All posts by: Sarah Hansen, M.S. '15


Tamra Mendelson advocates using human psychology framework to understand animal cognition

How animals choose when to migrate, with whom to mate, or what to eat can have a huge impact on their ability to survive and reproduce, and thus, the evolution of their species. That’s why evolutionary biologists like Tamra Mendelson, associate professor of biological sciences at UMBC, want to learn more about decision-making processes in animals. But the existing literature doesn’t make it easy to compare studies or unravel the many steps between input and action.

Researchers use “a mish-mash of terms to describe cognition,” says Mendelson. One research team might say that a female fish can “discriminate” between green and red male fish, meaning she can detect a difference. Another team might report that an insect “discriminates” by choosing a mate who offers her a larger morsel of food. In that case, the “discrimination” is the choice that follows the detection of difference. Inconsistencies in terminology like this can lead to confusion and discourage collaboration across research areas.

Because most evolutionary biologists are not trained in the language of psychology, “We come up with our own language,” explains Mendelson, “We say, ‘We know what we mean,’ but do we?”

In her new opinion paper, published in Trends in Ecology and Evolution and funded by the National Evolutionary Synthesis Center, Mendelson and colleagues propose a solution to the imprecision of language in their field. They argue adopting it would improve communication between research teams and also our understanding of how animals make decisions. The team recommends employing the Judgment and Decision Making (JDM) Framework, a lexicon that psychologists have used for decades to describe the steps involved in human decision-making.

The framework differentiates between “judgments,” the process of gaining knowledge about the world, and “decisions,” the process of choosing what to do with that knowledge, and it precisely defines terms associated with each stage. Terms like “discrimination” and “recognition” are associated with judgment, while “preference” and “choice” are decision-related terms.

The JDM Framework emphasizes the actual components of cognition (how animals think) rather than the behavioral outcome (what they do after thinking). Breaking down the process of decision-making into its components opens up a whole new world of possible research questions. Using the framework could reveal previously undiscovered complexities in animal thought, and eventually guide researchers to the specific genes that contribute to different components of cognitive processes.

Better understanding how animals think could have important implications for how humans work with animals, such as informing wildlife conservation efforts. As Mendelson points out, “An animal’s first defense against climate change is behavior.” Based on how they think, some species may be better than others at adapting to a changing climate. The species that have more trouble adapting may need more of our attention.

Mendelson acknowledges understanding the animal mind is an uphill battle. “It’s cognition,” she says, “It’s very complicated.” But adopting a consistent vocabulary could speed research progress. The terms the field needs are out there, she says, “It’s a matter of matching them to consistent, precise meanings to improve communication in the field and across disciplines.”

Image: Mendelson at a research field site; courtesy Tamra Mendelson.

Astrophysicist Robin Corbet discovers rare, high-energy binary star system beyond the Milky Way

Until recently, humans had only detected five binary star systems—pairs of stars orbiting each other—that emit extremely high-energy gamma rays. Robin Corbet, an astrophysicist at UMBC’s Center for Space Sciences and Technology (CSST), just discovered the sixth, and most luminous, and this one is special. Instead of being in our Milky Way galaxy, it’s located in the Large Magellanic Cloud, our next-door neighbor galaxy, 163,000 light years away.

This marks Corbet’s second gamma ray binary discovery, following his initial detection of such a system through the Fermi gamma-ray space telescope five years ago. After that initial find in 2011, he thought more would follow quickly, but the systems proved elusive. The fact that he found the sixth known gamma ray binary outside of the Milky Way came as quite a surprise. At first, he shares, “I didn’t believe it.”

In order to emit gamma rays, which contain one million times the energy of visible light waves, one of the “stars” in the binary system must be a black hole or neutron star, a star that has collapsed in on itself. “These are more massive than our own Sun but squeezed down to something about the size of Washington, DC,” explains Corbet. Hundreds of these binary systems have been found that emit X-rays, but only a handful emit even higher-energy gamma rays.

Corbet detected the system by analyzing variations in gamma rays coming from about 3,000 known gamma ray sources. In a gamma ray binary system, the intensity of the gamma rays as they strike the telescope varies depending on the relative position of the stars as they orbit each other. Because the gamma ray sources are so far away, only a small percentage of the rays ever reach the telescope. That means it can take a long time to collect enough data to detect a pattern.

Once the Fermi satellite collected enough data, Corbet ran analyses on a 12-core computer for a few months. Looking at gamma rays from all 3,000 sources, the analyses identified two stars orbiting each other every 10.3 days—a new binary system. Then Corbet requested data sets from colleagues around the world that included X-ray, radio wave, and visible light wave data. He hoped the additional information would corroborate the gamma ray signal and confirm the orbital period, which it did. The visible light data also supported the idea that the system contains a neutron star, but there’s still a small chance it could be a black hole.

Binary systems can only generate the energy required to emit gamma rays when the neutron star is rotating very fast. The fact that only six of these systems have ever been discovered suggests that very few neutron stars rotate that quickly, and there may be more slowly-rotating neutron stars than scientists thought.

Calculations suggest the neutron star in the system Corbet just discovered rotates around its axis in less than 39 milliseconds, compared to Earth’s 24-hour rotation. As a star rotates, it flings particles away from its surface, creating a “stellar wind.” With one star in a binary rotating so fast, interactions between particles in the stellar wind from each star can be intense, which is what creates the gamma rays. “It’s like having a particle accelerator in space,” says Corbet.

Next steps for the research include confirming that one star in the system is indeed a neutron star by making observations to directly detect its rotation period, although this is very difficult. Corbet is also interested in tracking the two stars’ orbits, to see if they are truly circular or more elliptical. Because there are so few of these systems, and this is the only one outside the Milky Way, anything learned will inform future research goals and theories about extreme binary star systems.

Read the full paper in The Astrophysical Journal here: A luminous gamma-ray binary in the Large Magellanic Cloud

Image: Yellow circle indicates the gamma-ray binary discovered by Robin Corbet in the Large Magellanic Cloud; photo courtesy NASA Goddard.