The Researches That has been Done So Far In The Field Of Brain And Psychology Point To The Point That A Certain Neurological Characteristic May Make A Person More Vulnerable To Autism Or Alzheimer’s, Or The Probability Of His Academic Success Is Higher. 

However, the critical question is how can we use MRI technology to confirm this issue?

In March, neuroscientists and psychiatrists at Washington University School of Medicine in St. Louis published research results in Nature, which sparked a wide-ranging debate among scientists and psychologists.

The research indicates that researchers are increasingly using MRI or magnetic resonance imaging to find connections between what is seen on the MRI (such as cortical thickness or patterns of neural connections) with complex psychological characteristics such as cognitive ability or mental illness. do

In theory, such studies as “brain-level connectivity” provide valuable information to scientists, especially neuroscientists. Knowing that a particular neurological trait makes a person more vulnerable to autism, Alzheimer’s, or other disorders can help predict, prevent, or treat that disease.

Likewise, if we can link specific traits to desirable traits, such as academic achievement, we may be able to use this knowledge to overcome some common problems.

According to the arguments of the authors of this research paper, the problem that neuroscientists have is that they often seek to find this connection in small groups of people, which makes the results obtained statistically not very reliable, and it is not possible to generalize it to society. According to their calculations, thousands of people would have to be monitored to study connectivity at the brain level to obtain results that could replicate in other studies.

However, the above news is not very pleasant; Research in this way faces a significant limitation because the use of MRI devices is expensive (often around $1,000/hour) and has a limited budget. If you search the internet, you will find many scattered studies on this topic, usually done on small groups of people.

Terry Jernigan, director of the University of California’s Center for Human Development, says: “There are so many such studies that it would be unfair to mention just one example.”

In fact, according to a 2020 neuroimaging article published in the journal NeuroImage, the average number of subjects studied in more than a thousand of the most cited brain imaging articles published between 1990 and 2012 was 12.

According to a Nature paper, the average number of study subjects in neuroimaging research uploaded to a popular open access platform as of September 2021 was 23.

Unfortunately, small MRI samples often randomly show strong correlations.

For example, suppose you are considering investigating whether there is a relationship between eye color and a liking for strawberries. Suppose you observe enough random groups of 25 people. In that case, you’ll end up with a group in which blue-eyed people like strawberries more than brown-eyed people, but if five independent research groups do the study and only one relationship group Between eye color and liking for strawberries, this group is more likely to publish their results, even if their results are less close to reality than others. For this reason, journals have long favored surprising correlations over non-correlational findings, A phenomenon known as “publication bias.”

“The paradox effect suggests that if you use a small sample, you will publish the most erroneous results,” says Nico Duesenbach, an associate professor of neurology at the University of Washington and one of the study’s authors.

Scientists in all disciplines have known this for a long time, but the paper noted how many participants are needed to avoid this problem, at least in brain-level communication studies. Using MRI data of about 50,000 people, the authors of the Nature article looked for connections between brain structure or activity and complex psychological characteristics in groups with different numbers of people.

For the studies to be reliably repeatable, the number of people studied should be several thousand on average.

The fact that most studies examining associations are weak and often not tested in other groups before publication makes published reports of myriad associations between brain characteristics and psychiatric disorders less reliable. “If you see a particular pattern of brain activity in someone with a psychiatric disorder, that doesn’t mean that pattern is causing the disorder or the symptoms,” says Jernigan. It’s just a connection.”

On the other hand, neuroimaging studies that show brain changes in people are still reliable despite very few participants. For example, Russell Poldrack, professor of psychology, “The first landmark paper showing that most human brains work in roughly the same way was published in the journal Science in 2001 and involved only six participants,” says Stanford University.

The researchers of this study recorded each person’s brain activity while viewing pictures of cats, faces, artificial objects, and nonsensical images. The fact that each person’s brain is unique was not very important in this study.

The changes in each person’s brain could be related to seeing different types of images.

Tested The patterns then, and it found that based on the brain activity, it was possible to predict what picture the participant was seeing.

“These general patterns, along with other evidence, proved that specific areas of the brain are engaged when people engage in certain types of mental functions,” Poldrack said in another part of his talk.

Understanding that we typically share brain patterns is of great interest to psychiatrists and neuroscientists because it suggests that changes in patterns may explain why some people have a particular trait or set of symptoms.

Others lack it. However, it is difficult to separate meaningful differences from the myriad random differences between human brains.

I am attempting to do this by comparing thousands of MRIs and looking for a change.

A particular neural connectivity pattern is more common in people with a specific mental condition.

Recent advances in MRI technology and the ability to analyze large amounts of data have made this kind of effort possible. For example, in the Adolescent Brain Development Study, nearly 12,000 children between the ages of 9 and 10 in the United States are enrolled to have their brains regularly scanned into adulthood.

Also, the study looked at socioeconomic variables, such as parental income and psychological characteristics, such as resilience, to see how they relate to brain development.

“Without this kind of research, you will never be able to get a convincing answer to these questions,” says Jernigan, director of the study’s coordinating center.

This comprehensive dataset enables researchers to examine the relationship between multiple factors simultaneously. However, other ways exist to explore connections between brain properties and complex mental functions that don’t require many people.

“Instead of looking for connections in the entire population, you can start by very precisely characterizing the brains of hundreds of people with different types of depression and build models that represent these states,” says Roberta Diaz-Brinton, director of the Center for Innovation in Brain Sciences at the University of Arizona School of Medicine.

What are they like?

In a paper published in 2016, Monica Rosenberg and colleagues at Yale University used this approach to identify specific types of brain activity in people with sustained attention.

 They gave 25 healthy adult volunteers a task that required concentration and created a composite map of what was going on in their brains.

Then they compared that map with the MRI data of 113 children with and without attention deficit hyperactivity disorder (ADHD). The sustained attention network they identified was weaker in children with the condition, which confirmed their results.

Rosenberg, now a professor of psychology at the University of Chicago, sees the Nature paper not only as a call for more samples but also as a sweeping reminder of the need for “systematic follow-up of results.”

“For any finding, scientists have to ask, does it hold for a different group of people?” he says. How common is this relationship in people of different ages?” Gutenberg believes that there are still many points to be explored but is optimistic that the paper published in the journal Nature is one of the best of the past few years and calls for better practices in brain imaging projects.