September 6, 2024 • 36 mins
Neuroscience is the hottest STEM field. Why? What does a neuroscientist actually do? Is the brain some mechanically deterministic box configured at birth? Cat knows Ashley has the answers, and now you will, too.
Credits
Ashley Juavinett, host + producer
Cat Hicks, host + producer
Danilo Campos, producer + editor
For an incisive breakdown of “the crimes against dopamine” please read the piece of that title by Mark Humphries.
The myth of mental illness book that Ashley mentioned was written in 1961 and we don’t really think it’s worth reading.
The longitudinal fMRI study that Ashley contributed to while in graduate school: Stewart JL, Juavinett AL, May AC, Davenport PW, Paulus MP (2015) Do you feel alright? Attenuated neural processing of aversive interoceptive stimuli in current stimulant users. Psychophysiology 52:249–262.
This is the Twitter/X account that highlights when a study happens IN MICE: https://x.com/justsaysinmice. And here’s the creator’s motivation: https://jamesheathers.medium.com/in-mice-explained-77b61b598218
The study that recorded from someone’s brain while they died is Vicente et al. (2022) Enhanced Interplay of Neuronal Coherence and Coupling in the Dying Human Brain. Frontiers in Aging Neuroscience 14. See also this commentary about their claims.
We once again mentioned field-specific ability beliefs. Here’s Cat’s blogpost on her own research.
This study explores the basic dynamics of field-specific ability beliefs and shows their connection to gender inequities in academic disciplines: Leslie, S. J., Cimpian, A., Meyer, M., & Freeland, E. (2015). Expectations of brilliance underlie gender distributions across academic disciplines. Science, 347(6219), 262-265.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Ashley (00:00):
You are a biological creature.
Your mental life rides on thechemicals sloshing around in
your brain.
Cat (00:07):
People have taken that to be like, okay, this picture of
your brain determines everythingthat you can do, but you're
saying the opposite.
Like, hey, we're in dialoguewith this brain.
Ashley (00:16):
You're on a trajectory that is in some part determined
by your genome, but you are alsomodifying that trajectory every
single day through yourexperience.
Cat (00:32):
We got a lot of interest from folks about Ashley being a
neuroscientist and what we canthink about here in this space.
Ashley (00:39):
Ooh, neuroscience.
Cat (00:41):
It's something that I love having in my house.
What does a neuroscientist likeyou do every day?
Ashley (00:48):
I do feel like there's a difference between what people
think neuroscience is and what atypical neuroscientist does in
their day job.
Throughout my training, I wasworking at this level that
people would call systemsneuroscience and systems
neuroscience is about thesequestions about how neurons work
together.
How do they help us behave andmake decisions and see things
(01:10):
and move about the world.
And, um, what that looks like onthe daily is playing with mice,
playing with microscopes,playing with lasers.
Cat (01:21):
All right.
The lasers.
Ashley (01:22):
Playing with genetic engineering techniques to get at
all of these things in reallyprecise ways.
That's one flavor ofneuroscience.
Neuroscience is so manydifferent things depending on
what you're doing.
Cat (01:33):
It's an example maybe of a field that we couldn't have even
had if we hadn't had all theseother, you know, technical and
creative breakthroughs in manydifferent fields.
And they kind of all cometogether to help us study the
brain, right?
Ashley (01:45):
Every time I talk about neuroscience, especially to
trainees.
One of the biggest messages isthat this is a constantly
evolving field, and it's a fieldthat's been catapulted into the
future because of technology,because of our ability to record
lots of things simultaneouslyand take really high resolution
images of the brain and sequenceour genomes.
(02:07):
That's all a part of this aswell.
I obviously care first andforemost about at the end of the
day, these kinds of things beingable to help people, right?
And that's like where a lot ofneuroscientists come from.
It's not the same as being adoctor where you know that every
day when you go in, you're goingto help someone.
I think as a neuroscientist orany kind of scientist, you hope
(02:29):
maybe in five years or 10 yearsor something, it's going to help
someone.
So it's a really different sortof timescale And then a second
piece of it is just the basicunderstanding of how these
things work, because at the endof the day, you don't know when
that knowledge is going to beuseful, right?
And in neuroscience, like wedon't really know, like we're
(02:50):
trying to just understand howthe brain fundamentally works,
both on the order of like singleneurons and then all of those
neurons talking to each otherand across brain regions.
We don't really know how thatworks and we don't know what
we're going to learn or whatwe're going to be able to do
with that information.
Cat (03:09):
Wow, yeah, that's a really beautiful perspective.
I feel like being able to staywhen I hear this as a
psychologist, I think you haveto stay motivated for these like
really long term things, youknow, and you have to kind of
like, care about, you know,it's, it's, it's an intrinsic
motivation, isn't it?
I remember one time I was in thegrocery store and I'm always on
the lookout for something thatsays like neuro on it.
(03:33):
Most especially when it's a formof marketing.
So there's like a, a drink brandthat's named neuro something,
um, and it's supposed to be goodfor your brain.
My favorite one that I everfound was a line of hair care.
No hairstyle products.
It wasn't even like, uh, itwasn't even shampoo.
It was a blow dryer
Ashley (03:51):
yeah, yeah.
It's like neuro blow.
I don't know.
Cat (03:54):
That sounds bad.
I'm pretty sure it wasn't that.
But it was neuro something and,and I sent a picture to Ashley
immediately.
I mean, at light speed, I brokethe sound barrier to text this,
to my neuroscientist wife,because, um, this is so funny to
us.
So what do you think is going onthere?
Hmm.
(04:16):
Hmm.
Ashley (04:19):
cutting edge or cool.
Um, and Like, yeah, like, whyput it on a hair product?
I don't know, like, unlessthat's like seeping into your
brain somehow, people have whatare called field specific
ability beliefs, right, and wehave these, you know, Ideas that
like specific fields are morebrilliant than others.
And so like, you know, a classicexample might be like
(04:41):
mathematicians, right?
We think like mathematicians arebrilliant and versus like, you
know, maybe economics, like weconsider like sort of less
brilliance in that same
Cat (04:50):
Yeah, I think a stronger contrast might be like poetry,
you know, or
Ashley (04:54):
Yeah.
Yeah.
Cat (04:56):
well, you're really creative, but that doesn't
necessarily mean you're cuttingedge or, or, or technological.
Ashley (05:02):
Right.
Right.
But music is actually like areally, a high brilliance field,
which is kind of interesting,like, but not literature.
Cat (05:09):
I remember that.
So what you're talking about is,um, for instance, Cimpian and
Leslie are the researchers whoput out a lot of work on this,
but they've looked at this inspecific fields, like within
chemistry, within physics is oneI remember.
They've also looked at it aroundthe world.
So it kind of emerges globallyand it emerges when you, you ask
people, Hey, what do you thinkit takes to do really great
(05:31):
science in these differentdisciplines?
And one of the things that Ithought was so cool about the
field specific ability beliefsresearch that's been coming out
the last decade or so is itdoesn't always map on to just
STEM or not STEM.
As you pointed out, it'ssometimes it's a little bit more
(05:51):
complicated than that.
So for instance, you're actuallyin biology, where we tend to
sort of think, Oh, okay, if Ihave sort of stereotypes about a
biologist, it's not usually thesame kind of stereotypes as I
have about a chemist.
So our beliefs about differentkinds of STEM fields, different
kinds of technical work are alittle more complicated than
(06:12):
just saying STEM or not STEM,right?
Ashley (06:15):
totally.
And I think it's interesting tocontrast even like neuroscience
with biology.
Even though a huge piece ofneuroscience is biology, people
don't react to the fact thatsomeone is a biologist in the
same way that they react to tothe fact that they're a
neuroscientist, right?
Cat (06:33):
do you experience this?
Do you mind introduce yourselfboth ways?
Something,'cause you're a,you're a neurobiology faculty
member
Ashley (06:39):
Well, it's interesting.
Yeah, totally.
So like my PhD was inneurosciences plural, which is
like a weird thing we dosometimes.
Um, but neurosciences and then,my postdoc was in neuroscience,
but now I'm a neurobiologyfaculty member and I did.
I do feel like there's adifferent vibe when people say
neuroscientists versusneurobiologists you wouldn't put
(07:01):
like neurobiology on a hairproduct to try to sell it.
Cat (07:04):
This made me think about computer science and how we just
get to tack science on certainthings and psychologists
absolutely do this too.
Some psychologists say thepsychological sciences or a
psychological scientist, andthis is a really.
Important helpful thingsometimes because like I go to a
party and I tell people I'm apsychologist.
(07:25):
They immediately say, where'sthe couch?
Let's talk about my childhood,which is fine But then I have to
say I'm I always say I'm lab labpsychology not couch psychology
I'm not a clinician.
