You'll love this week's featured science song, thanks to dopamine

"Whether it's the Beatles or Beethoven, people like music for the same reason they like eating or having sex: It makes the brain release a chemical that gives pleasure, a new study says."

Thus begins Malcom Ritter's article (Study: Love music? Thank a substance in your brain) summarizing a study just published in Nature Neuroscience (Anatomically distinct dopamine release during anticipation and experience of peak emotion to music by Valorie Salimpoor et al.).

To complete the dopamine/music pleasure circuit, how about listening to a song about this particular neurotransmitter (as well as its cousin norepinephrine)? "Chemical Love" by Charlie McDonnell is sure to fire up those striatal neurons!

Billy Joel, Adjunct Professor of Fishery Sciences

Thanks to Prof. Kira Wennstrom of Shoreline Community College for pointing us to this super-cool activity: Downeaster Alexa: A Fishery Story (PDF file).

It was created in 1991 through a National Science Foundation grant to an Ohio State University team led by Victor J. Mayer and Rosanne W. Fortner. Its in-depth consideration of the lyrics of the Billy Joel song "The Downeaster 'Alexa'" (embedded below), and its connection of those lyrics to relevant data, offer a strong rebuke to anyone tempted to dismiss educational uses of science songs as superficial or frivolous.

Science song of the week: Tevatron requiem

Tuesday's Nature News announced, "Tevatron faces final curtain."

After much debate, officials at the US Department of Energy's Office of Science revealed this week that they have decided not to extend funding for the Tevatron, the proton–antiproton collider at Fermilab in Batavia, Illinois, by an additional three years. The decision means that the first glimpse of the long-predicted Higgs particle, thought to endow other particles with mass, will probably be achieved by the Large Hadron Collider (LHC) at CERN, Europe's particle-physics lab near Geneva in Switzerland.

Below is the YouTube video for "Particle Business" by rapper funky49 (a.k.a. Steven Rush). It does a nice job conveying that CERN's LHC and Fermilab's Tevatron have been in a high-stakes race to find evidence of the Higgs particle:

Tevatron, OG atom smasher
say hello to CERN’s party crasher, the
new "Lord of the Rings" LHC, hear me, this
be competitive collaboration baby...
rock stars of physics, particle business
smash matter, antimatter and witness
quarks, bottom to top they don’t stop
"where the Higgs at?" yo that’s their mark
where the Higgs at? where the Higgs at?
where the Higgs at?

One more "year-in-review" song, and then on to 2011 in earnest!

The Scientist has published several compilations of the year's top biology papers, including a top 7 in biochemistry and a top 5 for all of biology, both ranked by the Faculty of 1000. The key advances included two prized crystal structures: complex I of the bacterial electron transport chain, and the two subunits of the yeast ribosome. The most pertinent song I found was "The Structural Biology Rap" by Zach Powers (a.k.a. The Science Rapper), which gives an overview of pertinent techniques including protein expression and crystallography.

Sonification: transforming data into sounds

NPR reports on Lily Asquith's attempts to analyze LHC data by converting them into sounds in "Particle Pings: Sounds of the Large Hadron Collider."

[Asquith] thought about a heart monitor in a hospital; it turns the electrical data from your heart into sound.

"You don't have to watch the monitor because you can hear it without making any effort," she says. "Just a steady beep — you can quite easily detect if it starts going quicker or if it stops even for a second."

She wondered what would happen if she used music composition software to turn data from the collider into sound....

What she got isn't quite music, but sounds that are more out of this world — bells, beeps and clangs.

Right now, Asquith says, the sounds don't tell scientists very much. But she hopes that in the future, it could help them understand the data in new ways.

She says that in certain situations, it's much easier to use your ears than your eyes, particularly with something that's changing over time. Collider data do that.