September 16, 2020

NeuroChat with Chris Berka #004 - Featuring Dmitri Poltavski & Thomas Petros

NeuroChat with Chris Berka #004 - Featuring Dmitri Poltavski & Thomas Petros

[00:01 – 05:02]

Chris: So, welcome Tom and Dmitri. It is a pleasure to have some time to chat with you. This is part two for Tom but we are just getting started here with Dmitri. So, Dmitri, if you could just give us an introduction; tell us a little bit about yourself, your background, your training, your current position, and then, maybe a little bit about your research interests.

Dmitri: Okay. Well, first of all, it is great to meet you. I have read some of your papers and they were the foundation for our research, and the system that we are using in our research is the IBM system, both the extend X24. I am trained as an experimental psychologist. I am actually the graduate of the University of North Dakota. For seven years of 2003, I worked for a medical school as a research analyst and then I got hired, back at the psychology department of the University of North Dakota, in a teaching slash research position- faculty position. And, I have been primarily teaching while things like perception physiology of behavior and psychophysiological measurements, biological basis of behavior and multivariate statistics. My research interests are, well, have been shaped by going to too many hockey games and hanging out with them optometrists. This was suggested that we should start testing those hockey players with some physiological tools; looking at some ocular motor functioning of their visual system and see how that corresponds to their performance. So, we started doing that and then, I incorporated more and more toys into our assembly of tools that we use. And pretty soon, we started looking at EEG as well as visually evoked potentials, APs. And, we got funded by the North Dakota department of commerce, the so-called research indeed program, where we looked at a youth athletes, youth hockey players; those with a history of concussion and those without the history of concussion. That was a big study so we baseline assessed them on a number of instruments, including what they call the Nike sensory station, now known as the synaptic sensory station. It is by the same Nike group but apparently, after 2015, there was some internal issues, they closed down the program. But it is kind of like a psychomotor type station that assesses multiple visual motor skills. And, our first baseline assessment, we used ABM's system to look at, perhaps, baseline differences between those with a history of concussion and those without the history of concussion, simply by looking at their theta to gamma ratios at the Fz site, during visual motor tasks that included things like go, no go perception span, hand-eye coordination, all that. So, there is a kind of a working memory with a temporal, constrained component. And the reason we were using that ratio was because of previous studies, when they tried to time lock gamma cycles within the theta cycle and they were able to predict even working memory span. We thought that in the absence of, perhaps, behavioral differences on reaction time and accuracy indices of their performance, we could find some type of EEG deficits; and sure enough we did. And we published in scientific reports that they had lower theta to gamma ratios, suggesting working memory deficits.

Chris: Yes.

Dmitri: Yeah.

Chris: And so, just to clarify, when you had a measurement of working memory, a behavioral measurement, along with the EEG measure.

Dmitri: Yeah. Simultaneously.

Chris: The EEG measure was more sensitive to the concussion effects than just the pure behavior measure.

Dmitri: Yeah. To the history of concussion, they were all, at least six months after their most recent concussion. Yes.

[05:03 – 10:19]

Chris: Okay.

Dmitri: We found a similar thing with VEPs as well. We looked at their p100 wave and looked at it in the environment of two different types of stimuli; one type of stimulus was kind of like, stimulating their part of cellular tract, and that is a high contrast checkerboard pattern that is reversing at a very low rate. The other type of stimulus was stimulating their magna cellular tract using a very low contrast, like 10 percent contrast, sinusoidal gradients that would reverse at a high rate. What we found with their VEPs is that their p100 was, both the amplitude and the latency, was significantly smaller.

Chris: For both of those stimulus sets you saw? Latency and amplitude.

Dmitri: Yeah. Suggesting that they have some persistent visual deficits in magna cellular processing that has to do with motion detection and anything that is relevant to motion processing. So they were not as efficient.

Chris: Right. And was this also… what was the window post-concussion for the…?

Dmitri: Yeah, six months.

Chris: Okay. And then, did you follow those participants?

Dmitri: So, yeah. Good question. So we actually trained them using two different protocols of, what we call standard optometric vision therapy that targets ocular motor training of the ocular motor system, so-called the hardware, your psychiatric eye movements, your emergencies as well as accommodation. And then, we fold it up with what they typically use in sports division training; that is more kind of like the intersection of your visual processing with attention, with decision making, all of those things. And so, for one group, so all of our players completed, I think it was eight weeks of training, no actually 10, considering that we also tested them for one week. Yeah, 10 weeks of training in both type of programs, but we reversed the order for half of them. So, to see if there was any order effect as well.

Chris: Right.

