all right everybody how's it going we're
gonna get going for today
pretty good all right it's nice to see
you you ready how are you doing doing
good do yourself alright are you uh able
to uh feel caught up with the class and
everything yes yes so far I've been
focusing on the lab work like getting
the data out first and then slow like
I'm done with almost like the material
like a lecture component that takes the
most time so I'm caught up with a lab
component I'm just like within like a
day I'll be done to the tee like today
awesome that's great I know you're
working hard to do that and it's good to
see and the lab stuff is really really
the important stuff it's so it's so
novel I feel like there's no over I feel
like bio psych has a lot of like
overlapping material so I've kind of
focused more on like the completely
novel material or stuff that's like
completely brand-new yeah yeah that's a
good path and you know obviously the
class the goal is to have you be able to
do this stuff understanding it's an
important part of being able to do it
but if you can manage the lab stuff
right the execution is that yeah how's
it going for the rest you guys you guys
feel like you're on track from from last
class aside from like the technical
issues that got even worse after I spoke
to you I think it was my laptop I think
because I'm like having to download so
much that for all my classes my laptop
just what's going crazy but I think I
finally got it but yeah beyond that the
videos really helped too okay okay
that's good and we can make more if you
want and something that we've done in
the past maybe you guys are interested
in this is we've had assignments in the
past where students make videos about
how to do dirt how to do
certain steps to analyze the data and
and sometimes that's it's one can be
helpful for you guys because you get to
practice and show what you're doing and
it's also helpful for other students to
see what you're doing and be able to
learn because it's one thing to hear
from me I you know I say one way but
maybe maybe there's another way that you
guys say it or talk about it that helps
another person to connect and understand
with it too so maybe we can think about
that for for later down the road because
that might be helpful too so if you if
you do have issues with the computer
still Vanessa just connect with me after
class and we can work on those
individually and and make sure that
you're squared away okay okay thank you
yeah so if if we were to start today and
start to work through the data again is
everyone has anyone not had a chance to
do get ready at least five people's
worth of data that we talked about as
our goal for today from last couple
classes hey I'm stuck I'm catching up
since I barely fixed the whole software
so it but I'll be able I'll finish today
okay I was in trouble with grabbing my
stats like we have to put them in Excel
yeah if I'm having trouble with a bit
totally we will definitely review the
stats and one thing that I want to kind
of I had this idea kind of preparing for
class today one thing I want to kind of
try out is I want to start try walking
you through it with having one of you
guys share your screen and this way you
guys get some more hands-on stuff
besides just me showing you and telling
you from my screen this way maybe
tishell we can work on that together and
we can have you do it from your screen
share well I kind of talked
through it we can all work together on
that would I be able to do that with you
probably outside of class only because I
use my brother's computer too for MATLAB
because they wouldn't download on my
computer
yeah sure that that's fine um we can do
that out of class but so you're saying
we're not going to get your brother's
computers not set up for for MATLAB or
to do that right now
no he's losing it right now I have
everything on it and everything
oh I see I see I see yeah totally cool
well we can we can do that you and I
absolutely outside of class and we can
have somebody else do that side that's
no trouble at all
yeah thanks for letting me know so
before we get going like I said I like
to experiment to try new ideas like that
which is definitely a new idea for this
class I wanted to ask as well is there
any generic kind of level feedback that
you guys have or want to give I'm sort
of the structure and organization the
class I know this is a different kind of
class stylistically than you're used to
a lot of times people can have a
difficult time adjusting to sort of the
lack of structure but that is that's
actually the intention of the
organization of the class which is that
it's designed to be free-flowing and to
be responsive to wherever you guys are
at which means that it's hard to have a
lot of formality in the structure but my
hope is that we can use that to have a
lot of independent work on your guys's
front but I want to get some feedback
from you guys and see how that's working
if there's things we can do to adjust
that you that you'd like to see more of
or things that we can adjust that you'd
like to see less of and just kind of
kind of open the floor for for feedback
if you guys have any that you want to
offer
I think only thing that took a while to
get accustomed to I think it's look with
everything else's quarter it was just
like the kind of like the self
initiative not just like going to class
and taking the notes it's kind of like
you reading the material or like the
asynchronous stuff like you reading the
material you going over what you need
and kind of like reassessing your
weaknesses what's out like common core
stuff instead of you know who's going to
close taking the notes reviewing the
notes it's more like active learning I
think that's only thing that's taken
adjustment that's only feedback I I can
think of that's really kicking like a
little bit of like active part of
learning and self-assessment without
much direction so it's like you don't
like the I said the other day like you
don't know what you know if you don't
know it kind of a things that you
there's no really like um you don't know
what pieces are missing until you go on
okay what is that it's like go back and
find your own links kind of instead of
like bullet put like going to lecture
and bulletproofing everything and then
going over those bullet points but it's
only like a little bit of adjustment
though we're halfway there so it
happened to it click hey that's great
I'm glad to hear that it's definitely
definitely an adjustment but one that
we're is part of the intentionality of
what we're aiming for so that's good to
hear what about other people you guys
any other perspectives or experiences on
that that might be useful feedback
Midway yeah I feel like um like weekly
to do this would help like like what to
read with what videos to watch Mike I
don't know just some tips like online
it's I feel like oh baby like okay okay
so that's we can we can try to do that
some more that is kind of what that last
part of the syllabus is a guide for two
there's like ten points and you know we
certainly have gone and adjusted among
them but I'll try to do more of that and
we try to do that at the end
the lecture when I try to give those
points in the chat list but maybe I can
try to send more announcements out or do
some more weekly to-do lists
although yeah the other thing to just
keep in mind is - you do want to be
checking in on that playlist for the
YouTube playlist for the course because
after every class I update that with
some some extra supplemental things
that's a great point Melanie and I think
we will definitely add that too little
to the list
any other suggestions or feedback
I have a question professor it's not
necessarily with the question that you
answer that you requested it - the
answer right now but as far as the
subjects have you uploaded them to
Google Drive because I I can't find more
than five and I don't know if I'm
looking in the right area or not that's
a great question let me show you exactly
where I've put them I'm gonna share my
screen here real quick so here we are in
blackboard I clicked the link for the
Google Drive folder at the bottom and
that takes me to this link here for our
class I come in here and I come to our
class and where I uploaded the raw data
was in the folder that's eg data raw and
you're right Mike there's well there's a
handful of subjects here about five or
maybe a little bit more or less if you
see within here I also have this folder
called raw EEG and if you click on that
bad boy you will see that there is a
time a subject data files okay I didn't
look at that thank you
yeah it's all good uhm yeah so they're
there um so we made some discoveries it
turns out over the last couple days I
guess today is Wednesday right all day
okay um yeah that was one of the dad
jokes some of my junior high school
teachers used to say it was that day of
the week all day the whole day so one of
the things we figured out I suppose
Tuesday cuz we had class on Monday and
then a couple students are emailing me
and a couple you guys found out that
there were some funky little parts of
some of these data sets
maybe subjects 65 or 66 in particular
anything come to mind for anyone when I
tried crafting them on the scalp map
everything just showed up green okay
anything else
he was a subject 65 seemed like there
was missing data our electrodes were put
in correctly or something was up with
that so I was uh as far as like looking
at it ft 9 and ft 10 it was just know
that there was almost nothing there so I
was I kind of made my own adjustments I
had to like work with the scale trying
to find the artifacts and strange yeah
well absolutely so anything anybody else
find anything else
you
yeah so some of those electrodes looked
like they were recording really well and
other ones maybe not so much and you had
a scale issue right down a very big
scale and some of them not when you
plotted them so
what did you think about that like what
was your solution did you come up with
any sort of ideas or hypotheses about
what could have been wrong or what's
going on
[Music]
well one of the things that some of
those students had emailed with me about
and they're concerned about that and it
turns out that those subjects those last
two 65 and 66 were subjects which we had
added to the list of our larger data set
and those are subjects that we've
recorded in this class last fall and one
of the things that we did is we did a
little mini experiment within those
subjects and we wanted to show students
kind of the difference between a good
connection electrode and a bad one and
so what we did is we only really use gel
and abrade of the scalp and really kind
of connected with low impedance a few of
the electrodes and not the other ones
and this way that when we looked at the
data afterwards and analyzed it like you
guys were able to do we could actually
see what the difference looked like and
see how important it is to have
electrodes that are really good
connections and to use the gel and to
use the approach to braid the scalp and
to do those other elements and really
get to see the impact of having invested
the work into getting good data versus
bad so so that's some of the reasons
that that data looks so weird
and I think we also probably cut some of
those sessions short and so there's
probably some trial types that might not
exist in that data and so when you try
to plot some of those contrasts you
might see some of those empty topography
maps like you mentioned tasers and so so
that's some of the reasons why that
might be the case and so I included
those subjects in there because I want
to make the class as real as possible
and when you record real data and real
laboratories and real situations
sometimes those things are gonna happen
you're gonna have wacky subjects you're
gonna have weird data collection
sessions sometimes you hope you don't do
everything you can to
that mitigative fight it does happen and
you get a few surprises in there so I
kind of want to keep you guys on your
toes and make sure that you're not just
blindly moving through the data but that
as you move through the data subjects
you're taking a critical eye and you're
saying hey is everything right in the
subject something doesn't seem something
seems off and then start to think about
is this someone who should really be
included in our analysis or might there
be some evidence that there could be
some technical difficulties in there and
the data that was collected and so for
some of those subjects in those
situations the answers would be yes and
usually what we can do are handful of
things you can try to correct some
errors in the data that gets a little
tricky but what we can do is also
exclude those data's so the subjects
from the data so let's say you could
downloaded here what did we say we're
kind of 10 or 20 subjects per person
let's say that you have you have your 20
subjects in your data set you now would
work with a sample of 18 out of those 20
and in your methods section you might
say we excluded two subjects that had
technical problems in recording and
didn't have enough trials for inclusion
and analysis or something like that so
or what you could do is replace it with
a different two subjects that you
download and work with and so so those
are some things that you can do how's it
how's it going if I ask you guys for
some feedback on the actual artifact
detection process are you guys feeling
like that's working or is it troublesome
you guys feel like you have a good
handle on picking out those blanks and
the secod give me some give me some
feedback from the field
I think it's going fine I'm not having
so much trouble with it and I think it's
getting easier for me to detect which
ones should be rejected and such okay
skinned anybody else I felt the same way
like once I went through once actually
just like watching the video it kind of
made it easier to pick out now knowing
