by Kevin Sitek
figures by Daniel Utter
Over the years, scientists have developed many techniques to observe what’s going on in the human brain as we think or move. Unfortunately, few of the insights we have made so far have resulted in any improvements in standard clinical mental care. Recent advances in neuroimaging may be changing this. Studies from the past few years have shown that various measures of brain activity and structure can predict who will develop certain mental disorders as well as how individuals will respond to particular treatments. In fact, measurements of brain activity can be better at diagnosing depression than standard clinical assessments. This is just one of many examples of modern neuroimaging techniques beginning to contribute to how we diagnose and treat diseases.
Developing tools to look at what’s inside our heads
Despite centuries—or perhaps millennia—of questions about how the brain works, there weren’t tools for looking at the living brain until the second half of the twentieth century. Before that, our knowledge of the brain’s organization and function largely came from dissecting patients’ brains after death and matching up any physical abnormalities with their reported symptoms during life.
Starting in the 1960s with the development of computerized axial tomography (CT or CAT scans) and magnetic resonance imaging (MRI), it became possible to take images of the structure of a living person’s brain. Next, in the 1980s, scientists figured out how to produce functional brain images using positron emission tomography, better known as PET. Instead of one image of the brain’s structure, they could now take snapshots of the brain over time to observe how brain activity changed.
However, a downside to PET is that it requires injecting the participant with a radioactive isotope, which is then tracked by the scanner while the participant performs a given task. The radioactivity is equivalent to what you’d receive normally just by living on Earth for about 5 years. Inspired by functional PET imaging, researchers figured out how to use an MRI scanner to create functional images without any radioactive isotopes.
Instead, the MRI scanner uses a large magnet to measure differences in various tissues in the body (Figure 2). During functional MRI, or fMRI, the scanner is specifically sensitive to oxygenated blood. Since active parts of the brain use up a lot of oxygen, new oxygen must be delivered through the blood stream. As a result, fMRI infers brain activity by tracking where oxygenated blood is increasing in the brain (see the image in Figure 1D). With this information we can look at brain activity differences between people with different mental states and disorders.
From voxels to discoveries: Analyzing brain imaging data
An fMRI scan results in a three-dimensional image made up of “voxels,” or 3-D pixels. Each voxel represents a volume in the brain about 2-3 cubic millimeters in size—pretty small, but big enough to contain hundreds of thousands of neurons. With fMRI, the scanner takes one image every two seconds or so, resulting in a time series of brain images, each with hundreds of thousands of voxels. Each voxel for each time point has a particular level of activity. This activity is “Blood Oxygenation-Level Dependent, ” meaning more oxygen leads to greater signal, so it goes by the name BOLD.
However, this time series isn’t ready to be published as a pretty picture yet. There are differences from one image in the time series to the next that aren’t caused just by changes in brain activity. This can be due to the participant moving in the scanner or even just due to normal breathing. If this isn’t fixed before the images are combined, then a voxel that’s in brain area A in one image could be in brain area B in another image! A computer program aligns all the images so they are lined up and can be compared across time.
After the fMRI data have been processed, they next go through rigorous statistical tests to figure out which parts of the brain were active during the scan. A common misconception is that only about 10% of your brain is doing anything at any particular time. In fact, your whole brain is always active! What this fMRI statistical analysis does is look for which brain areas are more or less active than the rest of the brain during a particular task. These differences are very small—BOLD activity might increase only 1% during a task—but historically, the differences have been noticeable if we combine results from many people, each of whom does the task a number of times.
Making new discoveries with brain imaging
Functional human brain imaging makes it possible for scientists and doctors to “see inside” the working brain. As a result, brain imaging can be used to investigate how the brain functions differently in people with various psychiatric disorders. Studies showed that during tasks involving emotions, people with depression had different activity in a region in the middle of the front of the brain than people without depression. Other studies showed that other frontal areas involved in attentional control are less active in people with attention deficit hyperactivity disorder.
Not all brain imaging discoveries had to do with how participants performed tasks. In fact, one of the biggest insights came from observing brain activity when people were asked to do nothing at all! When researchers looked at how similar activity across different brain areas was, they found fascinating networks of “resting state” activity.
What can brain imaging tell us about a single person?
New discoveries about brain functions and disorders are made using brain imaging every day. These findings tell us how most people use different brain areas, or how people with a particular disorder differ from people without that disorder as a group. However, it has been extremely difficult to use brain imaging to tell us information about a single person. So as we mentioned in the previous paragraph, people with depression process emotions differently than non-depressed people, on average. But we haven’t been able to pinpoint whether one specific person processes emotions differently enough that they’re probably depressed.
As mentioned earlier, some of the difficulty is due to BOLD activations being relatively small, so researchers need to collect data from 20 or 30 participants and average their results together in order to see any effects. Other issues arise from the computational challenges of brain imaging—each image can be made up of 100,000 voxels, so doing statistical analyses on these data have historically taken powerful computers a long time.
