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Alison Llave - Senior Research Project Presentation
1. The Excitability of the Motor
Cortex for Planning
Dexterous Manipulation
Alison Llave
Advisor: Mr. Paul McClernon
On-site Mentor: Dr. Marco Santello
May 11, 2013
BASIS Scottsdale Senior Research Project
2. Research Question
●Biomedical Engineering and Prosthesis
oNeural Motor Control Lab at ASU
●Investigating 2 planning situations
oPosition (P)
oPosition and Force Application (P+F)
3. Research Question
●Is there a difference in excitability when
planning either to position the fingers on an
object (P) or to position the fingers and
apply a normal force (P+F)?
●What is excitability?
o Muscle Excitability vs. Muscle Activity
4. Related Research
●Use of visual cues to anticipate hand
movement
●Modulation of both digit placement and
individual digit forces
17. Ideas for Future Research
●Why is there a difference in the excitability
between P and P+F?
●Brain areas:
oDorsal premotor cortex (PMd)
oVentral premotor cortex (PMv)
●Continuous theta-burst stimulation (cTBS)
19. References
Chouinard, P.A., Leonard, G., Paus, T. Role of the primary motor
and dorsal premotor cortices in the anticipation of forces
during object lifting. US National Library of Medicine.
[Online] 2005 2277-84 http://www.ncbi.nlm.nih.gov/pubmed/
15745953 (accessed Dec 10, 2012).
Fu Q., Zhang W., Santello M. Anticipatory planning and control
of grasp positions and forces for dexterous two-digit
manipulation. J Neurosci 2010. 30:9117–9126.
Gentner, R., Wankerl, K., Reinsberger, C., Zeller, D. Depression
of Human Corticospinal Excitability Induced by Magnetic
Theta-burst Stimulation: Evidence of Rapid Polarity-
Reversing Metaplasticity. Oxford Journals. [Online] 2007
2046-2053.
http://cercor.oxfordjournals.org/content/18/9/2046.full
21. The Excitability of the Motor
Cortex for Planning
Dexterous Manipulation
Alison Llave
Advisor: Mr. Paul McClernon
On-site Mentor: Dr. Marco Santello
May 11, 2013
BASIS Scottsdale Senior Research Project
Editor's Notes
To begin, *click* I chose this project because I knew it would help me learn more about the relationship between the brain and the fingers. And I figured it would be really helpful considering I would love to specialize in prosthesis when I major in biomedical engineering.
For my senior research project, I spent the last 3 months in ASU-Tempe's *click* Neural Motor Control Lab, comparing the excitability of *click* 2 different planning situations: *click* When the subject plans to position the fingers and *click* when the subject plans to position the fingers and to apply a grip force. For the experiment, a monitor shows where to position the fingers for position, or P, and it shows where to position the fingers and if to apply a normal force on the block for P+F. To relate the difference between the two tasks to a broader application, imagine placing your hand on your friend's shoulder to show consolation vs. placing your hand on your friends shoulder and squeezing his or her shoulder to massage them. For this experiment, we're trying to see if the anticipation of these two tasks are task-specific.
So the question that initiated my research was...
*click*
Is there a difference in excitability when planning either to position the fingers on an object (P) or to position the fingers and apply a normal force (P+F)?
We originally hypothesized that the excitability for P+F would be greater than that of P because P+F requires more muscle activity.
But before I begin, *click* let's define excitability. Excitability is the ability of the muscle to respond quickly. It's the anticipation of moving the muscle. It's the planning of an action. Muscle excitability differs from muscle activity in that excitability is the anticipation of muscle movement and activity is the moving of the muscle. In this project, it is measured by how much stimulation is needed for the finger muscles to move.
Previous studies on corticospinal excitability has focused mainly on the visualization and anticipation of hand movement, which is similar to this project I propose which involves the planning of the task of grabbing and object. It was hypothesized that people assume the weight of an object before lifting it. By assuming the weight of an object and positioning the fingers, a subject can proceed with lifting an object at optimal position with the right amount of force.