So there are all these all thesecomplicated divisions in these
things Different disciplinesthat you might not know from the
outside.
And I think that's one reason welike to use the word science,
(07:47):
because we're trying to tellpeople we do research, you know?
Ashley (07:50):
Yeah, totally.
I've heard you introduceyourself as an experimental
psychologist, like, many times,sometimes when I say
neuroscientist, people thinkneurologist, and like, I've had
people, like, this woman on aplane one time was like, oh,
like, I've had this twitch in myeye for weeks, and I'm like,
okay, cool, like, I don't knowabout that.
Cat (08:08):
I could do some statistics if you gave me a lot of images
across 20 different people.
Ashley (08:13):
We have these beliefs and then it impacts the way we
think about these differentfields, and it impacts the kind
of funding that those fieldsget.
Like, I can't complain thatneuroscience gets all of this,
you know, spotlight andexcitement Because it means like
a lot of research is gettingfunded, like the Brain
Initiative and all of the NIHfunding that goes towards
(08:33):
neuroscience research.
These are important problems forsure, but we just have to
inspect, like, why we're soexcited about neuroscience,
Cat (08:41):
It's so powerful and cool that you are a neuroscientist
and you are someone who, whogoes out there and has people
say, Oh my gosh, you're aneuroscientist.
You know, I will trust youropinion on hair products.
Um, but you're actually still,you know, ready to question this
and ready to say, are we alwaysthrowing our money at the right
thing?
Because we had theseconversations, during the early
(09:01):
days of, like 2020, forinstance, where we were talking
about, are we putting enoughwork into understanding
behavioral science andunderstanding the choices people
are making versus, ourwillingness to say, well, if
something is, looking at cells,then it must be real.
But if it's looking at humanchoices and human behavior, you
know, that's sort of moreintangible and less real.
Yeah,
Ashley (09:26):
married to you and being so familiar with your work has
really made this like supersuper clear to me there's times
when people need answers in theform of cells or neurons or like
brain regions, but then there'stimes when And this is probably
most of the time, honestly, whenpeople actually want a response
(09:47):
in the realm of psychology, likethey want to know how people
behave.
What are the knobs we can turnto like help people feel a
certain way?
What are the ways in whichpeople act given different like
environmental pressures orwhatever it is, right?
Like there are times in which aneuroscience perspective and
that kind of mechanisticunderstanding are necessary, but
then there are times when changeis possible with Without that
(10:11):
kind of understanding.
Cat (10:13):
It doesn't have to be competitive.
like psychologists, can sobenefit from this deep work
that's going on, turning up anddown the luminescence of cells
is something that I can't do.
But I can change the mindset,you know, that someone goes to
work with, and that actuallydoes involve their neurobiology
at some level, we don't have tobe competing with each other.
(10:35):
That's, of course, you know, alesson of our, like, life
together here.
I think it's often reallydisheartening when you have a
really good solution, somethingthat really seems to be helping
in the real world, like helpbuild trust, you know, in
reaching out to doctors andgetting sound information.
And that work comes frompsychology.
(10:56):
But then someone gets on aplatform and sort of says, well,
you know, your serotonin drivesyou to do this.
And people walk away from itfeeling like they don't have any
choice or any agency.
And that's just not accurate tomodern neuroscience.
But I think that's what we takeaway a lot of the time from
hearing about a sort ofmechanistic thing in
(11:16):
neuroscience.
Ashley (11:17):
This is a really good point.
And this is the double edgedsword of biological
reductionism, which is like, youcan tell people, Oh, you get
like a burst of dopamine whenyou get into your flow state
while you're programming orsomething like that.
Right?
Like you can tell people that.
I'm sorry, I did it.
Let me just say as an aside thatwe have limited ways to actually
(11:39):
measure dopamine release inhumans.
So almost everything you've everheard about dopamine is from an
animal model.
So let me just say that.
Cat (11:48):
What, what should, what, what does that mean for people?
Ashley (11:50):
It is true that humans have dopamine and plenty of
people have put people in a petscanner and that's like the, one
of the ways we have to measuredopamine in humans.
And they've seen that particularareas of their brain are like
more active with dopaminespecifically.
It is true that most of theresearch happens in animal
models.
So I do think it's just likegood to know where your
(12:12):
information comes
Cat (12:13):
Yeah.
And what we don't know yet,
Ashley (12:15):
and what we don't know yet and what we can do and what
we can't do.
The main thing I see my role as,as a neuroscience educator is
like for people to be able tosee a study or see a news
release or whatever it is andunderstand What study actually
would have gotten us to thatheadline?
Coming back to this like doubleedged sword of this kind of
reductionism is Okay, like solet's say You know, we do know
(12:40):
that dopamine gets releasedwhile you're like, in this like,
passionate moment ofprogramming.
Does that change the way youbehave?
Does that change the way othersshould treat you?
Does that what does thatactually do for you besides just
a fun little fact about whatyour brain is
Cat (12:55):
Some people to get really real about it have this belief
that.
Some people are doing thisbetter than others.
And they're maybe born that way,right?
there's some people whose brainsare programming brains.
Ashley (13:07):
Mmm.
Cat (13:08):
And they really think that and then they're looking for
kind of biological reasons thatthat might be the case.
And something you and I havetalked about a lot is hey, it's
not so deterministic, like thiscould be a thing that happens
for some people.
And other people might have adifferent sort of thing going
on.
The absolute brilliance of ourcognitive strategies and working
(13:31):
many, many different ways issomething that we need to take
seriously.
And whenever I hear peopletalking about Oh my gosh, I went
to the real science, which islike the serotonin and the
dopamine, you know, and it'schemical.
So it's real.
And that's what's drivingdeveloper productivity.
For instance, you and I areoften having these conversations
(13:52):
where, where I'm like, Hey,babe, like somebody said it was
dopamine.
Ashley (13:56):
Not to be too reductionistic about it, but
like, dopamine is the thing thathelps you feel good, so if you
feel good, it's probablydopamine.
It's, like, not thatinteresting, actually, at the
end of the day.
Cat (14:08):
So we know that, you know, you're not magically going to
get all the problems solved inthe world by giving people
pizza, but people might stillget dopamine when they get
pizza, you know?
Ashley (14:17):
This brings up is like this nightmare scenario, which
you could imagine, which islike, what if we started
interviewing people for oursoftware teams and instead of
actually having them do like abehavioral test or, you know,
what you've sort of proposed,right?
Like, what did you call it lasttime?
You called it like, um, Yeah,What if instead of talking to
people, you just measured, like,let's say you could do this,
(14:40):
which you can't right now, butimagine you could just like put
a little cap on them, be like,let's see how much dopamine gets
released while you'reprogramming.
Cat (14:46):
I'm pretty sure some companies might already be
trying to do this.
Ashley (14:51):
I mean, this is horrific,
Cat (14:52):
put them in a scanner and fMRI.
Ashley (14:55):
We sort of think about these things, That as if they're
like built in like how muchdopamine you release is somehow
like some intrinsic fixed thingabout you Right, which that
assumption and as you pointedout, we have to be more holistic
in the way we evaluate people,for one.
(15:15):
But also, these things change.
And dopamine is literally alearning signal.
This is one of the main thingswe know about dopamine, is that
it changes.
It's indicative of your brainlearning and growing.
And these things also changeover time.
So anything you measure aboutyour brain for the most part, Is
changing and it can change.
And so taking a snapshot of whatsomeone's brain might look like
(15:38):
today is really different thanlike a year from now.
And what it looks like a yearfrom now is entirely dependent
on what you've done in thatyear.
Cat (15:48):
Ooh.
Well, see, I think this is sortof scary and hopeful at the same
time.
Like, what we do changes ourbrain.
And people have taken that tosort of be like, okay, this
picture of your brain determineseverything that you can do, but
you're saying the opposite.
Like, hey, we're in dialoguewith this brain.
(16:09):
We're, we're, we're choosing theways that it's working in some
sense, or the things we getexposed to, at least, you know,
Ashley (16:17):
Yeah, absolutely.
And, and I mean, there is likegenetic determinants of these
things too.
Like, I don't want to say it'slike entirely experience
dependent, but it's both.
You're, you're on a trajectorythat is in some part determined
by your genome, but you are alsomodifying that trajectory every
single day through yourexperience.
Mm.
Cat (16:36):
Wow.
Boom.
So for the people who thinkstick you in a scanner, take a
snapshot of your brain.
That's who you are forever, youknow.
I think that this is a reallypowerful counterexample because
I, you know, I always thinkabout this.
We're always obsessed with thisidea of comparing between people
and finding individualdifferences.
So like in psychology, we talkabout it like group differences
(16:59):
or the differences betweenindividuals, but you know,
between individual differences,the jargon, but there's also
within individual differences isthis huge, amazing, fruitful
realm.
