Princeton, NJ - The brain is the ultimate big-data problem. Its billions of neurons give rise to numerous abilities, such as making decisions, interpreting color and even recognizing your best friend. Jonathan Pillow, a Princeton University assistant professor of psychology and the Princeton Neuroscience Institute, aims to understand the brain by using math and statistics to make sense of the reams of information collected by brain-imaging studies. Recently arrived from the University of Texas-Austin, Pillow, who also is affiliated with the University's Center for Statistics and Machine Learning, sat down to talk about how he got into neuroscience, his approach to teaching, and his latest research published earlier this month in the journal Science.
How did you become interested in neuroscience?
I was a philosophy major as an undergraduate and I was interested in questions such as where does the mind come from. I also studied mathematics and came to realize that neuroscience offered the kinds of tools that I thought would be most useful for understanding how the brain works.
What are the big questions that you are trying to tackle?
My research group is trying to understand how groups of neurons work together to process information. We aim to find out what is happening in the brain that allows you to recognize a face, identify what colors things are, or move your hand to catch a ball that is flying through the air.
How do you go about this research?
We analyze neural activity recorded using functional MRI and other brain-imaging technology, as well as recordings of single neurons, made while a human or animal is engaged in a task.
Given these recordings, our group works on figuring out what patterns of neural activity correlate with the incoming stimulus and the outgoing behavior.
How daunting is this challenge?
Understanding the human brain is one of the greatest challenges of science. The field of neuroscience is really in its infancy when it comes to understanding how behavior arises from neural activity. We understand a lot about how single neurons work, and in some cases how small groups of neurons work together to generate certain behaviors, but we still have a ways to go.
Where does mathematics fit in?
We have a "big data" problem because we can record what a lot of neurons are doing but the challenge is how those activities lead to behavior. It is an exciting time to be doing this because there are rapid expansions of computing power and a lot of exciting work in statistics and the theory of how to work with big data. My research group is developing algorithms that can extract the kind of patterns that we are interested in finding.
How can your research benefit society?
What motivates our research is the desire to understand how the healthy brain works so that we can figure out what goes wrong in brain disorders such as Alzheimer's disease, Parkinson's disease, dementia and schizophrenia. I am working in particular on decision-making, which seems to be compromised in a lot of brain disorders.
A potential application for this kind of fundamental research is sensory or motor prosthetics. If we can learn how your brain is able to recognize a face, or how it can plan a path through a cluttered environment, then we may able to design robots or other artificial systems that can solve those same tasks using the computational strategies that the brain uses.
You moved to Princeton recently from the University of Texas-Austin. What made you decide to come to Princeton?
It is an exciting time in the field of statistical neuroscience for developing tools to analyze data sets. At Princeton, I have the opportunity to collaborate with both theorists and experimentalists. It is an extraordinary group of collaborators and students.
For the full story: http://www.princeton.edu/research/news/faculty-profiles/a/?id=15343
I was a philosophy major as an undergraduate and I was interested in questions such as where does the mind come from. I also studied mathematics and came to realize that neuroscience offered the kinds of tools that I thought would be most useful for understanding how the brain works.
What are the big questions that you are trying to tackle?
My research group is trying to understand how groups of neurons work together to process information. We aim to find out what is happening in the brain that allows you to recognize a face, identify what colors things are, or move your hand to catch a ball that is flying through the air.
How do you go about this research?
We analyze neural activity recorded using functional MRI and other brain-imaging technology, as well as recordings of single neurons, made while a human or animal is engaged in a task.
Given these recordings, our group works on figuring out what patterns of neural activity correlate with the incoming stimulus and the outgoing behavior.
How daunting is this challenge?
Understanding the human brain is one of the greatest challenges of science. The field of neuroscience is really in its infancy when it comes to understanding how behavior arises from neural activity. We understand a lot about how single neurons work, and in some cases how small groups of neurons work together to generate certain behaviors, but we still have a ways to go.
Where does mathematics fit in?
We have a "big data" problem because we can record what a lot of neurons are doing but the challenge is how those activities lead to behavior. It is an exciting time to be doing this because there are rapid expansions of computing power and a lot of exciting work in statistics and the theory of how to work with big data. My research group is developing algorithms that can extract the kind of patterns that we are interested in finding.
How can your research benefit society?
What motivates our research is the desire to understand how the healthy brain works so that we can figure out what goes wrong in brain disorders such as Alzheimer's disease, Parkinson's disease, dementia and schizophrenia. I am working in particular on decision-making, which seems to be compromised in a lot of brain disorders.
A potential application for this kind of fundamental research is sensory or motor prosthetics. If we can learn how your brain is able to recognize a face, or how it can plan a path through a cluttered environment, then we may able to design robots or other artificial systems that can solve those same tasks using the computational strategies that the brain uses.
You moved to Princeton recently from the University of Texas-Austin. What made you decide to come to Princeton?
It is an exciting time in the field of statistical neuroscience for developing tools to analyze data sets. At Princeton, I have the opportunity to collaborate with both theorists and experimentalists. It is an extraordinary group of collaborators and students.
For the full story: http://www.princeton.edu/research/news/faculty-profiles/a/?id=15343