about the subject 65 makes sense as to
why that one looked crazy
trying to do that but yeah like it's
actually been kind of like interesting
to go through and be able to feel like
spot them because it'll be going well
for I forgot which subject it was in
England maybe for it there was a point
where it was really good and then like
for a few like pages or so and then all
of a sudden it just like so it was it's
really cool to see how it works okay now
so this sounds good I can I can hear
from a few guys that it seems like it's
working out okay but here's the second
kind of question for you even if you
think it's going okay do you think that
you're being too tight about throwing
out too much data do you think that
you're you're being too stringent and
throwing out anything that can look like
an artifact or are you like now if I got
a pretty good calibration how are you
approaching it where is your sort of
threshold or criterion okay and then
I'll throw something out and then I'll
go back and I was like wait a minute
like compare what is acceptable like
having your own benchmarks I think
consistency is key right keep something
keep it across the board I really don't
know how the data that's how I've been
kind of justifying it in my head so just
what I've been doing is trying to keep
yeah that's a good idea definitely keep
notes keep a benchmark and maybe even
keep a little log of how many trials you
threw out for each subject because you
know that you've how many you start with
about three hundred and twenty some odd
trials and if you find that you maybe
you throw out more than half maybe
that's not a good subject
to keep analyzing or maybe you went to
stuff and maybe you need to reassess so
also about that like if I see something
because you have so many things I see
something too messy I'll just try to
look for a cleaner one is the Zayat
contribute to like sampling error do you
think wearing your like kind of like
cherry like you don't also don't want a
cherry pick you also see something
you're like okay I'm not I'm not gonna
touch that so bad
kinda so that's a great point you raise
and it's a good opportunity to kind of
address that so we do want to be
delicate there we don't want a cherry
pick our data however if we if we're
good it is okay to exclude subjects from
analyses that's okay
especially but but you really you need
to have a scientifically justifiable
reason to do so and those exist and
that's kind of what we've been talking
about a little bit here today and the
past so one way you could do that is to
count how many trials were thrown out
right which it tells you like you can
you see in the little MATLAB GUI how
many trials are there when you start and
then when you throw them out and reject
them it shows you how many are now there
so then you can do that subtraction and
you know how many throughout and then
when you do that you now have a number
that you just essentially that's your
numerator over the divisor the bottom
number that you divide
but so you have your percentage so now
you have a mathematical number and now
you you don't have to be so subjective
you can say we threw out and excluded
anyone who you know lost 50% of their
trials due to noise or do the artifacts
and so now you can it's not so much
cherry-picking in terms of who's
included now you can say we're gonna set
a threshold ahead of time and say
whatever that is and I'm on it I'm gonna
let you guys determine that I don't I
mean you can vary as far as I'm
concerned that's okay for now so if you
think that throat you want to get rid of
anyone who throw out more than 10% of
trials that's fine but then you have to
replace him with another person you have
to go collect another set of data to
replace that with or or you know
download one that we've gotten and
process that again I think personally 10
percents gonna be way too stringent
you're not you're not going to keep
anybody because probably through a lot
of people out so 50% might be a good
number somewhere around there 40 or 60
or you know that's up to you I'm gonna
let you guys experiment with that but
you want to come up with a number and be
able to justify it and then you could
say that's why we excluded them and then
you can replace them with somebody else
from our list out of 60 or so we you
only have to do 20 so it's good to have
that threshold now now I know earlier
Fernando you look like you had yet
something to say about how stringent or
least you know I was gonna say the same
thing that's very you know I kind of had
like the standard as well yeah it's kind
of hard to set right yeah yeah I'm sorry
your video was breaking up I could hear
I said it's kind of hard to set that
threshold sometimes right oh yeah yeah
for sure for sure but anything had that
doubts about I just kind of threw away
which I mean right now it's just the
method I'm using okay that's good that's
good
let's see here
okay so so so that's it's good to know
you do want to keep track of that stuff
keep the log you get you find that you
change how you do it like if you don't
if you come and do them at different
times then maybe some subjects you might
have a tougher I for than others
I think that's where it would happen
with me I think my first one I was kind
of following along with the video and so
it did help like set a threshold but
then in other ones I realized like oh
maybe this isn't as bad because I would
like click on something and then later
on see it even more in a cluster and
realize like I was being a little too
strict so it would made me go back and
like be adjust how I was looking at
everything yeah
oh man I've definitely been there
definitely done that still do it um and
and it's good to second-guess yourself
that in some regards it's it's okay you
want to go back and check things out so
yeah it's funny right because we know
that obviously we're making some
subjective decisions there and our
decisions do change on outside factors
so they've done scientific studies where
they actually assess the sentencing
patterns of judges as they dole out
hearings to dole out sentences to
prisoners and the sentencing severity
will change based upon the time of day
whether it's before lunch or after lunch
cuz your judge is not a robot and you
don't want him to be right because what
if what if you roll the stop sign and
the robots like well you did roll the
stop sign and the fine is $500 don't you
kind of want to be like come on guys
judge you know I was a little bit of a
roll just can you give me some slack and
if it was a robot then it would say nope
I don't know what slack is you broke the
rules that's the definition you owe $500
but you want that variability you want
that difference in decision-making right
it's just that we see that that there's
a downside to that too so we have that
subjective element and if that can
affect judges sentencing for going to
jails and things like that basin if you
had a sandwich or not you know that can
affect how we do our data and our
science too so it's something to think
about as we're going through one way
that you could do this is to is to work
as a team with people to
this is why scientific teams and lab
teams work so well is you could have
other people collaborate with you and
kind of check your work or you know have
some sounding board ideas and I'm here
for that for you too you're also free to
make little groups among yourself to
work on that so so that is something
that I definitely want to encourage you
to do but basically is anybody having
problems doing that artifact rejection
I've heard a lot of good things you guys
are saying hey some people are like I
got a handle on this I got a handle on
that I feel comfortable with it it's
going ok yeah I found some wacky stuff
but we figured our way through it is
anybody have a trouble and it's okay to
say so cuz I mean I have trouble with
this stuff all the time and we figure it
out so I want to make sure that we're
attentive thereto if anybody needs to
talk about more that we can help catch
up
okay so you guys I'll feel like you're
experts in artifact detection you guys
how long so you guys you guys quit how
long does it take you to do a subject
you work through five of them and will
you put about five of those the blocks
of the trials on the screen or you guys
expand it to ten what do you do so
probably put like five on the screen at
the moment since it's like the defaults
I'm like that way I can at least know
what I'm scrolling through does that
make sense
yeah I would do five unless you have a
special widescreen monitor like if your
have like a monitor for gaming or
something else where it's actually
physically wider to accommodate
expanding to like ten I would keep it
five experts like I am used to cramming
everything like doing like prolonged
hours you know and it's something that I
have to only do like two to three hours
because then I'm afraid like fatigue or
whatever I won't be able to assess it
the same way so this is like one of the
things that I cannot I just can't cram
it I have to break it after work every
day I can't just like okay today I'm
gonna do and like I'm today I'm gonna do
an entire person like I can't I it's one
of the things an acquired taste yeah
like I try to fire a shot at nine three
four and then I just break it up I just
had a timer you know and I just commit
to that time and then whatever I get
done I get done totally that's a really
good thing to think about too is
maintaining that kind of structure
discipline of time on inside time off so
any of you guys have done sports or
played musical instruments or even learn
languages I think it's really helpful to
keep that model in mind of like practice
so you're gonna practice for maybe two
hours or three hours one hour but you
have that block and then you take that
then when you're done you're done and
you come back and you might do second
practices new in the afternoon but very
rarely will you go to like
you know a soccer team and see that they
practice from 9:00 in the morning until
5:00 at night not gonna happen
they're gonna go for maybe an hour to go
hard go home get some rest get some fuel
get some nutrition get some rehab and
then maybe come back and do a second
workout later on but they're gonna space
that out and that spacing can be really
helpful so that you avoid that sort of
fatigue effect that can come down on the
back end of that slope just like those
judges need to avoid in that regard um
you know that's one of the things that
they go we learned right is to kind of
have that self-awareness of like where's
my danger zone of falling off that cliff
and as long as you kind of keep that in
mind then you kind of know to avoid
those areas where you might get fatigued
so it's a good thing they're also a good
thing that you can work together with it
as a team of other study groups and
things like that too so so then I want
to show some stuff about we're talking
about artifact rejection so why don't I
show a couple little things here towards
that end and let's take a look I'm gonna
share my screen I'm gonna show show you
guys some tricks here and what this is
gonna do so by the way um can we go
around the table here maybe first and
let me know where you're at and you
serves or your sample size how many
subjects have you done your artifact
rejection for or your ERP averages for I
know some people have done more some
people have done less just give me a
ballpark where I can get some feedback
from you guys and I know where you're at
so far I've done the five saying I've
got five right now okay
I also have the five I didn't know
there's more in that folder okay
I'm a little bit fast live I'm like
almost gonna complete almost like at
7:00 almost them okay they're kind of
like I have to go back as I think I've
been like kind of cherry-picking a
little bit and it's like those sixties
ones that were messy I was like no
absolutely not but I think I have to go
back and like how you said count them um
I have like like a ratio of exclusion
like a threshold I'm start measuring
that but I usually I kind of have a
little more done by also it's like the
messy ones okay who else will get a
couple people missing
you
I only have the two that we did the
first time okay I was at like six and
hopefully I'll still clouds him once I
fix everything but yeah I got up there
and I was doing I like felt confident
with how it was going so okay terrific
I have six two as well I feel like I
gotta I'm just trying to figure out how
the art effects work but I feel like I
got it for some reason okay is that
Edwin yeah okay I just see it as is
because my computer is it's it's weird
right now so like um I still don't be
able to and weirdness is okay right
why your freak flag is what they say
weird is okay you just want don't want
the computers to be crazy so alright so
everybody's got some some subjects down
you guys feel comfortable one last thing
for you Edwin
when you said that you hair having some
trouble or confusion with the artifacts
what exactly were you referring to like
you know how or you know how the lines
are stuff like in other lines like we're
supposed to reject all the other ones
that here the other ones right like
there's a mistake or something's going
on around right there correct we can it
depends on if just I'm hitting the other
ones isn't necessarily always a bad
thing
but we definitely want the ones that are
rising that big steep rise and following
the blinks also like that means if it's
just a little bit it could still be fine
yeah but it depends that's the tough
part right you got it that's where you
the knowledge comes in you got to know
that you got to be over there that's
where you know we talked about what the
artifacts are we had those other
lectures posted on our playlist doing
more in-depth discussion of the
artifacts and then of course those
artifacts are discussed and a steve.luck