And it's often the stuff thatyou really care about trying to
change.
Like if someone is at level 6,you know, or whatever, you could
(17:20):
help them get to level 8.
You know, they have this rangeavailable to them.
And so the really impactfulquestion in the world is much
more like, can I move people?
You know, within their own rangeavailable to them.
Can I help them meet theirpotential?
And it's not always thequestions about, Oh, if I had a
thousand people for this onesnapshot in time, how would I
stack rank them?
Ashley (17:40):
This is actually some of my favorite use of, like, fMRI,
which you brought up, right?
Functional MRI, you put peoplein a scanner, you measure their
blood flow, not even theirneural activity, but you measure
their blood flow, and it tellsyou something about which areas
of the brain are active.
Um, my favorite use of thatYeah.
Technology is not actually tocompare people to each other,
(18:00):
but longitudinally.
So my earliest work in gradschool, when I got here during
my first research rotation, wastrying to, essentially, predict
whether people that had somereally early stimulant use would
progress onto being stimulantaddicted people.
And the idea was like, could youtake brain scans?
(18:23):
Like, is there something in thebrain that changes over time
differently in the people thatprogress into stimulant
addiction?
And for me, that's a, that's areally useful way to look at
that technology.
Cause as you pointed out, likeit's within an individual and we
can.
take a baseline and then measurethem like every year and see
what happens.
It just, and it gives us thispower to try to understand, is
(18:48):
there anything early on?
That you could measure with anfMRI, which is limited, but has
some power is there anything youcould measure early on that
might tell us who to interveneon more intentionally, you know,
that's starting to use likestimulants in this case?
Cat (19:07):
We are in this place where we just throw stuff at our
brains.
And the stuff that we can throwat our brains is really high
level sometimes like, Hey,here's a medication that just
pulls this huge lever, you know,and that we're on this path to
trying to get more and moretargeted and trying to
understand not just your brainas a static picture, but like
your brain in this moment doingthis one thing.
Ashley (19:30):
Yeah, totally.
Totally.
I think that's super, superimportant to remember.
I'm demonstrating a lot ofskepticism.
About neuroscience, but, thereare.
Many different ways in whichthis understanding of how the
brain works has been absolutelynecessary for things, right?
(19:51):
So, so to give one specificexample, in like the 1960s and
70s, it was hotly debatedwhether schizophrenia was like a
real mental illness, right?
And someone actually literallywrote a book called The Myth of
Mental Illness.
And The idea was like, oh, thesepeople are just kind of making
it up.
Like maybe they're like a littlestrange, but there's nothing
(20:13):
actually going on in theirbrains that's different.
It was just a myth.
Right.
And it wasn't until we hadsomething biologically to point
to that people started beinglike, Oh no, this is a real
thing.
We can actually treatschizophrenia with dopamine
antagonists.
And it turns out.
That that dramatically changesthe symptoms of someone with
(20:33):
schizophrenia.
They stop having hallucinations.
So that's a case in which thiskind of understanding was
necessary and necessary fortreatment, necessary for
societal understanding,
Cat (20:43):
necessary to stop blaming people for what was happening to
them.
Ashley (20:46):
Absolutely.
Yeah, absolutely.
And you see that same thinghappening, um, you know, more
recently with, um, things likedepression and anxiety, right?
We no longer immediately tellpeople, just pick yourself up
off the floor, right?
We have this like, right.
Some of us might, but like, wehave this sort of broader
understanding that some people'sbrains are built a little
different and there is meaningin that.
(21:08):
You are a biological creature.
Your mental life rides on thechemicals sloshing around in
your brain.
Cat (21:17):
think that's really compassionate.
And what we need here is likecompassionate science, and we
need to be able to say, wow,we're thinking about all these
levels and Yeah.
I guess the question I wouldthrow out to you, because I
think it's just constantly onethat people carry around with
them is, what can I do?
I'm riding around on all thischemistry and biology and like,
(21:38):
what can I do for it?
How can I try to take care of mybrain?
Ashley (21:41):
I was buying running shoes like a couple of months
ago and the guy who was helpingme was like super chatty and he
was like, oh cool you're aneuroscientist, like, so what
should I do?
And like what's the one thingyou would tell me?
And I said get some sleep.
Cat (21:53):
Yeah.
Ashley (21:55):
Like we know quite a bit about how sleep is necessary for
your emotional health, for yourphysical well being, for
everything.
Okay, sleep well.
And that's The truth is we'veknown that forever.
Um, we also know that you needto eat well and you need to
exercise like.
(22:16):
These have been tried and testedover human time.
Cat (22:18):
These are the biggest effects on your, biggest effects
on your
Ashley (22:21):
biggest effects on your brain, and it's, these things
aren't trivial, like some peoplehave trouble sleeping and I
don't want to like minimizethat, but if you can prioritize
making space for that andputting attention to it, you
know, that actually could have amuch bigger effect size than
many of these other like flashsolutions that you might sort of
see out there.
Cat (22:42):
so that raises another question, which is how are we
I'll use this word, normalpeople, supposed to evaluate
scientific evidence, like we seea headline come out and it's
like, Oh my gosh, you know, ifyou, you give mice macaroni and
cheese, you know, they all getdementia.
(23:03):
There's all of these, all ofthese headlines about
neuroscience and, and how do youevaluate it as a person in the
world?
How do you teach your studentsabout
Ashley (23:12):
Yeah, this is, this is a tricky one, right?
Cause I don't think we canexpect everybody to become
experts, right?
You're already, you are anexpert in your own field.
You know, the listeners of thispodcast have their own
expertise, right?
I don't want to ask everybody tobecome a neuroscience expert,
but.
I do want people to ask maybelike two or three different
(23:33):
questions.
One of them is what is theevidence for the headline,
right?
And does it come from a mousestudy?
Immediately, if it comes from anon human study, we have to go,
okay, in mice, and there'sactually this I don't know if it
still exists, but there was thisTwitter account for a while that
would republish scientificheadlines, but add in mice, if
it like happened in mice, youknow, it's just a,
Cat (23:56):
And in male mice, mo in male mice, most of the time.
Ashley (23:58):
Totally, in male mice.
And it's, that's not to say wecan't learn things from mouse
models.
Like, we can.
However, it has to be evaluatedand we have to
Cat (24:07):
It's one step in the ladder of evidence.
Ashley (24:10):
totally.
So, like, the first question is,okay, how do we know the thing
this article is claiming?
The second thing that I wouldhave people ask is, you know, is
this just one study?
Or is it a study that's embeddedin like a whole series of
research about this thing,right?
And, because the way science isbuilt and the way understanding
is built and textbooks arewritten, not on a single study.
(24:34):
Nothing ever rests on a singlestudy, right?
And things rest on bodies ofresearch, lots of iteration,
lots of redoing and rethinkingand re evaluating what we've
already done.
And so, you know, the secondquestion is just like, does this
stand alone or is there otherstuff?
And obviously, you're not goingto be able to like do a
(24:55):
literature review on everysingle finding you find, but
hopefully wherever you'refinding that scientific
Evidence, like whether it's likea headline, a news article,
whatever, hopefully thejournalist who wrote that piece
is giving you the context that'snecessary, right, to say like,
okay, this is built up.
It's like one of several studiespointing at, you know, mac and
cheese being a contributor todementia, whatever it
Cat (25:18):
Not only are you a neuroscientist and a teacher,
you know, you also have donescientific journalism.
And the difference, I think,between a piece that's like very
sensationalist, it's kind oflike misinformation anywhere,
right?
You can start to develop yourspidey sense that's like, oh,
this seems a little extreme.
You start to see that things arewritten in such a way to like
(25:39):
scare you or to alarm you or to,you know, to really make an
extreme, to say, don't look anyfurther, just react.
Ashley (25:45):
Yeah, totally.
Cat (25:47):
And the difference between like someone like Ed Yong, who
does this beautiful journalism,that's like very rich and kind
of goes into, this is not justwhat we think we know, but why
we think we know it and how weknow it and what there's left to
know.
And
Ashley (25:59):
I actually spent an entire class period with my
neurobiology class talking aboutthis one article.
Where the headline is, your lifemay flash before your eyes now
we know it, or something likethat, or before you die, sorry,
your life may flash before youreyes when you die, and that's
the headline, and we look at it,it's one paper, it's a wild
(26:22):
paper, because we actually wereable, they actually were able to
record from someone as theydied, while they were recording
from their brain, Right?
So it's like this rare instanceof actually having a recording
during death, and they measureall the changes that happen in
this person's brain before theydie, and they conclude that
there's like this uptick ingamma activity, and therefore
(26:45):
this person relived all of theirmemories.
