Tag Archives: brain imaging

New neuroscience tools for team science in ‘big data’ era

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By Esther Landhuis

Wandering the convention center among 30,000-plus researchers, students and vendors at the Society for Neuroscience annual meeting in San Diego last November, I struggled to wrap my head around a feature I was writing for this week’s Nature, on managing big brain data. Mice, molecular biology and cell sorting reigned supreme in my former life as a bench scientist. Neurons, brain imaging, terabytes — not so much. So when it came time to find an entry into the vast universe of the brain, I latched onto something that seemed small and manageable: the fruit fly.

Ann-Shyn Chiang of National Tsing Hua University, Taiwan, told the SFN crowd his team has spent a decade imaging 60,000 neurons in the Drosophila brain. The pictures produced 3D maps detailed enough to show which neurons control precise behaviors, such as shaking the head side to side (see video). But here’s the part that blew my mind: They aren’t even halfway done (flies have 135,000 brain neurons), and mapping the human brain with similar methods would take 17 million years!

Head shake behavior elicited by a 593.5-nm laser. Credit Po-Yen Hsiao and Ann-Shyn Chiang.

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It’s time to map the brain

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A special complimentary focus on technology for large scale mapping of anatomy and function of brain circuits at Nature Methods
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These are exciting times in neuroscience. The technology available for  large-scale anatomical and functional brain mapping is advancing at a very high speed and it is foreseeable that these brain maps will have a profound impact on our understanding of how the brain works. Because of the importance of this topic, we devote a special focus to it.

To understand the brain we need to know how and when neurons fire in the living animal while it performs naturalistic behaviors. We need to know the underlying wiring patterns and anatomical configuration of the circuits and we need to be able to develop testable models of how behaviors arise from the underlying function of the cells in the brain.

Obtaining this type of systems-level information about the brain has not been easy up to now. But thanks to technological development, this is rapidly changing.

Rendering the connectivity maps of entire areas of the mammalian nervous system, like the retina, at nanometer resolution is now feasible in a few years work. These structural maps will contain unique information about the characteristics of neural circuits. But in addition to anatomical information, we need to monitor the brain at work at cellular level and we need to gather molecular information about its components. Together, the compilation of functional, structural and molecular data about the circuits in the living brain and their relation to behavior opens new posibilities for neuroscience.

Data-gathering alone will not, however, deliver the answers. Neuroscientists will need help from statisticians and mathematicians to make the information understandable and interpretable. After all, the data is only a tool that one hopes will lead to testable theories and models about how the brain works.

Because of the exciting moment at which the technology for mapping the brain is, we have put together a collection of Reviews, Perspectives and Commentaries in which experts discuss the state of the art technologies available for mapping the brain, the challenges and the potential of this endeavor. All the materials in this focus are freely available (thanks to our sponsors)—you can also read more about our views on the importance of this topic for neuroscience in our editorial.

We hope that these pieces will inform, inspire and incite discussions about mapping the brain and its potential to help us advance towards a deeper understanding of our own minds.

What’s behind an fMRI signal?

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In this month’s editorial we discuss the importance of gaining a deeper understanding of the signals underlying fMRI technology.

Despite the increased interest in this technology and the huge investments, we know very little about the underlying biology that produces these signals. This lack of understanding limits the type of information that can be obtained from this methodology and its utility to help us understand how our brains work.

We discuss new technological developments that might help address this question, including a research article by Dr. Helmchen and colleagues in this issue.

Dialogs between neuroimagers and cellular neurobiologists are critical to solve this question, as has been discussed before and funding institutions should give a higher priority to projects focused on gaining a deeper understanding of these complex signals.

Using the NIH RePORTER database we performed a search based on the following terms: ‘functional magnetic resonance imaging’ and ‘brain imaging’. We restricted the search to active projects starting on 1 January 2010 and we screened through the list of projects to remove those that were related to MRI but not fMRI. We then added up the total cost of all projects in the curated list. The number that we present in the piece is approximate and has not been scrutinized in detail. This way, we came up with the approximate amount of money that the US National Institute of Health has spent over different time periods in the last years. 

An exponential increase in scientific publications based on fMRI research has also been observed over the last years.

We’re curious to hear what you think of this!