Yves Sciama is a freelance science writer, trained in biology and science journalism, who covers life and environmental sciences. His work has appeared in Science et Vie, Le Monde and other major French-language media, as well as in Science. He has won multiple prizes and fellowships, including a yearlong Knight Science Journalism Fellowship at the Massachusetts Institute of Technology in 2014, and is former president of AJSPI, the French association of science journalists.
Yves Sciama
Contributing writer
From this contributor
At the end of the earth with Paul-Antoine Libourel
The French researcher’s accomplishments working with chinstrap penguins in the Antarctic highlight the importance of recording sleep in the wild.
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Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.