Today I was there to introduce or
a little bit of both mechanical

engineering in a very disagreeable
University of Colorado Boulder.

On the roof in the chemical
temple of various universities.

Of.

The University of Michigan Law School.

And of course our group
with us in your first.

Appearance.

In the movement.

Certainly but there are certain programs.

You.

Think you live.

Your life.

Thanks Lena thanks for the invitation it's
great to be here today thank you guys for

coming so I want to sabbatical.

A year ago maybe two years ago now and
sabbaticals are great for many reasons but

one reason is that it really gives
you a chance to just sit down and

think about one idea really just focus on
one question and and give it your all and.

The question that I really spent
a lot of time thinking about was

the speed of our movements so
why do we move at the speed that we do.

Why do some people move slowly.

And why do some people move fast and

do people who reach slowly also walk and

talk slowly and do fast awkward
talkers also reach fast and

walk fast and
this isn't idle curiosity because

the speed at which you move can actually
say a lot about individuals health.

OK So for example and Parkinson's disease
the cardinal symptom is a break can you

first slow or slowness of movements.

So I thought if I want to understand
the neural determinants of movement speed

then Parkinson's Disease is a reasonable
place to start now Parkinson's Disease

is a disease of the basal ganglia and it
arises from loss of dopaminergic neurons

in the substantia nigra a part of
the basal ganglia in these neurons release

a neurotransmitter called me
to various parts of the brain

so in a study back in two thousand and
seven John Krakauer and

his only investigated reaching movements
in individuals with Parkinson's disease.

And so they had Park and park and P.V.
patients and healthy age

controls they asked them to make reaching
movements to targets on a screen out of

prescribed philosophy and
this study had surprising results for

two reasons one when
sufficiently motivated

the Parkinson's patients could reach
just as fast as the healthy H.

match controls OK.

And when they reach just as fast
they could also they not only could

they reach just as fast but
they did also reach just as accurately and

this is surprising because the under
what was thought to be the cause for

slower movements and Parkinson's disease
at least partially part of the cause

in people with Parkinson's was that
they couldn't move just as fast but

they could they would move less
accurately OK but in this case they saw

that Parkinson's patients could move just
as fast and sufficiently motivated and

they did so just as accurately so
the common reasoning for why P.T.

patients were moving more slowly wasn't
some way debunked it seems that P.B.

patients were moving slowly
because they chose to OK And

I thought this was really interesting
because as I mentioned earlier

the main pathology and Parkinson's
disease is loss of dopaminergic neurons.

Which produced a neurotransmitter.

That called the mean so to understand why
this is interesting let's look a little

closer I don't mean so the don't mean
neurons in the basal ganglia are located

in these essential Niagra and the ventral
tegmental area shown here in areas

eight through eight ten in
these neurons send axons along

a long distance trajectory that could
influence brain activity in many areas so

from the stray them all the way to the
frontal cortex an area that's critical for

decision making what this means is
that don't mean is not just involved

in movements but
also plays a role in decision making OK So

what role does adopting in play in
decision making in a series of pioneering

plastic experiments Wolfram Schulz
recorded from single dopamine neurons in

the midbrain of monkeys as they learns
a Pavlovian conditioning task and in

one variant of these experiments a thirsty
monkey sat in front of a waterspout and

unpredictable intervals
a tone was played OK and

a drop of juice would be provided to the
monkey shortly after the tone was played

so initially if you look at the top plot
the dopamine neurons would respond to

the unexpected juice reward
indicated here as R.

and they would increase their firing rate
OK let's see if I can move it up here so

here is the unexpected tone.

With a way to get a turn Here's the
unexpected reward and then you would see

an increase in the firing rate here but
showing up great OK So but

as the monkeys learned to associate
the stimulus with the reward the dopamine

neurons began to respond to the tone
that was predictive of the reward so

if you look at this middle plot here
here is the stimulus the tone and

now here you see the increase in
firing rate even though the reward is

provided right there OK in here so the.

