Michael Skeide is a cognitive neuroscience researcher at the Max Planck Institute for Human Cognitive and Brain Sciences. Michael studies the development of learning, language, memory, perception, and attention. He is trying to decode cognitive processes by looking at children’s brain activity, with the hope of understanding individual learning trajectories in early childhood. Annie Brookman-Byrne talks with Michael about the new questions cognitive neuroscience researchers are asking, and his hopes for the future of this work.

Annie Brookman-Byrne: What are the biggest mysteries in your research field of cognitive neuroscience?

Michael Skeide: The human brain is the smartest self-organizing system in the known universe. How this unique system works remains a major mystery. We don’t yet have a theory that explains how the human brain generates natural intelligence in the course of development. Much of what you read in textbooks seems to be a metaphorical description rather than a scientific explanation: There are references to an “attention network” here and a “memory hub” there, and so on. It is much harder to come up with a mathematical model of cognitive computation in the developing brain.

“Current computer hardware has little in common with the biological hardware in our heads.”

Artificial intelligence research offers helpful tools to move this field forward. But there are considerable challenges that limit communication between the artificial and natural intelligence research communities. Current computer hardware has little in common with the biological hardware in our heads. This makes it hard – if not impossible – to test the notion that deep learning algorithms might be at work in the human brain. Moreover, what these computer algorithms actually compute when they are trained and tested remains largely hidden in a black box.

Cognition is an umbrella term for the mental processes involved in perception, thinking, reasoning, decision-making, and problem-solving.

ABB: What are you investigating as you conduct research into fundamental cognitive abilities, and how?

MS: I am trying to discover the developmental origins of learning, language, memory, perception, and attention. During the earliest stages of life, cognition can be hard to observe. For example, it is far from obvious that newborns can understand speech or even numbers. My lab employs a cognitive neuroscience approach to overcome this limitation. This means we record children’s brain activity and develop methods to decode cognitive processes using the brain data. Such work has shown that newborns can distinguish between the speech sounds ga and ba, and between 4 and 12 dots on a display, for example.

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ABB: What changes have you seen in this research over time?

MS: Cognitive neuroscience research has traditionally focused on exploring when and where information is processed in the brain. For example, recording techniques allow us to measure with millisecond precision the brain’s different stages of recognising a face. Other techniques can show precisely, to the millimeter, where in the brain signals come from that allow a person to focus on the left eye of a face while ignoring the right.

More and more, researchers are going beyond merely exploring where and when brain functions occur, to determine how the brain might process information. To give an example, we are currently testing the theory that there are number neurons in the brain. In our model, we can change the range of numbers each neuron responds to as well as the specific number to which each neuron responds most strongly. We hope that this model will be useful for determining how sharply individual brains are attuned to numbers, thereby leading to a better understanding of individual differences in mathematical ability.

ABB: How do you hope your research will help children?

MS: So far, cognitive neuroscience research has rarely translated into real-world applications like educational programs to help children learn. A major obstacle is that the data we collect do not typically allow us to draw conclusions about individual children. Instead, results usually take the form of group statistics that describe the average person. The goal of my lab is to overcome this obstacle by finding novel experimental approaches that allow us to investigate cognition in the brains of individual children.

We hope to discover predictors of learning outcomes by decoding brain activity, which will, in turn, guide practical efforts to detect individual children’s possible strengths and weaknesses. Ultimately, I hope that this knowledge will enable educators to recommend targeted early intervention efforts that are more effective than “one-size-fits-all” programs. That might pave the way for more effective support measures for neurodiverse children, like those with dyslexia, dyscalculia, and ADHD, but maybe also for highly gifted children with extraordinary cognitive capacities.

“A system as complex as the radically reorganizing brain of a human child remains one of the biggest mysteries in science.”

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ABB: What are your hopes for the future of cognitive neuroscience research?

MS: My dream is that one day we will be able to read the neural code for cognition that is written during a child’s development. Such an insight might require revolutionary brain recording technology. For example, it would be exciting to find a non-invasive way to measure the real-time activity of individual neurons in children. Right now, we get very noisy signals generated by hundreds of thousands of neurons. Trying to find a trace of cognition in these signals is like searching for a needle in a haystack.

High-resolution technology alone, however, will not get us there. We will also have to make major strides in creating mathematical models of computational change in complex systems like the developing human brain. This task seems to be too difficult for our existing modelling frameworks – even when they are applied to much simpler systems, such as the brain of a fruit fly. A system as complex as the radically reorganizing brain of a human child remains one of the biggest mysteries in science.


Michael Skeide completed his undergraduate studies at Heidelberg University and Harvard University before obtaining a PhD in Psychology from Leipzig University. He is currently the head of a research group at the Max Planck Institute for Human Cognitive and Brain Sciences. His group investigates how cognitive abilities are generated by the developing brain. His award-winning research is published in Nature and Science journals and supported by the European Research Council (ERC), the German Research Foundation (DFG), the National Institutes of Health (NIH), the Alexander von Humboldt Foundation and the Jacobs Foundation. Michael is a Jacobs Foundation Research Fellow 2021-2023.

This interview has been edited for clarity.

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