American Scientist

In the past few years, there have been major initiatives to increase diversity, equity, and inclusion (DEI) in science and in the workforce. Yet the root causes of inequities are still being revealed. Neuroscience researchers are suggesting that poverty is a major player—noting that poverty is contributing to decreases in academic success, education level completed, and even brain mass. Gabriel Reyes, a PhD student in developmental and psychological sciences at Stanford University, is working at the heart of this subject. Reyes grew up in a low-income, underserved section of Albuquerque, New Mexico, where opportunities were limited. Nevertheless, his passion for neuroscience led him to attend Brown University, Columbia University, and now Stanford. He is the first in his family to graduate from college and is working at the intersection of DEI and neuroscience research. Reyes is also the founder of FLi Sci, a program that provides research opportunities to first-generation and low-income science students. Reyes attended Sigma Xi’s 2022 International Forum on Research Ethics (IFoRE), which focused on science convergence in an inclusive and diverse world, and spoke with Jordan Anderson, producer of American Scientist’s DEAIComSci podcast, about debunking poverty and educational inequity myths, and what current neuroscience research reveals about a path toward more equitable educational outcomes for students nationwide. (This interview has been edited for length and clarity.)

What pressing issues in neuroscience does your research explore?

My research has two buckets. The first bucket is neuroscience and understanding how experiences and the environment affect our behavior. I had planned to understand how specific experiences influence decision-making. Two scientists who inspired me were Kim Noble and Bruce McCandliss, who are examining whether there is a correlation between poverty and academic achievement from a neuroscientific standpoint. Dr. Noble, at Columbia University, has written a lot of papers on poverty and brain development. Dr. McCandliss teaches at Stanford University and runs the Educational Neuroscience Initiative, using neuroscience to improve learning. Their work created a path for me to explore the associations between socioeconomic status and brain development and to theorize how that might translate into academic performance. But I didn’t get anywhere with that topic, because I was finding more research questions than insights.

As I was learning more about the field, I began to realize that there are two problems. One is that how neuroscientists theorize and conceptualize poverty needs to be more consistent. For some people, poverty is defined by how much income your family makes. For another person, poverty might be defined by specific experiences communities endure. Are they able to pay rent on time? Are they in a lot of debt? Are they experiencing a lot of stress? This discrepancy is a conflict, because both definitions are related but are different constructs and therefore have different conclusions.

The second issue was that we still need to fully understand fundamental learning mechanisms. How can we speak to how people from low-income versus high-income backgrounds learn, when we’re still figuring out how people generally learn? We are exploring how to bridge the two without problematizing the work. We want to avoid jumping to conclusions that have yet to be reached in neuroscience.

“We are looking at large datasets with a myriad of income analyses and thinking through how the story changes if you alter how you define poverty.”

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I want to start first by thinking about poverty as a construct. At Stanford, many of my projects interrogate how the field has measured poverty and whether we’re measuring it correctly. The most common index that I see these days is an income-to-needs ratio. And that is a federal poverty index, where officials define poverty by household income. However, for example, many neuroscience studies need to consider that in New York City and the San Francisco Bay Area, rent is much higher on average than in rural Alabama. In rural places, $30,000 can take you much farther, but won’t get you very far in vast urban areas. That’s a massive issue for data analysis. Part of what I am now working on with Philip Fisher at Stanford is looking at large datasets with a myriad of income analyses and thinking through how the story changes if you alter how you define poverty. We want to explore the general theory of poverty in a way that speaks more to the environments that people experience. So that’s the second bucket of my research.

You were exploring how poverty affects cognitive development with Dr. Noble. Can you give an example of how you are applying your previous neuroscience work to your current PhD research with Dr. Fisher, and how you are examining the definition of poverty?

Researchers such as Dr. Noble have found a particular association between looking at one’s socioeconomic status and the amount of cortical volume in particular individuals. Often, what they see is that there is a positive association between cortical volume and income. However, it is a nuanced question, because cortical loss in higher- income communities does not mean equal or more significant cortical loss in people with lower socioeconomic status. Some studies don’t find that association. There are a lot of other variables, such as the research participant’s school and how socioeconomic status is measured.

Researchers in this field are pushing toward different ways of understanding brain development, looking at nuanced ways of thinking through socioeconomic status. One of the ways is looking at experience with material deprivation or other factors beyond just the income-to-needs ratio to understand what happens with brain development. People who experience certain forms of economic adversities, such as food insecurity, are often more likely to have differences in cognitive function, cognitive behavior, and neural development. Some people don’t experience food insecurity but might be in the same income bracket.

What sort of data are you exploring in your current research, and how is it affecting the field of neuroscience?

In my research, I analyzed data from the Fragile Families and Child Wellbeing Study. I was looking at various outcomes, one of which is working memory. That is an aspect of executive function—mental processes that enable us to plan, focus attention, remember, and juggle multiple tasks. It measures how much information people can hold at any given moment and is a typical topic in cognitive studies. It is also one where people often find things such as the association that people with lower income generally have lower working memory capacity than someone with higher income. And I used a friend’s framework for how we think about that to look at it through a different lens. So instead of just looking at the effect of income on performance, I wanted to see how people who experience more aspects of material deprivation behave throughout different income barriers.