Suggest that those mean activities
linked to the expectation of reward and

here we see an example at the bottom where
there is a tone but it's a trick and

no reward is the livered So the neurons
increase the firing rate when they hear

the tone but then you see a slight
depression when they don't get the juice

they expected or the water they
expected in this case so this and

many other studies suggest that
the activity of those mean neurons

is strongly tied to
the expectation of reward.

In these neurons fire in proportion to the
value of the stimulus that is the greater

the expected value of the stimulus
the greater the release of the mean.

So all these findings highlighted
an interesting puzzle so

the same neurotransmitter dopamine
is involved in movement control via

its connection with movement slowing and
Parkinson's disease as well as this

issue making via reward expectation
in value based choice so

could it be possible that these
two processes decisionmaking and

movement control are linked and

that puzzle is the central theme of
my talk today so when it comes to

understanding the brain there are two
types of decisions that are often studied

the first is what to do for example do
you eat the apple or the cookie and

the second is how to do it so
the choice of the movement that follows so

if you like me prefer the cookie of course
why would you not prefer the cookie but

if you prefer the cookie does that
mean you're going to reach faster for

the cookie than if you
were forced to reach for

the apple so traditionally seen ever
thought about these questions before but

you can think about the months about so.

So traditionally these two questions
have been treated separately but

recent results have demonstrated that
people will actually reach faster for

items they prefer more.

So I thought this was super interesting
that the way that people move

in the decisions they
make may be related but

I realized that to investigate
this further I needed to determine

whether there is actually a framework
capable of explaining both so single

framework capable of explaining not just
your decisions but the movements we make.

In the framework we proposed is based on
the intuitive idea that our choice of

action and our movement reflects
an interplay between reward and

effort OK so how do we make these
choices so a standard approach and

decision making is to ascribe to
each option in case two factors

the reward at stake in the effort
required to acquire that reward so

the former serves as a gain and
the latter serves as a loss now a major

determinant of most movements we
make is the effort they require so

but the spite this decades of
research in decision making and

movement we still don't have a good
understanding of how the brain represents

efforts and that is really
the central question of my top.

Or of this really research projects how
does the brain represents effort and

we're going to I hypothesize
that the brain represents effort

as the metabolic cost of the action.

And if we represent effort as metabolic
cost then this framework where

you consider both reward and efforts can
explain not only the choices you make but

also the movements that follow OK but
to move forward

with this we need to know what the
energetic costs of movement actually are.

And when it comes to locomotion scientists
have been measuring metabolic cost for

decades OK And they've observed
a consistent relation between

the rate of metabolic expenditure and
walking velocity so

they've see they've showed many many times
that metabolic rate increases linearly

with velocity squared OK now
velocity is distance over time so

we can reply this here because I like
to put things versus duration so

this is metabolic rate versus duration and
so you see that if you were to walk one

kilometer you know the longer the duration
the lower the metabolic rate so

the metabolic rate decreases with time for
a fixed distance OK now this is for

walking but what about reaching OK So
up until this point there'd been no

measures of metabolic rate in reaching
PE So we thought let's do an experiment.

So my post back to Helen and
I brought fifteen subjects in civil out

well Helen Helen brought fifteen
subjects into the lab and

had them make plainer reaching movements
across a range of speeds very slow

slow medium fast and very fast OK and

as they reached in each block we measured
metabolic rate via expired gas analysis

in this is the data so this is rate of
energy consumption in Joules per second.

Or Watts plotted versus reach duration so
this is the data for

a ten centimeter reach so
it decreases with increasing duration and

now we did two other distances twenty
centimeters and thirty centimeters OK So

we want to do is we want to promote
our eyes metabolic rates as a function

of distance and duration so
we use an equation similar to what was

observed in locomotion and
we fit the data to it.

And we found that it fit the data rather
well and now this is metabolic rate

we wants what's When I showed
you the utility equation

the value the variable there is not
metabolic rate it's metabolic cost

to the total energetic cost of a movement
of a given distance and duration so

if we want metabolic rate metabolic costs
we need to multiply rate by duration and

we get an expression for total movement
energy which looks like this and.

