After taking a long and hard look at avian noggins, scientists have now determined that the method biologists and other scientists have been using to predict and compare brain size is simply not good enough. In fact, it may not even be accurate for animals of the same species!

That's at least according to Corina Logan, a researcher with the University of California at Santa Barbara whose work focuses on a very intelligent member of the blackbird family, the great-tailed grackle.

Primarily concerned with the cognitive abilities of her favorite bird, Logan has been looking to find a way to accurately estimate the brain size of live grackles by measuring their heads, rather than taking the time to brain scan the birds. As you can imagine, getting a fidgety and confused bird to sit still for a scan can be a bit challenging.

"That's what I was trying to do - study them in the wild after measuring them so I could see whether their brain size influences their behavior or the number of offspring they have," she said in a recent statement.

To see if they could simplify their work, Logan and biologist Christin Palmstrom acquired blackbird skulls from various museums and measured them via CT scans and then simple caliper assessments - recording the size and shape of a skull.

"If the external skull measurements matched the volumes from the CT scans well enough, then we could use the CT scan or caliper methods interchangeably," Logan explained. (Scroll to read on...)

This was what the pair were hoping for - a revelation that could save a lot of time and money. Unfortunately, Logan and Palmstrom found the complete opposite: not only did brain-size-to-skull ratios vary wildly between different species, but also were stunningly varied among individuals of the same bird species.

"People love to study brain size," Logan added. "It's a huge topic. And there is growing interest in how brain size varies within a species, which can tell us what factors contribute to the evolution of large brains."

That's why she was committed to publishing these findings, despite the fact it completely contradicts what many experts have assumed when running their numbers in large data-sets.

"People see a 'significant correlation' between two sets of measurements and think it works," Logan said. "But it's often not a very tight correlation. There is an overreliance on any level of correlation as long as it's significant."

The consequence? To avoid skewed data, researchers may have to simply break out the elbow grease, CT scanning each and every brain they study. And with calipers, at least for birds brains, you might as well be guessing.

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