chapter that we had online in the pinyin
to
these artifacts are really important
because of what we talked about that you
don't want to say that your results are
actually the result of someone blinking
you want to be able to know for sure
confidently that your results that you
report are actually reflecting brain
activity differences not essentially
blinks or eye activity and so it's it's
a really important part to get right
which is why we spend a lot of time on
it because it can really change how your
results play out cool thumbs yeah and
that's why it's so difficult because
like you said sometimes it's hard to get
this he spent a lot of time talking
about the subjective nature of these
decisions so now that you guys have a
little bit of experience working with by
hand with these I want to show you some
new things about how you can have some
help
how many guys would like would like some
help in your artifact detection me yeah
a little up too okay all right all right
all right so then get your pencils handy
start taking some notes I'm gonna show
you some new things all right
all right i'ma share my screen and we're
gonna dive in where's my okay I'm
sharing my screen let's come into our
lap and as we're in MATLAB I'm in my
folder for our groups I've set my path
let's say that I bring up EEG lab so I
type that in we see the little marker on
the bottom left saying busy this is all
good and it'll come up so what I'm gonna
do is let's see here I'm gonna start and
you know what I'll do I'll start from
this like Drake from the bottom and we
will I'm gonna just show you from the
front straight beginning import data I'm
going to import one of our subjects say
good ol number two
[Music]
so as this is working something I talked
with a cup you guys offline about today
is that when we're done analyzing the
data for some of your subjects you can
end up deleting the raw files that are
big in size to save up some space on
your computer now you don't want to do
that just yet because you're not done
with it yet because you're gonna see
today we're gonna add some new stuff so
you might still need some of those raw
files but you don't have to say download
20 all at the same time you can do it
one at a time download subject to
process subject to into an herb then you
don't need subject two's raw files you
can delete those then download subject
threes that's one way to keep your
memory space a lot better so I'm just
gonna call that subject to we name it
you guys are all familiar with this
process the next thing we did was to
rear efference it and we did that to the
average of our masters was just TP 9 +
TP 10 okay okay then we did our
filtering operations so do filters for
EEG we're gonna ply our point 1 Hertz
high-pass filter which allows everything
above that super low frequency of not 1
Hertz point 1
it's like one tenth of one Hertz
anything above that and higher frequency
is gonna be allowed to pass through
because it's higher than point one and
that's basically gonna again serve as a
linear D trend to our data which means
that it tooks that big long kind of
diagonal line shape out of it and kind
of makes our eg go um flat Proctor which
is good
it's where those skin potentials drift
things of that nature
okay so that will come up here in a
second we'll hit OK again because we're
not saving it just yet we're just
keeping it in that named sort of work
memory spaces system as its populates
all these new data sets
now we're gonna down sample it to 256
Hertz which is gonna mean that we're
making smaller the file size so it saves
you more space on your computer once
it's all done now that space is not
going to go become available for your
computer until you delete those existing
RAW files after you're done with the
subject so here we are we've resampled
oh let's do our channel so where's our
channel locations okay and again they've
preset things nicely so we hit OK again
and then we apply our events list this
list it continue we create right Lister
function so first remember what these
processes do which by the way I think we
have a test next Wednesday of my
syllabus reading is correct and so on
the test we often ask you to explain
what these steps are doing and so when
we created our events list it created a
list of all the kinds of events that we
have and now that we're doing our bin
list now it creates a list of all the
kind of bins which are the categories
that we can place those events into so
in order to preset our file therefore
our bin list or so lucky for us we just
hit OK
let that work and it's kind of thinking
they're so work there for a little while
and so this is where we're all familiar
with you guys have all done this on your
own you guys all just told me that
you're feeling pretty good about these
steps so what I wanted to share with you
with today's the step we do next is what
stuff do we do after we've oh we have
picked the data okay I'll do that
afterwards what do we do after we have
picked the data look for artifacts
exactamundo yes good job pronoun you
look for artifacts and we don't just
look for them we reject them and that's
what we talked about getting some help
form so I'm gonna show you some ways
that we can use an automatic algorithm
built into our system to help identify
those artifacts now it's not perfect and
the only reason that it works well is
because it allows us to interact with it
and allows us to override it if we need
to and that's the reason why I didn't
show it to you at first is because
before we go to the digital age
you have to know how to do it by hand
you have to have the conceptual
knowledge in your mind but before you
allow the machine to operate so we need
to know that you can work with the data
in identifying the artifacts but now
that we know that you feel comfortable
that you are able to do that a little
bit we're gonna take that next step and
allow allow that to happen by getting
some help so now I'm going to go to my
append a step --ax I like that setting
of about negative 212 under baseline
correction no no we run
and you hit okay okay so now we've got
our bin epics now what we're gonna do
here is we can do an automatic artifact
detection so look what I'm coming out
here so I'm in the menu for herb lab and
I drop down to artifact detection in
epic data okay so it has to be data that
you already epic and once we're here
let's take a look if you want to
identify blinks let's look at our blinks
alpha version okay so let's just hit
that and it's gonna ask us some
questions some parameters we need to put
in for us right now we're basically
gonna keep these the same presets for
the number channels this is basically
our window and this is the length of
time about 400 milliseconds so it's
gonna look to detect blanks okay I'm
just gonna keep it the same you just hit
accept okay
and what that's gonna do is it's going
to run through the data and it's gonna
identify anything that meets the
definition that criteria so we that's
exactly why we talked about this idea of
a criteria so it's kind of leading you
guys a little bit today and look what
happens it pops up our data just for
this point right now let's just hit OK
so now we have all these data sets right
of everything we've done an AR means
artifact reject so that's where we're at
in our data set and if we maximize this
here we can see that it automatically
identified a trial to reject and what's
really cool about it especially on the
help side so what's helpful is that it
automatically detected it but it also
shows you why it shows you in red the
trace of the bad apple in the bunch and
you can scroll through and see what else
it identifies oh there's one there too
let's see what else we got there's some
more so you see how it shows that that
red line shows basically the violating
elektra that through the channel out
what do you think about that that's real
cool on a professor could you change it
to 75 so I can see a little more a
little more clear absolutely there you
go
cool I feel pretty nifty huh now look at
this though it missed this blink coming
in here see it this pre-stimulus period
is important see how this one down here
where my mouse is at the bottom left on
trial 42 by FB - it missed that it did
not define it get it as a blink because
it's it's just a machine
it's just now girly it only does what we
the parameters and it slid just
underneath the threshold so that goes
back to that lecture that slide that we
talked about when we talked about
artifact projections that criteria and
steve.luck showed those a couple
different ways that you can actually
miss stuff right and so now you might
want to click on it and add that
yourself so but the point is is you get
help here you have help now here's the
thing it also did not reject this
wouldn't you want to reject this one in
46
so let's X out of here
what I'm gonna do is I did not save that
but this is the data set that we're
operating from let's do a let's add a
few more to it let's do our step like
artifacts isn't that kind of like our
saccade boom let's hit that and again
for simplicity sake for the class we're
just gonna keep our presets anything
have a step where it's like a flat then
up then over kind of like a Sakata at a
threshold of about 100 mu goals let's
give that a shot and now we accept and a
different kind of algorithm we'll run
and look in the data and so we'll do
this process a couple times and by doing
this process we'll use and apply
different kinds of algorithms that will
find different kinds of artifacts
because that's what you're trying to do
you're trying to
find different kinds of artifacts EMG
saccade blanks what have you again we
hit okay now I'm not saving anything yet
okay well if I move this 75 again we
could start to see if other things are
detected oh there's a saccade see that
one there this was not numbered file to
a trial twenty was not thrown out before
but now we've got the secod based upon
that detection pretty cool huh
and it gets the blinks because it's it's
preserved from our earlier running of
the process and like we saw before or 42
is not yet detected in it nor is 46 but
we're adding our detection so now
there's artifact rejection that we did
earlier now there's two rounds of it AR
and AR who says that anybody know
nobody wants to give a guess on who says
this I'll tell you
pirates I know it's just billowing
laughter behind all the muted
microphones right but let's try doing
the other part effect detection so
before we do that I'll break it out and
drop another joke for you um speaking of
pirates you guys see the Johnny Depp is
coming out with a new Pirates of the
Caribbean what's gonna be like number
seven or something did anybody see that
coming up no how old is you know 16 yeah
right crazy and it's not you most people
aren't even gonna be able to watch it
like the it's not gonna be PG or ever
yeah you guys know it they're they're
gonna have it be rated yeah okay so
spice aisle class a little bit let's try
to see if we can apply another artifact
detection right so let's try our simple
voltage threshold okay so this is
basically saying anytime a line of eg
exceeds our voltage threshold here of a
hundred millivolts for mutant evil it's
really that's a little mutant not a
Milla then on any of the channels then
flag that as an artifact and we're just
gonna use that preset and any time it
goes above or below 100 accepted
just like before it'll think and then
it'll ask us if we want to save it oh
okay looks bad let's open this bad boy
up and take a look oh okay
so threshold here 275
okay so let's scroll through here and
see if it detected anything else so we
know they've got the secod there at
least the cons so far so good
okay the cards and blanks so this one
over here 35 that wasn't detected before
that's kind of interesting see how it
there huge bump there that exceeded that
100 Newell threshold who said 37 this
one here is now identified ooh
42 isn't this the one that we said was
not detected before it is now detected
due to that threshold
I wonder there it is
another thing a beauty goes
yes yes it is a thing of beauty because
that saves you some time of having to
detect these but what we want to do is
still run through it we just get this
help and the red line tells us why and
so you get to see these artifacts all
better it's very educational that's a
good thing so what do we do now you run
through it and you still want to cruise
through that because there might be
stuff that you see to throw out that it
didn't detect and somehow it might have
detected something that you think is
okay to keep it there is not common but
just in case you do want to run through
your data so as we come through all of
our data we get to see it and the
reasons why the trials are rejected why
oh isn't this nifty isn't this really
cool yes thank you you know I get a
little nerdy about this but I think this
is a really cool and it really is a
great help scientifically gives us that
objective criteria to rejecting
artifacts rather than just our
subjectiveness that's partially
determined by if we ate a sandwich for
lunch yeah and these red lines
highlighting why is a really educational
tool to help you like create that
benchmark
I feel like mmhmm yeah it's really
really cool so I'm just moving through
here quickly for times sake but you can
see you know kind of what the effect are
is of being able to do these three
analyses so we did volt simple voltage
peak to peak we also did the step like
artifacts and we did the blink algorithm
automatically algorithm so those are
three ones that you can take to the bank
right now and start using on your data
and so when you're doing I'm gonna show
you how we do this
[Music]
it's cruising through here hey you're
gonna want to do this to all your
subjects oh you consider the five that
you've done up till now practice that's
what he learned on but you don't want to
do fifteen other subjects using a