For example, someone who makes $10,000 and someone who makes $90,000 represent people in two separate income groups. But let’s say the person who earns $90,000 lives in a costly part of San Francisco and supports a family of eight. $90,000 may seem like a lot, but it doesn’t go that far when you think about how they’re using that money versus someone who is making $10,000 but is a single adult living somewhere like New Mexico. You can then ask questions like: Can you pay your rent on time? Did you make enough money to pay the electricity bill? Are you able to go to the hospital? Or did you not go to the hospital because you couldn’t afford the medical bill? We add up the number of those experiences and see that maybe someone who’s making $10,000 only had two moments of material deprivation for the questions we asked, but the person making $90,000 had nine of those moments out of 10. We want to see if there was an association between that sort of interaction effect with income and experiences of scarcity. My initial research found that income as a single variable is insufficient to understand how poverty affects cognitive development. Higher levels of material deprivation can affect performance and working memory tasks for people across different income groups. We would not have found that association if it was just income alone.

One of the things that we want to do is to see if we can measure qualitative rather than quantitative responses by creating written response questions on a massive survey database. By doing so, we can extract specific factors of the poverty experience that we can use to uncover a different way of categorizing family and community poverty without looking at income.

How has the research in your field changed over time?

Many studies have divided tasks or groups of people by low income, high income, or middle income. It could be a quick correlation task that measures a behavioral outcome such as test scores. Based on prior studies, we might theorize that low-income people will have lower test scores than higher-income people. The problem is that this does not provide the root cause of what is happening. It also implies that low-income people are less capable than high-income people at standardized testing. This logic is not accurate. Even if those associations are occurring, income is not causing test performance. Instead, income might produce specific experiences in which higher-income people can score higher.

“Instead of just looking at the effect of income on performance, I wanted to see how people who experience more aspects of material deprivation behave throughout different income barriers.”

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Rather than asking people what their income is and dividing them by those groups, we can add a second variable that asks questions such as: Did you get access to private tutoring on the SAT or ACT? Did you attend a rigorous high school that provided resources to learn how to perform well on standardized testing? Now we have questions that might get to experiences contributing to test performance. If you add this dimension on top of income, we might find that, for example, low-income students who scored highly on the test had access to private tutoring or went to top-tier high schools. We may also find that low-income students who performed poorly had none of these resources. This pattern also exists in middle-income groups and high-income groups.

Neuroscience researchers are currently working on these insights, and we are building off of them. Applying that to the brain, we can see that there might be differences in cognitive performance and neural signatures when you only look at income, but we have started adding all these other measurements, such as: Are you experiencing high levels of threat? Are you experiencing high levels of food insecurity? Are you experiencing high levels of monetary scarcity? These new insights have created a differentiation between our knowledge of which part of the brain has specific patterns, which tells us that it’s not just income but rather experiences that income is either allowing or preventing some groups to have more often than others that are contributing to brain mass.

How have your personal experiences influenced your choice of research?

I often had to turn down research opportunities that I knew would help me be a better scientist. I was poor, and I could not afford the opportunities. I would be pushed away if I tried to advocate for financial assistance. In my undergraduate years, I had the chance to work on my thesis with a researcher I love, but I needed a lot of money to help my parents hire an immigration attorney. So instead, I worked for Google because they offered a larger salary. Two months as a full-time research assistant would barely pay rent. In my master’s program, a similar situation occurred where I could not afford to take the research assistant salary. So, I needed to figure out how to find a way to continue training as a researcher while managing my family’s financial circumstances. And the thing that galvanized me to create a program during my PhD that would allow me to support other students born into low-income situations like myself was knowing that I could more easily have become a scientist if I only had had a little more financial support.

Much of your neuroscience research is geared toward DEI. Are there other DEI spaces that you are involved in?

For many people who try to do scientific research, it is often hard to avoid diversity, equity, and inclusion efforts, because we often have to point out scientific injustices or champion for spaces for us to exist. So, on the one hand, I focused on poverty and development in psychology. On the other hand, I also do a lot of work in science education and diversity in science. One of the projects I am involved in is figuring out the antecedent to academic career success. We want to find the common factors that help people transition from an undergraduate experience to a tenure-track profession, especially for minoritized scientists.

Another major project I am involved in is called FLi Sci. In the summer of 2020, every scientist talked about diversity and inclusion in science. Implementing graduate mentorship programs was their number-one solution to provide more diversity efforts. Although these programs are important, scientists often pose them as the only solution. The root cause starts a lot sooner than college programs. I wanted to target high school students who went to lower-income schools, like I had, to prepare them earlier for college and graduate school. The goal was not to let lower-income students become college seniors lacking the research experience they needed to be competitive for PhD programs.

“We want to find the common factors that help people transition from an undergraduate experience to a tenure-track profession.”

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Many students do not have enough experience to get postbaccalaureate opportunities, because it’s so competitive nowadays for people to get opportunities without a research background. So, I created FLi Sci because I was looking for other nonprofits targeting low-income or non–high-achieving high school students. Often, these programs accepted previously accomplished students. They were students who did well on the PSAT or went to a magnet school. I struggled to find a program trying to recruit students without those opportunities. So, I decided to create it and see what would happen.