Dmitri: And also, collected their VEP data, their AEG data at the point when we reversed the training order, so they switched them four weeks and four weeks like, the blocks or if you want to consider five weeks and five weeks, and tested them again. And that is where I am, right now, analyzing the data. I have just finished analyzing the VEP data and it is looking good; just like we suggested. In fact, one type of program was more beneficial for retraining of the magna cellular pathway than the other.

Chris: Meaning, you started to see some restoration of the p100 and the latency was not as late.

Dmitri: Right.

Chris: Did you also look again at the working memory and the…?

Dmitri: That is my next series of analyses, so I will be looking at that as well. Yes.

Chris: Interesting.

Dmitri: But this is not just the only study that we did with your system. My graduate student, who is now working for Boeing, he just graduated and he is a human factors engineer now, but yeah, he was looking at air traffic controllers, at Kyle. Yeah, you know Kyle.

Chris: Great guy.

Dmitri: Yeah, he is brilliant. He helped us out, quite a bit, in processing all our data and analyzing the data.

Chris: So, he was also working on the concussion study or he had a completely different study as well?

Dmitri: Yes, he had his own, where I participated in an advisory second author type capacity so, but he was looking at air traffic controllers as well as at, kind of like a simulation of the MATB; you know, that application, the NASA MATB battery. And he was looking at workload, really that dusky's thing and engagement. and what we did find in one of our studies, using MATB that links his type of research to mine, was that we used a measure called convergence insufficiency symptom survey; it is like a 15 item questionnaire that is a really good screener for ocular motor issues, like accommodative insufficiency or convergence insufficiency that you oftentimes see, not just in, say kind of, ADHD population.

[10:20 – 14:59]

Dmitri: There is a huge comorbidity of ocular motor disorders and ADHD, but you also see it as a persistent deficit of concussion; that the ocular motor system becomes inefficient in I-team and emergencies, in eye movements etc. and what we found in that study, when we equipped them with EEG during completion of the MATB task, so half of their task was automated, half of their tasks they had to do some basic monitoring of the system. And so, by the time of the automated component, it is like a 40 minute task, the last 10 minutes we analyzed it to see if they are going to develop kind of like, boredom and start to idle, so their engagement goes down.

Chris: Right.

Dmitri: Well, we did not analyze ABM's indices of workload and engagement, but we simply used the alpha at POC, and it was diminished for the automated condition, in the last two minutes of the task. So, which is kind of interesting because we are thinking now, of using TDCS, Transcranial Direct Current Stimulation, to see if we can modulate those things with different type of stimulation protocols.

Chris: Right. Have you done work with TDCS?

Dmitri: Yeah, a little bit. Just in, kind of like, a pilot studies. I did a workshop at Baron. Was it baron? The Harvard med school, center for transcranial magnetic stimulation. Yeah, I did a workshop there, on brain stimulation and have tried to incorporate it into some of my studies.

Chris: Interesting.

Dmitri: Finally, the other line of research, since I am kind of like the psycho-phase guy in our department, when professors wants to add another line of evidence to their behavioral cognitive protocols, they would ask me to come…

Chris: Come to you.

Dmitri: Right. So, one study that we did with the elderly actually, we were looking at positivity bias in memory, more towards recall of positive memories as opposed to negative ones, in old and very old folks. And we also looked at their working memory and used an ABM system and actually used your guy’s indices of workload and engagement, and to compare the groups and the tasks. So it was a between group and within task type of comparison. So, what we found in that study that well, while the groups did not really differ much, in terms of the memory, in terms of the workload, the workload was quite predictable from the demands of the task and was nicely reflected in your output. So, cognitive load and engagement, like the highest engagement was on a task where we would present them with emotional stimuli, so a bunch of pictures, and the lowest was when they were having to do some type of mental arithmetic type tasks.

Chris: And this was for age 65 and up? Or…

Dmitri: I think, one group was up to 75 and the other one was like 65 to 75, one was 75 up. Yeah, and then, the one that we did with Kyle and air traffic controllers; they had four distinct… and it was a kind of like, a simulation protocol that they use in the aviation department. And so, you have distinct phases of workload, really, when it is really easy, medium, and high. In addition to ABM's indices of workload and engagement, we also used pupilometry, eye tracking, and measured pupil size; and there was a really nice correlation with people size and...

Chris: Yes, and workload.

Dmitri: Yeah.

Chris: Yes, we have seen that as well. Yeah, we have been doing a lot of work with pupilometry, recently.

[15:01 -20:07]

Chris: I think the eye trackers have gotten much better over the years, you know we have been using the Tobi and finding really good results. We have been looking at social media posts and online videos and, you know, looking at the types of responses that get people's attention and keep their attention and as you can imagine it is you know the more salacious or evocative material but we get a nice correlation between some of the EEG measures, as well as the pupilometer that you know suggests, just how engaging and arousing I guess you know the different stimuli are. But it is nice to use the combined metrics for sure.

