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What if the blind spot in social
neuroscience is that we've been 

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studying social life, but 
without the social part? 

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Like we've been scanning 
people's brains while they stare

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at faces on a screen, and then 
we call it interaction. 

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Today we're talking with someone
who's helped push the field 

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forward towards studying the 
brain during real social 

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interactions and doing it across
development. 

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We're talking with Doctor Liz 
Redkay. 

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Tracking that shell now. 
Happy band. 

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Mike, Joey, let's go. 
Cracking the shell on the MIC 

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Psychological sciences site. 
Abby bringing that fire sparks 

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when she speaks. 
Ignition on sight. 

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Been with the breakdown. 
Mind state takedown. 

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Never missed the details. 
Mic kit and concepts. 

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Heavy like brake trains on steel
rails. 

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Joey, steady mapping brain 
waves, decoding how we feel. 

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They turn that abstract real. 
Yeah, the knowledge is real. 

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They peel it back slowly after 
layer. 

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Mine's so deep. 
Yeah. 

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We ride that elevator. 
Cracking the shell. 

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Yeah. 
We diving. 

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Welcome back to Crack in the 
Show on psychological science. 

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I'm Mike. 
And I'm Joey, and today we're 

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joined by Doctor Elizabeth 
Redkay, whose work examines the 

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development and neural 
mechanisms of social interaction

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and social cognition in both 
typical development and autism. 

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Howdy Liz, thanks for being 
here. 

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Thanks for having me, I'm 
excited to talk. 

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OK, great. 
So to set the stage, when people

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hear social cognition, they 
often think theory of mind or 

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emotion recognition or empathy. 
But your work emphasizes that 

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these processes unfold in live, 
dynamic context. 

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So what's the core question that
drives your lab? 

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So I'd say the core question is 
thinking about how we navigate 

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social interactions, how we form
social connections, what makes 

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those social connections 
successful and also what brain 

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systems support that. 
So thinking about that, 

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especially across development 
and thinking about in autism 

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where those interactions can be 
particularly challenging. 

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So Liz, I've known you for now, 
I want to say about 15 years 

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roughly, and I still don't know 
exactly how you got into this 

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line of research. 
What is it about social 

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cognition and autism that drew 
you in to make this part of your

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life's work? 
Yeah. 

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So you know, initially I really 
became fascinated with thinking 

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about just links between the 
brain and behavior. 

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So how you know variability 
within individuals brains can 

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lead to such differences in 
behavior and particularly 

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thinking about how changes in 
the brain can change development

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over time. 
And that was from, you know, a 

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combination of personal 
experiences and coursework. 

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So when I was seeking out 
graduate, you know, for my PHDI 

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was trying to find a lab and I 
was looking into different labs 

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that were released in the 
neuroscience of different 

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developmental conditions. 
And so that's what kind of 

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brought me to this lab at UC San
Diego that was focused on the 

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neuroscience of autism. 
And that was kind of my first 

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introduction to autism and where
I really got to know what autism

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was and get to know different 
working with autistic youth, 

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autistic adults, and see first 
just how variable autism was. 

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Thinking if there's so much 
heterogeneity, which was 

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fascinating itself, that so many
kind of such a different range 

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of behavioral features could 
kind of lead to the same 

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diagnosis. 
And then also thinking about the

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sort of core challenges with 
navigating one social world. 

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And you know, if you think about
it like social interactions from

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the very first moment of life 
are just pervasive and shaped so

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much of what we do. 
They're so important for 

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language development, cognitive 
development, for our well-being.

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So it just was a really 
important to understand what is 

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what is underlying some of these
challenges. 

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How can we better understand 
them? 

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And then how can we provide the 
right supports to help 

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individuals who are dealing with
social challenges? 

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That's a nice segue into talking
about sort of the nuts and bolts

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of your research. 
So let's talk about what makes 

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your research unique in the 
field of social neuroscience. 

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A lot of classic neuroscience 
experiments are, or what people 

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call third person experiments. 
You watch a person, or see a 

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photo or hear a story. 
Your work pushes towards second 

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person approaches studying 
social cognition as it actually 

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unfolds between people. 
Why does this matter? 

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It matters because interaction 
isn't just perception. 

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So in real life, there's this 
contingency. 

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I do something, you respond, I 
adjust. 

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And that loop changes the 
attention, motivation and kinds 

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of inferences that we make about
one another. 

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OK. 
So it's not simply more 

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realistic, it can recruit 
different computations. 

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Yeah, exactly. 
So when we believe we're 

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interacting with a person, it 
can change the neural systems 

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that are engaged. 
So these include systems like 

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thinking about what other people
are thinking. 

