Is Your Brain a Computer?

By Allison Mohan

All science involves data. Scientists collect and interpret data every day. The information gathered from research can be applied to everyday life. Science strives to find answers and to make the world a better place. This can be done by collecting data and analyzing patterns. Computers have provided scientists with the opportunity to have data processed and analyzed at greater speeds and magnitudes as time goes on, and they are now necessary in the fast-paced and growing world we live in.

Mark Albert, PhD has advocated for the necessity of scientists, particularly neuroscientists, to have at least a basic understanding of computer science.  In a research article he coauthored, “Could a Neuroscientist Understand a Microprocessor?,” an argument is made that “current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data.” The brain is complex, and at the same time, a lot of data on the brain is being collected every day by researchers. But how can someone confidently interpret the data of something that they do not understand? How is there any way to know that a conclusion is reliable? Albert argues “for testing approaches using known artifacts, where the correct interpretation is known.” Albert says that many modern neuroscience methods rely primarily on reporting correlations, and a mass of such correlation experiments alone are not sufficient enough to understand the brain as well as we can understand computers such as microprocessors.  Albert believes that scientific knowledge needs to be externalized. Computer models are clear and can be understood.

In a New York Times article entitled “Face It, Your Brain is a Computer,” Gary Marcus argues that the brain is analogous to a computer, and subscribing to that idea could greatly help to “profitably guide research.” A particular type of computer, a field programmable gate array, is what Marcus argues to be a good model of how the brain operates. He references a research article he wrote in which he and his colleagues suggest that “the brain might similarly consist of highly orchestrated sets of fundamental building blocks” much like those in a field programmable gate array. Brains are “exceptionally complex arrangements of matter,” and there exists no evidence to support that brains are “exempt from the laws of computation,” so why approach them differently?

Albert argues that neuroscientists should possess an understanding of computer science in order to analyze the brain in more reliable ways. Marcus argues that the brain is a type of biological computer, and therefore should be researched as such. To Marcus, conquering understanding of the brain is, put simply, just a matter of figuring out “what kind of computer” it is.  Both believe that the brain needs to be approached in research differently. Conclusions drawn about the brain will be more reliable when the brain is approached using analytical techniques that have already been proven correct on known objects, such as computers. Information gathered about the brain will be more reliably transferred to others through computer models. And, maybe, using Marcus’s analogy, there will come a day when we can identify what type of computer the brain truly is.

References

            “Face It, Your Brain is a Computer.” Marcus, Gary. 27 June 2015. https://www.nytimes.com/2015/06/28/opinion/sunday/face-it-your-brain-is-a-computer.html

            “Could a Neuroscientist Understand a Microprocessor?” Jonas, Eric et al. 2017.