The Gab Lab: Week 5/Last Week

Hi everyone. This is Michelle again, and I'll be posting about my fifth and final week at the Gabrieli Lab at MIT. This week was a little different in terms of less data entry work and more sort of 'one-off' opportunities. On Monday, I spent the morning as usual: updating current subject info on the database, scoring, and recording. However, I spent the afternoon observing an EEG, which meant that I was unable to attend a lunch meeting with Dr. Aaron Matfeld. Each EEG session is roughly 4 hours, as there is a lot of prep work and clean up involved. Nayeon and Calvin first showed me how to cleanse all the electrodes by soaking them for 10 minutes in an ionized solution. Then, we had to gel each individual node, and each node's corresponding attachment slot on the EEG cap.  When the subject came in, we adjusted the EEG cap on her, attached the chin straps, and in addition to plugging in all the nodes, we also attached special nodes under her eyes and ears to measure the vertical and lateral eye movement that I posted about several weeks ago. 

EEG Nodes

EEG Cap

When everything was set, we placed the subject in a dark room and monitored her brain's electrical signals as she performed various language training tasks such as the syntactic/semantic error test that elicits the N400 or P600 response. Next, we ran the first MAL training session with the subject. Since I've mentioned scoring and testing so much in all my posts, here's a quick rundown on how these testing sessions work. Each session consists of 30 vocab questions and 30 grammar questions. During the vocab section, subjects see a picture, and have to say the correct word in MAL. In the grammar section, subjects see a scene, and have to produce a grammatically correct sentence that describes it. A correct sentence has this layout: subject - article - object - article - verb - article. However, there are two classes of subjects and objects, and each class uses a different article (Ihn or Ihd). Furthermore, the verb's article (Ahn or Niy) is entirely dependent on the subject's class.

Example of vocab testing

On Tuesday, I met up with Kelly, the lab's psycho-educational evaluator, to talk about the psychological context of the tests I have been scoring. We talked about the KBIT (IQ test), the CVLT (you hear a list of 16 words and have to recall them over various periods of time/in various ways), the CnREP (you listen to made up words and have to reproduce them perfectly), and the WJ3 Sound blending test. Kelly ran a little bit of the sound blending on me, and I have to say, it was surprisingly difficult. In this test, you have to reproduce a word after hearing a recording of it that has been split up phonetically. For example, the word 'grasshopper' sounded like 'guh-ra-ss-huh-opp-er'. Kelly also talked about the role standard deviation, standardized scores, and normalization play in these tests. 

On Wednesday, Cirkine and I got to shadow Maiya in the hospital! In addition to researching at the Gab Lab, Maiya is a neurologist at Brigham and Women's Hospital in Boston. Maiya showed us around the hospital, and we sat in on an interdisciplinary meeting. During this meeting, which is attended by 30 or so psychologists, neurologists, and neuropsychologists, several of these doctors spend 10 minutes presenting puzzling cases, ranging from memory loss to language problems, that they cannot seem to diagnose or solve. They show brain images of these patients, give us a brief medical history, and so on. Then, everyone in the room asks questions or gives suggestions as to what do next. I wish I could talk more about these cases as they were truly very fascinating, but I had to sign a confidentiality agreement. Because I was away for the day, I missed the weekly stats meeting with the LAP/CASL members, but Calvin was nice enough to send me a video that covered analysis of variance (ANOVA - basically a t test for multiple samples) to make sure that I was up to date.

The next morning, I did more sentence production scoring. Then I had my last meeting with Amy, in which she gave me lots of data for my poster. She also suggested that I send her multiple drafts of my poster so she can give me feedback; Thanks Amy! Next, all the interns went down to the MEG (Magnetoencephalograpy) lab for a tour (organized by Joanna & led by Demetrius). MEG is basically the same thing as the EEG, but it looks completely different, and uses magnetic fields instead of electrical signals to look at the brain. 

MEG (Your head goes up that tube thing!)

The MEG machine is in its own small room. Demetrius told us that the room weighs over 7 tons and is made of 3 layers of metal alloys in order to prevent magnetic fields from interfering with the process. 

Rather fittingly, my last day today was extremely relaxed and low-key. I spent the entire day scoring sentence production and saying my goodbyes/thank yous. 

Thank you to John Gabrieli for allowing me to participate in his lab. Thanks to Amy, Zhenghan, Michelle, Calvin, Jenni, Nayeon, and everyone else for an amazing experience. Thanks to Dr. Peretz for the opportunity to work in a lab and preparing all of us properly. I can say that after just 5 weeks at the Gab lab, I had a lot more fun than I thought I would, had a fantastic time, and would really love to pursue more research in the future. 