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So think about people's minds 
and networks that support 

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engagement and attention. 
So for listeners, it's like the 

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difference between watching a 
tennis match and playing tennis.

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Same objects, totally different 
demands. 

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It's one thing to observe 
someone responding to their 

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opponents at volley. 
It's much different to be 

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reacting to a volley in real 
time and anticipating the next 

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shot. 
And this matters for autism 

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research too, because does some 
social challenges show up most 

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strongly in live social context,
right? 

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Right. 
Yeah, that's the key point. 

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So many autistic people can do 
well on structured lab tasks, 

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but yet still find real world 
interactions difficult. 

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So if we were only setting those
static or more structured tasks,

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we might miss what's actually 
driving these everyday 

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challenges. 
So another thread in your work 

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is using more naturalistic 
stimuli like maybe movies or 

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extended narratives to capture 
how social understanding unfolds

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over time. 
Why are these approaches so 

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powerful? 
The social life has structure 

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over seconds to minutes, 
tracking goals, updating 

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impressions, integrating context
and naturalistic paradigms. 

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Let us measure brain responses 
to complex, temporarily extended

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social information. 
We can use tools that quantify 

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how similarly different people's
brains respond to the same 

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social events. 
So that's such a key idea idea. 

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It's not just about which region
lights up, but the timing and 

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coordination of networks as the 
story unfolds. 

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And developmentally, it seems 
especially relevant, right? 

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Kids, social worlds, they change
very quickly, right? 

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You know, friend, they have 
friendships, school dynamics and

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perspective taking and all that.
Yes, right. 

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And we can also ask how neural 
systems for social understanding

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mature. 
How do children become better at

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integrating information across 
time, and how does that relate 

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to their everyday social 
functioning? 

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So, Liz, earlier you brought up 
the term heterogeneity. 

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Recently there's been a wave of 
works suggesting that there may 

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be distinct clusters, for 
example in autism traits. 

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Can you walk us through what 
this research actually means and

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what's new here? 
Yeah, absolutely. 

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So the big shift is that 
researchers are moving from 

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thinking about autism as a 
single continuum, like more or 

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less autistic traits, for 
example, toward asking whether 

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there are qualitatively 
different profiles. 

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And they're doing this at scale,
so using very large samples. 

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So there's one recent paper in 
Nature Genetics and it took this

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very large data set of autistic 
children and adults and used 

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person centered statistical 
modelling. 

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So that's basically where you 
let the data tell you how to 

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separate people out into groups 
that have different patterns of 

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traits or Co occurring features.
And they found a solution with 

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four latent classes. 
And what's important is that 

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these classes or profiles or 
groups weren't just mild to 

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severe. 
They differed in their 

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configuration of 
characteristics. 

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So things like their social 
communication features, 

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repetitive behaviors and 
developmental or language 

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differences as well as Co 
occurring conditions like mental

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health or ADHD. 
Right, so the idea is different 

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packages of traits tend to 
travel together. 

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Yeah, exactly. 
And then the study went a step 

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further. 
That's really important. 

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So it asked whether those 
different phenotypic packages 

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map onto different genetic 
signals. 

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So they reported the class 
showed different patterns of 

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genetic enrichment, and they 
linked them to different 

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developmental gene programs. 
So this suggests that there may 

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be multiple biological routes 
that can lead to an autism 

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diagnosis. 
So that's the the phenotype plus

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genetic side. 
What about the neuroscience 

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angle? 
Yeah. 

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So another major piece comes 
from a Nature Neuroscience study

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that tackled heterogeneity from 
the brain side. 

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Instead of starting with 
behavioral classes, they started

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with functional brain network 
connectivity. 

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And they asked, can we describe 
individual differences in autism

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in terms of underlying 
dimensions that connect brain 

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and behavior. 
So they identified 3 latent 

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dimensions or patterns that 
relate to different aspects of 

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cognition and symptoms. 
Things like variation to in 

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verbal cognition abilities, 
social affective traits, and 

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restricted or repetitive 
behaviors. 

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So then when participants were 
clustered based on where they 

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fell along those dimensions, 
then the analysis yielded for 

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reproducible subgroups and those
subgroups then have distinct 

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connectivity signatures. 
So like different network level 

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fingerprints and different 
behavioral profiles? 

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And they also try to connect 
that back to biology beyond 

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connectivity, right? 
Right. 

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So they integrate the brain 
network patterns with maps of 

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gene expression and so that's to
infer potential molecular 

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pathway association. 
In other they suggest that 

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different connectivity, altered 
subgroups may relate to 

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different underlying 
biologicals, the genetic 

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mechanisms. 
So that's still an inferential 

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step, but it's part of a broader
push to connect the levels, 

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behavior, brain networks, 
muscular biology. 