different procedure than the eyeball
procedure you did for the first five the
point is is scientifically you want to
be consistent you want to be able to say
in your methods section that we use the
same analysis for every one and so you
don't have to use these algorithms by
the way you can do all the other 15
subjects by hand and eyeball if you want
that's perfectly fine they just need to
be done the same way as the dye the way
you did the first five or what I
recommend is essentially starting over
and doing this to those five subjects
data so that you can rest more
confidently that you had the help from
the algorithm to make sure you rejected
the right trials and kept in the right
trials as well does that make sense yes
so we're almost done here I'm 356 and
that's the end here's what you do
just like before now you hit update
marks and they'll prompt us to save I
think they've been noted to actually
reject these we now hit okay and go to
reject data epochs and marked epochs so
here we're gonna go to plot we're gonna
go to that said project
[Music]
I'm not gonna do components we're gonna
do that we're gonna go to plot channel
data scroll and as we scroll here now
those trials are all still identified
and we're gonna hit reject it's gonna
ask us if we want to really reject him
and again we say yes
and look it tells us 90 look at red
under the blue here 94 out of 360 trials
are rejected so right off the bat that
gives you your number to put in your
little log book that you're saving your
notes to say how many were rejected so
you know proportionally if it was 50% or
not or 60% of the originated trials and
that's good so what we're gonna do is
we're now we're gonna save this and so
let's say copy that name we check this
box to save it as we paste it in the
name and this is really good to keep
because now we know the subject numbers
too we know that's been filtered
resample there's been an events list
there's been a bin Lister they've been
bin epic to be e stands for bin epic and
now the three ARS
that's really helpful too because we
know what procedures of algorithms have
been done we know that all three of
those have been done as opposed to two
or one or five so that way we know that
all the subjects have had the same
things done to them later on in case you
ever need to verify that let's just
browse to make sure we put it in the
right area of our data and I like to put
it in pre-processed here and I'll save
it with that name
now it's saved now you see that I had
some of those other files in my folder
so let's make sure I go check that out
again okay so here's that folder we were
in pre-processed I had a lot of stuff in
here and now this is what I was saying
we can go ahead and start deleting so I
don't need these anymore because these
this is my new current active file that
I know is good because we did this 3/8
artifact rejections for the subject we
can also clean up a little bit the raw
data folder if I need to I don't need
the one that says practice there are
these so I can delete these and what I
can do is I can now delete that raw file
it's clear up the space ok now one thing
to note for you guys to okay is that
it's not really deleted a little
reminder until you empty your recycling
bin so make sure you come to your
recycling bin and click empty recycling
bin and now that'll make sure that your
computer's memory space is kind of
protected a little bit and it's not
holding all this extra stuff in its
memory professor yes could you cover
what the three AR rejection ones that
you used I know it was blank rejection
but I can't remember the other
absolutely I will do that right now I'll
show it to you again
so what we're gonna do is you come to
ERP lab you come to artifact detection
in epic data and you can start with the
first one you can do a simple voltage
threshold then you do it again and I
jump down to blink rejection alpha
version and then you could do it a third
time and do what's called step like
artifacts so the simple voltage
threshold that's going to capture a lot
of your EMG and craziness your blink is
gonna capture the blinks and stiff legs
gonna capture your sakata's those are
your three big ones you don't need to do
these other ones unless you really want
to experiment in there but it's not so
necessary
so so that's where we are we've got
these here and that's our data set and
don't forget the next thing we want to
do is then we want to create computer
average ER Peas and now I'm gonna come
in here I'm gonna average that just say
yes continue without and I'm gonna call
it to subject subject to and I might say
updating click the same make sure I
browse to put it in the folder that is
for ERP data boom so get to updated ok
all right let's save it there now you
can see I've already saved a bunch of
other subjects I've got a bunch of in in
here ok so I got that in there I hit ok
so just kind of this is kind of a review
now reminding you guys what our steps
are for ERP processing and now we're
going to come and take that herb set
that we've created something to updated
and I'm gonna do our ERP operations to
do a bit operations on there just gonna
add all these extra bins we're gonna
modify it and hit run because it's
preset that'll think for a moment and
then we'll save it and now that'll add
this subject to the existing group of
files that we did as that's thinking
what are you thinking about this process
no pop I think that definitely artifact
detection really helps out yeah it's
gonna make your life easier and as you
can imagine though right it's really
important that you know how to do it by
hand first which is why we went there to
start with
so we're almost done here with in
operations and now I'm going to save my
upset ass and I'm gonna come to your PE
data and I'm gonna add a name there to
make it consistent with the other ones
so it's underscore Ben 971 that's how
far we went up to in the bins okay so
remember what we do next now is create
an average erp a grand average that is
the way that we're gonna do that has
come to average across your psets and
when we do that let's clear all these
earpieces lovely doctor wife over there
and just come in to say hello to the
dogs
oh sorry actually I thought you guys saw
my video behind me after that screen
share knowledge ease for that they're
coming in for lunch so we're gonna add
our herb set
let's grab that I'm gonna go to our
three RP data and I'm gonna grab all of
these ones that essentially updated to
bin 91 because you can't average herb
sets unless they all do share that same
number of bins so we got that and again
he just basically say run
I might ask us to save the list sure
we'll save it we'll call it as a group
I'll just put today's date April 29 so
now we have our grand average Oh we'd
had different numbers of bins and I
suspect it's because that last one I did
is maybe a little different than the
ones I had existing so let's do that
again I'll just adjust that a little bit
and what I'll do
is my subject - I'm just gonna remove
that one there and I'll run that again
because I think I've always had it
slightly different so again we're
creating that grand average now for the
group and what we'll do next is kind of
what I think Mike you had asked earlier
in the class to focus on how do we
focusing on how we drew this statistics
out and made some of the figures so we
named our herb set our grand average
just cause grant group and I think we
had a sample of ten I'm gonna save that
same name I wanna browse to make sure I
put it in our data groups
hit ok so let's say that your hypothesis
was about I don't know somebody give me
a hypothesis a good chance to practice
we need to make some figures what figure
should I look for what conditions do you
guys want to compare
[Music]
um the dunning-kruger effect good
question let's take a look at that now
um so let's plot some ear piece what
would we look at to see the
dunning-kruger effect
shouldn't it be an option under bins
that says like DK one through I believe
ten uh sort of we don't have ten if it
might be one through five or something
so we could look at the dunning-kruger
effect compared to say correct
rejections that is look at all the
dunning-kruger judgments versus correct
rejections or we could just look at see
how the dunning-kruger effect might
differ between all memory judgments um
what do you think is your idea what do
you think is gonna be a good one here um
could we do one with all the correct
rejections okay so this we need to find
each of these ear peas dunning-kruger
one two three four five let's see where
we can find that that looks bin 933 and
i'm gonna hold the ctrl key down i also
need to select correct rejections means
i need to come up here and find the
condition for correct rejection so there
it is 855 and I select both of those in
my head okay so that tells us there are
two bins
um let's keep our life simple for now
and stick with this idea of setting our
hypotheses what electrode would you
expect to maybe show a difference here
this way we don't plot all channels
let's pick our electrode which one do
you want to fall think that these would
be a core area to to differ between for
Diane Kruger
just thrown out there how about a guess
eptein 959 yes frontotemporal okay
I'm not sure I'm gonna veto ft and I'm
gonna say why it's a good good
suggestion especially since I said to
just guess do anything but that frontal
temporal one is basically your temple
and it tends to have a lot of EMG noise
but it's also really hard to really get
rid of the ocular activity from there so
let's move inland a little bit little
smaller a little bit from how about pick
any electrode that's not on the edge of
the scalp so something in the parietal
region um I don't know exactly where but
Idol cryo so let's start super simple
mid parietal let's do PZ right that
isn't that midline parietal this okay
and the other thing we want to do is
show that standard error and we saw last
time that the transparency is good at a
bad point
so let's snag that sucker and yeah let's
apply
okay there it is now let's click on it
to get a closer look trying to click on
it okay a couple times there okay so now
we can kind of work with this pretty
cool look at that huge difference so
here you know what I'm gonna do I'm even
gonna plot it again real quick and I'm
gonna get rid of these clunky well let's
use this to show something else let's
get rid of these clunky terms have been
855 who cares about the bid now right
let's say that what we can do is come in
here and actually edit it which is cool
and can actually get rid of all of this
SEM stands for standard error of the
mean that just kind of shows the
variance there and you don't actually
see now DK one two three four five
that's also kind of funky let's rename
that to let's say correct rejections
let's make sure it a little space in
there too okay so what we can do is
let's adjust our image and if you click
this little panel it's gonna give us
options to actually adjust our our image
should it's thinking right now because
it's our properties
farmer computers a little slow he rises
like that too
okay so it gives us all the stuff we can
change I know this looks funky but like
just take it slow and stay here and we
can see this says font size are you know
all the different information we have so
let's say our X label let's grab these
guys so if you click on that x-axis says
our font size is 8 but that's super tiny
what we made it 18 okay look at that
down there didn't that look nice now
what else we got let's take our y-axis
we double click that and let's make our
y-axis also 18 so I'm over here at font
size and as long as you click out of it
isn't that nicer let's see what else we
got here
PZ this tells us our site we got to make
that definitely bigger than 18 so let's
make that giant let's make that 28 boom
okay and then let's do the same thing
for our legend up here okay font
it's not gonna be twelve point six let's
make that also let's make that twenty
okay and then we can do that for our
correct ejections as well
set that properly there we go
I'm trying to make sure that um that
over here a little bit I'll get rid of
these lines here what are you guys
thinking about this as you're watching
it looking nicer
yeah looks uh cleaner and like more
concise like you know it helps you like
know what you're looking at you know
yeah and you might even be able to you
know you can move this stuff to wherever
you know you might have put these on the
bottom
maybe we can so basically the point is
you can make all this stuff change it's
all flexible however you just gotta find
the right place and the right setting
there's a kajillion of them and
sometimes they get a little funky
confusing as you see here I'm struggling
to try to get rid of these little lines
or we don't need all four we just need
one and trying to figure that out but
that's one way we can do it and that's
one way you make a really nice I'm gonna
call like a publication quality figure
okay you might want to put it around in
a place or maybe right now it's just
kind of a weird spot but I get free of
this
it's actually a panel that's up embedded
within it that's what you would do and
you could look at all these different
features and eventually we'd find it I
just can't seem to snag it off the top
here anyways I think this is good for
now we figure out the details and later
um and then what you can do is let's
actually take this what I should
actually do is change the I should I
maybe make that a little smaller in this
particular case let's take our text 1720
let's make it 16 well for now let's see
if we can do that and what we can do is
take this and I say file save as and you
might go to figure make a new folder six
figures up and we'll save this not as a
MATLAB figure but we can save it in a
couple different ways because start as
simple as a jpg for now I'll call this
group sample of ten and in Kruger vs.
