Neuroscience Conference 2007

I spent the past several days at the huge (~32,000 attendees this year) Society for Neuroscience Conference (SFN) in San Diego. This annual meeting of neuroscientists is an opportunity to learn about the latest brain-related research going on throughout the world, and for each scientist to show off their own findings.

The sheer volume of people and presentations at SFN can be overwhelming, but here are some interesting tidbits:

• Kirk Erickson from the University of Illinois at Urbana-Champaign found that exercising rats were faster learners than sedentary rats. And more running is better: The animals that ran the most also became the best at learning and memory. (Abstract: search for “voluntary exercise enhances place learning”)

• Ken Nakayama presented data from over 22,000 people of various ages showing how the ability to learn faces changes over the lifespan. He found that our ability to learn faces peaks at about age 30, and that it’s about the same at age 65 as it is at 16. (Abstract: search for “human face learning”)

• I presented research from Lumos Labs showing that the internet can be a good tool for conducting cognitive neuroscience research. Our methods of leveraging the internet for basic research and cognitive training are being used by collaborators to figure out how under-performing students can do better in school, and how chemobrain patients might recover their cognitive abilities. (Abstract: search for “using the web for behavioral research”)

Early Biomarker for Alzheimer’s?

By contributing author Paul Li, a neuroscience graduate student at Columbia.

Researchers from Stanford might have found a biological marker for Alzheimer’s disease via a simple blood test. This is exciting news given that it might predict the onset of the disease several years before the symptoms begin. The procedure involves examining 18 key proteins in the blood that are typical in Alzheimer’s patients. Preliminary tests have been 90% accurate at detecting the disease. Dr Susanne Sorensen, of the Alzheimer’s Society, said that “Early diagnosis is essential if we are ever to develop treatments that can change the course or halt the progression of dementia rather than just treat the symptoms.”

Eat your vegetables, do your homework, and play your video games?

By contributing author Paul Li, a neuroscience graduate student at Columbia.

When I was a kid, I was constantly scolded by my mother for spending countless hours on my 1989 Nintendo Entertainment System. She thought reading or playing outside would be more beneficial for me than Duck Hunt or Super Mario Brothers. My mother could have never predicted that recent research would show that video games can sometimes actually be good for your brain!

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Where art thou soul?

Nowadays it seems almost intuitively evident that the brain is in the head and it controls our behavior. However, it was not always this clear. A popular notion was that the heart ultimately controlled thoughts and behavior – until a brutally direct “experimental” observation was made…

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Monkey see, monkey do mathematical calculations

Guest author Elizabeth Buchen is a neuroscientist and science writer, and a member of the Lumos Labs science advisory board. Below she describes new research showing 1.) that monkeys can inform decisions by learning probability distributions; and 2.) individual neurons encode this information by adjusting firing rate. Visit Madam Fathom to read more about the biological basis of mind.

Humans are constantly making decisions with uncertain outcomes—betting on a poker hand, predicting the weather, and selecting a lane of traffic, for example. Because the consequences of such decisions are not guaranteed, we must base our decisions on clues from the environment, determining the probabilities of potential outcomes before deciding on a rational course of action.

How does the brain perform these calculations? During the formation of a decision, what happens between sensation (our interpretation of the outside world) and behavior (the manifestation of our decision)?

To answer these questions, Tianming Yang and Michael Shadlen from the University of Washington trained Rhesus Monkeys to perform “simple” statistical calculations, and measured the activity of particular neurons during the decision-making process. The results were published on June 3 in an advance online publication in Nature.

In the task, the monkeys were presented with a random series of four abstract shapes on a video screen. They then directed their gaze toward either a red or a green target light, only one of which would be associated with a juice reward. The light that would give the reward was not fixed, but could be calculated probabilistically.