*click*
There have also been studies investigating the modulation of digit placement and digit forces needed to reduce torque when lifting objects. So when placing fingers on an object, if the object is L-shaped, for example, the fingers would either compensate for the added asymmetrical weight by applying more force in other fingers or position the fingers differently, reducing the force distribution on each finger.
The experiment was tested using only *click* 8 subjects, *click* all right-handed with normal or corrected-to-normal vision. The experiment was approved by the *click* Institutional Review Board at ASU. Each subject was subjected to 6 blocks of 48 trials, resulting in 288 data points. This may seem like a limited sample size for an experiment, but this research was needed as *click* preliminary data for an even more complex experiment.
This chair was custom-made so that when the location of the primary motor cortex was found on the subject, the TMS coil would remain stagnant at that one point. Since all the subjects were right-handed, the TMS coil remained on the left side of the chair, as you can see in the image. And the chair is a lot more comfortable than it looks. With the premium cushioning and neck support, who wouldn't want to sit in this chair? *click*
Transcranial magnetic stimulation, or TMS, is a kind of brain stimulation that doesn't require *click* cutting open the scalp. It is completely noninvasive, making it safer for neuroscientific experiments. The coil of a TMS machine uses electromagnetic induction to stimulate areas of the brain through the scalp. It is used to treat mood disorders such as major depression *click*, but for this project, it will be used to stimulate the primary motor cortex. My entire project revolves around planning data, but in order to collect muscle activity that isn't there, TMS is used to stimulate the primary motor cortex, which controls hand movements.
For the trials, we use this inverted T-shaped grip device. A monitor shows where to position the fingers and if to execute a normal force on the block. The block measures the vertical distance between the fingers *click* and the force applied *click*.
The procedure involved cues and transcranial magnetic stimulation, denoted as TMS. *click*
1. A monitor shows different cues: a Ready cue, 2 task cues for P or P+F, and a Go cue.
2. There is a second between each cue, and the task cues are randomized for each trial, so the cues have only two paths: Ready, P, Go, or Ready, P+F, Go. Once the Go cue is given, the subject can move his or her hand towards the T-shaped grip device. During the Ready cue, the subject recuperates from the last trial to avoid as much muscle fatigue as possible. After one second, the task cue indicates which task the subject will do after the Go cue. Another second later, the Go cue tells the subject to do the task.
3. Stimulation of TMS occurs at one of the randomly chosen times: 500ms after the task cue, 750, 1000, 1100, 1200, 1300, 1400, 1500. We chose these time points because we wanted to optimize the amount of TMS timings we had without discomforting our subjects. Even though the data we need occurs before the movement of the hand takes place, we still try to collect data points after the Go cue. Visual information from the Go cue would take 300-500ms to process, which is why TMS still stimulated after the Go cue.
4. Since there isn't any natural stimulation coming from the brain because the subject hasn't moved their hand yet, TMS is used to stimulate the motor cortex so that muscle excitability can be recorded.
To collect data, *click* electrodes are attached to the skin of the subject where the relative location of the muscles would be. For this experiment, we had 4 electrodes for 4 muscles *click*: *click* the first dorsal interroseus (FDI) of the index finger, the abductor pollux brevis (APB) for the thumb, the abductor digiti minimi (ADM) for the pinky, and the flexor carpi radialis for the forearm (FCR). We chose abducting finger muscles for the experiment because they were main contributors to muscle activity when it came to gripping an object.
*click*
To record data from the electrodes, *click click* we have an amplifier to amplify the muscle activity for the electromyogram (or EMG). In the image, the white box on top is the amplifier while the black box is the EMG. Muscle activity is translated to MEP values by the electromyogram. MEP values, or motor-evoked potentials, are used to measure the muscle activity and excitability recorded from the electrodes. A real-time graph illustrating those MEP values appear on a program *click* called Spike. *click* MATLAB is then used to translate the data collected by Spike.
The data actually represents the stimulation from the TMS. TMS sends a signal to the fingers that causes the muscles to contract inconspicuously. Because there is no actual muscle activity to record since we're investigating planning data, TMS is used to find the excitability of the motor cortex.