correct rejections at PZ
you always want to clue that information
so you know what is being measured and
now you go to our folder our figures
flood folder we'll see that this is here
and you can even open up say I'll click
on that and it'll open up as a figure my
computer's a little slow but you'll see
it come up
there it is edit you all sorts of things
nothing can you just open it even more
simply something like open with painting
for example see not just a little bit
okay
we can start to shape the figure a
little bit more get rid of all the extra
whitespace you can have our legend that
we were having trouble with um let's
actually put that up there for now but
what you do is for example a little
closer save some space you grab here you
can make a little line there it's like
that guy for example there now I'm just
kind of doing this kind of janky you you
wouldn't need to do that you would just
draw your own line essentially you show
red lines and black line and then you
could kind of take this stuff here now
that's a little closer together and you
can put that down there a little bit
tighter and it looks a little bit
cleaner if you need to and you'd get rid
of these two and so you can see that
paint is one way that's kind of useful
to doing that right but it's a little
tougher to just paint as a clunky system
but if we were back at our figure you
could also save it as what's called a
file type called dot eps
you save it as that then when you come
to your folder here and you get your EPS
file you could right-click and you can
open it with a Photoshop and see more
apps let's get it I like illustrator but
let's see here so illustrator is a
really nifty program let me show you how
we can make some really nice
high-quality figures from there but it
takes a little bit of time to open so
we'll let that kind of think in the
background
in the meantime who can tell me when you
might want to look for a time that these
effects are different so right so this
is a very nice pretty picture but your
jobs that are also going to be to show a
topography map and it's also going to be
to extract statistics so what somebody
besides daisies she's done a great job
today contributing come up with our
hypothesis what time window does this
figure suggest we should look for or
hypothesis from before looking at the
figure either way when should we plot a
topography map and when should we
extract our statistics to compare if the
red line is different than the blue line
the difference
do we want to catch it before 200 I know
it's up to like ripe shows are we doing
I don't I think they're the greater
difference are from 400 to a thousand
right that's like the greatest
difference that are we also whining -
Krabbe sure the what we were overseeing
before that I don't I just I know I see
that they're different I just don't know
what I'm looking
as far as like units if that makes sense
so the units are milliseconds so that's
like 400 milliseconds 600 milliseconds
800 milliseconds and when we go to get
our stats matlab's gonna ask us to say
hey sweet I'd be happy to get you some
stats for each of these conditions
between what time do you want me to give
you the average amplitude and you need
to come up with an answer right like
that is together we need to figure this
out
and same thing for the topography map
thing we're gonna say hey plot a Mapple
this difference between the red and
black line and it's gonna say great well
during what time do you want to see the
differences cuz look look at look at
like here right at 200 milliseconds the
red is exactly on top of the black
there's not gonna be any differences but
here the red is hugely different than
the black so you're gonna have a much
bigger difference so when should we plan
in milliseconds
I'm telling that lab to give us both
statistics hook extracted and topography
maps plotted put above between 400 and
600 that's a great idea let's do that
for six so let's keep that in mind
looks like our figures up in illustrator
so let me just show you that a little
bit freer too since we're here so this
is illustrator what I like to do is some
basic formatting a right-click on the
highlight and the first thing I do is
ungroup it so that I can sort of
distinguish the different features and I
will essentially right click again we
will
[Music]
let's see release clipping mask is the
first thing we want to do so the
clipping mask there this is change sound
playing some games here trying to figure
that why I say that is partly I don't
know why it actually did that but looks
like we do probably want to do it back
to the other piece but what this will
allow us to do is to start start doing
some editing on it never actually seen
this before we respectively like anyways
we'll come back to this once we figure
out some more of those details few
things like cropping it in here to kind
of just select the spot that we want so
you know different things like that we
can do um but let's come back to
answering that other core question so
let's say we're now not alive and we
need to plot our topography maps so we
know that our bins need to be the same
ones from before but now it needs to be
a bin that subtracts those which means
we need in 9:51 to subtract all done in
Kruger judgements one through five or
that is actually subtract the current
rejections from there so now we just
click that one so it's just mid nineteen
fifty one we want to select average
amplitude between our two
Slayton C's Mike when was this Layton
sees you tell me to put in here what
what what time is a time window did we
say we were gonna grab exactly so I
typed that in there with a space between
and we want to display our color scale
and hit block all right nice beautiful
typography map and this is a topography
map so if any guys go hiking like in the
San Bernardino Mountains or anywhere
else
maybe you've looked at some maps that
are called topography maps or relief
maps and you know that these these lines
these concentric lines as they get
closer and closer and smaller and
smaller it means that the mountains
getting taller and steeper the same
thing is true here this is basically
representing a peak that's shown in the
map this is the difference between those
dunning-kruger and correct ejections and
the red shows the biggest number a
difference so we're right in the middle
there and this is the big peak in the
head so the central parietal peak from
four to six hundred milliseconds and
what we can do is actually we can even
adjust part of this map the way that we
talked about doing that
earlier so let's grab our property
inspector I'm going to take our font
size let's make that 20 and then here we
can actually take grab bigger and that's
good so and we can say save this as sync
this as a JPEG like yeah do our figures
let's name this to this is our group
saying and it's 10 and this is
dunning-kruger vs. correct rejections
from 400 to 600 silence don't you see
okay and as you'll see later on we can
pick up stuff like a Power Point that'll
help us to make some pretty nifty little
fingers okay so now the thing is how do
you know that this big red part
represents something statistically
significant right because that big red
part is the difference between these two
lines during these two times how do we
know if these are statistically
significant well we got to run a test
right so we got to use a t-test to see
is the red line significantly bigger
than the black line during this
particular time and if it is
presentation here if it is we're gonna
want to know that we'll start making our
figures here okay I'll come back to the
stats in just a second I want to show
you kind of what we got going on here
how to make some simple figures so here
we are in PowerPoint
super-easy maybe insert photo from this
device and navigate to my figures to
folder which it is there I grab both of
these bad boys insert them and we're
gonna do a couple of quick little
editing okay
so first let's just grab this one let's
shrink it down a little bit okay next
let's grab this guy and we'll also need
to shrink him down a little bit but
notice it's got all this extra
whitespace in so let's double click that
I double click it I can hit this crop
button under picture format my crop it I
can squeeze it to be just like that now
it's kind of reasonably sized it has
kind of matched pretty nicely there
isn't it what you might even want to do
is crop that so that you get rid of that
funky label and you can go to insert
text and say this is Kruger
- correct objection - correct rejections
or gonna get 600 milliseconds like that
right there
now we've kind of got a nice little
setup where when we take these you can
hold the shift key down and I like both
together and then you right click format
group now they're together they're
easily moved all together as one okay
and this is how we're gonna show some
figures should the here Peas and then
you show the topographies later on we'll
add one more second there
so to do that bring this down let's say
that we want to go to European
measurement tool and those are all of
our herb sets that we used right so you
already have those we have them safe
from last time and we want to measure
the average amplitude between our two
fixed Leighton seeds our latency is now
at 400 to 600 milliseconds the bins we
want to measure we need to make sure
that we still have essentially correct
rejections and wherever all of our
dunning-kruger vinyls
okay yeah 933 okay so in 55 and 933 our
channel we want to make sure it's the
right one which is not fc2 here we
actually want to come up to PZ so we're
actually measuring what we're looking at
and now let's let's browse and change
our we're in our stat files and now it's
changes to 400 to 600 milliseconds we're
doing Oh
dunning-kruger responses vs. correct
rejections 10 and we're at site PZ say
yes and I will see his matlab is
thinking it's taking those measurements
it's counting and 3 to 4 sample picture
size excuse me
data sets now that's done so what we do
if you remember come back to our folder
want to open that file which is saved in
our folder called stats files I'm gonna
grab that we're gonna right-click and
open it with Excel
okay you can expand these columns a
little bit and we know that 855 that bin
is our correct injections I'm 33 just
kind of organizing things a little bit
you know that fact what we can do is we
can create a graph
that includes our mean standard
deviation and their standard
just kind of call that standard Davis
yeah now the way that we calculate that
so we have a last 50 little formula it's
called the equals give me the average
open parentheses and I drag all of that
close your parentheses and press Enter
that is the average of everything in
your dunning-kruger gestures in fact
type equal there you'll give us that
we want to know standard deviation the
formula here is equals St D P P open
parentheses highlight and drag close
parentheses you now know the standard
deviation one of the standard error of
the mean the way we do that really easy
as we go equal we press the up arrow key
to select the standard deviation and the
formula for that then is the standard
deviation divided by square root which
is SQ RT of which means open parentheses
sample size so the way we know the
sample size here is we can tell it to
count the number of observations in this
selection e to be twelve close
parentheses you close it a second time
to match the first parenthesis and hit
enter and the last thing we can do is
just format this to look nice just to
right click format cells got a number a
decimal point is 2 now that looks nice
you grab this little deep green corner I
get dragged out there it does the exact
same thing
excels pretty smart it already has it in
there even drag that now look what we
have if you take this highlight those
four cells to make a nice little bar
graph you say it's a bar graph we can
now plot that get rid of these ugly
horizontal lines you can make this stand
out a little bit nicer like increasing
our font size to say
I don't know 18 this maybe 16 okay our
title like I say whoopsie
now the thing you want to add to this a
standard error bars you highlight that
you click on one of these or they're
both selected will you do that is go
chart design you're gonna add element
maybe error bars or options let's go all
the way to the bottom and select a
custom because we've already calculated
that we specify our value what you do is
you just for position error for the
first top line you grab those two press
the tab key you have it those same two
again cuz that's the standard error mean
that we calculated we know is right and
now got a very nice-looking there you go
it's little error bars and that's nice
the other thing you can do let's grab
these two like this and you can make a
scatterplot grandad well that looks
funky gonna switch our rows now we're
gonna get rid of these cookie lines we
have as essentially the variance so we
can see these are the same points but it
shows each individual data point for
each of the it's the same graph it just
shows the actual variance of where the
real data is
okay so what you might do for that then
is and you can take you can adjust this
graph a little bit insert text box and
write our little something here that
says I pick our font size they're a