The Gab Lab: Week 4

Hi, this is Michelle. I've just finished my fourth week at the Gabrieli Lab, a brain and cognitive sciences lab at MIT. If I had to describe this week in one word, it would be busy. Throughout the week, I continued my usual administrative duties whenever I had time to spare. These tasks ranged from more scoring, organizing, and entering data, to creating an official MIT certificate of completion for the subjects who had taken part in the CASL study.  I also scored these subjects' final exams, known as the HSK test. The HSK is China's standardized test of Chinese language proficiency for foreigners, and amazingly, nearly everyone passed after just 2 weeks of training! 

In addition to running a Session 1 on Monday, I also touched base with Amy, who decided that it was time for me to edit brains. As a result, I met up with Nayeon, one of the lab's many undergrads here through UROP (MIT's undergraduate research opportunities program). Nayeon showed me how to edit brains using Mindhive (MIT's portal for brain research) and FreeSurfer, a program created specifically for the reconstruction of the brain's cortical surface from structural and functional MRI data. Editing brains is a 5 step process that takes around 3 days to be completed. I spent the day going through the first three steps: skullsplitting (the thinning out of the skull to create an image of good quality), control point edits (the adding of white matter that the program did not initially include), and white matter edits (the editing of white matter volume to erase gray matter that is inside the surface boundary). While this was an informative and enjoyable experience, what I found surprising was how much computer skills were required. Not only did I have to use Terminal, which is code that commands a Mac, but FreeSurfer and MindHive were also heavily based on computer coding. I forgot to take pictures of the process, but I'll be sure to upload some next week because they are really cool.

This week I also had a lot of meetings. On Tuesday, Amy organized a statistics club for the LAP & CASL members. As this was the first session, we started off relatively 'simple' (for them!) by looking at the general linear regression model. Having little stats experience, I was nervous because I had not understood the paper we had to read. However, I found that Amy and Caitlin's (undergrad) step by step explanations were incredibly helpful, and by the end of the meeting, I understood everything and was active in discussion. This week we went over the basic regression model, matrices, and rank deficiency, and next week we will be continuing this. Then, the other interns and I gathered for a lunch meeting with Satra Ghosh, a research scientist who focuses on 'finding novel computational approaches for representing data in the context of clinical disorders, and developing models for diagnosing and predicting treatment outcome'. During these lunches, which were organized by post doc Joanna, we get the chance to ask these scientists anything we want. We talked to Satra about his bee farm, his dream to build a super robot, and his profession, which he refers to as a 'social engineer', because of the opportunity to interact with a very diverse group of people. Today we met with Dr. Maiya Geddes, who spends half of her time in the lab as a post doc researching cognitive reserve in aging, and the other half in the hospital as a clinical neurologist, where she meets patients ranging from having dementia or schizophrenia, to patients who are slowly losing their memory or ability to speak. This talk was fascinating, but the best part was when she offered to let us 'shadow' her in the hospital on Wednesdays, which we are hoping to do next week! 

On Wednesday and Thursday, I ran several Session 1's again, but was not able to administer the KBIT, as Kelly, who was going to approve me for testing, unfortunately was out sick this week. Following Amy's instructions, I also taught Lilla and Louisa (interns) how to use the LAP database to score production recordings. When we all met up with Amy today, we had many questions concerning patterns and individual language components (verbs, subjects, articles, conjugations), which sounds boring, but is actually extremely fascinating. As a result, Amy decided that I should further modify the database to include all these patterns that we have been noticing. Then, we discussed a cognitive neuroscience article about the different methods to study the brain (EEG, fMRI, PET, MEG), which was also highly informative and interesting. 

Next week, I will continue running Session 1's and helping out with fMRI's. I will also meet up with Kelly to discuss the psychological background and use of the tests I am scoring, have another lunch meeting with a lab member, and observe an EEG that Amy scheduled me for. Needless to say, I am super excited for my last week here at the Gab Lab!

Week 3 at the Gab Lab

Hi everyone. It's Michelle again, checking in from the Gabrieli Lab at MIT. Week 3 was quite slow, due to most of the lab not coming in starting Wednesday. This week, I worked more with the CASL team, which is headed by post doc ZhengHan, who like everyone else, is very nice and encouraging. I began by organizing subject folders, grading homework and quizzes, and scoring various tests. Then, ZhengHan brought me down to help out with running Session 1s with the subjects. Session 1s are the first time we meet subjects. During these sessions, we give subjects a bunch of computerized tests, as well as interactive tests, where we are the examiners. I received a script that I had to follow with all the subjects in order to instruct them on what to do, and downloaded the program 'PsychoPy' so I could run the PCPT test, which tests tonal recognition and analysis on subjects. For example, the test will play a sound, and subjects have to identify whether it has a rising, neutral, or falling tone.

PCPT set up (not the actual test)

However, I have not been licensed to test the KBIT (IQ test) on my own because it involves interaction with the subject, and a good poker face! As a result, I'm meeting with Kelly, the psycho-educational evaluator, next Monday to go over administering the KBIT. Kelly will also teach me about the various tests I've been scoring for the past three weeks in order to give me some context as to what I am actually doing.