Dmitri: Yeah, yeah. So, I mean, your guys’ metrics have been useful as well. Again, I just, I think the more studies were on more validated they become. But I think that...

Chris: I think your concussion work is really important and very relevant to the discussions that we are having today about athletes, whether they are, you know, professional athletes down to, you know, little leagues and you know should my Should I allow my child to play sports and at what age, and how can we assess? What is happening to the brain? When there is a concussion? And I do not think we have, as of yet, great biomarkers that suggest okay now is a good time to go back on the field your, you know, back to normal. So I think anything you could do in that domain will be greatly appreciated you know by the sports community and, all the concerned parents. It is tricky research because you have to follow, you know, from the concussion, you know, for as long as you, you know, is feasible and those kinds of studies always take a lot of time and are expensive.

Dmitri: Yeah, absolutely no.

Chris: But it is interesting that you are doing some interventions as well, so when you did the ocular motor interventions how frequently, did they have to, did they come into your lab to do it or is it to do at home.

Dmitri: My wife is a visual therapist and supportive as a trainer.

Chris: Okay well that is a good collaboration.

Dmitri: So we put her on the grant, they did it for us.

Chris: So these are the thing that interventions that she does routinely.

Dmitri: Yeah, we just created a protocol for her based on what she does and our supervising atomic trust is my research collaborator that, with whom you know we started doing all these types of studies so it was a... it is a very good collaboration since I am kind of like the Science guy and they are all on the clinical side. And they have all the equipment as well it is not like we have all kinds of toys here and they have all those type of stations and gadgets that oftentimes just sitting around and not being used.

Chris: Yes. Oh, yes, definitely. Does your wife perceive the need for an objective measurement of these, I mean she probably knows about the outcome because she has worked with them a lot but if she had a relatively simple EEG measure to document the outcome with that for her.

Dmitri: Yeah, so, the VEP system that they are using is deposes. I believe they are the largest one, and they have multiple modules. A lot of them have been kind of FDA cleared for different types of things, like, what the doing for, some just the retinal pathologies that they use. But, so I previously worked with another optometrist who created those magnetic Parvo stimuli. And, and we, and he pitched it to deposes and they created for us. An experimental module, essentially. That is the module we have been using. And now she is actually using my wife is using it in pre and post assessments, and then insurance companies are starting to recognize those VP assessments as well. But, couple of issues from looking and you probably know that as well. That is when you look at those VP data, especially when it comes to amplitudes you see you see a lot of noise, there is a lot of variants there.

Chris: Sure, sure.

Dmitri: Latency is probably a better. Kind of a metric goldmine.

[20:08 -25:01]

Chris: But generally within, within an individual, of course, then you know, ideally within an individual you would have a baseline established measure before they ever hit their head, and then you would be able to track them because generally you know there is a pretty good fingerprint both for the event related potentials as well as the power spectral densities for each individual, but you need to be able to assess them in the intact state and that is not possible.

Dmitri: Which in a clinical setting is not an option because a lot of them they are like WA size WorldCom type referrals, showing off from car accidents, what have you. So the reasonable bet baseline. But, you know, my optometric partner has started actually routinely just running all his patients on VP, just in case you know they have a great.

Chris: That is great.

Dmitri: But definitely, it is not the best, most accurate marker right now. And so, yeah, there is potentially something.

Chris: Really there are no established useful blood or other biomarkers and you can certainly go through both CT and MRI and not see what you might see with the EEG because it is assessing you know the way the neurons are communicating, you know, as opposed to gross structural damage. So we are keenly interested in that area, we have been asked to various times we did a little bit of work with the NFL and a couple other sports teams, you know, is there something you could give us that we could have on the field as an assessment. I do not think we are there yet. But I do think it is feasible, you know, for the future so it is really exciting to hear about your work in that area and hopefully you will continue to develop that. One question that I would like to ask everyone is, if you suddenly found yourself the beneficiary of a very large amount of research funding. What are some of the dream research projects that you would really like to accomplish?

Dmitri: Tom.

Thomas: I already asked, this is yours. I cannot wait to hear your answer buddy.

Dmitri: So well. I really think we are onto something when it comes to magno-cellular processing and different type of pathology I do not think magno-cellular processing deficits are limited to concussion. What we also see now is that it may also be underlying the etiology of dyslexia and the way you should approach dyslexia treatment and standard for it. Often times is phonemics based and really has to do with graphene phoneme type correspondence training. Whereas, more and more study show that they may suffer from similar. A lot of dyslexia may suffer from similar. Magnesium processing deficits and in have very inefficient psychiatric movements, and even efficiently process that motion eye movement related information. So we just got another grant from research indeed that Tom is on it. Where we are looking at.... Basically, comparing the two types of treatments, these are standard, you know the gold standard, standard of care treatment for dyslexia, with magno-cellular train. And we are going to be collecting, you know, EEG stuff.

