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Connection Between Music And Math

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I remember the first time I heard the statement “Did you know that listening to classical music enhances your mathematical abilities?”

I was both intrigued and excited, intrigued because I did not understand how music and math, two seemingly unrelated subject could possibly affect each other. I was also excited because I began to view classical music as some kind of magical potion that would transform my math skills from decent to extraordinary. When I had the opportunity to write this web paper for The Silo, I immediately jumped into the topic of music and math. The questions that I wish to answer throughout this paper are; does listening to music really help you do better in math? If so, which part of the brain is controlling the correlation between math and music? In addition, how does music stimulate the brain in a way that enhances mathematical abilities?

It turns out that there is much evidence that supports the positive effects of music on one’s ability to do math.

Most research shows that when children are trained in music at a young age, they tend to improve in their math skills. The surprising thing in this research is not that music as a whole is enhancing math skills. It is certain aspects of music that are affecting mathematics ability in a big way.

Studies done mostly in children of young age show that their academic performance increases after a certain period of music education and training. One particular study published in the journal ‘Nature’ showed that when groups of first graders were given music instruction that emphasized sequential skill development and musical games involving rhythm and pitch, after six months, the students scored significantly better in math than students in groups that received traditional music instruction. (1)

The result of this study posed another important question. How does this type of music that emphasized sequential skills, rhythm and pitch manage to improve children’s ability to do math? It turned out that there are two distinguished types of reasoning, spatial temporal (ST) reasoning and Language analytical (LA) reasoning. LA reasoning would be involved in solving equations and obtaining a quantitative result. ST reasoning would be is utilized in activities like chess when one needs to think ahead several moves.

The effect of music on math sometimes termed the Mozart effect.

The Mozart effect gain its name after the discovery that listening to Mozart’s compositions, which is very sequential, produces a short-termed enhancement of spatial-temporal reasoning. Some key reasoning features used in spatial temporal reasoning are:

1. The transformation and relating of mental images in space and time

2. Symmetries of the inherent cortical firing patterns used to compare physical and mental images and

3. Natural temporal sequences of those inherent cortical patterns (3).

The same people who conducted the Mozart effect experiment also suggested that spatial-temporal reasoning is crucial in math. The areas of math that require ST reasoning are geometry and certain aspects of calculus, which require transformations of images in space and time. In higher mathematics, the ability to write mathematical proofs is also associated with ST reasoning because proof writing is a task that requires intuitive sense of natural sequences and the ability to think ahead several steps.

As to the question, what part of the brain controls the correlation between math and music, there are also many resources that provide answers.

Dr. Gottfried Schlaug, found that certain regions of the brain such as the corpus callosum and the right motor cortex, were larger in musician who started their musical training before the age of 7 (2). As to what happens in that area of the brain when one listens to music, we turn to the experiment performed by Xiaodeng Leng and Gordon Shaw. Gordon and Leng developed a model of higher brain function, which is based on the trion model. The trion model is a highly structured mathematical realization of the Mountcastle organization principle, with the column as the basic neuronal network in mammalian cortex. The column comprises mini-columns called trions.

One particular columnar network of trions has a large repertoire of spatial-temporal firing patterns, which can be excited and used in memory and higher brain functions (3). Shaw and Leng performed an experiment in which they mapped the trion model of firing patterns in that particular column onto various pitches and instruments producing recognizable styles of music. This mapping of the trions gaves insight to relate the neuronal processes involved in music and abstract spatial-temporal reasoning (3).

It shows that the part of the cortex, which contains the repertoire of spatial-temporal firing patterns, can be excited by music and is utilized in higher brain functions such as spatial-temporal thinking in mathematics.

In conclusion, my research into math and music does seem to suggest that music truly enhances mathematics skills. Music targets one specific area of the brain to stimulate the use of spatial-temporal reasoning, which is useful in mathematical thinking. However, as to the question of whether or not music is the magical portion that will elevate anyone’s ability to do math, the answer unfortunately . . .would be no.

Just because most mathematicians are fond of music, doesn’t mean that all musicians are fond of mathematics. I found a letter posted on the web written by a fourteen-year-old overachiever to a mathematics professor. The student expresses his frustration that even though he is an excellent musician, math is one of his weakest subjects. In math, he is not making the grades that he needs to stay in a certain prestigious academic program (4).