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Now, is there a developmental 
angle to this work? 

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Glad you asked. 
So there's a third recent paper 

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using a similar kind of profile 
approach. 

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It showed that the age of 
diagnosis, so early versus late 

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diagnosis seems to actually 
differentiate two groups of 

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autistic individuals that vary 
in a range of behavioral 

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features and Co occurring 
conditions. 

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And what's striking is that they
seem to have pretty different 

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genetic profiles. 
So you know, I should note that 

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there are structural barriers 
that may affect the age of 

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diagnosis. 
But this paper suggesting like 

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if you removed all of those 
structural barriers, there still

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is this kind of genetic 
difference and the behavioral 

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features kind of emerge early 
versus late in getting a 

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diagnosis. 
Can you say something about 

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these structural barriers just 
so our listeners understand what

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you're talking about? 
Yeah. 

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So structural barriers would 
include things like not having, 

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not just not having access to 
diagnosis so that they're often 

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very long wait list to get a 
diagnosis. 

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They, you know, if you don't 
have insurance then they're they

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can be very expensive. 
So they wouldn't be covered by 

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those costs. 
There also can be structural 

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racism that's playing in. 
So we know that boys of color in

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particular might be misdiagnosed
if the autistic boys who might 

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be get misdiagnosed with for 
example, behavioral problems or 

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like official defiant disorder 
where it's really often. 

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So it can take a long time to 
kind of get to the to the 

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accurate diagnosis. 
OK. 

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So returning to these papers, so
if you put these papers side by 

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side, what's the responsible 
bottom line for our listeners? 

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So the responsible bottom line 
is we're accumulating evidence 

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that autism heterogeneity can be
decomposed in these structured 

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ways. 
So for example, from a couple of

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the papers into four groups, 
depending on the method in the 

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data set. 
But but we shouldn't treat these

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clusters as fixed natural kinds.
They're best thought of as 

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useful models that can help 
design better studies and 

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eventually importantly, think 
about how to design better 

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support. 
So different profiles likely do 

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have different support needs. 
And importantly, these models 

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highlight also that averaging 
across all autistic people will 

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wash out these meaningful 
signals. 

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So if different subgroups have 
different brain network 

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mechanisms or genetic programs, 
then a single autism versus 

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control result is can be an 
oversimplification. 

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So how does this connect back to
your labs? 

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Focus on real interactions. 
So suggest a practical next 

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step. 
So we should be asking whether 

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these different profiles show 
different patterns during live 

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social interaction. 
So for example, differences in 

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social learning, reciprocity, 
maybe anxiety in this kind of 

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real time exchange or synchrony 
or alignment between 

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individuals. 
And if we can identify which 

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social contexts are challenging 
for which profiles and in which 

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ways, that moves us closer to 
thinking about mechanisms that 

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matter in daily life and to the 
supports that are better 

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tailored to individual rather 
than the average autistic 

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person. 
So there's growing interest in 

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studying synchrony, how behavior
and Physiology align between 

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people, and even how neural 
signals relate across 2 

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individuals. 
When people hear brain sinking, 

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they can get a little sci-fi 
about it. 

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What's a grounded way to think 
about it? 

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Yeah. 
So a grounded view is that 

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during interaction, people 
coordinate, coordinate 

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behaviors, attention, emotions, 
and these measures of synchrony 

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can index aspects of that 
behavioral coordination. 

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But we have to be careful about 
what it means and what drives 

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it. 
So is it that it's a shared 

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stimulus or is it true 
interaction dynamics? 

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OK, so synchrony isn't 
automatically good or bad, and 

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it doesn't automatically mean 
minds are emerging, right? 

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Exactly. 
So in the lab, we've shown that 

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being In Sync behaviorally can 
actually lead to both positive 

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or negative social outcomes, 
depending on the behavior. 

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So while the methods promising, 
the theory and design really 

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matter. 
All right, lightning, round 

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time, short answers, whatever 
comes to mind. 

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OK, one misconception about 
neuroscience, social 

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neuroscience you wish would go 
away. 

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That you can fully understand 
social cognition using only 

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static non interactive tasks. 
OK, how about a method or tool 

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that you think will shape the 
next five years? 

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I think we really need still 
better computational and 

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analytic methods for 
naturalistic and interaction 

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data. 
There's such rich data sets, but

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we need to be able to parse that
complexity and I think AI will 

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probably play a large role in 
advancing that. 

