a huge step forward.
Provided by: The Conversation
https://medicalxpress.com/news/2017-12-collaborative-approach-brain-decision.html
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