However, recent advances in computational power and machine learning algorithms have opened the door to single-subject data analysis. Faster, more powerful computers means that we can use higher resolution brain scans with more sophisticated processing steps. Improved data processing steps result in “cleaner” data and make BOLD activity easier to see. This means participants don’t have to do a task for quite as long, and we don’t need to combine results from as many participants in order to see brain activity differences.
Machine learning algorithms—along the same lines as what Netflix uses to recommend you movies based on what you’ve enjoyed previously—make predictions about new data based on earlier data. (See the special edition article on computational neuroscience for more.) These same principles can be applied to neuroimaging data. An algorithm can look at the fMRI activity of some participants, along with important information about the participants (such as their age, gender, or intelligence). Then, with only the fMRI activity of a new group of participants, the algorithm can “predict” information about this new group (like which ones are male, old, or average IQ).
In the past few years, neuroscientists have used these computational advances to investigate various mental health disorders. For instance, a study of patients with social anxiety disorder took brain scans before the patients underwent cognitive behavioral therapy. The patients looked at pictures of faces with various emotions. The study found that the patients who went on to respond best to the therapy had the greatest brain responses to angry faces before the therapy.
A recent study from MIT and Harvard Medical School scanned children whose parents have major depressive disorder. Children with a parent who is depressed are three times more likely to develop depression themselves. The study also scanned a group of children whose parents were not depressed. By looking at brain activity when there was no task, the researchers found that the resting state network was more synchronized with areas that process emotions in the brain in the at-risk children. That is, when the fMRI participants were lying in the scanner without an explicit task, the emotion-processing regions were active in similar patterns as the resting state network (which is shown in Figure 4),. This synchronicity could represent overactive emotion processing and could explain why children whose parents have depression are more susceptible to developing depression themselves.
Beyond the findings that compared the two groups directly, the researchers also trained a computer classification model to guess whether each child’s brain activity makes them more likely to be in the at-risk group or the control group. The computer model based on brain activity ended up classifying the children correctly 80% of the time with very few misclassifications of control children as at-risk (20%). In contrast, a computer model that was built on behavioral tests that clinicians use to diagnose mental disorders was correct only 64% of the time, with many more misclassifications of controls as at-risk (73%). These results suggest that brain activity is actually a better predictor of whether someone is at risk for a psychiatric disorder than the behavioral data used by clinicians!
So are my next doctors an MRI and a computer?
Despite promising results using computer algorithms to predict whether someone has a disease or not, we won’t be replacing MDs with MRIs anytime soon. For one, most studies have been successful at picking out who has a disorder from the pool of study participants that were included because they had the disorder (the test participants) or because they didn’t (they were control participants). It is much more difficult to pick someone out of the general population and accurately predict which disorder they may have—the resting state networks of two very different disorders could actually look quite similar.
However, it is extremely encouraging that researchers may soon be able to make accurate medical predictions with a “data-driven” approach. Diagnosis of mental health disorders is notoriously subjective, with clinicians diagnosing patients differently. Recent advances in human brain imaging show that diagnosing medical disorders will be more consistent and more accurate in the near future.
Kevin Sitek is a graduate student in the Harvard Program in Speech and Hearing Bioscience and Technology and conducts research at the McGovern Institute for Brain Research at MIT.
This article is part of the April 2016 Special Edition on Neurotechnology.
For more information:
“Diagnosing depression before it starts”
“Idle minds: Neuroscientists are trying to work out why the brain does so much when it seems to be doing nothing at all”
Featured image (top) created by Kevin Sitek.
12 thoughts on “Can Computers Use Brain Scans to Diagnose Psychiatric Disorders?”
Autism – There is a “Brain Balance” theory that suggests autism may occur when the two hemispheres of the brain do not ‘cross over’. The patient is given exercises to ‘teach’ and help this connection in the brain. In the clinic, children have been said to be much improved and especially those with severe autism. Wondering how this might be a great breakthrough to help if the study above can show this premise to be true.
Kevin, I thought this was kind of interesting. I’ve heard that in the past that the ridges and grooves on your skull were actually used to help diagnose things. I think it’s amazing how advances in technology allow us to further understand the brain and neurological structures.
Dr. Melillo, Founder of Brain Balance, is said to be releasing a clinical study on his theory this Fall. Hopefully, it will provide a strong case against the nay-sayers.
On another note, Dr. Daniel Amen has done clinical studies using SPECT with great results.
I looked into Dr Amen. Do you know much about his work or do you know anyone who has gone to his clinics.
Well written article here.
I do agree with you on M.D.s still having a place in all this and not being replaced by MRI’s.
This allows the clinician to utilize a better more objective way to diagnose a psychiatric disorder, not a way to replace the physician. With the use of these tools, the clinician could measure treatment, and let’s face it, if there is a misdiagnosis, no treatment may be beneficial but instead harmful. I think this is a way utilizing both what the patient is demonstrating behaviorally and the neuroimaging analysis would limit misdiagnoses and that’s better for everyone.
