Article first published online: 24 SEP 2013
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Annals of the New York Academy of Sciences
Volume 1305, Annals Reports pages 83–93, December 2013
How to Cite
Jbabdi, S. and Behrens, T. E. (2013), Long-range connectomics. Annals of the New York Academy of Sciences, 1305: 83–93. doi: 10.1111/nyas.12271
- Issue published online: 10 DEC 2013
- Article first published online: 24 SEP 2013
- brain connections;
- chemical tracers;
Decoding neural algorithms is one of the major goals of neuroscience. It is generally accepted that brain computations rely on the orchestration of neural activity at local scales, as well as across the brain through long-range connections. Understanding the relationship between brain activity and connectivity is therefore a prerequisite to cracking the neural code. In the past few decades, tremendous technological advances have been achieved in connectivity measurement techniques. We now possess a battery of tools to measure brain activity and connections at all available scales. A great source of excitement are the new in vivo tools that allow us to measure structural and functional connections noninvasively. Here, we discuss how these new technologies may contribute to deciphering the neural code.