And explains the data
well as you would expect.

Our rates so now we have an expression for
movement energy as a function of distance

in duration which means then
that we can take our utility.

Function here and replace that term for
effort with our newly or

newly determined expression for movement
energy Ok so now we have a movement

utility in which effort is represented
objective leak as the metabolic cost.

So I want to go back to the data for a
minute and highlight something interesting

so it's interesting that there appears
to be a metabolically optimal movement

duration so fast movements have high
costs and as you move more slowly these

costs decrease but as you as you move
slower still these costs increase again so

there seems to be a metabolically
optimal speed so a speed non-zero

duration that minimises that minimizes
them medical costs are non-zero.

That minimizes metabolic costs OK And
this is surprising but

we can obtain an expression for this OK
for this energetically optimal speed and

so we have a prediction now for
how fast someone should reach if they were

only concerned with
minimizing energetic cost.

And we can plot that prediction here so
this is the duration that

minimises energetic cost
plotted versus reach distance.

And then we brought the subject in and
the same subjects and

we asked them to reach at their preferred
reaching speed OK Actually we did this

before the experiments and
then we did the metabolic testing so

we had measures of the preferred
reaching speed at each distance and

we see that the duration that minimizes
energetic cost does not predict how

fast people prefer to reach so people
reached faster than energetically optimal

OK So all right so let me summarize
what I've shown you that so

far we have measured metabolic
cost in reaching and

found that it decreases with duration and
increases with distance.

Interestingly metabolic cost of walking
is that exhibits a similar relationship

also there is an energetically optimal
reach speed but people prefer to

reach faster than energetically optimal
OK suggesting that there's something

other than effort that is influencing
a person's choice of reaching speed.

So if we go back to this utility function
we see that reward can discount effort

costs so maybe when you're moving
to rewarding items like the cookie

there increased value discounts the motor
commands resulting in faster movements so

do we have any evidence that reward
influences the speed of reaching movement.

So to test this idea we did another
experiment this is my graduate student

Eric Summerside is about ready to graduate
hopefully he'll defend in a couple months

which cost so Eric brought
twenty subjects into the lab and

asked them to make horizontal out and back
reaching movements to four targets that

were equally spaced around the perimeter
of a ten centimeter circle and

there were no constraints
on their accuracy and

in each block of one hundred trials
one target one sector was consistently

rewarded while movements to
the other targets were not OK and

what I mean by reward is that once they
cross the target the target would explode

there would be a nice pleasant sound in
the subjects saw that they had gotten four

points and they just they didn't get this
when they reach to the other targets so

for this subject here I'm
plotting their velocity traces so

you can see the velocity trace when
the target is rewarded is in red and

when it's not rewarded is in blue this is
the same target just in different blocks

and you see that when that
reward target is rewarded has

the subject reaches to it with
a greater peak philosophy and

then when it's not rewarded in this
was consistent across subjects so

subject consistently increase
their significantly increase their

peak philosophy when reaching to rewarding
targets and reduced their movement

duration OK So it suggests these results

suggest that targets with a greater reward
this increase in value discounts the motor

commands even though it's only four points
and I sound resulting in faster movements.

So these results support the idea that
reward can influence movement OK movement

speed but we still need to describe
the relationship between reward and

utility so a large body of work
in psychology neuroscience and

decision making suggest that
reward is discounted by time.

Hyperbolically So based on these findings
we're going to represent reward here's

Alpha and we're going to discount it
hyperbolically as a function of duration

where gamma is the temporal
discounting factor and T.

is the movement duration.

And now we're going to combine it with the
effort term to obtain our movement utility

and one way to represent
utility is to simply take

the reward that's temporally discounted
and subtract the movement cost

from it so that's one way to
represent represent utility.

But we have found that a utility that
explains does a better job of explaining

the data is one in which effort like
we're award is discounted by time.