Lovely post. Awesome job. Thanks for sharing your though and experiences. was very interesting to read i have to say-the images and all. But most of all what has grabbed my attention was the title. I think computers are already diagnosing our brain and health. For the most of the accuracy i believe it has to be a few methods used if in doubt, or the examination repeated in a short time of period. Computers replacing everything and now even people…detecting the problems, and even there is a machine that makes implants right after you open your mouth…I would rather have a human…sounds safer
An articles makes want you to sop and think about everything. what the world is going to be like in 5,10 years?… is there are lot going to be humans completing their tasks???…i wonder..
This was really cool but, I just wish they could scan my brain and see what’s going on inside. I’ve been diagnosed with PTSD, severe depression, and gender dysphoria. I’ve been on hormones for about a year now but, even with my transition academia is still a major challenge for me. It’s hard for me to read and for most my life growing up it has been. Not typing or talking or even articulating thought in general. However, something major in my mind just feels wrong. I don’t know how to describe it. I just want to know if that’s all that’s going on in my brain. Maybe my amygdala are hyperactive because of the trauma I went through the first seventeen years of my life and maybe there’s a way to fix it. I wish I could just see it and fix it. Life is such a battle with mental illnesses like these. Every single day I have a hard time getting out of bed and every single day I just wonder if I’m doing anything right. How can it be right when it feels so wrong?
“This synchronicity could represent overactive emotion processing and could explain why children whose parents have depression are more susceptible to developing depression themselves.”
Whilst I understand how much we want, possibly need, a visual (and this believed more objective) criteria for depression the above formulation boarder dangerously on an argument of causation.
That the brain-structure of at-risk children will be affected by and show constructed details of the system in which we are nurtured might not be as revolutionary at this article, possibly, suggests.
For years the stimata of mental illness have been that the involvement of personality and emotion in the presenting symptoms have made it ‘feel ‘ like mental illness is something the sufferer should be able to control or modify themselves. The emergence of fMRI and other functional imaging , even when it isn’t yet sophisticated enough to be used for diagnosis, means at least we have tools that prove a medical foundation to mental illness, which I know my patients find reassuring.
I look forward to further developments in objective functional imaging to advance psychiatry diagnosis in the future.
Enjoyed reading the article above , really explains everything in detail, the article is very interesting and effective.Thank you and good luck for the upcoming articles
yes, there is most gratifying breakthroughs with images and scanning, however, unless an organic disfunction in a brain area, such as a mass, any tissue damage or abnormality in brain structure, chemicals change like the weather at any moment. anyone can have at any moment a powerful emotion causing a sudden and even severe dopamine-serotonin –epinephrine imbalance. whether it is contestant, an on going imbalance, or momentary, or genetically induced and born with, it is not a tool you can bet on. i have, after much investigation and satisfaction that psychopathology as sociopathic narcissism (SAME ACTUALLYY) does show up. it is an anomaly due to some thickness in a particular area of brain tissue. this is all i know. this also, is not a chemical or mental or emotional imbalance. so much can show up on pet scans and radiographic images of the brain. it is a most marvelous of breakthroughs that have been rather recently come to be. however, i personally hope that as far as chemical imbalances, there are so many more qualified neuro-psychiatrists that come into practice. those with high aptitude for pharmacology. in the not-so-distant past, it was unheard of to arbitrarily diagnose labels understandings of not understanding why meds for one thing may have nothing to do with why the medications or needed combination works for different symptoms. they also virtually never used term “mental illness, but knew there was a large distinction of psychosis, and majority of most imbalances ranging from most severe to moderate to mild. psychiatry has been given way too much power by now to diagnose. there is no way about it. most people needing-some desperately will not even go for therapy and help with meds due to the fear of labeled mentally ill. this has been an ongoing travesty of misinformation and politically maneuvered strategy to get reimbursed for the diagnosis. stated, “not a stigma” it sure is. “mentally ill–illness of the mind!” the healthiest minded-noted-can be mentally ill, and those not mentally ill can be most unhealthiest of mind!” this is stated time and time again. even on internet mental health sites. unfortunately this is not how it is accepted in the real world. people are frightened to be themselves. how will other drs. perceive them. titles and symptoms and labeling are lopped into one. this is not the real world any more. perhaps a god complex or value system of money grubbing drs. who are likely to be truly mentally ill, or for sure, sociopaths–(bet on a pet scan-perhaps that area of thickness in brain tissue will show up—wake up america. you have no idea what your foreign allies are reveling. i feel loads better and have, in an exhausted attempt, to help someone-anyone who is of fear. after all, we are going into the mind and that is a horrifying thing to waste and or to terrify–perhaps–worse than cancer–hmmmmm!