Does motherhood dampen cocaine’s effects?

Mother rats respond much differently to cocaine than female rats that have never given birth, according to new University of Michigan research that looks at both behavior and brain chemistry.

The findings may help lay the groundwork for more tailored human addiction treatment, based on scientific understanding of how gender, hormones and life experience impact drug use.

In an oral presentation at the Society for Neuroscience meeting, U-M researcher Jennifer Cummings, Ph.D., summarized findings from experiments with rats at the Molecular and Behavioral Neuroscience Institute, part of the U-M Medical School. She worked with Jill Becker, Ph.D., of the U-M Department of Psychology.

They identified clear differences in how intensely the “pleasure centers” in the mother rats’ brains reacted to the drug, compared with non-mothers. Mother rats’ brains released less of a chemical called dopamine, which helps cause the “high” from cocaine.

They also found an interaction with stress: mother rats that were exposed to periods of increased stress weren’t willing to work as hard to get a dose of cocaine, compared with rats that had never given birth or mother rats that weren’t exposed to the stress – even though the stressed mother rats showed an increased tendency to use cocaine when it was easy to get.

Taken together, the findings suggest that the experience of becoming a mother alters a female’s overall response to cocaine – adding complexity to the issue of how best to treat addiction.

“While we have not yet identified a mechanism to explain these differences, they do suggest that the reward system and brain circuitry affected by cocaine is changed with maternal experience,” says Cummings, a research investigator at MBNI and former postdoctoral fellow in Becker’s laboratory. “The next step is to determine how factors such as hormone changes in pregnancy and early motherhood, and the experience of caring for offspring, might be differentially contributing to this response.”

Plaque Build-Up in Your Brain May Be More Harmful Than Having Alzheimer’s Gene

A new study shows that having a high amount of beta amyloid or “plaques” in the brain associated with Alzheimer’s disease may cause steeper memory decline in mentally healthy older people than does having the APOE ɛ4 allele, also associated with the disease. The study is published in the October 16, 2012, print issue of Neurology®, the medical journal of the American Academy of Neurology.

“Our results show that plaques may be a more important factor in determining which people are at greater risk for cognitive impairment or other memory diseases such as Alzheimer’s disease,” said study author Yen Ying Lim, MPsych, with the University of Melbourne in Victoria, Australia. “Unfortunately, testing for the APOE genotype is easier and much less costly than conducting amyloid imaging.”

Image credit: PASIEKA/SCIENCE PHOTO LIBRARY

New merciful treatment method for children with brain tumours

Children who undergo brain radiation therapy run a significant risk of suffering from permanent neurocognitive adverse effects. These adverse effects are due to the fact that the radiation often encounters healthy tissue. This reduces the formation of new cells, particularly in the hippocampus – the part of the brain involved in memory and learning.

Researchers at the University of Gothenburg’s Sahlgrenska Academy have used a model study to test newer radiation therapy techniques which could reduce these harmful adverse effects. The researchers based their study on a number of paediatric patients who had undergone conventional radiation treatment for medulloblastoma, a form of brain tumour that almost exclusively affects children, and simulated treatment plans using proton therapy techniques and newer photon therapy techniques.

Each treatment plan was personalised by physician Malin Blomstrand, physicist Patrik Brodin and their colleagues. The results show that the risk of neurocognitive adverse effects can be reduced significantly using the new radiation treatment techniques, particularly proton therapy.

“This could mean a better quality of life for children who are forced to undergo brain radiation therapy,” says Malin Blomstrand.

A Future Without Seizures

Five-year-old Nathan Kalina of Naperville will enter kindergarten this fall after spending the summer in day camp: playing games, enjoying field trips, and romping in the pool. He loves playing with action figures and acting out scenes from his favorite movies.

The scene two years ago was very different. After getting a few reports from daycare about unexplained falls, Nathan’s parents started to notice him having minor seizures. His mother, Megan, wasn’t too concerned at first; both she and her father had had childhood seizures and recovered from them without incident. Then came Nathan’s first tonic-clonic seizure (formerly known as a “grand mal” seizure), a major event involving his whole brain and body. A trip to a local emergency room for basic tests led to an electroencephalogram a few days later. All the while Nathan was having more seizures, large and small.

"We went from zero to crazy in a matter of days," Megan said.