So for now I'm going to move forward with
this utility where not only is reward

discounted by time but so is efforts
kind of think of it as it's the net gain

that is being discounted by time and
if I have time or

be props in the question and I can I can
explain to you more the the data sets

the multiple data sets we found that
support this function over a function in

which effort is simply subtracted from
Award and not temporally discounted but

for now we're going to move the with this
so what we have here is a utility that

tells us whether one movement or decision
has a higher utility than another so

that's the one you should choose so
the cookie may have a higher J But

it will also tell you that for a movement
of a given distance its utility is

also going to depend on how fast you make
that movement so how fast should you make

that movement let's look at an example
movement here with a distance of one so

this is a plot of utility versus movement
duration Here's the reward term.

Reward is high initially but it is
discounted with time here's the negative

effort term effort is high for very fast
movements it costs you a lot to make.

Of minutes but it decreases with time now
if we add them together we get a utility

and that utility has a peak so
very fast movements have a high reward but

they cost you a lot of effort very
slow movements cost you less but

the reward is no longer as valuable so

this gives us an optimal duration that
is neither too slow nor too fast and

together movement utility in the optimal
duration yields a number of predictions.

So first what happens when you add
reward when you increase reward So

here's the utility of a movement with a
reward Alpha equals one thousand great and

there's its optimal duration Now here
is the utility of movement we've

doubled the reward Alpha
equals to thousands and

so these equations predict that with
increased reward utility increases in

optimal duration decreases so you should
prefer the rewarding option more for

the Cookie Cookie has a greater day and
you should also reach faster

to it OK So this is confirmed by
the reward studies I described earlier.

So in reaching.

And it's also been shown in
the Qods book in monkeys and

in humans OK Now second
the equations predict the following

are going to have is going to happen
when you have a greater effort cost so

we're going to increase the effort
cost by increasing mass OK So

this is a movement made moving
a mass that is two kilograms and

here is the utility of making
a movement of mass four kilograms OK so

so as you move increasing mass utility
decreases so you should prefer At last

the optimal duration increases so
you should move more slowly OK So

the question is can we examine
this in the context of movement.

So let me rephrase this
question can you to a T.

were effort is.

Represented as metabolic cost explain mass
based changes in reaching speeds OK And

this is really a three part question we
first have to know what the effect of mass

is on the metabolic cost of
reaching then we need to know what

is the effect of mass on preferred
reaching speed and then finally we can ask

if metabolic cost can explain mass based
changes in preferred regions OK So

let me walk you through this to answer the
first question we measured metabolic cost

of subjects made reaching movements with
added load on there are OK and their arm

was supported against gravity they made
ten centimeter reaching movements to four

targets equally spaced around the around
the perimeter of a ten centimeter circle.

And we added four different
loads to their arm

two point five kilos four point five
six point five and ten point four and

so they would reach for five minutes
with a constant added load and

as they did so we would measure
metabolic rate the expired gas analysis.

OK And within each mass condition we would
have them reach six different speeds so

we would measure metabolic rates
different speeds and different masses.

And here their data so
metabolic rates on the Y.

axis versus duration so
as you can see metabolic rate

decreases with increases in increasing
duration what we found previously and

we see that metabolic rate
increases with added load and

when we parameterize this relationship as
a function of mass and duration we find

that metabolic rate increases with mass
to the Power Point seven OK So our next

question is what about the effect of mass
on preferred reach can magics and again we

tested this directly in the lab we had it
twelve new subjects come into the lab and

make or just horizontal out and stop
reach movements to four targets again.

Equally spaced on the perimeter of a ten
centimeter circle and in each block of two

hundred trials we would add
a different load to their arm OK And

in this case we added a mass of
either three five or eight pounds and

we order a randomized order across
subjects and importantly in this case

we didn't tell them how fast to reach
we just let them choose their preferred

reach velocity so we could just quantify
how mass affected their movement velocity.

OK These are the average velocity
traces across the objects

the black is zero added mass
the red is eight pounds added mass

so added mass significantly
reduced peak velocity and

we found that when we saw
this across subjects' so

peak philosophies reduced
with added mass and

movement duration
increases with added mass.