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OK. 
How about a question you're most

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excited about? 
South At the end of the day, the

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most important thing is that 
this work we're doing with 

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autistic individuals is actually
addressing the questions that 

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they care about. 
And so my lab currently is 

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really focused a lot on 
understanding social connection 

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and loneliness, taking some of 
these ideas of, you know, 

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understanding real world social 
interaction. 

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We want to know what predicts 
it, How do autistic youth 

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experience loneliness and what 
can we do to reduce it. 

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And I'm also very interested in 
kind of other directions of 

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thinking about chatbots and AI, 
how those can actually be 

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helpful social tools, but also 
how they could be harmful. 

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So really better disentangling, 
understanding how those are 

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affecting youth, including and 
especially for autistic youth. 

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Fascinating. 
Well, Liz, it's been wonderful 

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having you on the show today. 
I hope we can have you back at 

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some point. 
Thanks, this is great. 

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If listeners want to learn more 
about Doctor Redkins Lab and 

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research, we'll link the 
Developmental Social Cognitive 

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Neuroscience Lab site in the 
show notes. 

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In the meantime, I'm Mike. 
And I'm Joey. 

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Abby got the wisdom, dropping 
pearls on the mic. 

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Ben with the insides sharp as a 
spike. 

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Mike's got the vibe, Always 
keeping it chill. 

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00:13:31,320 --> 00:13:35,360
Joey cracks jokes, flexing 
comedy skills. 4 minds collide 

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00:13:35,520 --> 00:13:37,880
the combos. 
Electric cracking the shell, 

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00:13:38,080 --> 00:13:40,720
peeling layers. 
Eclectic topics on deck. 

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00:13:40,720 --> 00:13:43,680
From the D to the front, every 
episode's a journey. 

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00:13:43,680 --> 00:13:45,920
We've only begun Cracking the 
shell. 

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00:13:46,160 --> 00:13:49,600
Yeah, we're cracking it well. 
Stories are loud, Sky well to 

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00:13:49,680 --> 00:13:52,760
unveil happy. 
Ben, Mike, Joey, ring the bell. 

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00:13:53,040 --> 00:13:58,000
Turn it up loud. 
Yeah, we're cracking it. 

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00:13:58,000 --> 00:14:03,680
Well, stories and laughs ring 
the bell. 

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00:14:04,040 --> 00:14:07,680
Turn it up loud. 
Deep dive. 

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00:14:07,680 --> 00:14:09,600
Big laughs. 
Always something to say. 

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00:14:09,760 --> 00:14:12,840
Pop culture to the philosophy. 
They pave the way from the wild 

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00:14:12,840 --> 00:14:14,640
to the wise. 
It's a balancing act. 

319
00:14:15,240 --> 00:14:17,640
Brains meet banter. 
That's a podcast fact. 

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00:14:18,000 --> 00:14:21,240
I'll be dropping gems like a 
treasure chest bend dissects 

321
00:14:21,240 --> 00:14:25,120
ideas, puts them to the test. 
Mike's move to lick me cool as 

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00:14:25,120 --> 00:14:27,360
the breeze. 
Joey's punch lines hit, bring 

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00:14:27,360 --> 00:14:31,000
you to your knees. 
Crack the code, crack the case. 

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00:14:31,520 --> 00:14:33,680
Crack a smile, let it light up 
your face. 

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00:14:34,640 --> 00:14:37,200
Hey, this is Mike from Crack and
the Shell on Psychological 

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00:14:37,200 --> 00:14:39,360
Science. 
Just a quick thank you to all of

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00:14:39,360 --> 00:14:41,840
our listeners. 
Joey, Abby, Ben and I really 

328
00:14:41,840 --> 00:14:43,400
love putting these episodes to 
get it for you. 

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00:14:43,520 --> 00:14:46,360
If you enjoy them as much as we 
do, we'd really appreciate it if

330
00:14:46,360 --> 00:14:48,640
you hit that subscribe button 
and share it with your friends 

331
00:14:48,640 --> 00:14:50,520
and family. 
It's free and it helps us more 

332
00:14:50,520 --> 00:14:52,600
than you might think. 
While I'm at it, I'd like to 

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00:14:52,600 --> 00:14:55,720
give a big shout out to 
Anthropics Cloth and Pseudo AI 

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00:14:55,720 --> 00:14:56,960
for the help behind the scenes 
today. 

335
00:14:57,200 --> 00:15:00,200
If you have ideas for a future 
episode or just want to say hi, 

336
00:15:00,400 --> 00:15:03,680
e-mail us at Crack on the Show 
on psychology@gmail.com. 

337
00:15:03,920 --> 00:15:06,840
Until next time, remember that 
the most beautiful minds are 

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00:15:06,840 --> 00:15:08,840
often the ones that see things 
differently.