Okay, so there's this likemajor, major jump in this, which
is like, okay, having gammaactivity in your brain doesn't
mean you're like thinking aboutyour mom and where you went to
high school and like relivingyour marriage or whatever it is,
right?
It just means you had anincrease in gamma activity
Cat (27:02):
what's gamma activity?
Ashley (27:03):
gamma activity is a particular frequency of brain
activity.
So if you were to record fromthe brain, you'd get this, like,
big squiggle over time.
You could take that squiggle ofvoltage over time and break it
down into different sine waves.
Um, and so think about it inlike the frequency domain, in
other words, so rather thandescribing what the signal looks
(27:24):
like over time, we woulddescribe the signal in terms of
what frequencies are containedwithin.
And gamma is one of thosefrequencies, it's high frequency
activity.
And like, if you look online,you'll find a bunch of stuff
about people trying to improvetheir gamma and blah, blah,
blah.
Um, in this particular paper.
They selectively choose this oneexplanation for what Gamma is,
(27:44):
which is that it's memoryretrieval, which is one thing
that Gamma does, but it's notall of the different, um, it's
not everything you'll find whensomeone has Gamma activity.
Like, you have Gamma activity inyour mind right now, for sure.
Most people do when they'reawake and, and attentive.
So the paper makes this big leapabout, like, you reliving your
life, and that's just, that's aleap, right?
(28:05):
And I should say the articlemakes the leap more so than the
paper.
The paper is kind of like, oh,maybe this could be a little bit
of, uh, memory retrieval
Cat (28:13):
We always see this happen as scientists, like the, the
second you speculate onsomething, a journalist takes it
and they're like, This is ity'all, the scientist discovered
this, and then people get reallymad at you when it, you, you,
they say you discoveredsomething, even though maybe you
were just saying, hey, I noticedthis.
Ashley (28:30):
totally.
And you wonder why scientistsare so tight lipped, Right,
Cat (28:33):
Right, scientists are sometimes scared of talking to
the media, for
Ashley (28:37):
totally because of stuff like this.
I think like a savvy reader ofthese things would just like
think twice, right?
Like think twice before yourepost that, like, Little flashy
Instagram thing.
I found out about this articlefrom a student cause it was on
Tik TOK like, oh my God, likewe, you, you see your whole life
before you die.
And then my student was like,wait, is that true?
(28:59):
And I was like, all right, let'stalk about it.
And now we spent a whole class.
Cat (29:02):
No, it's amazing because you get people come into your
class, right?
Because maybe they saw somethingabout the brain on TikTok, you
know, but that those stories arebeing used to sell a lot of
stuff, a lot of different stuff.
And
Ashley (29:15):
Yeah, and that's a pretty innocent one, right?
Like, that's like, okay, it's anice thing to think, like, I
would like to think, like, rightbefore I die, I get to, like,
see our dog and our house and,like, relive all those beautiful
moments.
Like, that's a lovely thought.
That's not hurting anybody,really, to, like, think that
way, but there are examples thatcould be hurtful, right?
And that's the stuff I wouldreally, really be concerned
(29:36):
about.
Cat (29:42):
I saw you give this talk that was like, You can be a
neuroscientist.
Like anyone can be aneuroscientist.
Tell me about this thesis thatyou have about getting more
people involved in neuroscience,including technical people,
maybe out there who haven't everthought about this for
themselves and their skills.
Ashley (30:00):
Neuroscience.
is one of these fields that wethink of as being closely
associated with brilliance,right?
There's, there's often thislike, barrier for people getting
in.
And so it has been a mission ofmine for many years.
And I wrote a book that came outin 2020 that was like, so you
want to be a neuroscientist.
I would go back and retitle thatlike anybody can be a
neuroscientist.
(30:22):
So this has been like aparticular interest of mine
because I see that there's thisbarrier and I really do believe
it.
It's just another field.
where you need to learn thingsand you need to get particular
skills to succeed, um, and Thecool thing is now that most of
this actually doesn't livebehind closed doors.
(30:42):
So the talk I gave that you'rereferring to is for Nerd Night,
which is an event here in SanDiego.
And it's like a drink beer andlisten to scientists sort of
event.
My message was kind of like,look, if you want to look at
neuroscience data, like when yougo home or even on your phone
right now, like you could do itactually, here's a, list of
datasets, you know, you couldjust like, if you know, a little
bit of like, How to wrangle somedata.
(31:02):
Go open it up.
Look at some neurons firing.
You could play with that rightnow because neuroscience is
opening up in like some reallybeautiful ways.
Like different funding agenciesare requiring you share your
data.
We have these like cool new datastandards where like everybody's
fitting their data into thesestandards so we can share them
and try to reuse them.
And this is the stage ofneuroscience and it's cool for
(31:25):
the potential of like citizenneuroscience as well.
Cat (31:28):
What are the needs of neuroscience?
Say you're a programmerlistening to this.
We had a friend who came up toyou and said, I never realized,
I didn't have no idea there werethese big open data sets and you
were describing all this stuffthat I know how to do.
Ashley (31:41):
Yeah.
Our friend came to this nerdnight event and yeah, he was
like, can we get coffee and justtalk about like, what does
neuroscience need from someonewho knows how to code?
I love that question.
One, if you live on the datascience side of things, just
know there's a ton of open datasets and there's also some
pretty good, like documentationabout typical, um, approaches
(32:04):
people would use with that kindof data.
Cause it, it's probablydifferent than.
Other data you might've workedwith as a data scientist.
So be a little bit more timeseries, maybe more images, like
stuff like that, but still it'sin the same kind of wheelhouse.
So that's one thing you couldplay with data,
Cat (32:18):
What are some examples of those data sets?
Ashley (32:21):
Everything from like, um, you know, single recording
of, uh, individual neurons.
So recording the voltage frominside of neurons and maybe like
hundreds of those neuronssimultaneously.
To whole brain recording or likewhen we were talking about fMRI
earlier, you can find lots ofopen fMRI data for basically
anything you might be interestedin.
(32:42):
Let's say you have kind of a petinterest in like Alzheimer's
disease or something, right?
I am willing to bet there issome open access data set.
where there's like patients withAlzheimer's disease and controls
and you could like go in andlike compare, you know, the
brains or something or look atthem over time.
Cat (32:59):
Are there any big names?
Places, websites people shouldgo visit?
Ashley (33:03):
I'm a huge fan of the Allen Institute, which is a big,
uh, research institute inSeattle and they make all of
their data public and it's alsoreally well documented.
Most of that's going to be, Likeon the single cell side of
things and not really diseaseoriented, a little bit more like
basic science.
There's also a couple of dataformats that are really cool.
So there's one called B I D S Iactually don't know if people
(33:25):
say bids, but that's EEG, fMRIor whole brain stuff.
They have a lot of awesomedocumentation and a ton of data
sets are in that format.
There's one that I work reallyclosely with called NeuroData
Without Borders.
Um, so yeah, we'll put them inthe show notes.
I have like a growing list, aspreadsheet of all of these
datasets that exist out there.
So that's like thing number oneyou could do is like play with
(33:48):
data.
If that's your thing.
The other side of it is actuallysoftware development, you know?
So there's this like whole fieldof research software and a lot
of it is open source and peopleare all the time.
Like releasing cool packages fordoing particular things with,
um, data.
Right.
And like, maybe you have to do alittle bit of legwork to
(34:09):
understand what are thechallenges that people are
trying to overcome using thesedifferent software.
But, at the end of the day,like.
Those projects, many of them areopen source.
Many of them could probablybenefit from a lot of the
expertise.
So one thing I ended up talkingabout with our friend was like,
data formats and like datacompression.
And he's like, okay, like myexpertise is on, you know, data
(34:32):
compression.
Like, is that a problem inneuroscience?
And I was like, Oh man, are youkidding me?
Like, do you know how big thesedata are?
Like, it's insane.
Cat (34:40):
Yeah, we're drowning over here,
Ashley (34:42):
We're drowning! I would just spend hours moving shit
around my lab computers when Iwas, like, a postdoc,
Cat (34:48):
well and it's like these PhD grad students doing their
absolute best to learn softwarestuff also, but you know, not
everybody can be everything.
Ashley (34:56):
There's a ton of opportunity for stuff like that,
whether it's just, like, writinga package for visualization or
it's writing a package to, like,help compress a time series or,
you know, whatever it might be.
Um, there's
Cat (35:08):
And then you get to contribute to science and I
think that would be reallylovely and cool, you know,
imagine you're a softwaredeveloper and hey, you know,
maybe you're not feeling soappreciated in your work.
I know there's a lot that comesalong with that.
deciding you have the time andenergy and bandwidth and
motivation to do open sourcework we we're not going to gloss
(35:28):
over that but it is like abeautiful thing to get to be a
part of.