So these are the results of the MEP values we received for each task. ADM and FCR were only measured as control variables for the experiment to confirm that the electrodes weren't collecting data from other muscles. The TMS sends a signal to move the hand in general. The coil, although already very precise, still sends a stimulation large enough to move all the fingers. These two muscles, ADM and FCR, were chosen as controls to remove that extraneous muscle activity from other fingers, making sure that the FDI and APB muscles were the only ones being recorded. Also, ADM and FCR are not directly involved in performing the tasks. So we can remove ADM and FCR from data analysis ... *click*
So analysis is reduced from this... *click*
to this *click*
... resulting in this. These two graphs show us the excitability of the FDI and APB muscles when planning for the two different situations. This is what the EMG collected from the electrodes. But what does this really mean?
After days of data analysis and re-interpretation, we get this. The results proves that there's task-specific modulation for both FDI and APB. The graph on the left illustrates the difference between the excitability values coming from the FDI (index finger) muscle. The two lines seem to be quite parallel until it reaches 1000 ms. At 1000 ms, there exists a significant difference between the MEP values for position and the MEP values for P+F.
The graph on the right illustrates something similar to what the left graph shows, except this is for the APB (thumb) muscle. It also shows a significant difference at 1000 ms. Now, you may point out that data points at 1300-1500ms seem to have a significant difference as well. Actually, some data points at that time interval were completely disregarded because data become really noisy. This is because a few subjects actually started to move before the 300-500ms which is completely plausible since visual information takes 300-500ms to process. So, we focused mainly on the time interval 500ms-1300ms.
This graph summarizes the last slide by directly comparing the two planned actions by taking the ratio of the normalized MEP values. By doing so, we can see that the MEP values for the planned action of position are higher than those of P+F. We originally hypothesized that the excitability for P+F would be greater than that of P because P+F requires more muscle activity. But our experiment concludes that planning for P requires more excitability than planning for P+F. Because there is less excitability in P+F than in P, the results indicate a suppression or inhibition keeping the subject from reacting until the Go cue. After reading many articles with related results, we conclude that this is because of the added intensity of the action caused by force application. P also needs some inhibition, but P+F requires more suppression to keep it from moving before the Go cue.
So in short, planning for P requires less excitability than for P+F because acting on P+F needs to be held back more until the Go cue.
So for the future, this research can be applied to the following *click* Why is there a difference in excitability? What causes the added inhibition in P+F? *click* We hypothesize that two areas of the brain--the dorsal premotor cortex (which is PMd) and the ventral premotor cortex (PMv)--are the two areas that we should be focusing on. PMd has been linked to arbitrary force cues and associative learning. It has also been seen to be responsible for the inhibition. PMv is said to be linked to the difference between planning the position of 2 fingers (index and thumb) and the whole hand. So to see if PMd and PMv are responsible for planning force application and position, respectively, we will inhibit each of the areas using the a type of TMS called *click* continuous theta-burst stimulation (cTBS). cTBS causes a decrease of MEP values. In other words, it temporarily shuts down an area and creates a virtual lesion.
All of this research can be applied to fine-motor prosthetics. By further understanding the relationship between the brain and fingers, improvements can be made with the precision of prosthetics today!
*click* The challenges I encountered at ASU were mainly in *click* analyzing data. There were times where I just wasn't able to see the trends because of my lack of knowledge in statistics, such as in using standard deviation and variance to find the percent error of a data point. Then other times, *click* it was challenging to understand what was happening during lab meetings, which were held weekly for other people in the lab to describe what they're working on.
But a highlight of my 3-month adventure include seeing the virtual reality projects they create in the lab. *click* Learning about the different research projects related to my project just helped me learn so much more about how the hands work, and it was incredibly helpful when it came to understanding my own project.
Here are the references I used in creating this presentation.
Lastly, I would like to acknowledge a few great people. *click*
I would like to thank Mr. McClernon for helping me organize and clarify my senior research project these last 3 months. *click*
Dr. Santello and Dr. Pranav Parikh for mentoring me through the project *click*
Mrs. McConaghy for keeping me and all the seniors on schedule for today's presentation *click*
And the Blocks for making this project possible.
Thank you!
