Using Resting State fMRI imaging to determine connected regions of the brain

The brain can be classified into many different scales. As you can see on the image they go from the largest (people) to the smallest (molecules). To truly understand the brain, we need to look at it at the neuronal level. However, the technology we currently have isn’t fast enough to have a complete network and understanding of all the neurons in the brain (just for context that’s about 100 billion). Cognitive neuroscience tends to focus on brain organization of function of the areas of the brain or the mapping of the areas of the brain each section at about 1cm small. But once we have these maps we can go deeper and deeper and eventually be able to map out networks, neurons, synapses, and eventually molecules.

What I’m going to talk about in this article is one of the first steps we have to take in order to completely map the human brain.

But before we get into it. What even defines a brain area?

In short, a brain area can be defined to the extent to which it can be differentiated from other regions of the brain based on given sets of properties: function, architectonics, connectivity (patters of inputs and outputs), and topography (maps of sensory surfaces of cortical locations). We need to be able to identify distinct brain areas and regions to basically understand how the brain works.

The brain represented as a network from data taken from an MR connectomics

Now if you’re a normal person I’m guessing that you don’t know what connectomics is. Heck, I had no idea what it even was until about 2 months ago. But in short, connectomics is the study of the wiring diagram in the brain. The only problem is, we don’t actually have a connectome yet… And here’s why.

There are 86 billion neurons in the brain, and each neuron is connected by a synapse to 7000 other neurons. That’s a lot of connections, and mapping them is not as simple as playing a gigantic game of connecting the dots. So the study of connectomics is the study of mapping the neural connections in the brain. In order to map all these connections, we need to know the areas of the brain as neurons tend to connect primarily with those in close proximity to them. If you are curious about the specifics of it, I wrote an article specifically about the connectome.


fMRI is a technique of brain mapping that relies on the flow of blood in response to brain activity during tasks such as tapping a table, listening to music, talking to someone, reading, basically any kind of stimulation. In order for an fMRI to work, it relies on the blood oxygen level dependant contrast (BOLD). This is basically what I said before; it’s the concentration of oxygenated in one region of the brain versus another that shows up on scans.

Want to read this story later? Save it in Journal.

But what about if your brain is doing nothing?

This is called the resting state and it also can be mapped using fMRI techniques! When in the resting state the brain exhibits an intrinsic functional organization at lower frequencies (lower frequencies being lower activity levels) Your brain is still active when you are doing nothing and the purpose of resting-state fMRI is to try to be able to map out cortical regions of the brain when you are in that resting state. Resting-state fMRI’s can reveal correlations between cortical and subcortical regions in many brain areas and systems which is very important for the study of connectomics.

The primary motor cortex or also called M1 is located in the frontal lobe in your brain and primarily controls (yup you guessed it), most motor functions. It generates neural impulses that control the execution of movement.

Let’s look at the graph down below:

Electrical signals taken by an fMRI of the left and right motor cortex

When the brain is doing nothing you can see this pattern of rising and falling which is expected there is no external stimulus to cause a jarring change in activity. This is shown in the red lines which represent the left-hemisphere motor cortex. However, if you plot the right hemisphere motor cortex from the homotopic region, as well as also looking differently random you can see a very strong correlation between the two signals. These two regions both control function so it would be predicted that their signals would look similar. And it is a known fact that brain regions that co-exist together exhibit similar properties when at rest.

But what if we made it more complicated….

Let’s take two regions of the left hemisphere that are very close to each other: the angular gyrus and the supramarginal gyrus. If we look at the resting state correlation maps of a seed region placed in the angular gyrus and the supramarginal gyrus, they exhibit very different patterns of resting-state correlations.

Activity levels in the angular gyrus and the supramarginal gyrus measured by an fMRI while in the resting state.

The angular gyrus is part of the default network (a network of interacting brain regions that are typically activated when one is doing nothing). It is correlated with the middle frontal gyrus and the lateral inferior temporal cortex. In contrast, the supramarginal gyrus is correlated with the anterior insula and superior parietal lobe.

The key takeaway here is that neither of these two brain regions, although they are in very close proximity to each other correlate with the same brain regions. The circles in the pictures represent one region that the angular gyrus is correlated with and one that the supramarginal gyrus is correlated with. As you can see, there is virtually no common activity levels between the two.

These two properties can be mapped but there shouldn’t there be a place where these two maps make a transition to each other?

We can determine this transition area by examining the correlation maps along a line of regions placed at the angular and supramarginal regions. (two-dot maps). As we saw before, the two areas are connected to each other yet have very different resting-state correlations. And now with this picture, we can see that there is an area between the angular gyrus and the supramarginal gyrus that acts as a transition point (shown on the pink dot above).

The map below is of resting-state regions along the supramarginal gyrus ROI and the angular gyrus ROI.

Spatial correlation between the seed ROI’s of angular gyrus and supramarginal gyrus.

At the supramarginal gyrus (shown by the yellow lines), the maps are very similar to each other as we go from left to right. However, there is a point at which the pattern changes and there’s suddenly there’s a new map and then the maps of the angular gyrus start (shown by the blue lines).

The lines demonstrate how different the maps are in comparison to every other map. The orange is like the orange, the blue is like the blue. But the orange and blue are not like each other. The pink map is unique. It’s a location where the resting state pattern changes.

So the hypothesis is that distinct areas have distinct patterns of resting-state correlations. These locations of transitions (or the pink line) is a distinct way of measuring the transitions between two areas. This location can be taken across the brain to identify putative areal boundaries.

→ A.N. this experiment was presented by the cognitive neuroscience compendium in this video.

So now I’m sure you’re asking yourself, okay but so what? Why is this important?

There are many clinical applications of resting-state correlations. The first and most obvious being that if we don’t’ understand the regions of the brain we just can’t understand the brain it’s not possible and understanding the brain is pretty important.

But if for some reason you just aren’t convinced that mapping the brain is important, here is a few other clinical applications:

  1. Identifying abnormalities in patients with neurological disorders. Using fMRI resting-state technology, we have an idea of what BOLD signals should look like in areas of the brain. With this information with can scan patients with neurological disorders and use this data to try and identify the problems, they may have.
  2. Understanding the brain’s metabolism. The brain represents 2% of the human body yet consumes 20% of its energy. We can use fMRI to locate the regions of the brain that absorb the majority of this energy while under the resting state.
  3. Specifically, the resting state is extremely important as if one is doing a stimulating activity during the fMRI scan, any brain region will have spontaneous fluctuations in the BOLD signal.

That’s it. If you are curious about the minute details of resting-state fMRI’s here are some papers and clinical trials I recommend reading!

Resting-State Functional MRI: Everything That Non-experts Have Always Wanted to Know

Architectonic Mapping of the Human Brain beyond Brodmann

Resting-State Functional Connectivity in Psychiatric Disorders

Connectomics news and research

Using Resting State fMRI imaging to determine connected regions of the brain was originally published in Noteworthy – The Journal Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.

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