Writes OK So
question one we measured metabolic

rate as a function of added mass question
two we measured preferred speed as

a function of mass OK so we can now turn
to our last question our third question

does metabolic cost explain the can
a matter of math based changes and

preferred movements OK so here is
our preferred movement duration data

OK Now according to our theory the effort
of so stewed with reaching is specified

by the metabolic data which we can now
estimate without any free parameters.

Then we can compute the expected
duration of each reach by estimating

the only free parameter in our utility
function which in this case is Alpha and

we set a gamma equal to one OK now the
circles there are the data with standard

error and the line is the model prediction
and as you can see it can occur.

For the data in the data rather well.

But let's also look at so
movement preferences can

be explained by representation of
effort as metabolic cost OK but

we're also interested in other
representations of effort OK So

for example in motor control it is
often assumed that effort is the sum

of squared torques joints works
required to generate the movements so

in this representation effort would
increase quadratically with mass and

when we try to explain the data again
only fitting alpha in our utility

function we see that this representation
is inconsistent with the data

there's a much steeper change in
movement duration as a function of mass

OK Now another alternate
cost in ones is one seen

in the study of locomotive preference so
and locomotive preference when

people study preferred walking speed they
find that there is the preferred speed

corresponds rather well with with
a speed that minimizes metabolic cost so

in that sense the utility there is a
utility that is only metabolic cost OK So

we asked Well could a utility that was
only represented as metabolic cost

could that explain mass based changes
in preferred reaching can Magic's.

And the black line there is the prediction

if you were to only care about metabolic
costs that's how fast they should reach so

it actually predicts people should
reach faster than they were

so let me summarize in this last study so

we found that people choose to
reach slower with added mass and

preferred movement speed can be
explained with the utility that

represents efforts as
the metabolic cost of the movement.

OK So in that experiment we added mass but

there's an even simpler more naturalistic
way to alter effort and that's by moving

by reaching in different directions so
the human arm has a mass distribution

such that it resembles a heavy object when
you're reaching in certain directions and

the lighter object when you're
reaching in other directions OK so

in a classic experiment back in one
thousand nine hundred four quad guess and

colleagues asked subjects to
make horizontal rapid movements

centimeter rapid movements and importantly
they could choose whatever speed they

wanted three chats OK And what's
interesting is they found they found that

people would reach at sixty centimeters
per second in some directions but

only thirty centimeters per second and in
another direction so there was a two fold

increase in preferred reached speed simply
as a function of the reach direction and

again these people have no time
constraints on their movements.

So so the question is can we use
our utility equation to consider

these observations so according to our
theory the effort associated with reaching

again is specified by the metabolic
data OK which sets the parameters in C.

to fix the values so we use the inertial
properties of the arm to estimate

the effective mass of the hands as a
function of the direction of the reach and

that and that's how we
determine what the premier M.

was then we computed the expected duration
of each reach by estimating the only free

parameter in this utility function in this
case the Alpha because we said get me one.

OK.

And the resulting peak velocity
is shown here in sighing and so

it has a direction dependent pattern
the velocity was largest for

the directions for which the effective
mass was smallest So the direction

dependent speed of reaching movements
could be accounted for by to a T.

in which effort was objective we measured
via the metabolic cost of the movement

now if this framework is useful
it shouldn't just account for

the speed of our reaching movements
it should also say something

about the decision decision making
associated with those movements So

in other words it shouldn't just tell
us how fast to reach for the cookie

It should also tell you that you should
choose the cookie over the apple

now I showed you earlier that as
mass increases utility declines for

all durations OK that means your
preference for a certain option

is going to be greater if it has less
mass keeping everything else constant so

the difference in utilities should predict
the probability of choosing one option

over another so we tested this prediction
so and that's how we have been sky and

colleagues few years ago instructed
subjects to make a fifteen

centimeter out and back movements
in any direction but they were not

provided with the targets OK so you just
have to reach out fifteen centimeters you

could reach in any direction you like
OK so their choices are descript

described by a probability distribution
shown here for the left and right arm.