You know, helping us learn moreabout depression or helping us,
you know, get more of a pictureof the brain.
Ashley (35:39):
there's like an amazing organization, I'm sure many of
you know, called theCarpentries.
They've got a few differentbranches.
They are always looking forinstructors to teach programming
and computing skills to folks inresearch.
You can get certified as aninstructor with them.
You can do stuff virtually or inperson.
Like we need people who canteach these skills to
(36:02):
researchers.
And that's an amazing way forsomeone who, you know, knows how
to program and wants toinfluence the next generation,
wants to get involved.
The friend I had talked to,that's the place he came from
too.
It was like, you know, my job'sokay, but I'm not, I'm not
getting like a ton of meaningout of it at the moment.
And it would be really cool tolike get involved in some
science stuff to just have thatlittle dopamine,
You are a biological creature.
Your mental life rides on thechemicals sloshing around in
your brain.
Cat (00:07):
People have taken that to be like, okay, this picture of
your brain determines everythingthat you can do, but you're
saying the opposite.
Like, hey, we're in dialoguewith this brain.
Ashley (00:16):
You're on a trajectory that is in some part determined
by your genome, but you are alsomodifying that trajectory every
single day through yourexperience.
Cat (00:32):
We got a lot of interest from folks about Ashley being a
neuroscientist and what we canthink about here in this space.
Ashley (00:39):
Ooh, neuroscience.
Cat (00:41):
It's something that I love having in my house.
What does a neuroscientist likeyou do every day?
Ashley (00:48):
I do feel like there's a difference between what people
think neuroscience is and what atypical neuroscientist does in
their day job.
Throughout my training, I wasworking at this level that
people would call systemsneuroscience and systems
neuroscience is about thesequestions about how neurons work
together.
How do they help us behave andmake decisions and see things
(01:10):
and move about the world.
And, um, what that looks like onthe daily is playing with mice,
playing with microscopes,playing with lasers.
Cat (01:21):
All right.
The lasers.
Ashley (01:22):
Playing with genetic engineering techniques to get at
all of these things in reallyprecise ways.
That's one flavor ofneuroscience.
Neuroscience is so manydifferent things depending on
what you're doing.
Cat (01:33):
It's an example maybe of a field that we couldn't have even
had if we hadn't had all theseother, you know, technical and
creative breakthroughs in manydifferent fields.
And they kind of all cometogether to help us study the
brain, right?
Ashley (01:45):
Every time I talk about neuroscience, especially to
trainees.
One of the biggest messages isthat this is a constantly
evolving field, and it's a fieldthat's been catapulted into the
future because of technology,because of our ability to record
lots of things simultaneouslyand take really high resolution
images of the brain and sequenceour genomes.
(02:07):
That's all a part of this aswell.
I obviously care first andforemost about at the end of the
day, these kinds of things beingable to help people, right?
And that's like where a lot ofneuroscientists come from.
It's not the same as being adoctor where you know that every
day when you go in, you're goingto help someone.
I think as a neuroscientist orany kind of scientist, you hope
(02:29):
maybe in five years or 10 yearsor something, it's going to help
someone.
So it's a really different sortof timescale And then a second
piece of it is just the basicunderstanding of how these
things work, because at the endof the day, you don't know when
that knowledge is going to beuseful, right?
And in neuroscience, like wedon't really know, like we're
(02:50):
trying to just understand howthe brain fundamentally works,
both on the order of like singleneurons and then all of those
neurons talking to each otherand across brain regions.
We don't really know how thatworks and we don't know what
we're going to learn or whatwe're going to be able to do
with that information.
Cat (03:09):
Wow, yeah, that's a really beautiful perspective.
I feel like being able to staywhen I hear this as a
psychologist, I think you haveto stay motivated for these like
really long term things, youknow, and you have to kind of
like, care about, you know,it's, it's, it's an intrinsic
motivation, isn't it?
I remember one time I was in thegrocery store and I'm always on
the lookout for something thatsays like neuro on it.
(03:33):
Most especially when it's a formof marketing.
So there's like a, a drink brandthat's named neuro something,
um, and it's supposed to be goodfor your brain.
My favorite one that I everfound was a line of hair care.
No hairstyle products.
It wasn't even like, uh, itwasn't even shampoo.
It was a blow dryer
Ashley (03:51):
yeah, yeah.
It's like neuro blow.
I don't know.
Cat (03:54):
That sounds bad.
I'm pretty sure it wasn't that.
But it was neuro something and,and I sent a picture to Ashley
immediately.
I mean, at light speed, I brokethe sound barrier to text this,
to my neuroscientist wife,because, um, this is so funny to
us.
So what do you think is going onthere?
Hmm.
(04:16):
Hmm.
Ashley (04:19):
cutting edge or cool.
Um, and Like, yeah, like, whyput it on a hair product?
I don't know, like, unlessthat's like seeping into your
brain somehow, people have whatare called field specific
ability beliefs, right, and wehave these, you know, Ideas that
like specific fields are morebrilliant than others.
And so like, you know, a classicexample might be like
(04:41):
mathematicians, right?
We think like mathematicians arebrilliant and versus like, you
know, maybe economics, like weconsider like sort of less
brilliance in that same
Cat (04:50):
Yeah, I think a stronger contrast might be like poetry,
you know, or
Ashley (04:54):
Yeah.
Yeah.
Cat (04:56):
well, you're really creative, but that doesn't
necessarily mean you're cuttingedge or, or, or technological.
Ashley (05:02):
Right.
Right.
But music is actually like areally, a high brilliance field,
which is kind of interesting,like, but not literature.
Cat (05:09):
I remember that.
So what you're talking about is,um, for instance, Cimpian and
Leslie are the researchers whoput out a lot of work on this,
but they've looked at this inspecific fields, like within
chemistry, within physics is oneI remember.
They've also looked at it aroundthe world.
So it kind of emerges globallyand it emerges when you, you ask
people, Hey, what do you thinkit takes to do really great
(05:31):
science in these differentdisciplines?
And one of the things that Ithought was so cool about the
field specific ability beliefsresearch that's been coming out
the last decade or so is itdoesn't always map on to just
STEM or not STEM.
As you pointed out, it'ssometimes it's a little bit more
(05:51):
complicated than that.
So for instance, you're actuallyin biology, where we tend to
sort of think, Oh, okay, if Ihave sort of stereotypes about a
biologist, it's not usually thesame kind of stereotypes as I
have about a chemist.
So our beliefs about differentkinds of STEM fields, different
kinds of technical work are alittle more complicated than
(06:12):
just saying STEM or not STEM,right?
Ashley (06:15):
totally.
And I think it's interesting tocontrast even like neuroscience
with biology.
Even though a huge piece ofneuroscience is biology, people
don't react to the fact thatsomeone is a biologist in the
same way that they react to tothe fact that they're a
neuroscientist, right?
Cat (06:33):
do you experience this?
Do you mind introduce yourselfboth ways?
Something,'cause you're a,you're a neurobiology faculty
member
Ashley (06:39):
Well, it's interesting.
Yeah, totally.
So like my PhD was inneurosciences plural, which is
like a weird thing we dosometimes.
Um, but neurosciences and then,my postdoc was in neuroscience,
but now I'm a neurobiologyfaculty member and I did.
I do feel like there's adifferent vibe when people say
neuroscientists versusneurobiologists you wouldn't put
(07:01):
like neurobiology on a hairproduct to try to sell it.
Cat (07:04):
This made me think about computer science and how we just
get to tack science on certainthings and psychologists
absolutely do this too.
Some psychologists say thepsychological sciences or a
psychological scientist, andthis is a really.
Important helpful thingsometimes because like I go to a
party and I tell people I'm apsychologist.
(07:25):
They immediately say, where'sthe couch?
Let's talk about my childhood,which is fine But then I have to
say I'm I always say I'm lab labpsychology not couch psychology
I'm not a clinician.
So there are all these all thesecomplicated divisions in these
things Different disciplinesthat you might not know from the
outside.
And I think that's one reason welike to use the word science,
(07:47):
because we're trying to tellpeople we do research, you know?
Ashley (07:50):
Yeah, totally.
I've heard you introduceyourself as an experimental
psychologist, like, many times,sometimes when I say
neuroscientist, people thinkneurologist, and like, I've had
people, like, this woman on aplane one time was like, oh,
like, I've had this twitch in myeye for weeks, and I'm like,
okay, cool, like, I don't knowabout that.
Cat (08:08):
I could do some statistics if you gave me a lot of images
across 20 different people.
Ashley (08:13):
We have these beliefs and then it impacts the way we
think about these differentfields, and it impacts the kind
of funding that those fieldsget.