Medication helped some. Nathan’s father David, a teacher in the Naperville schools, devoted his summer to adjusting Nathan’s regimen. But in the fall, the seizures ramped up again. One specialist suggested a high-fat ketogenic diet, which has been shown to help some children with epilepsy — but it didn’t help Nathan. “Feeding a 4-year-old picky eater on meat, cheese and cream was hard on us and started making him sick,” Megan said.

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PNAS Study: Language Structure Arises from Balance of Clear and Effective Communication

When learning a new language, we automatically organize words into sentences that will be both clearly understood and efficient (quick) to communicate. That’s the finding of a new study reported today in the Proceedings of the National Academy of Sciences (PNAS) which challenges opposing theories on why and how languages come to be organized the way they are.

With more than 5000 languages in the world, it would be easy to assume all vary endlessly, but, in fact, there is great commonality: languages follow only a few recurrent patterns. These commonalities are called “language universals,” a notion suggested in the 1960’s by Noam Chomsky and Joseph Greenberg. A team of researchers from the University of Rochester and Georgetown University Medical Center set out to investigate how these language universals come to be.

Linguists and cognitive scientists have opposing ideas on how a language is developed and shaped. Some believe that languages all derived from a common ancestor; others think that languages vary quite widely and universals do not exist at all. Some have suggested that language universals are an arbitrary evolutionary outcome. The position of the Rochester-Georgetown team is that the human mind shapes a language, even while learning it, based on the need for robust and effective information transfer.

“The thousands of natural languages in our world only have a couple of formats in which they appear, and we are good at understanding and learning languages that have just these formats. Otherwise we could never succeed in learning something so complicated as human languages,” says one of the study’s authors, Elissa L. Newport, Ph.D., a professor in the department of neurology at Georgetown University Medical Center.

Evolution Mostly Driven by Brawn, Not Brains, Analysis Finds

The most common measure of intelligence in animals, brain size relative to body size, may not be as dependent on evolutionary selection on the brain as previously thought, according to a new analysis by scientists.

Brain size relative to body size has been used by generations of scientists to predict an animal’s intelligence. For example, although the human brain is not the largest in the animal kingdom in terms of volume or mass, it is exceptionally large considering our moderate body mass.

Now, a study by a team of scientists at UCL, the University of Konstanz, and the Max Planck Institute of Ornithology has found that the relationship between the two traits is driven by different evolutionary mechanisms in different animals.

Crucially, researchers have found that the most significant factor in determining relative brain size is often evolutionary pressure on body size, and not brain size. For example, the evolutionary history of bats reveals they decreased body size much faster than brain size, leading to an increase in relative brain size. As a result, small bats were able to evolve improved flying maneuvrability while maintaining the brainpower to handle foraging in cluttered environments.

This shows that relative brain size can not be used unequivocally as evidence of selection for intelligence. The study is published in the Proceedings of the National Academy of Sciences.

Theresa Klein talks about Achilles, the first machine to move in a biologically accurate way.

"Our robot, named Achilles, is the first to walk in a biologically accurate way. That means it doesn’t just move like a person, but also sends commands to the legs like the human nervous system does.

Each leg has eight muscles—Kevlar straps attached to a motor on one end and to the plastic skeleton on the other. As the motor turns, it pulls the strap, mimicking the way our muscles contract. Some of Achilles’ muscles extend from the hip or thigh to the lower leg so they can project forces all the way down the limb. This allows us to put most of the motors in the hips and thighs. Placing them up high keeps the lower leg light, so that it can swing quickly like a human’s lower leg.

In people, neurons in the spinal column send out rhythmic signals that control our legs. It’s like a metronome, and sensory feedback from the legs alters the pace. Your brain can step in to make corrections, but it doesn’t explicitly control every muscle, which is essentially why you can walk without thinking about it. For our robot, a computer program running off an external PC controls movement in a similar way. With each step, the computer sends a signal to flex one hip muscle and extend the other. The computer changes the timing of those signals based on feedback from the legs’ load and angle sensors. A similar control system handles the lower muscles.

Modeling human movement has applications outside of robotics. It could also help us understand how people recover after spinal-cord injuries, for example. But our robot is still a very simplified model—it has no torso and can’t handle complex terrain. Initially, we also had a problem with its feet slipping. We thought about different types of rubber to give its feet more grip but eventually realized a solution already exists. Now, the robot wears a pair of Keds.”