Today was probably the most 'science-y' day I've had in the lab. Since only Zhenghan and 'Big Michelle' were at work, and only 1 subject came in for testing, I spent the day 'pruning' raw EEG data. EEG, which stands for electroencephalography, is the recording of electrical activity along the scalp (it's the thing where people put on a swim cap with a bunch of nodes on them). Although nodes are placed all over the scalp, Zhenghan explained that the nodes near the eyes are used to record vertical eye movements (VEOG), which includes blinking, and lateral eye movement. Because EEGs are super sensitive, noise, speech, and muscle movement all produce huge peaks in the data. When these peaks occur in eye movements, they are considered garbage, and they usually affect the data from the scalp. Therefore, my job was to 'prune' these peaks, which means flattening the lines, using a process known as independent component analysis (ICA). This is important because if you simply edited out the peaks, you may be deleting sections of significant information from the scalp! Below is the ICA process:

Raw EEG Data. Scroll component activities on the left, scroll channel activities on the right.

I first had to identify which components (left side) corresponded with the eye movement channels (right side). These eye channels are the bottom two lines on picture on the right. Next, I used the technical computing application 'MATLAB' to prune the data:

In the figure above, the red lines show the pruned EEG data. As you can see, a lot of the blips are now straight lines, making it a lot easier to analyze later. 

Zhenghan was also kind enough to show me the results she had obtained from CASL's EEG sessions so far. She told me that during EEG sessions, subjects were tested on two types of language errors: syntactic and semantic. Both errors elicit strong responses in the brain, so huge peaks, which are called event related potentials (ERPs) are created in the EEG. The semantic error induces a N400 ERP, while the syntactic error induces a P600 ERP. This is shown in the figures below (Courtesy of S. J. Luck)

However, Zhenghan's data shows a fascinating trend: People are significantly better at processing one error over the other. Unfortunately, I don't have her graphs and diagrams (she said they were preliminary), but her figures indicated that people with a stronger N400 response had a weaker P600, and vice versa. Her graphs also hinted that people better at identifying one type of error in his/her native language had an easier time identifying the same error in a different language. Moreover, she had these cool, colorful maps of the scalp that showed which areas of the brain were activated during the N400 and P600. Her data suggested that even after 45 minutes of training, certain people began to utilize these specific areas when spotting errors in Mandarin or an artificial language. Basically, the big picture of EEG is to identify people who are adept to learning new languages, and her data seems to imply that this may be possible in 45 minutes!!

I finished the week sitting in on my second fMRI. Next week, I'm helping out with several S1 and fMRI 2 sessions, as well as meeting up with Amy to learn about stats and the brain. I'm excited!

Week 2 at the Gab Lab

Hi everyone. This is Michelle, and I will be writing about my second week at the Gabrieli Lab, a brain and cognitive sciences lab at MIT. The beginning of this week was rather similar to my first week here. I continued organizing subject folders, updated subject test spreadsheets, and created an 'Assistant Production' and 'S9' (2 month retention test) tab, along with scoring guidelines for the database I had been working on earlier. 

Screenshot of the LAP Database

I finished all this pretty quickly, so I was asked to help out with CASL, LAP's sister project. Similar to LAP, CASL is trying to find predictors of good language acquisition skills in adults  by training subjects in a new language. The only difference is, LAP uses 'Miniature Artificial Language' (MAL), which is taught by animations and games, whereas CASL focuses on Mandarin, taught by a professor in a traditional classroom setting. I was given the task of grading homework and quizzes, taking attendance, and entering this data into the CASL database. 

On Thursday, I went to the weekly LAP/CASL meeting, where we went over administrative stuff and presented new data. I was asked by Amy to explain the database that I had made, and was happy to find that everyone was super pumped, as it is safer and more efficient than Excel in terms of storing data. Then, Amy said that since I finish stuff so fast, I could  help to write parts of the lab's paper if I wanted to. That night, I was also able to sit in and observe a fMRI scan, which needless to say, was really cool. It was nice to see how people prepared for a scan (NO METAL IN THE ROOM!), what subjects actually did in the scan (play animated games, take quizzes, and watch Arrested Development), and see amazing real-time images of the brain. 

fMRI machine

Today was part 2 of the 'Data Blitz' lab meetings, where around 20 people give quick 5 minute presentations on their work. Like last week, there was a huge variety of presenters, ranging from undergrads and TA's, to our PI John, and his wife Sue, who gave a compelling presentation about using cannabis to help schizophrenic patients. The meeting was 2 hours long, but the information was really interesting, plus there was pizza and bingo! 