Like, I can't complain thatneuroscience gets all of this,
you know, spotlight andexcitement Because it means like
a lot of research is gettingfunded, like the Brain
Initiative and all of the NIHfunding that goes towards
(08:33):
neuroscience research.
These are important problems forsure, but we just have to
inspect, like, why we're soexcited about neuroscience,
Cat (08:41):
It's so powerful and cool that you are a neuroscientist
and you are someone who, whogoes out there and has people
say, Oh my gosh, you're aneuroscientist.
You know, I will trust youropinion on hair products.
Um, but you're actually still,you know, ready to question this
and ready to say, are we alwaysthrowing our money at the right
thing?
Because we had theseconversations, during the early
(09:01):
days of, like 2020, forinstance, where we were talking
about, are we putting enoughwork into understanding
behavioral science andunderstanding the choices people
are making versus, ourwillingness to say, well, if
something is, looking at cells,then it must be real.
But if it's looking at humanchoices and human behavior, you
know, that's sort of moreintangible and less real.
Yeah,
Ashley (09:26):
married to you and being so familiar with your work has
really made this like supersuper clear to me there's times
when people need answers in theform of cells or neurons or like
brain regions, but then there'stimes when And this is probably
most of the time, honestly, whenpeople actually want a response
(09:47):
in the realm of psychology, likethey want to know how people
behave.
What are the knobs we can turnto like help people feel a
certain way?
What are the ways in whichpeople act given different like
environmental pressures orwhatever it is, right?
Like there are times in which aneuroscience perspective and
that kind of mechanisticunderstanding are necessary, but
then there are times when changeis possible with Without that
(10:11):
kind of understanding.
Cat (10:13):
It doesn't have to be competitive.
like psychologists, can sobenefit from this deep work
that's going on, turning up anddown the luminescence of cells
is something that I can't do.
But I can change the mindset,you know, that someone goes to
work with, and that actuallydoes involve their neurobiology
at some level, we don't have tobe competing with each other.
(10:35):
That's, of course, you know, alesson of our, like, life
together here.
I think it's often reallydisheartening when you have a
really good solution, somethingthat really seems to be helping
in the real world, like helpbuild trust, you know, in
reaching out to doctors andgetting sound information.
And that work comes frompsychology.
(10:56):
But then someone gets on aplatform and sort of says, well,
you know, your serotonin drivesyou to do this.
And people walk away from itfeeling like they don't have any
choice or any agency.
And that's just not accurate tomodern neuroscience.
But I think that's what we takeaway a lot of the time from
hearing about a sort ofmechanistic thing in
(11:16):
neuroscience.
Ashley (11:17):
This is a really good point.
And this is the double edgedsword of biological
reductionism, which is like, youcan tell people, Oh, you get
like a burst of dopamine whenyou get into your flow state
while you're programming orsomething like that.
Right?
Like you can tell people that.
I'm sorry, I did it.
Let me just say as an aside thatwe have limited ways to actually
(11:39):
measure dopamine release inhumans.
So almost everything you've everheard about dopamine is from an
animal model.
So let me just say that.
Cat (11:48):
What, what should, what, what does that mean for people?
Ashley (11:50):
It is true that humans have dopamine and plenty of
people have put people in a petscanner and that's like the, one
of the ways we have to measuredopamine in humans.
And they've seen that particularareas of their brain are like
more active with dopaminespecifically.
It is true that most of theresearch happens in animal
models.
So I do think it's just likegood to know where your
(12:12):
information comes
Cat (12:13):
Yeah.
And what we don't know yet,
Ashley (12:15):
and what we don't know yet and what we can do and what
we can't do.
The main thing I see my role as,as a neuroscience educator is
like for people to be able tosee a study or see a news
release or whatever it is andunderstand What study actually
would have gotten us to thatheadline?
Coming back to this like doubleedged sword of this kind of
reductionism is Okay, like solet's say You know, we do know
(12:40):
that dopamine gets releasedwhile you're like, in this like,
passionate moment ofprogramming.
Does that change the way youbehave?
Does that change the way othersshould treat you?
Does that what does thatactually do for you besides just
a fun little fact about whatyour brain is
Cat (12:55):
Some people to get really real about it have this belief
that.
Some people are doing thisbetter than others.
And they're maybe born that way,right?
there's some people whose brainsare programming brains.
Ashley (13:07):
Mmm.
Cat (13:08):
And they really think that and then they're looking for
kind of biological reasons thatthat might be the case.
And something you and I havetalked about a lot is hey, it's
not so deterministic, like thiscould be a thing that happens
for some people.
And other people might have adifferent sort of thing going
on.
The absolute brilliance of ourcognitive strategies and working
(13:31):
many, many different ways issomething that we need to take
seriously.
And whenever I hear peopletalking about Oh my gosh, I went
to the real science, which islike the serotonin and the
dopamine, you know, and it'schemical.
So it's real.
And that's what's drivingdeveloper productivity.
For instance, you and I areoften having these conversations
(13:52):
where, where I'm like, Hey,babe, like somebody said it was
dopamine.
Ashley (13:56):
Not to be too reductionistic about it, but
like, dopamine is the thing thathelps you feel good, so if you
feel good, it's probablydopamine.
It's, like, not thatinteresting, actually, at the
end of the day.
Cat (14:08):
So we know that, you know, you're not magically going to
get all the problems solved inthe world by giving people
pizza, but people might stillget dopamine when they get
pizza, you know?
Ashley (14:17):
This brings up is like this nightmare scenario, which
you could imagine, which islike, what if we started
interviewing people for oursoftware teams and instead of
actually having them do like abehavioral test or, you know,
what you've sort of proposed,right?
Like, what did you call it lasttime?
You called it like, um, Yeah,What if instead of talking to
people, you just measured, like,let's say you could do this,
(14:40):
which you can't right now, butimagine you could just like put
a little cap on them, be like,let's see how much dopamine gets
released while you'reprogramming.
Cat (14:46):
I'm pretty sure some companies might already be
trying to do this.
Ashley (14:51):
I mean, this is horrific,
Cat (14:52):
put them in a scanner and fMRI.
Ashley (14:55):
We sort of think about these things, That as if they're
like built in like how muchdopamine you release is somehow
like some intrinsic fixed thingabout you Right, which that
assumption and as you pointedout, we have to be more holistic
in the way we evaluate people,for one.
(15:15):
But also, these things change.
And dopamine is literally alearning signal.
This is one of the main thingswe know about dopamine, is that
it changes.
It's indicative of your brainlearning and growing.
And these things also changeover time.
So anything you measure aboutyour brain for the most part, Is
changing and it can change.
And so taking a snapshot of whatsomeone's brain might look like
(15:38):
today is really different thanlike a year from now.
And what it looks like a yearfrom now is entirely dependent
on what you've done in thatyear.
Cat (15:48):
Ooh.
Well, see, I think this is sortof scary and hopeful at the same
time.
Like, what we do changes ourbrain.
And people have taken that tosort of be like, okay, this
picture of your brain determineseverything that you can do, but
you're saying the opposite.
Like, hey, we're in dialoguewith this brain.
(16:09):
We're, we're, we're choosing theways that it's working in some
sense, or the things we getexposed to, at least, you know,
Ashley (16:17):
Yeah, absolutely.
And, and I mean, there is likegenetic determinants of these
things too.
Like, I don't want to say it'slike entirely experience
dependent, but it's both.
You're, you're on a trajectorythat is in some part determined
by your genome, but you are alsomodifying that trajectory every
single day through yourexperience.
Mm.
Cat (16:36):
Wow.
Boom.
So for the people who thinkstick you in a scanner, take a
snapshot of your brain.
That's who you are forever, youknow.
I think that this is a reallypowerful counterexample because
I, you know, I always thinkabout this.
We're always obsessed with thisidea of comparing between people
and finding individualdifferences.
So like in psychology, we talkabout it like group differences
(16:59):
or the differences betweenindividuals, but you know,
between individual differences,the jargon, but there's also
within individual differences isthis huge, amazing, fruitful
realm.
And it's often the stuff thatyou really care about trying to
change.
Like if someone is at level 6,you know, or whatever, you could
(17:20):
help them get to level 8.
You know, they have this rangeavailable to them.
And so the really impactfulquestion in the world is much
more like, can I move people?
You know, within their own rangeavailable to them.
Can I help them meet theirpotential?
And it's not always thequestions about, Oh, if I had a
thousand people for this onesnapshot in time, how would I
stack rank them?
Ashley (17:40):
This is actually some of my favorite use of, like, fMRI,
which you brought up, right?
Functional MRI, you put peoplein a scanner, you measure their
blood flow, not even theirneural activity, but you measure
their blood flow, and it tellsyou something about which areas
of the brain are active.
Um, my favorite use of thatYeah.