little higher 16 see you bring that down
that's kind of what we're doing you
Center that so can't go much further
down what you can do and then just copy
that you'll see control these might
paste of that in here too you just
adjust this trials now this looks a
little bit closer I wouldn't like that
in entirety so what we can do is just
grab this
and let's copy that same information
here the chart design I want to add an
element of a title of the chart
nice title and I can take that graph
copy that
come back here it's that third and now
we can show a series of information of
the neural time course data in the ERP
is including the variance of the
standard error the mean there may be
show topography of where that's maximal
in the head the relative size of that
difference during that latency and we
can actually see the individual variance
one thing you might even do grab a
little box and show the window that this
is measuring so this is 4 to 600
milliseconds right just here and then
you can change that format so there's no
fill and the outline is dashed like that
so it shows a nice little thing so then
what you do for these figures you can
press ctrl-a which is highlight all and
now we right-click them together and
then I can right-click again say save
this picture we change it to a jpg I put
it in my folder say let's just say Janis
pz 400-600
ok so now I have that saved okay and
let's say I have a document so let's say
that for example let's say this is your
manuscript you come in here say insert a
picture from your pictures they're good
here navigate to your figures folder and
now you have your figure add it into
your manuscript it shows all the
relevant important information that we
need to know pretty cool huh
that is cool right I can go back sure
yeah so as far as I know it's definitely
being recorded I also have done this in
other classes and we have these kind of
videos already on our playlist for the
YouTube list from similar yeah yeah I
should be there so so the that's there's
a research but this is certainly more
tuned to what we're doing so will
obviously keep this video here and what
you guys can use is so this took me like
an hour to go through you guys can make
your own little quick videos and then
send it to me and I'll upload them to
the list for other people too so you
know you can use zoom with each other as
groups and saves your zoom meeting or
Skype meeting Skype saves it
automatically to if you want to hit
record and Skype with each other you can
make like a little five-minute video
making sure a little quick there's tips
and we'll add it to the list and it can
help a lot of people
so that well let's just actually so here
we are right let's say this is in your
manuscript whatever you know and you're
explaining your results this is why
we're doing all those other steps right
we need to get to this point in your
manuscript in order to do that we have
to have the data available in groups in
order to have it available in groups we
need to have the individuals processed
in order to have the individuals process
we need to have the artifacts rejection
in order to have the artifacts rejected
we have to pre-process the data so this
is me trying to connect everything that
we're doing for you guys to give some
context and relevance and tie it
together to show you why it matters all
these early steps we're doing are the
essential ones so we get these nice
pretty pictures at the end but we only
get there by doing all these other steps
properly now let's do this last step
here that we have not yet done which is
actually perform the statistic so let's
come back to excel here and what we're
gonna need to do is we need to know is
there a statistical difference between
these two bars right now this is just a
cartoon it's just a pretty picture we
don't know if it's real we don't know if
it's meaningful right we got it we got a
hit paydirt so we're gonna do a t-test
between our subjects correct rejections
and between there done and Kruger
judgments okay now the way we're gonna
do that is remember last time we went to
our data tab we did data analysis as a
reminder this might not be there in this
one this might not be there for you if
you have not first gone to file where
were we options you need to go to
add-ins so there's a tab for add-ins
takes a moment to load here and then
down here you need to go to go heat
depress the button go at the bottom and
select analysis toolpak and hit OK okay
after you
do that then you'll see this data
analysis and you click on it and it
brings up a nice little GUI this is why
I said you don't need to know the math
of your statistics for this class this
is not a statistics class but you do
need to understand what statistics are
and how they work which is why it's a
prerequisite so where you need to
understand that we're doing a t-test
between two measures within the same
group of people which is our two sample
two samples for means you're gonna hit
OK it's gonna ask you what is the range
of your first variable our first
variable is correct ejections and the
range for that you just select all that
data what's the range of the second
variable that's here select those bad
boys okay that's all now the last thing
that's gonna ask you do is where do you
want to put output that data okay now
usually I select this one and I put it
in the same worksheet but I have these
kind of filled up right now in my
viewpoint for for the figures so let's
just allow it to continue by a new
worksheet okay just hit OK so it creates
this new worksheet here
and it gives us our results now variable
one was correct rejections variable two
was Kreuger judgments okay and what we
see here is our mean we know that we
have our degrees of freedom there is 10
we know our T statistic here is negative
four point seven and so a t statistic
for a degree of freedom of 10 degrees of
freedom which is a sample size of 11 for
a two-tailed t-test that means our
p-value is hugely significant point zero
zero zero eight which means woohoo we
found a real fact statistical
significance there really is a
difference in the brain between dev
dunning-kruger judgments and correct
rejections in this particular case
which makes a lot of sense because
they're fundamentally different
decision-making processes so you would
expect the brain would probably be
handling that different and so don't
forget we need to now add in I need to
write into your report the result so we
say within-group t-test you'll that mean
here p amplitudes from centro / r pc
from 600 milliseconds or kathleen archer
or judgments 6-8 standard deviation will
fill in when we come back the other side
and we'll even add our sample size here
is 11
okay significantly large with
dunning-kruger judges then for direct
actions then was negative point nine two
three sandy a shuffling in a minute
sample was and the way we say that these
are T value using a degree of freedom of
10
well negative four point seven one which
was a p-value that equaled it was
essentially less than point zero 1 . and
so I can take that back here let's just
paste that here and I can fill in our
standard deviation information for the
dunning-kruger is in cell b15 which is
six point six zero and our standard
deviation for correct rejections is in
cell eight 15 which is two point six one
okay so that's just all the information
since your service standard stat
reporting you might not need to include
the sample size in there all the time
there's an APA way of doing that and now
you have your basic information
essentially that you can use as a draft
to then paste in let's say that you're
writing your report and you're like oh
it's boom and that would be I just paste
it into the head of an expert here you
go results and that's how you would
write that up and of course you'd write
then what do we talked about last class
here's a little pop quiz what do we say
next about this result
well we would say what that means right
so say indicating decision processes or
something right you just you'd come up
with a something that that would be
representative sort of what that
indicated rather than just force-feed
people a bunch of numbers did you say t
says says this is different than this
you got to add a little something right
flavor that's steak you know don't just
force them to eat it give it some good
flavor so you know this is what it kind
of suggests this is what it implies you
know this is you know so when how would
we describe how would we word so on the
first image on the topography map you
know you know highlight that 400-600 how
would we verbalize why we chose between
400 and 600 to do our statistics of or
our topography method that's a fantastic
question and I'll show you right now I
would think that'd be like um inflation
I originally I thought it'd be like
inflation just to look from like the
biggest difference but how would we
justify looking into that difference
very good question the reason we justify
that is by first in the introduction
doing your literature review in such a
way that you identify the reasons why
you make the hypotheses you're gonna
make about the data your hypotheses are
what directed you to look from 400 600
milliseconds so what you would say you
would identify that the introduction but
then here you'd remind your readers of
that they say
you know that subjects process let's say
recollection
you know she's fake - mints require
excuse me
inherent requirement which guided us to
wait and see well for recollection it
would actually be 600 to 900
milliseconds but in this case we went to
four six so you might say change that -
actually it's a bit earlier process yeah
he you do there's people in their memory
and how was it formed chat us to explore
the activity that make latency between
600 milliseconds her between 600 and 400
and 600 milliseconds
which you exhibit maximal place site
your finger one okay and then you'd say
not there so now is the answer to that
question Gary their musics you explained
why you look there right and you want
that to be based upon a priori
hypotheses okay and you'd say when the
next thing we got to do here to be APA
format consistent right
zina caption look you need to say figure
one give it a title and say you know
geology trigger fish mince - okay then
you're gonna say what's in the Left
panel
it's your peas it's like say change the
regions
[Music]
then you're gonna say what's in the
middle panel this is a - sections say
colored scale our scale is oh it's been
some you volts and I'm going to show you
a little trick right now to say new
that's the actual thing the the unit you
know insert symbol grab this little new
symbol their color scale is and then
here say right is scatter lots of your
PD seconds
each and you'd say why this again or
meatballs so let's go back to our insert
simple just click it it's automatically
in there just like any good figure or
they're all the title and there you have
it this is single spaced right so you
know you might you would double spaced
that for your you know thing so what do
you think about that how does that
especially because like different I
don't know I'm not computer savvy so
yeah so so let me start with another
works in here so just a reminder for
your introduction sections here's what
I'm looking for
here's an unexpected right I some things
you need to review you need to basically
do a background ok and let's just say
and within that literature review you're
gonna want to explain to people what is
memory
sonic Sosa's action dirty we're also
going to want to do you're gonna want to
tell people a little bit about you're
gonna want to tell people is Fiji and
what are some maybe even what he can
find out about fluency one sees a form
of implicit memory I will just do that
there you're also gonna want to explain
to people what is um when we talk about
episodic memory processor or earpiece
and memory right and you might also want
to explain differences is its actions
this is okay what is metacognition
the Sugar Act Kruger effect this theory
this oratory station the size that is
say additions
that's basically your introduction um
that's kind of a lot of stuff but
frankly we've spent a lot of time
together it's been a month we've had
some long classes and we've talked about
all this we have slides about all of it
you have all the extra stuff about it
and we talked about how to get those
citations and references found in the
primary literature premier reviews on
PubMed for that last class so um you
know you might even talk about some
other parts about memory right like
let's say here I've got this - maybe
you're gonna talk about false alarms if
you want to talk about false memory
right also false alarms these are
basically for correct is memory reliable
that eyewitness memory we talk about
customer would you want to be convicted
by an eyewitness testimony of somebody
who saw you do something yeah I wouldn't
be why I wouldn't want to be convicted
by anything ever right but naturally if
I had to be convicted not by an
eyewitness testimony based on eyewitness
testimony it's a major major problem in
the criminal justice system and it's
something that psychology as an industry
has been a major contributor to in
helping Society that nobody expected
Society we heard that that psychology
would play a role in that but we really
have as an in