Bingo, Half of the Data Blitz's Program, Presentation Room

Afterwards, Lilla (high school intern) and I met with Amy, who began explaining the different parts of the brain, and different methods such as fMRI and EEG. I noticed that my preparation in the spring really helped me, as I shockingly understood everything Amy talked about. Then, Amy suggested that the 3 of us meet every week to learn more about the brain, something I am definitely looking forward to. Next, I showed her my progress on the database, which she was very impressed by and grateful for. She then mentioned that before I left, the lab was thinking of getting all the high school students to do a mini data blitz, something that has me excited, but extremely nervous. I finished the week by playing around with the database, changing the format, and adding extra calculations and formulas to improve the experience.

I have definitely enjoyed this week more than my first week. While the database was tedious, I find that I am becoming more interested in using FileMaker to create a more user-friendly layout for everyone. I think this change in attitude came after I realized how genuinely grateful everyone was for the database, and how happy they were with my work. Next week, I will be testing subjects during training, and sitting in on an EEG. Oh, and I couldn't resist posting the pictures below.

Farmers market in the building & Tri-weekly ice cream bars..what?

The Gab Lab: Week 1

My first week here was relatively uneventful. The first day, I met with Jenni, a research affiliate with whom I will be working with. She gave me a quick tour of the building, introducing me to several post docs, grad students, as well as showing me the fMRI and EEG rooms. I have to admit, all the winding hallways were rather confusing at first (the McGovern Institute for Brain Research is the largest neuroscience center in the world!), but I am glad to report that I have learnt to navigate them. Perhaps what surprised me the most was that the workplace isn't a typical 'lab' setting. Instead, it resembles an office, with most of the work being done in little computer-filled rooms. Here are some pictures of the building, including the very cool 'Jungle room', which has a ping pong table!

I came into the lab with no idea on what I would be working on, but I assumed that it would be on dyslexia, as that was the most current news on the lab website. However, Jenni explained that I would primarily be working on the Language Acquisition Project (LAP), a project funded by the Department of Defense to see if there are certain brain markers that indicate which adults will be better at learning new languages. To do this, subjects first take many IQ and memory tests in order to establish a neural baseline. Then, they learn the artificial language 'MAL' (known in the lab as Silly Speak) in several training sessions. They also take take an fMRI and EEG before and after these sessions, and we track their progress throughout this time via assessments. Finally, they come back after 2 months, and we test how much of the language they have retained. Jenni is also working on a 'Soldier Study', a joint project with the US Army to investigate the effects of caloric deprivation and stress on a soldier's cognitive functions. If I have time, I'll probably help out with that project as well.

Before all this cool research, I first had to take a long and tedious online training course. After I had passed, I spent the remainder of the day creating new subject folders, which entailed printing and copying a ridiculous amount of papers, and then organizing them. The second and third day, I had to go through all the completed subject folders and score the KBIT (IQ test), the MLAT (Modern Language Aptitude Test), as well as a syntactic word puzzle. Grading these and entering them into the database was incredibly tiring (and rather boring...), but I finished quickly and was able to leave the lab before 2! I also briefly met with Amy, a post doc who I will be working with starting next week (Jenni is leaving to Switzerland). She gave me the project's grant, as well as a review to read for more background info. The fourth day, I continued with more mundane administrative stuff, as Jenni gave me the task of creating a spreadsheet that detailed the lab's payment to all its subjects for each session. Here is a quick pic of my working area:

Today, things began to look more interesting. First, I attended the LAP & CASL (Chinese language test) meeting. After an hour of going over what we would do next week, the ten of us went to the lab meeting for the entire lab. The Gab Lab is huge. There are around 40 people, all working on different things. Here, I was introduced to a whole bunch of people, including my PI John Gabrieli, who is super funny, nice, and laid back (like everyone else in the lab), and Cirkine, a fellow high school intern who I share a room with. I was lucky to start this week, as this meeting involved around 15 people presenting on what they were working on, so I got to hear about topics ranging from autism and dyslexia, to marshmallows! Moreover, everyone got a bingo sheet with words the presenters talked about, so I was paying especially close attention. Afterwards, I met with Amy again, who has scheduled me for more hands on research in the coming week. Not only will I assess video recordings of subjects speaking MAL, but I will also sit in on an fMRI scan, and learn to edit brains! However, before I can assess these recordings, Amy had Michelle (a recent Brown grad who just started working here) teach me how to use FileMaker in order to create a database for the LAP Study. 

Although all this computer work has been pretty uninteresting, I am starting to see that most of a neuroscience lab's work is completed through collecting and organizing data. Yes, this is the not so glamorous side of research, but I am starting to appreciate how significant this data is, as well as how useful computer skills can be. Nevertheless, I am definitely looking forward to more practical work in the coming month, and have enjoyed my first week here. Next week 2 more high school students start (there are 10 of us!), and the three-times-a-week ice cream bars continue! What's not to like?