Each shape (there were a total of 10) represented the probability that the rewarding target was either red or green. For example, a square strongly favors the red target as rewarding (weighted 0.9), while a triangle indicates that green will be rewarding (0.9 in the opposite direction). A cone weakly indicates the red will be rewarding (0.5 towards red), and a pac-man weakly indicates green (0.3). Thus, the probability that the monkey will be rewarded by looking at a particular target is the sum of the probabilities for each of the shapes.

With 10 shapes, there are 715 unique combinations (and 10^4 permutations), thus precluding memorization of specific four-shape patterns, and encouraging the monkeys to learn the shapes and calculate the reward probability of each target. This is a far from trivial demand of a monkey, but eventually (after two months and over 130,000 trials), they chose the correct target 75% of the time, indicating that they had learned to base their decisions on the combined probabilities for reward. This capacity of monkeys to make such subtle probabilistic deductions is quite impressive, but is only the first half of the story.

After thus establishing a complex reasoning task, the researchers could begin exploring the neural basis for these types of decisions. They measured the activity of neurons in a particular area of the brain, called the lateral intraparietal area (LIP). This area lies intermediate between the visual input (the abstract shapes) and the behavioral output (the appropriate eye movement), and is thought to carry information involved in transforming visual signals into commands to move the eyes; i.e. in making decisions that result in eye movements.

What they found was awesome. When the monkeys saw a shape, the activity of their LIP neurons was proportional to the probability associated with that shape. With each sequential shape, the neurons altered their firing rates to match the updated probability. Although it is unknown how their brains converted information from each shape to their respective probabilities, the activity of these neurons indicates that they either play a role in the transformation, or represent the outcome during the decision-making process.

Apart from showing that monkeys are closer to furry calculators than previously thought, the study has grander implications. As the authors conclude, “the present study exposes the brain’s capacity to extract probabilistic information from a set of symbols and to combine this information over time.” A similar neural process may underlie our abilities to reason about alternatives, and make decisions based on subtle probabilistic differences.

Reference: Yang T & Shadlen MN (2007) Probabilistic reasoning by neurons. Nature (doi:10.103/nature05852)

Enriched environment can uncover memories lost to Alzheimer’s

It is well established that mice living in an environment that is rich in sensory stimuli, social contact, and cognitive stimulation are better able to learn and remember than mice in a relatively impoverished environment. Enriched mice also show physical signs of a healthier brain, including more synaptic connectivity, more new neurons, and less neuron death. On the other hand, it is generally believed that once a significant amount of neurodegeneration has occurred, such as in Alzheimer’s disease, it is too late for an enriched environment to have much impact.

Yesterday, MIT researchers in the Li-Huei Tsai lab published groundbreaking work arguing that it is not too late to improve learning and recover lost memories even after substantial, Alzheimer’s-like brain degeneration. A richly stimulating environment or a histone deacetylase inhibitor can have this dramatic effect on mice.

In this study, mice first learned to navigate a maze using spatial memory. By genetically manipulating the expression of a particular protein,
p25, the researchers then induced the symptoms and neural pathology of Alzheimer’s in these mice. Over several weeks, their brains atrophied and they lost their ability to navigate the maze they had previously learned. Some of these mice then began living in a much more interesting cage, which included toys, tunnels, running wheels, other mice… you name it, it was an exciting time for these privileged animals.

When compared with mice that lived in a standard boring lab cage, the enriched mice were better able to learn new things and had more synaptic connections between their neurons. Incredibly, they also recovered the ability to navigate the maze and other tasks they had learned before the symptoms and neural degeneration took place.

According to Tsai, “…our mouse model shows that even when there has been a significant loss of neurons, it is still possible to improve learning and memory.”

While these results are very exciting, an important caveat is that rodents are different than people, and the p25 manipulation is not exactly the same thing as Alzheimer’s disease. Thankfully, I’m sure we’ll see more research like this soon. In the meantime, it can’t hurt to live more like privileged rodents: challenge your brain, be social, and always wear close-toed shoes on the running wheel.