Technology is not actually tocompare people to each other,
(18:00):
but longitudinally.
So my earliest work in gradschool, when I got here during
my first research rotation, wastrying to, essentially, predict
whether people that had somereally early stimulant use would
progress onto being stimulantaddicted people.
And the idea was like, could youtake brain scans?
(18:23):
Like, is there something in thebrain that changes over time
differently in the people thatprogress into stimulant
addiction?
And for me, that's a, that's areally useful way to look at
that technology.
Cause as you pointed out, likeit's within an individual and we
can.
take a baseline and then measurethem like every year and see
what happens.
It just, and it gives us thispower to try to understand, is
(18:48):
there anything early on?
That you could measure with anfMRI, which is limited, but has
some power is there anything youcould measure early on that
might tell us who to interveneon more intentionally, you know,
that's starting to use likestimulants in this case?
Cat (19:07):
We are in this place where we just throw stuff at our
brains.
And the stuff that we can throwat our brains is really high
level sometimes like, Hey,here's a medication that just
pulls this huge lever, you know,and that we're on this path to
trying to get more and moretargeted and trying to
understand not just your brainas a static picture, but like
your brain in this moment doingthis one thing.
Ashley (19:30):
Yeah, totally.
Totally.
I think that's super, superimportant to remember.
I'm demonstrating a lot ofskepticism.
About neuroscience, but, thereare.
Many different ways in whichthis understanding of how the
brain works has been absolutelynecessary for things, right?
(19:51):
So, so to give one specificexample, in like the 1960s and
70s, it was hotly debatedwhether schizophrenia was like a
real mental illness, right?
And someone actually literallywrote a book called The Myth of
Mental Illness.
And The idea was like, oh, thesepeople are just kind of making
it up.
Like maybe they're like a littlestrange, but there's nothing
(20:13):
actually going on in theirbrains that's different.
It was just a myth.
Right.
And it wasn't until we hadsomething biologically to point
to that people started beinglike, Oh no, this is a real
thing.
We can actually treatschizophrenia with dopamine
antagonists.
And it turns out.
That that dramatically changesthe symptoms of someone with
(20:33):
schizophrenia.
They stop having hallucinations.
So that's a case in which thiskind of understanding was
necessary and necessary fortreatment, necessary for
societal understanding,
Cat (20:43):
necessary to stop blaming people for what was happening to
them.
Ashley (20:46):
Absolutely.
Yeah, absolutely.
And you see that same thinghappening, um, you know, more
recently with, um, things likedepression and anxiety, right?
We no longer immediately tellpeople, just pick yourself up
off the floor, right?
We have this like, right.
Some of us might, but like, wehave this sort of broader
understanding that some people'sbrains are built a little
different and there is meaningin that.
(21:08):
You are a biological creature.
Your mental life rides on thechemicals sloshing around in
your brain.
Cat (21:17):
think that's really compassionate.
And what we need here is likecompassionate science, and we
need to be able to say, wow,we're thinking about all these
levels and Yeah.
I guess the question I wouldthrow out to you, because I
think it's just constantly onethat people carry around with
them is, what can I do?
I'm riding around on all thischemistry and biology and like,
(21:38):
what can I do for it?
How can I try to take care of mybrain?
Ashley (21:41):
I was buying running shoes like a couple of months
ago and the guy who was helpingme was like super chatty and he
was like, oh cool you're aneuroscientist, like, so what
should I do?
And like what's the one thingyou would tell me?
And I said get some sleep.
Cat (21:53):
Yeah.
Ashley (21:55):
Like we know quite a bit about how sleep is necessary for
your emotional health, for yourphysical well being, for
everything.
Okay, sleep well.
And that's The truth is we'veknown that forever.
Um, we also know that you needto eat well and you need to
exercise like.
(22:16):
These have been tried and testedover human time.
Cat (22:18):
These are the biggest effects on your, biggest effects
on your
Ashley (22:21):
biggest effects on your brain, and it's, these things
aren't trivial, like some peoplehave trouble sleeping and I
don't want to like minimizethat, but if you can prioritize
making space for that andputting attention to it, you
know, that actually could have amuch bigger effect size than
many of these other like flashsolutions that you might sort of
see out there.
Cat (22:42):
so that raises another question, which is how are we
I'll use this word, normalpeople, supposed to evaluate
scientific evidence, like we seea headline come out and it's
like, Oh my gosh, you know, ifyou, you give mice macaroni and
cheese, you know, they all getdementia.
(23:03):
There's all of these, all ofthese headlines about
neuroscience and, and how do youevaluate it as a person in the
world?
How do you teach your studentsabout
Ashley (23:12):
Yeah, this is, this is a tricky one, right?
Cause I don't think we canexpect everybody to become
experts, right?
You're already, you are anexpert in your own field.
You know, the listeners of thispodcast have their own
expertise, right?
I don't want to ask everybody tobecome a neuroscience expert,
but.
I do want people to ask maybelike two or three different
(23:33):
questions.
One of them is what is theevidence for the headline,
right?
And does it come from a mousestudy?
Immediately, if it comes from anon human study, we have to go,
okay, in mice, and there'sactually this I don't know if it
still exists, but there was thisTwitter account for a while that
would republish scientificheadlines, but add in mice, if
it like happened in mice, youknow, it's just a,
Cat (23:56):
And in male mice, mo in male mice, most of the time.
Ashley (23:58):
Totally, in male mice.
And it's, that's not to say wecan't learn things from mouse
models.
Like, we can.
However, it has to be evaluatedand we have to
Cat (24:07):
It's one step in the ladder of evidence.
Ashley (24:10):
totally.
So, like, the first question is,okay, how do we know the thing
this article is claiming?
The second thing that I wouldhave people ask is, you know, is
this just one study?
Or is it a study that's embeddedin like a whole series of
research about this thing,right?
And, because the way science isbuilt and the way understanding
is built and textbooks arewritten, not on a single study.
(24:34):
Nothing ever rests on a singlestudy, right?
And things rest on bodies ofresearch, lots of iteration,
lots of redoing and rethinkingand re evaluating what we've
already done.
And so, you know, the secondquestion is just like, does this
stand alone or is there otherstuff?
And obviously, you're not goingto be able to like do a
(24:55):
literature review on everysingle finding you find, but
hopefully wherever you'refinding that scientific
Evidence, like whether it's likea headline, a news article,
whatever, hopefully thejournalist who wrote that piece
is giving you the context that'snecessary, right, to say like,
okay, this is built up.
It's like one of several studiespointing at, you know, mac and
cheese being a contributor todementia, whatever it
Cat (25:18):
Not only are you a neuroscientist and a teacher,
you know, you also have donescientific journalism.
And the difference, I think,between a piece that's like very
sensationalist, it's kind oflike misinformation anywhere,
right?
You can start to develop yourspidey sense that's like, oh,
this seems a little extreme.
You start to see that things arewritten in such a way to like
(25:39):
scare you or to alarm you or to,you know, to really make an
extreme, to say, don't look anyfurther, just react.
Ashley (25:45):
Yeah, totally.
Cat (25:47):
And the difference between like someone like Ed Yong, who
does this beautiful journalism,that's like very rich and kind
of goes into, this is not justwhat we think we know, but why
we think we know it and how weknow it and what there's left to
know.
And
Ashley (25:59):
I actually spent an entire class period with my
neurobiology class talking aboutthis one article.
Where the headline is, your lifemay flash before your eyes now
we know it, or something likethat, or before you die, sorry,
your life may flash before youreyes when you die, and that's
the headline, and we look at it,it's one paper, it's a wild
(26:22):
paper, because we actually wereable, they actually were able to
record from someone as theydied, while they were recording
from their brain, Right?
So it's like this rare instanceof actually having a recording
during death, and they measureall the changes that happen in
this person's brain before theydie, and they conclude that
there's like this uptick ingamma activity, and therefore
(26:45):
this person relived all of theirmemories.
Okay, so there's this likemajor, major jump in this, which
is like, okay, having gammaactivity in your brain doesn't
mean you're like thinking aboutyour mom and where you went to
high school and like relivingyour marriage or whatever it is,
right?
It just means you had anincrease in gamma activity
Cat (27:02):
what's gamma activity?
Ashley (27:03):
gamma activity is a particular frequency of brain
activity.
So if you were to record fromthe brain, you'd get this, like,
big squiggle over time.
You could take that squiggle ofvoltage over time and break it
down into different sine waves.
Um, and so think about it inlike the frequency domain, in
other words, so rather thandescribing what the signal looks
(27:24):
like over time, we woulddescribe the signal in terms of
what frequencies are containedwithin.
And gamma is one of thosefrequencies, it's high frequency
activity.
And like, if you look online,you'll find a bunch of stuff
about people trying to improvetheir gamma and blah, blah,
blah.