Chris: That is fantastic.

Dmitri: Yeah, yeah. So with them as well. So, what if I have more funding. We have an F near system. I want to see what kind of correlates we can find with, you know blood oxygenation flow and age information.

Chris: Do you have a whole herd or the frontal.

Dmitri: Well, the gap is the whole half but well I have so many opcodes so we have to kind of like, configure them either depending upon what area. But yeah, I wish we had. We even when we are rich or cheap, we could not afford the whole head. So, and I want to also combine it with TDCS, see how those modulations, how they affect EEG metrics after year.

[25:02 – 30:16]

Chris: Yeah I think that F nears is very interesting, we have been playing around with it ourselves and trying to put the EEG and that mirrors on at the same time which is doable. And certainly nears is going to give you a much better spatial localization. Not as good of a temporal, you know you do not pick up the fast millisecond level time changes like to do with the aging but it does give you a much better spatial localization. The thing I think we are all struggling with because there is a lot of research, now on yours is. We do not have the library of artifacts and how to deal with artifacts that we do with the EEG. EEG is 100 years old, right. So we have had a lot of time to figure out what, how we decontaminate it a lot less time on near so you still get you know if you have gross head movements or other muscle movements. You are still going to get contamination of the near signal and there is no easy ways to get to decontaminate but I know there is a lot of great engineers out there working on it and ultimately to me, I would like to have the EEG and the engineer simultaneously because it is kind of two sides of neural activity basically.

Dmitri:  Yeah, exactly. So you get both spatial and temporal resolution.

Chris:  Right, exactly. Yeah. Tom have you been working with nears. So I do not know if we talked about.

Thomas: No, I have not, that is been Dmitri’s gig. I have not jumped into that at all.

Dmitri: We only use one space so far. So the NIR X system. That is the one that we use.

Chris: Yes, that is the one we have to.

Dmitri: Yeah, okay. Yeah, well their software is not very friendly. I mean you can run like SPM one and two analysis within the software on your subjects, but we have trouble kind of like exporting emergent data.

Chris: Yeah, we have had our share of challenges too. But again, it is a relatively new technology. So you know there is only a handful of manufacturers and, and I do not think you know the software will come along. We do we need a lot of smart graduate students and research fellows who have lots of time to, you know, develop help them develop the software and the tools for analysis.

Dmitri: Yeah.

Chris: So, what do like Tom and Dimitri, what are some of the projects that you collaborated on? Did you work together on the concussion study, I guess.

Thomas: Not the concussion. We work together on the air traffic control.

Chris: Traffic control sure.

Thomas: We work together on the ones I may have mentioned to you where we are measuring EEG.

Chris: Right.

Thomas: And for learning predator training. We are working together on those, I hope now that I have that lab x software and I am getting smarter by the day. When if and when we ever get to run humans. I am hoping to talk him into collaborating on more educational applications of your system.

Dmitri: Well, we right now, we are not running these subjects clinically with a dyslexia grant but you have Thomas also.

Thomas: Yeah and I mean we collaborate on that. I am in, I am also in my spare time. I run a clinic where I evaluate dyslexia and ADHD and learning problems. So I am Demetrius designated evaluator.

Dmitri: Yeah Tom also juggles quite a bit.

Thomas: Yeah. One of those things from the 60s and 70s that you too much on your plate and not smart enough to pick and choose.

Chris: So have you been looking at EEG biomarkers for ADHD.

Thomas: No, no, not yet to be true you may have right?

Dmitri: No, when I was doing my research. When I was a grad student. I was actually looking at cognitive measures and nicotine patches.

Thomas: So we hope to start doing some of that but the literature we have looked at, only looks at biomarkers that I have seen published on during the resting EEG. I have not seen anyone. And I may not have looked more recently, look at EEG as the person does different tasks than vote working memory.

Dmitri: I think they do like especially on corner CPT theta waves and beta waves quite a bit of research published on, all the stuff that we use back when we were just trying to understand what the EEG was all about and your skies one electro and you know, he said, we use that in one study with corner CPT and ADHD symptoms.

[30:17 – 31:29]

Dmitri: we would use those symptoms, by making subjects where minus diopter lenses, so it can be harder for them to focus. And that will take energy away from processing. Well, the signal to actually decipher the signal to the brain. And we will look at all. You know that one electrode EEG frontal as well as accommodative lag we had a pretty sophisticated Wham 500 automatic refractor. That would measure the accommodative lag, where they are focusing at you know millisecond by millisecond. What we found was that increase in error rate and other type of clinical indices.

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