and you know if you care about social
justice if you care about discrimination
in the legal system there's already
issues that exist about those fronts and
which are exacerbated by these effects
of like false incrimination or false
testimony that doesn't mean they're
lying right like the people that it
doesn't mean like the person on the
stand has some axe to grind against the
accused sometimes they just honestly
remember it wrong it's not empirical
right well it is empirical it's just not
necessarily like intentional but what we
know from the empirical is that it's not
very raw well so you if you're
interested in studying false memories
and false alarms and our data sets this
might be something that you explain in
your background you know are there some
famous examples of failures in sort of
this kind of memory or you know are
there reasons to be cautious there right
we talked about that with Christine
Blasi for actually retrieved these
memories from from therapy that
generally scientists know are highly
unreliable if there's not anything to
other kinds of corroborations so um big
history of research in those domains and
maybe that is something that you get
interested in as something that you
construct your hypotheses to explore in
our data set right you don't have to do
dunning-kruger by the way in this data
set it's just you don't have to do any
of that it's just here for you if you
want to because maybe some of you guys
are like oh my god memory is super
boring and lame and you don't want to do
this but you're way more interested in
studying that kind of career so so I
mean this is here for you guys as you
know options because what you need to do
is say here
start this again here so here basically
your research paper assignment is to up
to your own analysis of set each sample
size of 20 subjects do you need to UM he
buys your own for which you must have at
least do different offices explore them
based upon research site APA to group
analysis including fishing quality
figures that we just talked about
statistics that we talked about today
etc I
this section driving teacher used
detailing steps each step
processing and of course provide a full
session section use a summary fine
discussion you know accept or reject
office ease I it also includes
you your well first of all say and it
cleans your interpretations results
reputations don't also say results
limitations to your interpretations and
suggestions or research well so again
this is just a research paper but these
are the sections these are the things
I'm gonna look for
and when you're doing that intro these
are the things that you're gonna want to
have included in it and all that good
jazz okay what do you guys think about
all that because basically none of this
is new we've been talking about this all
class but I thought for a moment that
maybe this is a nice way to kind of you
know bring it home for you a little bit
more in terms of clarity and structure
what do you guys think this is hopeful
[Music]
yeah so this kind of gives you more that
roadmap so earlier today some of the
feedback you guys said you wanted a
weekly to-do list this is not just your
weekly to-do list this is your entire
course to-do list okay and there's of
course more to it in the sense like your
method sections are gonna include all
the stuff we talked about last class
same with the results and discussion and
all that all those sections but this is
your whole this is what you're working
on now and this is your job the rest
this semester and if you get it done
early you're done so we're about halfway
through the semester I'm going to test
you with a midterm next Wednesday here
I'll stop sharing here I could talk so
I'm gonna test you next Wednesday
because who doesn't like a chance to
score points and get a good grade right
um you definitely don't want to leverage
your whole grade on just let one paper
because you don't know how it's gonna
turn out all right
so
[Music]
so it's good to you know it's good to
have the extra help your midterms should
provide you extra help if you've been
working on this regularly every day of
the week as much as you can and you're
up to date on the readings you're
up-to-date on our videos you're
up-to-date on our notes and practicing
through the data analysis you're gonna
do great that's my job on the midterm is
to find out if you've been doing those
things and by testing you with that is
the way that I can find out for that so
you've done these things you're gonna do
great
but that midterm is gonna let me know
that you're that you know the stuff you
need to know to do this project and then
I'm gonna be I'll cut you loose and this
is gonna be your job
I'll keep showing you more advanced
stuff and other cool tips and tricks and
ways to do things but what we covered
today was kind of that final step of how
to do what you need to do in the data
right so if your goal is to produce this
paper well the paper needs a conclusion
so your goal is to really just conclude
something about your hypotheses in order
to do that you need to have results in
order to have the results you need to
know what they mean which means you need
to know if they're statistically
significant and you also need to be able
to illustrate that and show that to your
reader which is what your figures are
that's your ear apiece that's your stuff
ography maps and so big picture big goal
that's where you need to be you need to
be able to make a statement of
statistics represented by figures of
what those statistics represent and show
which means that you need to be able to
have groups of data ready to analyze
which means you need to have the
individuals prepared to join that group
and all of our work up until then we're
teaching you how to work with the
software and how to understand the steps
in order to get to where you need to be
so that you can explore the brain
through this brain activity to
investigate your hypotheses to test
those hypotheses so that you
drop meaningful conclusions through
critical analysis critical thinking
about what they mean draw those
meaningful conclusions and be able to
write about it and be able to share that
communication with what you found what
he discovered and that is science that's
you being a scientist so you're ready to
graduate you're ready to go and this is
what you got a big a wrap it up you know
be that scientist be that's
psychological scientist and use what
we've you've been trained on through
your college degree to finish strong and
sure that you can pull all these skill
sets together and that's it overwhelming
little overwhelming like now I know like
now I know what I don't know that's not
a cougar yeah so I tried I made it a
little bit dramatic there for you guys
but but you can do this right like this
is matt is overwhelming as it is I'm
letting you know that is very manageable
to
that's just a that's just a dramatic way
for me to get you guys to be like holy
I gotta take this class seriously
because it's gonna get real but like
everything that we all just talked about
we've done every single part of that in
this class already there's already
available on the videos that we have on
the YouTube playlist you already know
how to do all that it's just gonna be
some practice you're gonna fall down a
little bit scrap and scrap your elbows
and knees here and there and that's okay
and I'm here to help you and we'll make
it work or all of its manageable
all of its manageable and you can do it
so what questions do you have for me
what concerns
let's pop with your head because I've
been talking a lot I need to start
listening
I mean ultimately I like the fact that
you're able to give us the rundown as
far as what we need to do but to-do list
is actually very beneficial for me I'm
sure other students as well and the fact
that we're halfway through the actual
order but we're able to work on this
paper throughout the rest of the room
with you so yeah yeah that that's our
goal for here on out is gonna be like
just paperwork and in the sense of
working on the papers and I'm just I'm a
resource for you guys but like I feel
like kind of like your parents when they
sent it off to college like I feel like
all right I've taught you the basics I
know you can read and write I know you
can analyze the data I know you I know
you can do all these steps and so now
you're you're the captain of the ship
I'm giving you control of your ship and
I'm here as a guide for you to help you
but you're gonna steer the car you're
gonna drive and that's cool you know so
I'm on your side and I'm trying to help
to make sure that you you drive the car
home safe and sound
and all that but don't drive like an old
granny let the gas to the federal have
some fun you know you don't get to work
a brain data like this very often so the
first thing that I would say so I've
done this for six years now I've been
teaching this class the big thing the
big hurdle the first thing you need to
do right now is to start you need to
come up with hypotheses and that's not
always easy and that takes a lot of work
together with me so we can do that in
class we can do that in office hours we
can do that just emailing back and forth
or just private sessions on Sam but for
the next week or so really be thinking
about what we just talked about like
what are the what's the hypotheses that
you want to explore
in this day in this data sometimes
you're not going to be able to be to do
that because the data might not be
suited to actually like satisfying those
hypotheses which is why it's helpful to
talk with me because I can help redirect
that I can help guide you yeah oh yeah
okay yeah we can do that in this data or
you might want to be like something
that's awesome but I'm like you know our
data is not awesome enough to be able to
do that so there's lots of different
ways we can slice and dice it and I'm
here to help you so the first thing you
need to do is start really thinking
about how those hypotheses a lot of the
places where that comes from is from
reading the literature which is why last
class we said you really need to start
reading and looking up some cool stuff
on PubMed some of these topics and start
building that literature review section
because essentially what you need to do
in this class rating this paper is is
essentially do what it took a lot of
three years to do as like the top
student in the master's program in the
university this is her master's thesis
so you need to do in about three to four
weeks like she did in about three years
and the good news is she already
collected all your data we already added
for you and we got it nice and
streamlined so it just it's a lot of
stuff but we're here to help and that's
kind of the gist any thoughts about that
okay so I know can be overwhelming I
said I wanted to kind of rattle your
cage a little bit and kind of get it get
a jolt of electricity put in there for
you to be like hey this is this is go
time I need it you need to really start
getting after it but but know that it's
manageable
everyone does great and you guys would
be fine the trick is getting ahead early
staying ahead and just you know a little
bit a little bit each day and we'll fix
that's you guys see stuff goes wrong all
the time we fix it it'll be okay
look plan for that plan for some extra
time it'll all work out so how many you
guys are are already thinking of ideas
that you might want to explore yeah I am
how many people are like me and are like
I have no idea what I want to do right
now but I'll figure it out
along the way yeah okay that's me okay
cool so it's good to have a little bit
of both I always feel that way huh yeah
you just want to get the I don't know
fishing if you look at the would it be
considered fishing if you're like
looking how you did those graphs and if
you're like looking for is that fishing
like if you're like looking perfect to
kind of help direct your hypotheses like
okay like what can explain this yeah it
can be right but we need to talk sort of
responsibly about that too so you know
if anybody doesn't know what he's
talking about when she's like is it
fishing to do this so there's kind of
like the snarky term the scientists use
we call like going on a fishing
expedition which means you don't know
what you're looking for in the data but
you're you go and find where it's
different first and then see if it's
significant and that's a whole lot
that's like saying like that
Columbus just sit set off from Spain and
just float it around the ocean just
floated and just then we're gonna go on
a suicide mission from Spain and just
float around and he accidentally
stumbled upon some land but he thought
he was gonna fall off the edge of the
earth and it was his they were on a
suicide mission that's not right
right that's not right that's not what
happened they had a plan they had a
hypothesis the hypothesis was wrong by
the way right he said my hypothesis is
that if I sail straight west outta India
you strong no big deal that's how
science works we explore but he had a
hypothesis so the fishing expedition is
like you know you want to be clear if
that you set off from shore with an
engine with a tiller with a rudder
something you had a direction that you
were trying to go that you were you got
something you were looking for for a
good justified reason right that there