This letter seems to suggest that listening to music, or being able to master a musical instrument does not automatically guarantee that one can perform well in math. In other words, there are many musicians who are good in music but not in math. Music is a lot more than notes conforming to mathematical patterns and formulas. Music is exhilarating because of the intricacies of the patterns that occurs. Whether or not these patterns resemble math has no relevance to many musicians. More often than not, musicians are inclined to practice music because of the wonders and awe that they feel for music even if they are not aware of the math that is in music. Cindy Zhan

WWW Resources (1)Making the case of music education (2)Music on the mind (3)Spatial-temporal versus language-analytical reasoning: the role of music training (4)Letter written by a young musician

This Is Your Brain On Music BookThis Is Your Brain on Music: The Science of a Human Obsession is a popular science book written by the McGill University neuroscientist Daniel J. Levitin, and first published by Dutton Penguin in the U.S. and Canada in 2006, and updated and released in paperback by Plume/Penguin in 2007. It has been translated into 18 languages and spent more than a year on The New York Times, The Globe and Mail, and other bestseller lists, and sold more than one million copies.
Sci-Tech

University Of Maryland Will Investigate AI Limitations Via Army Research Grant

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COLLEGE PARK, MD: University of Maryland College of Information Studies (UMD iSchool) researchers, led by principal investigator Dr. Susannah Paletz, have been awarded a three-year $616,700 usd grant funded by the Army Research Office (ARO), overseen by ARO Program Manager Dr. Edward Palazzolo. This project examines how teams of intelligence analysts can work together and with artificial intelligence (AI). AI has the potential to support intelligence analysts in reviewing potentially hundreds of thousands of source documents, pulling out key findings, and assembling them into actionable intelligence. AI can also aid in the flow of information and projects among members of the intelligence team, improving the efficiency and accuracy of their work.

“AI-driven technology has sometimes been touted as a replacement for human intelligence,” said Dr. Adam Porter, the project’s co-principal investigator, professor at the UMD Department of Computer Science, and Executive and Scientific Director of the Fraunhofer USA Center for Experimental Software Engineering (CESE). “In practice, however, AI doesn’t always work, or gives limited or biased answers. Human oversight is still required, and it’s therefore critical that we deeply understand how humans and AI can work best together.”

The Human-Agent Teaming on Intelligence Tasks project coordinated through the iSchool will focus on two particular research areas; 1.) how interactive AI agents, such as chatbots, have the ability to mitigate or exacerbate the communication and coordination problems that can occur with shift handovers of intelligence work, such as inaccuracy blindness and overlooking potentially relevant information, and 2.) examining how humans could potentially deal with these blind spots, biases, or inaccuracies. 

The research team plans to develop an experimental infrastructure to help test team cognition challenges within the work completed by intelligence analysts consisting of task-relevant input materials, such as mission descriptions and source documents, activity recording tools, experimental monitoring capabilities, and different AI supports for human analysts, such as chatbots offering advice on a particular task. 

“We want to develop a task that can raise the problems with asynchronous team cognition in intelligence tasks, but is simple enough to be used by research participants with minimal training,” said Dr. Susannah B.F. Paletz, research professor at the UMD iSchool, and affiliate at the UMD Applied Research Laboratory for Intelligence and Security (ARLIS). 

Susannah Paletz
Dr. Susannah B.F. Palletz


This task will substantially increase insight into the strengths and weaknesses of AI technology to support intelligence tasks, help shed light on how and when human analysts can safely place their trust in AI technology, and how they can proactively identify problems in AI-generated input. It will also aid teams of humans, including asynchronous teams, working together in situations that include AI-generated input.

“This basic research is an important step in the early process of learning how humans and agents can collaboratively become a single team with considerably greater capacity and productivity than human only teams,” Palazzolo said. “Moreover, this research has broad implications into the work of many teams focused on knowledge work and information management such as medical teams involved in shift work, collaborative software development teams, and research teams.”

In addition to Porter, the Fraunhofer USA team also includes Dr. Madeline Diep, Senior Scientist, and Jeronimo Cox, Software Developer, at Fraunhofer USA CESE. The Fraunhofer USA team will lead the effort to create configurable AI agents used in the experimental tasks, and a data collection and analysis infrastructure for capturing and understanding participant behaviors.

The UMD iSchool team includes graduate students Tammie Nelson, a fourth year PhD student, Melissa Carraway, incoming first year PhD student, and Sarah Valhkamp, incoming first year PhD, in Information Science.

The grant proposal team includes UMD Office of Research Administration Contract Manager, Stephanie Swann; iSchool Business Manager, Jacqueline Armstrong; and former iSchool Business Manager, Lisa Geraghty.

Outside of UMD, Dr. Aimee Kane, the Harry W. Witt Faculty Fellow and an Associate Professor of Management in the Palumbo-Donahue School of Business at Duquesne University, will be a consultant and an intellectual contributor on this project.

ARO is an element of the U.S. Army Combat Capabilities Development Command’s (CCDC) Army Research Laboratory. The Human-Agent Teaming on Intelligence Tasks project (grant no. W911NF-20-1-0214) is slated to run through June 30, 2023. For the Silo, Mia Hinckle.