OK So as you can see there are some
directions that are more preferable

over another OK there were
chosen more frequently and

we can predict these probabilities with
our framework via movement utility

as a function of reach direction OK so for

each possible movements we calculate
its utility and then we calculate

the ratio of this utility to the sum of
utilities across all movement directions

to obtain the probability of
a reach in a given direction and

then estimating the only free parameter
here alpha we use the movement utility

equation to predict subject choices and
which is shown here in science

OK so this same utility that
described the velocity of.

Movements as a function of movement
direction can also describe the movement

choices that people me made when they're
free to reach and any direction.

So let me summarize these last
two these last few studies so

we found that expectation of
reward increases reach speed

result that is consistent with
our utility framework and

subjects prefer to reach to stimuli that
require transport of smaller mass and

they do so with a higher velocity OK and
interesting Lee kind of a side note

people prefer to reach slower in this
case than metabolically optimal.

OK so now I want to take a step back and
remind you of this point that I brought up

earlier so an important aspect of our
theory is that when you compute utility

both reward and effort are temporally
discounted OK Now if someone

if you search through the literature
you're going to find examples of

both types of utilities one in which
rewards discounted by time and

you subtract effort from it maybe even
divide effort divided by effort or

you may find a utility where effort
as well as discounted by time and

ultimately the question is which function
can best account for animal behavior.

So let's consider the simple task
of producing an isometric force for

duration T.

case you're just going to produce
an isometric force for duration T.

in order to an acquire a reward so
it's been shown empirically that and

the energy required to generate
an isometric force is linearly related to

the Force time integral OK so
the utility of the action is going to be

that force time integral discounted
by time according to our

utility framework now if we just
consider the case of a constant force.

We can simplify that effort utility so
the integral is just F.

times T.

when again discounted by time now what's
interesting about that bottom equation

is that as T.

increases.

It doesn't continue to grow but
it approaches asymptote and this

makes an unexpected prediction that as
the duration of force production increases

subjects' will become increasingly
indifferent to duration so as you produce

a force for longer and longer you're
going to care less and less about time.

OK So in two thousand and
four Konrad Corning and

Daniel will perform the pioneering
experiment where they ask volunteers to

produce a given force for
a given time period a or

and then to produce a given force be for
given time period B.

and then they ask them which one did they
prefer which one did they want to do

again.

And the data of the change represented
in different points were each line

Connex Force time pairs
the subjects felt were quick glance

were quickly effortful or currently.

Effortful OK So
let's take this part of take this apart so

this red line here is connecting a series
of force time pairs what this means

is that this point here is generating
a high force for a small amount of time

in subjects felt that that was equivalent
to generating a smaller force for

a longer amount of time which makes
sense lower force longer time

Force time interval that makes sense but
those it makes sense is that as

the force as the force as the duration
increased the force that they

found equivalence did not decrease but
rather plateaued OK so for

holding it longer they held the same force
longer they still felt it was equivalent

and they observed this across
a range of force levels so

this is a surprising result but
it's one that can be explained

if effort is represented as
temporally discounted metabolic cost.

And shown here so
we did our simulations so

this is our utility function so you
have your Force time interval on top for

constant force and it's discounted by
time and as you can see those force those

Force time pairs do not continue to
decrease but they rather plateau OK.

And here so if you were to take
the standard representation of effort

in motor control which is for
squared times time.

You would see that those forced time
pairs are going to decay to zero as you

as you would expect and
even if we consider a case where it's just

the forst time in a row again we find
that those lines decay to zero in case so

this is then consistency with
the data remains whether forces

are quadratically penalize or
linearly penalized the key thing here

is to temporarily discount the force
of the Force time interval so

in February a consequence of temporal
discounting is that the utility of effort

doesn't continue to grow but rather
reaches the plateau an asymptote and

people become more and more indifferent
to time with increasing duration.

