Translator: Pik Yan Wong Reviewer: Denise RQ
What if I told you that the brain could be described
using just a set of mathematical equations?
My fascination with a human brain began as a young student
volunteering in a psychiatric ward.
There I met a woman who had an incredible talent.
She was able from a first encounter
to see through the mask of social convention,
the essence of a person.
She had an incredible intuition,
in an almost instinctive way of understanding others:
she could literally read people's minds, patients or doctors.
At the same time, she heard voices, had violent outbursts
that led to her confinement to the padded room
where she rocked back and forth or stood motionless for hours.
How could this woman, on the one hand, have such an incredible talent,
but be so profoundly impaired in another domain?
How was her perception of the world different from mine?
I really wanted to understand her.
Now a decade later,
I study how you read people's intentions during social interactions.
I want to understand how the brain represents other minds.
In other words, what does it mean to have a good theory of mind,
to be able to put oneself into another person's shoes?
What made this woman's talent so incredible?
My research collaborators and I found something really exciting.
What if I told you that this complex cognitive process,
the theory of mind,
and its neural representation,
can be actually translated into a set of mathematical equations?
This mathematical model says
that we simulate a person in our minds.
Now let's put it into context.
Imagine the following scenario.
Zurich is your new home,
and you have to make an important decision.
For instance, what health insurance to apply for,
or what bank account to open.
I'm giving you advice: choose option A, not B.
Of course, you would like to alleviate uncertainty
and become more informed,
so you take my advice into consideration.
However, you have no idea beforehand how informed I am,
or how trustworthy I am in the first place.
Over the course of our interaction,
that is, me giving you advice several times,
you form a mental representation
or a sculpture of me, my intentions,
and the accuracy of my advice in your minds.
So essentially, what our mathematical model says
is that we start with the coarse representation
of another person,
and over, in social exchange, we sculpted element by element,
until this representation starts
resembling the person we actually interact with.
The graphs on the right show how through social interaction,
this representation becomes crisper.
These graphs become more stable,
as you become better able to understand
the goodness of my advice and my intentions.
So what does this mathematical model actually do?
It says that we start with a set of sensory inputs;
for instance, the image of me giving this talk today.
You integrate this information with previous experience.
This could be distant episodes from your youth,
for example, your first encounter with public speaking,
or more recent episodes,
such as the journey we took this morning to arrive here.
You integrate these two sources of information
to make sense of the world around you,
to create new experiences.
But what does our model actually do?
It represents learning about intentions and advice
as hierarchically coupled processes.
These processes evolve over time,
evolve as people engage in social interactions as they learn.
The dynamics of these processes
are determined by mathematical parameters.
Take, for example, the parameter kappa.
Parameter kappa describes
how we use our internal representation of another person
to make sense of their advice.
These mathematical parameters are different for different individuals.
They're, in a way, learning fingerprints
because they describe one's own unique learning style.
We can also look at how the brain represents
these mathematical equations, and how it learns to simulate other minds.
We do that by measuring brain activity using magnetic resonance imaging,
and we can apply these very same mathematical equations
to make sense of the brain activations.
Let's start by navigating from the back of the brain.
The brain regions in orange depict increases in neural activity.
By applying these mathematical equations to understanding brain function,
we can actually delineate the different stages
of theory of mind processing.
Let's start with the first stage.
That is, paying attention to a person's eyes
and looking at the direction of their gaze.
We see that this process is captured
in the eye and face and regions of the brain.
This is the initial stage.
Then we move on to something more sophisticated,
such as reading a person's mood
based on their body language, facial expression.
This is represented in multimodal brain regions,
as well as emotional centers in the cortex.
We get closer to the more sophisticated stage,
and that is being able to simulate a person in your mind
and predict their decisions or what future actions they will take,
and this is represented in the most frontal part of the brain,
the executive center.
My research collaborators and I have combined these two methods,
learning models, mathematical models that describe how people learn
with methods of recording brain activity,
to identify at least two different types of learners.
For instance, the first type.
These are individuals that represent advice in exactly the same brain regions
that have been previously associated with mentalizing and theory of mind processes.
I mentioned the parameter kappa earlier.
This tells us about how we use
our internal representation of another person
to make sense of social cues such as advice.
These individuals have high values of kappa.
It means that they use this internal representation,
and they seek out social cues
because they can put them into a context.
However, there's also a second type of learner,
people that represent advice in general purpose brain areas
that are not, in fact, associated with theory of mind processes.
These are individuals that have low levels of kappa.
What it means is they're not attending as much to social cues
because they don't have an internal representation
in which to place them.
What is the distinguishing feature between these two types of learners?
That is the connectivity between brain regions,
in particular, regions that comprise a theory of mind network.
We know that these regions become more efficient
at communicating with each other in type one learners,
over the course of the social interaction.
However, for those individuals who cannot build
an internal representation of somebody's intentions,
these regions are disconnected.
Now that we have this mathematical model in place,
we can ask some very interesting questions.
For instance, what happens when things break down?
We know that social cognition
is particularly impaired in psychiatric disorders.
Take for instance, schizophrenia.
One distinguishing feature of this disorder is the perception
that people are secretly plotting against you,
is this emergence of paranoid ideas about people's intentions.
On the other side of the spectrum, there is autism.
Individuals with autism do not very much enjoy engaging in social interactions,
and have difficulty
making sense of people's intentions predicting their actions.
We can use this mathematical approach
to cast hypothesis and predictions about the mechanisms
that underlie these symptoms we observe in psychiatric populations.
For instance, schizophrenia.
Our model would predict that individuals with schizophrenia start
with a displace negative prior expectation about people's intentions,
that they are negative, that they are evil, so to say.
But these initial expectations do not change
in spite of disconfirming evidence.
As you can see with the graph below, learning is very much reduced.
They don't want to re-examine these initial beliefs.
Now, in the context of autism,
our mathematical model would predict
that perhaps individuals with autism cannot make sense of people's intentions
because over the course of the social interactions,
people's facial expressions and moods are changing so rapidly
that they're perceived as being too volatile,
making it difficult to form this consistent internal representation.
Putting people into a social context allows us to understand
how the brain simulates other minds,
and because social cognition is especially vulnerable in psychiatric populations,
it could be a very great tool
in order to understand the pathophysiological mechanisms
underlying psychiatric disorders.
So I propose that we really need a deep mathematical understanding
about how the brain actually learns in a social context,
and this understanding would pave the way
of uncovering the mechanisms that underlie psychiatric disorders,
such as autism and schizophrenia.
Understanding maladaptive behavior by using a mathematical microscope
instead of descriptive categories,
we can design better experiments.
We can design longitudinal studies in which we can predict
if patients might relapse in the future,
or if individuals who are at risk would develop the disorder
in the first place.
By looking at mechanisms using a mathematical perspective,
we can objectively and precisely test
whether individualized treatments would work.
This could be pharmacology-based and cognitive behavioral therapy based.
Think of this difference this might make for patients,
especially in the context of this woman that I met ten years ago.
It would make a huge difference,
because these types of treatments would target their specific impairment
and not impacting on other existing exceptional skills.
So I hope that today
I've shown you how we can build a mathematical microscope
that will allow us to look through the curtain of symptoms
onto mechanisms, mechanisms that underlie psychological disorders.
Thank you very much.
(Applause)