LEARN ABOUT OUR BRAIN: a magic black box.

This Saturday evening, In the story I'm about to share, I aim to delve into what sparked my growing interest in cognitive neuroscience. Throughout the pandemic, I embarked on my exploration of neuroscience, a subject that truly captivates me. When I first started my online classes focused on the sleep cycle. What intrigued me most was the enigmatic nature of our brain, often likened to a mysterious black box. Just imagine with me for a moment this black box, seemingly capable of performing feats like effortlessly adding “1+1” to yield the answer '2'. But how does it do that? How does it learn, and how can we learn from it, with relatively little guidance beyond observing someone's example?

During this period, I realized that diving deep into this topic is crucial if I want to better understand how our brains learn and think, which can help make education better and improve how we learn things. So, let's start by comparing how we learn to how machines learn. Think of it like a robot that gets better at tasks by watching and practicing, just like when you practice a game to get better at it. With clear instructions, the robot can do things really well. But here's the cool thing about us humans: we often figure things out on our own without anyone teaching us every step. This is why I chose to work in a neuroscience lab. It's like a special place where I can gather technical information and dig even deeper into this interest. I knew I'd need some technical help for my research there.

On my very first day in the lab, I got started with a computer program called MATLAB. Inside MATLAB, there's a special tool called EEGLAB that helps us deal with data about what's happening in the brain. As part of my job, I watched and took part in the process when a person came into the lab. They put some electrodes on their head, almost like a special hat, and did tasks that involved looking at different pictures. After each task, I had to use the computer program to carefully study how their brain reacted to each of those pictures. It was really interesting and gave me a lot of new knowledge about how our brains work in cognitive neuroscience.

1.1: Why EEGLAB?

An electroencephalogram (EEG) is a recording of the brain's electrical activity, and it can be used to treat many disorders by measuring the charges and the response from stimuli such as sight, sound, or touch. During the procedure electrodes are attached to the scalp.

A particularly important milestone should be highlighted in this section when in 1962 the first computer for EP averaging was created (CAD) and the event-related Potential (ERP) averaging was. During this period people did not have any access to raw data, so what could be interpreted as the peaks of ERP after many trials?

ERP Experiment procedure: recording → electrodes/time → offline processing  

Follow the basic principles of how to read an EEG.

For the offline processing, you would do event-related (stimuli/base time) potential Averages: electrode X → slice the signal – baseline = ERP

           EEG = ERP + EEG “noise”

It concluded that the EEG data is just accurate when the average appears in each trial. And the background “noise” is not perturbed by any event during the time presented. Another important topic to discuss is the understanding of physical concepts because while reading an EGG diagram you will question yourself about what frequency is, and what period.

Frequency (Hz) = 1/ period (s)

Frequency can be defined as how many waves that pass a fixed point in one unit of time.

Period is defined as time quantity.

The understanding of these concepts is essential to provide a better understanding of EEG frequency analysis, and traditional ERP analysis.

1.2 The origin of EEG signal.

When recording EEG at the surface of the scalp, you record the field from regions of the cortex. However, when you several electrode patches actively simultaneously, you can notice that most of the electrodes record a combination of the activity of the two regions. So, when you have potential at the surface of the scalp the cortex acts as a dipole, having a positive and negative potential, which can be represented as a battery.

Where this electrical potential comes from?  

The electrical potential comes from pyramidal cells because these types of cells have an open field with magnetic potential. But to be able to record you will need to have a lot of them.

Now, let's delve into my experience at the EEG lab, breaking it down step by step:

Step 1: Start MATLAB and enter "EEGLAB."

Step 2: Add spherical eye channels.

Step 3: Reduce the data size to 250Hz.

Step 4: Extract Epoch and divide your data as retrieval and encoding.

Step 5: Filter the data for ICA.

Step 6: Open ICA maps.

ICA Maps diagram

Step 7: Analyze the data and delete artifacts.

Step 8: Delete Artifacts

The seventh step can be challenging. You need to be consistent with your data because it can be affected by various factors like muscle activity, eye movements, and blinking. At this point, I'll show you how to distinguish and identify each of these elements.

(This is a EEG diagram, and all those waves must be read by the following segments)

Having grasped this concept, my goal is to explore even more intricate methods and approaches to delve deeper into this subject. I'm proud to say that I've maintained steady progress since I first started online classes in this field two years ago, and I'm thrilled that I've had the chance to gain hands-on experience in a physical lab setting. I'd estimate that I've only uncovered about 15% of what there is to learn, leaving a significant 85% yet to be discovered. This mystery is something I'm eager to keep researching and gathering more information about.

That's it for now

Best,

Bruna