So let me summarize all
the results that I presented so

in both walking in reaching We found that
metabolic rate increases with movement

distance in decreases with duration we
found that there is an energetically

optimal reach speed and in but in that
experience people prefer to reach faster

than energetically optimal we found that
subjects move faster towards a rewarding

stimulus compared with a non rewarding
stimulus they prefer to reach for

stimuli that require transport
of less mass and they do so

with higher velocities and finally as the
duration of generating an isometric force

increases the utility of effort did not
continue to increase but rather plateaued

which is consistent with the utility in
which effort is the discounted by time but

inconsistent with the utility in which
when effort is not discounted by time.

Alright So in summary what I
presented here is a framework

with which to consider
both decision making and

movement control under a common rubric and
within that rubric.

Effort is represented as metabolic cost
we parameterized effort as a function

of movement duration mass and
distance and both reward and

effort are discounted by time and when we
represent effort as metabolic cost and

consider this utility framework then
this utility framework can reveal

results that are consistent with
the maximisation a common utility

so far and
I want to mention a few limitations so.

There's still a lot of work to be done so

we assume here that total movement effort
is discounted at the planning stage

whereas there could be a continuous
temporal instantaneous temporal

discounting of movements pain that's
something that we're we're looking into.

Also.

You know how can we talk about motor
control without considering probability so

that's something we still
need to incorporate so

in more realistic scenarios there's going
to be the probability of her ward and

in movement that is kind of votes
reflected through your movement

variability or your accuracy so
that's something that we need to consider.

We also presented you with that example
of the Apple versus the cookie.

I didn't give you I didn't give you
a single experiments that actually

did that that looked at the choice as
well as the speed of the movement you

believe again these are these are looked
at independently so we need to design

experiments that are going to look at both
the choice and the movement simultaneously

and just to bring it full circle I want to
return to the question of movement slowing

and Parkinson's disease so within this
framework we can make a few hypotheses for

why individuals with Parkinson's disease
may choose to move more slowly so

one the loss of dopaminergic cells
may lead to reduce reward valuation

compared to healthy individuals so

they may not find the action as rewarding
which according to our framework is going.

To lead to slower movements OK Also I.

Mean has also been implicated in effort
valuation as well as reward valuation

OK so so P.T. patients may actually
with the loss of don't mean may

lead to an overvaluation of effort that
is required of the movement which would

according to our friend work which
will also lead to slower movements and

then finally it could be that
the objective effort cost the actual

metabolic cost of the movement is
higher in Parkinson's patients OK And

and we don't know that we don't
have that data yet so and

according to our framework This would
also explain slower movements so

these are all questions that we're going
to we've started to pursue We have a new R

one just in last April April so
we're excited to be moving forward with

these with these questions to look
at the futility framework not

just in healthy individuals but
also also individuals with Parkinson's.

So I'd be remiss if I didn't think
the many many students that have helped me

collect this data and put this framework
together so Eric Summerside and

Gary Bruning are grad students
currently with me at C.U.

Boulder my going to O'Brien is
the post doc that worked on

the study She's currently
at Northwestern R.C.C. and

Helen was started started collecting
this data long ago with me and

she's an assistant professor at
the University of Central Florida and

my collaborator Reza shadier at Johns
Hopkins University we've been working on

putting together this framework for a few
years now and it's been in a lot of fun of

course funding so that we like to thank
you and be happy answer any questions.

The metabolic on the metabolic data.

So are you talking much utility curve that
the metabolic the optimal metabolic curve.

Or that there's an.

Aha.

It's and are you asking whether it aligns
kind of whether the they're very below

the kind of covered the optimal
metabolic optimal duration.

Right right so you know I mean I like
it's it's an interesting point though

the fact that the utility has different
slopes on either side of the optimal and

we haven't probed that to look at you know
either sensitivity to it in their choices

and the optimal whether the choice
they choose their biases

just to maximize the top of the chance
that they're going to be on the optimal

We haven't we haven't looked at that
at all that's an interesting question.

But.

