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"Black Lives Matter"​: Neuroscience view

Updated: Jun 19, 2020

When I saw the news about Floyd and how this event affected the Black community to speak up and other racial groups to support, it made me wonder about how a lot of people live under oppression and stress all their lives and no one has any idea about how this affects their health and wellbeing. For over 10 years that I lived abroad, I had to come up with a strategy to deal with racial discrimination. I have used science as a tool to deal with the hidden - and sometimes not so hidden - biases, as I thought to be in a science-based environment will less likely to expose me to racial discrimination. I have been naïve, safe to say! Recently we have conducted a study in which we explored the interaction between belief and logic. The results are quite relevant to the current climate, so I decided to briefly discuss our findings in relation to what we see now in the world. Here is what my science has to say about our belief and logic and how they interact:



What does science say about the root of bias?

In an imaging study, we asked people to reason about a statement that followed either believable or unbelievable assumptions. An example of an unbelievable assumption is “all dogs are parrots” and a believable one is “all parrots are birds”. We looked at the brain’s activity responses when participants were processing these statements. What we found was that assumptions we hold intrinsic to us affect the way we reason, no matter the given facts, and it is deeply rooted in our memory and emotional systems. Interestingly, during reasoning, our memory and emotion guide our attentional to be oriented towards scenarios that are not in line with our beliefs at a relatively early stage of reasoning. This means our experiences and emotional preferences influence how we navigate new scenarios and new situations that need reasoning. This could be expanded to other currently held beliefs.

If you believe Muslims are terrorists, your reasoning will be clouded by this belief!

How can we cope with this bias?

We have the control system that can help us to overcome this bias, our prefrontal cortex. As an adult, if you are aware of your biases, you are more likely to accept different assumptions and be more logical. If you have better control over your emotions, it is also more likely to overcome this bias and be more logical.


Implications in parenting, justice, education, and more

These findings have broad implications for justice and schooling systems. But I am not a sociologist nor a policymaker. As a parent, though, I feel responsible to think about how we can use these findings to raise unbiased children. As parents, we should think about ways that we can expose our children to different cultures, different environments, different colors, and races. How would that help? Well, it would teach them to be objective and evaluate facts rather than being biased by their assumptions, which teaches them how to truly respect others. And importantly, teach them how to control their anger and frustrations, this is not given, so needs training but will have a huge impact on kids’ strategies to deal with difficult situations in their lives. I think this would be a great start to create an inclusive and respectful generation.

Next time you encounter a racially different individual, before you make any snap judgment, try to evaluate your assumptions about that group of individuals, whether Muslims, Blacks or Asians. We all have our differences and we can contribute to a better community if we are respectful and inclusive.

References:

Ziaei, M., Bonyadi, M.R. & Reutens, D.C. (2020) Age-related differences in structural and functional prefrontal networks during a logical reasoning task, Accepted for publication (Preprint available here).

Ziaei, M., Bonyadi, M.R. & Reutens, D.C. (2020) A new role of the hippocampus in logical reasoning and belief bias in aging, Frontiers in Aging Neuroscience (link here)  

Ziaei, M., Bonyadi, M.R. & Reutens, D.C. Belief loads of assumptions impact brain networks underlying logical reasoning: A machine learning approach (Preprint available here)

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