was something something intellectual
there is a reason that you were looking
in this particular spot for this
particular thing it's okay if you don't
find it right none of us are crying that
Columbus didn't find India we're all
pretty happy we're here right so it's
okay if you don't find it but then Grady
what you want to say then is you don't
want to be like a so I went on a fishing
expedition not yeah I know I looked for
my data first and I found this crap no
no but what you do want to do is be fair
and honest to your readers and say we
set off on this expedition expecting to
find differences related to correct
rejections and hits at this time points
based upon these this rationale we
didn't end up finding that but when we
looked at the data the data revealed
instead then it looked like there is
this other effect somewhere else okay
and then what we did we conduct we
conducted an exploratory analysis right
you're saying so
instead of saying oh this doesn't look
like India I'm going home to Spain I'm
not gonna get off the boat and check out
the Indians and make friends just what
they did right they're like oh hey we've
been sailing for a while it'd be pretty
nice to sleep on land for a night or two
maybe get a home-cooked meal right you
went and you explored even though it
wasn't what you look for so so or like
we conducted this whole experiment we
didn't see what we thought we'd see but
we did see this other thing and we
thought we'd explore it and when we
explored it we these are the statistics
of what we found there turns out there
was this effect in this other condition
in this other place
in your discussion you're going to
reiterate that
and say we didn't expect to find these
findings they were not predicted it was
not part of our hypothesis but visual
inspection of the data did lead us to
this exploratory analysis this is what
we found this is what we think it means
however this is the core part that we
talked about Monday limitations and
interpret and alternatives you can say a
big limitation of these findings is that
they were exploratory these were not
hypotheses based at results and so the
next it's gonna be really important for
future research to confirm what we find
it's you know this these these results
should be taken tentatively and as
exploratory findings that remain to be
corroborated by further investigation
so you see how that's a way to salvage
that and be professional and scientific
about it but not be like
you know I was just fishing and I just
got lucky and it turns out this thing
was there and okay I gotta go bye you
wanted
okay thank you that I think someone yeah
many of the data person trying I know I
want to do like something to do with
like like I feel like by a season half
may affect how do you identify this by
C's can help just like you know society
at large
yeah no okay so how many you guys want
to turn this into a group project how
many of us are they well right now I see
good if anyone liked him like small
group so this is only pairs this is what
I was thinking is that you can work in a
group of two I'd even consider three but
right now I want you to start by
yourself okay and let me explain what I
mean by that so I want you to have I
want you be able to do this on your own
you need to be able to push through
these 10 or 20 people with your analyses
you need to do your own literature
review need to do your own analyses the
reason that's important is that so you
do not screw over your partner and so
that your partner does not screw over
you because we've all been in group
projects before where we get screwed
over and we don't
that's not fair we want to practice
being good team weights and having good
teamwork and so by having this stuff
done first what it allows you to do is
have a little mini draft and now you get
together with your partner and you talk
about well what was I looking at okay
well what were you looking at okay so
you're looking at memory cool I was
looking at metacognition awesome let's
put it together and now you guys have
extra stuff to put together now you're
gonna have a big-ass paper this is
awesome this is gonna be really cool cuz
you're gonna have extra so now each if
you cheat you guys have two hypotheses
your your paper is gonna have four
hypotheses which might have eight
analyses right
that allows you to really pull it
together and help each other out and as
you work with each other you might say
you know what this is a cool idea you
had but the comparison you use for this
hypothesis was kind of bad it doesn't
really work you can't do this comparison
to get it this hypothesis why don't we
change it around you can help each other
strengthen each other what you're doing
through some editing some feedback some
teamwork and have you know iron sharpens
iron but you can't do that unless you
guys all bring together to the table
something that you already done on your
own and so I do want to throw that out
there in the future to keep in mind if
you want to do that you can science is
collaborative and almost all papers have
co-authors and people who work together
on it and frankly it makes it hard to
it's good I can even cost you more time
taking by taking more time to work with
the other person than just work on
yourself but you can do it no more than
two or three people but you can also
work entirely on your own if you want
just totally ignore that so a little
something to think of in the future down
the road to help maybe that feeling of
being overwhelmed if maybe you feel that
way um but now you know that if you're
gonna analyze say 20 subjects you see
how much easier it is to go through
their artifacts right with that
automatic algorithm and stuff so yeah
they're definitely hell yeah
so anyways we've been going for about
almost shy of three hours I think we're
I think we find a pretty good spot to
stop here cuz it doesn't seem like you
guys have much more to just say if
questions or ideas or stuff that you
need me to fill in the gaps on and I
know I've been rambling on for the WHA
here so I'm just reading my notes here
I'm gonna upload that list I just typed
would you guys like that yes okay look
I'll put it on both the drive and on
blackboard
and and then you know what I'll do also
I'll also upload air you know what I'll
do I'll show you I'm a screen share here
for a second okay so here I'm gonna save
this and okay so have that the other
thing I'm gonna do is ooh this is
perfect I'm gonna take this copy that
out of my thing and paste this into the
research so here we have same example
results sound good what you can do is
even take this do a little formatting
put a little border around it can that
look sharp okay
and figure you might even want to either
shrink your text down a little bit there
that's looking for an example okay so
we'll save that in there this is part of
your research assignment paper there
I'll come to this document my powerpoint
I'll save this to I'll share this all
with you guys essentially is what I'm
saying okay I'm gonna put this look what
I'm going to put it
[Music]
templates so now we have a folder for
templates and you already have one so we
have another draft template for making
figures that's from a previous semester
so now you'll have two options the other
one uses bar graphs here but I want to
move away from bar graph let's just
really emphasize to use the scatter
plots this cycle around okay and the
same thing here we have our you know
stuff here and I'm gonna save this as
within our template as well okay and up
here we'll go to templates I'm gonna
make sure you can say that as an Excel
workbook okay so I have these three
saved close that close this I'm gonna
close this realize that and I'll come up
here and in our folders I'm gonna show
you right where I'm putting as you guys
I'll see it we're in templates and you
can see these are from last previous
year's classes actually but it doesn't
hurt to have more examples does it let's
add some more and templates
[Music]
I want to say 433 right in our main one
here going to that bad file that we just
typed up together see teaching
now this is uploaded here too so is this
okay do you guys one of them blackboard
to here's it fun just have this here in
Google Drive that's cool for you ready
does anybody else prefer it in
blackboard I can put it there too and
I'll just know if both would be good
that way at least we get the
notification from blackboard as well
then natural obviously save the video
and post that that won't be a little bit
too later today because it takes a long
time to do those lot videos but I've
been up there pretty diligently for it
and you just want to make sure that
you're on top of the game for you know
that that playlist is updated and we're
in the content page now building that
[Music]
okay then I think we're good I covered
everything on my list the last thing I
will just show you is I will remind you
that this is our syllabus and I think
that we're finishing week number four
right now as far as I know next class we
will have a review I'm here for you guys
I'm gonna let you guys drop your review
session I want you guys to bring some
sample questions of what you think
should be asked on the test or what you
think could be asked on the test and
I'll be here to talk with you about it
on Wednesday next week we will have the
exam the midterm and that's a big chunk
of your grade so it's not just on
concepts and knowledge it's gonna know
it's gonna be do you know the steps to
take to analyze this data to work with
this so it's all the stuff together so
be working on your analyses be
processing your data because that's a
good way to study as well and that takes
us right to the middle of the class the
last part of which is gonna be
essentially you guys now leading working
on those lab reports based on the
analyses they and research that you're
doing I'll remind you that we've covered
what is MATLAB and eg live how they work
we've talked about what is eg an ERP is
what are the memory processes we've
talked about the processing issues of
order epochs and event codes and our
memory conditions we've talked a little
bit about events lists and bin
operations files for the steps and the
procedures and what they're doing um we
spent a lot of time now talking about
artifacts and how we account for them
we've covered what the sections are of a
scientific paper we've talked about
memory related ERPs
FM 400 LPC implicit memory and the
posterior sights during the early time
points we've now covered how to make
publication quality figures we've also
talked about statistical
now we perform them we haven't yet
really gotten two oscillations and I'm
kind of holding off on that so you're
not going to need to know that so much
just now other than to the extent that
which we've covered in some basic
lectures and the goal then is to use the
midterm and your paper to demonstrate
that you're able to produce competency
with this material through this
examination through your written papers
through our discussions and enzyme work
together and that's our class guys
so I think that's all I got for y'all
yeah yes you guys got anything left for
me just like maybe a little bit just I
don't know I hate to be that person but
like the logistics of the exam like how
long can we expect is it gonna be like
filling like is it gonna be online
version or ripping it out or like
multiple-choice like do you know
anything about like or do you want to
give me insight about the logistics of
the exam
yes a basic logistics it's gonna be in
blackboard you're gonna have to use
respondus like we've been practicing so
have your ID card with you have all that
stuff ready have power cords connected
so your battery doesn't die have your
internet connected it's probably a
combination of multiple choice and short
answer maybe some essay stuff I always
think of it as being straightforward but
you know you know I'm gonna nerd with
this stuff so but but it's gonna be the
stuff we've been talking about it's the
stuff we've covered and again the
framework that I use and designing the
test is what do I need to ask you to
know that I can trust you to become is
so think about testers just think about
what just think about what you would ask
someone to know that okay and I'm like
how long is it like it obviously it's
timed but um is there like a rough
estimate unlike a regular lecture two
hours or whatever it's a good question
for any part that a lot of that's always
based on the individual right like how
how long did Alec Asian I mean I mean
look you'll have the whole five hours to
do it if you want that's not I mean you
will not need it if you need five hours
we need to have another talk okay you'll
be okay all right
it shouldn't be that long you know
normal kind of test length for a midterm
it's hard to say you know maybe an hour
maybe less I
I mean I try to be very practical I
don't care if you can get it done in two
minutes instead of two hours I'm like
wow okay you must know it really well I
mean I'm not trying to go for time so by
not trying to rush you either NASA oh no
I was just taking okay anybody else I'm
gonna sign off all right have a good
weekend guys stay on top of this stuff
don't let it get behind you or don't let
it get in front you actually know a key
you guys get the idea
I gotta get lunch