I've been increased or
maybe less variability so

all of our experiments are yeah we do them
we the reaches are multiple trials because

we want to rule out any learning effects
reduce learning as much as possible so

it's an interesting question when somebody
performs something optimally first of all

how do you define something as sub optimal
but is that because you know increased

variability in their movements is that
because they haven't learned the model

the effort model as well or they haven't
learned the dynamic model of their of

their of their own limbs as well so it's
really it's just an interesting question

overall so why you know why are athletes
so good at what they do is it because they

have reduced the variability they're more
accurate let's say someone who you know

back I'm back in the good good old days
is it because he has less variability or

is it said because he's better
at identifying the optimal.

That's as far as I know there
are any things that really

been probing that very well that one.

In which experiments.

All of this of.

I never assume humans are rational.

But we do assume that there we bring
them in a kind of a base state Yeah so

we don't do we don't manipulate affix we
don't scare them there are we do have

ongoing experiments where we look at the
effect of threats on decision making so

we have a controlled condition low threat
versus a high threat environments but

in all these explain but
in the experiments I presented today

it's a very neutral lab environment and
we do make this assumption that

they're coming in with the normal level of
stress you would expect in an undergrad.

But.

Yeah and I completely agree so
when when I was starting down

this line of research I looked at a lot of
the decision making papers and more and

more people are interested in effort and

everybody has a different way to
quantify quantify it so whether is.

I symmetric force or
was number of key presses or

whether you use your pinky versus your
index finger one was more effort full.

And of course there's all whole world
of cognitive efforts literature so

for us for me I wanted to start with
terms of physical movements and

I thought medical cost is a good place to
start but it's no means a good place to

to to keep it there so there are many
things that could very right there's

a subjective perception of effort so even
there's there's just that psychological

some you know ten joules may feel
differently to me than it feels to you and

also depends on my physiological states
it's really interesting that you

bring up this control so we're thinking
up experiments now to look at you know

movements that have the same mechanical
effort or same physiological effort but

maybe rather you know there
instead of using two joints or

using one joint is that simplify
Is that another form of effort

that something you're going to
be adding to the equation so

those are all in cognitive effort we've
been trying to read more about that and

find Look at how people are quantifying
that and also to see whether we can kind

of compare it you know put cognitive
effort on a scale with physical

efforts and map them onto each other.

What do you mean by preferred
I'm interested in and.

Thing related to movement but what is
what is the preferred movement pattern.

Here.

Or.

Was here so if you are this.

Way.

But.

Let's see her.

FACE.

More.

People might.

Like.

Based on.

Her No no that's a those are all great
points so one thing that may be affecting

your decision to use one can rig
configuration over another is

how accurate you're going to be used one
can figure for another so one the more

of the well practiced movement you're
more accurate less practice you're not so

you're going to choose the and it may not
be dictated by the physical the physical

effort that I would measure metabolically
another interesting question is strength

so if your you know your flexors vs your
extensors or one arm is stronger than than

another so maybe it's not metabolic costs
in that case or maybe it's your capacity

to perform to produce force those are all
so again it just opens up all these

questions we're providing kind of a base
So here's metabolic cost Now let's And

there's already more studies coming
out like in this recent to this year.

Finding that you have people don't
necessarily make decisions according to

a meadow they don't measure
metabolic costs but

it's true that they say it's not
according to metabolic cost seems people

have a preference for I can remember
moving in towards the body versus out

towards the body something like something
like that which adds another factor.

In your.

Choice.

But.

It was very.

Well.

It would be.

So.

Big.

You know what.

You.

Were.

Very.

Very.

Well.

I don't remember.

Yes or.

Yeah I'd have to see how they were
determining what was actually optimal

I mean for our part what we would do
would we would look at probably so

accuracy gives you some probability
of reward right that's that's

kind of an just another way of saying
accuracy so how do they trade off

that probability of reward with
the with the decay of value and

reward without a time so so it's hard to
say what would actually be optimal so

I'd have to read the studies
to know exactly man but

we would expect that as you know as
you reduce the probability of reward.

Then we have very specific predictions for
how that you chile function would change.

And no no not necessarily I mean
it really depends on how rewarding

it isn't what that what they're
variability of is looks like.

But I've been great.

For.

Thinkers.