Um, in this particular paper.
They selectively choose this oneexplanation for what Gamma is,
(27:44):
which is that it's memoryretrieval, which is one thing
that Gamma does, but it's notall of the different, um, it's
not everything you'll find whensomeone has Gamma activity.
Like, you have Gamma activity inyour mind right now, for sure.
Most people do when they'reawake and, and attentive.
So the paper makes this big leapabout, like, you reliving your
life, and that's just, that's aleap, right?
(28:05):
And I should say the articlemakes the leap more so than the
paper.
The paper is kind of like, oh,maybe this could be a little bit
of, uh, memory retrieval
Cat (28:13):
We always see this happen as scientists, like the, the
second you speculate onsomething, a journalist takes it
and they're like, This is ity'all, the scientist discovered
this, and then people get reallymad at you when it, you, you,
they say you discoveredsomething, even though maybe you
were just saying, hey, I noticedthis.
Ashley (28:30):
totally.
And you wonder why scientistsare so tight lipped, Right,
Cat (28:33):
Right, scientists are sometimes scared of talking to
the media, for
Ashley (28:37):
totally because of stuff like this.
I think like a savvy reader ofthese things would just like
think twice, right?
Like think twice before yourepost that, like, Little flashy
Instagram thing.
I found out about this articlefrom a student cause it was on
Tik TOK like, oh my God, likewe, you, you see your whole life
before you die.
And then my student was like,wait, is that true?
(28:59):
And I was like, all right, let'stalk about it.
And now we spent a whole class.
Cat (29:02):
No, it's amazing because you get people come into your
class, right?
Because maybe they saw somethingabout the brain on TikTok, you
know, but that those stories arebeing used to sell a lot of
stuff, a lot of different stuff.
And
Ashley (29:15):
Yeah, and that's a pretty innocent one, right?
Like, that's like, okay, it's anice thing to think, like, I
would like to think, like, rightbefore I die, I get to, like,
see our dog and our house and,like, relive all those beautiful
moments.
Like, that's a lovely thought.
That's not hurting anybody,really, to, like, think that
way, but there are examples thatcould be hurtful, right?
And that's the stuff I wouldreally, really be concerned
(29:36):
about.
Cat (29:42):
I saw you give this talk that was like, You can be a
neuroscientist.
Like anyone can be aneuroscientist.
Tell me about this thesis thatyou have about getting more
people involved in neuroscience,including technical people,
maybe out there who haven't everthought about this for
themselves and their skills.
Ashley (30:00):
Neuroscience.
is one of these fields that wethink of as being closely
associated with brilliance,right?
There's, there's often thislike, barrier for people getting
in.
And so it has been a mission ofmine for many years.
And I wrote a book that came outin 2020 that was like, so you
want to be a neuroscientist.
I would go back and retitle thatlike anybody can be a
neuroscientist.
(30:22):
So this has been like aparticular interest of mine
because I see that there's thisbarrier and I really do believe
it.
It's just another field.
where you need to learn thingsand you need to get particular
skills to succeed, um, and Thecool thing is now that most of
this actually doesn't livebehind closed doors.
(30:42):
So the talk I gave that you'rereferring to is for Nerd Night,
which is an event here in SanDiego.
And it's like a drink beer andlisten to scientists sort of
event.
My message was kind of like,look, if you want to look at
neuroscience data, like when yougo home or even on your phone
right now, like you could do itactually, here's a, list of
datasets, you know, you couldjust like, if you know, a little
bit of like, How to wrangle somedata.
(31:02):
Go open it up.
Look at some neurons firing.
You could play with that rightnow because neuroscience is
opening up in like some reallybeautiful ways.
Like different funding agenciesare requiring you share your
data.
We have these like cool new datastandards where like everybody's
fitting their data into thesestandards so we can share them
and try to reuse them.
And this is the stage ofneuroscience and it's cool for
(31:25):
the potential of like citizenneuroscience as well.
Cat (31:28):
What are the needs of neuroscience?
Say you're a programmerlistening to this.
We had a friend who came up toyou and said, I never realized,
I didn't have no idea there werethese big open data sets and you
were describing all this stuffthat I know how to do.
Ashley (31:41):
Yeah.
Our friend came to this nerdnight event and yeah, he was
like, can we get coffee and justtalk about like, what does
neuroscience need from someonewho knows how to code?
I love that question.
One, if you live on the datascience side of things, just
know there's a ton of open datasets and there's also some
pretty good, like documentationabout typical, um, approaches
(32:04):
people would use with that kindof data.
Cause it, it's probablydifferent than.
Other data you might've workedwith as a data scientist.
So be a little bit more timeseries, maybe more images, like
stuff like that, but still it'sin the same kind of wheelhouse.
So that's one thing you couldplay with data,
Cat (32:18):
What are some examples of those data sets?
Ashley (32:21):
Everything from like, um, you know, single recording
of, uh, individual neurons.
So recording the voltage frominside of neurons and maybe like
hundreds of those neuronssimultaneously.
To whole brain recording or likewhen we were talking about fMRI
earlier, you can find lots ofopen fMRI data for basically
anything you might be interestedin.
(32:42):
Let's say you have kind of a petinterest in like Alzheimer's
disease or something, right?
I am willing to bet there issome open access data set.
where there's like patients withAlzheimer's disease and controls
and you could like go in andlike compare, you know, the
brains or something or look atthem over time.
Cat (32:59):
Are there any big names?
Places, websites people shouldgo visit?
Ashley (33:03):
I'm a huge fan of the Allen Institute, which is a big,
uh, research institute inSeattle and they make all of
their data public and it's alsoreally well documented.
Most of that's going to be, Likeon the single cell side of
things and not really diseaseoriented, a little bit more like
basic science.
There's also a couple of dataformats that are really cool.
So there's one called B I D S Iactually don't know if people
(33:25):
say bids, but that's EEG, fMRIor whole brain stuff.
They have a lot of awesomedocumentation and a ton of data
sets are in that format.
There's one that I work reallyclosely with called NeuroData
Without Borders.
Um, so yeah, we'll put them inthe show notes.
I have like a growing list, aspreadsheet of all of these
datasets that exist out there.
So that's like thing number oneyou could do is like play with
(33:48):
data.
If that's your thing.
The other side of it is actuallysoftware development, you know?
So there's this like whole fieldof research software and a lot
of it is open source and peopleare all the time.
Like releasing cool packages fordoing particular things with,
um, data.
Right.
And like, maybe you have to do alittle bit of legwork to
(34:09):
understand what are thechallenges that people are
trying to overcome using thesedifferent software.
But, at the end of the day,like.
Those projects, many of them areopen source.
Many of them could probablybenefit from a lot of the
expertise.
So one thing I ended up talkingabout with our friend was like,
data formats and like datacompression.
And he's like, okay, like myexpertise is on, you know, data
(34:32):
compression.
Like, is that a problem inneuroscience?
And I was like, Oh man, are youkidding me?
Like, do you know how big thesedata are?
Like, it's insane.
Cat (34:40):
Yeah, we're drowning over here,
Ashley (34:42):
We're drowning! I would just spend hours moving shit
around my lab computers when Iwas, like, a postdoc,
Cat (34:48):
well and it's like these PhD grad students doing their
absolute best to learn softwarestuff also, but you know, not
everybody can be everything.
Ashley (34:56):
There's a ton of opportunity for stuff like that,
whether it's just, like, writinga package for visualization or
it's writing a package to, like,help compress a time series or,
you know, whatever it might be.
Um, there's
Cat (35:08):
And then you get to contribute to science and I
think that would be reallylovely and cool, you know,
imagine you're a softwaredeveloper and hey, you know,
maybe you're not feeling soappreciated in your work.
I know there's a lot that comesalong with that.
deciding you have the time andenergy and bandwidth and
motivation to do open sourcework we we're not going to gloss
(35:28):
over that but it is like abeautiful thing to get to be a
part of.
You know, helping us learn moreabout depression or helping us,
you know, get more of a pictureof the brain.
Ashley (35:39):
there's like an amazing organization, I'm sure many of
you know, called theCarpentries.
They've got a few differentbranches.
They are always looking forinstructors to teach programming
and computing skills to folks inresearch.
You can get certified as aninstructor with them.
You can do stuff virtually or inperson.
Like we need people who canteach these skills to
(36:02):
researchers.
And that's an amazing way forsomeone who, you know, knows how
to program and wants toinfluence the next generation,
wants to get involved.
The friend I had talked to,that's the place he came from
too.
It was like, you know, my job'sokay, but I'm not, I'm not
getting like a ton of meaningout of it at the moment.
And it would be really cool tolike get involved in some
science stuff to just have thatlittle dopamine,
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