Posts tagged caudate nucleus
Articles and news from the latest research reports.
Study reveals workings of working memory
Keep this in mind: Scientists say they’ve learned how your brain plucks information out of working memory when you decide to act.
Say you’re a busy mom trying to wrap up a work call now that you’ve arrived home. While you converse on your Bluetooth headset, one kid begs for an unspecified snack, another asks where his homework project has gone, and just then an urgent e-mail from your boss buzzes the phone in your purse. During the call’s last few minutes these urgent requests — snack, homework, boss — wait in your working memory. When you hang up, you’ll pick one and act.
When you do that, according to Brown University psychology researchers whose findings appear in the journal Neuron, you’ll employ brain circuitry that links a specific chunk of the striatum called the caudate and a chunk of the prefrontal cortex centered on the dorsal anterior premotor cortex. Selecting from working memory, it turns out, uses similar circuits to those involved in planning motion.
In lab experiments with 22 adult volunteers, the researchers used magnetic resonance imaging to track brain activity during a carefully designed working memory task. They also measured how quickly the subjects could choose from working memory — a phenomenon the scientists called “output gating.”
“In the immediacy of what we’re doing we have this small working memory capacity where we can hang on to a few things that are going to be useful in a few moments, and that’s where output gating is crucial,” said study senior author David Badre, professor of cognitive, linguistic, and psychological sciences at Brown.
From the perspective of cognition, said lead author and postdoctoral scholar Christopher Chatham, input gating — choosing what goes into working memory — and output gating allow people to maintain a course of action (e.g., finish that Bluetooth call) while being flexible enough to account for context in planning what’s next.
Of cognition and wingdings
In their experiments Badre, Chatham, and co-author Michael Frank, associate professor of cognitive, linguistic, and psychological sciences, provided their volunteers with four different versions of a similar working memory task. The versions distinguished output gating from input gating so that the anatomical action observed in the MRI could reliably associate with output gating behavior.
In each round, volunteers saw a sequence of characters — either letters of the alphabet or wingdings (typographical symbols like stars and snowflakes). Before or after the sequence, the volunteers were also given a context cue in the form of a numeral that told them which kind of character would be relevant at end of the task (e.g., “1” might mean a wingding while “2” might mean a letter). The last step for volunteers was to select between groups of characters on the screen that included whichever contextually relevant character they had seen in the sequence (e.g., if the subject had seen a “1” and later a snowflake during the sequence, they should select the group that included a snowflake).
When the context numeral came first, say a “2,” volunteers would “input gate” only letters into their working memory. When it came time to make a selection, they’d simply “output gate” the correct letter from the letters in working memory. If the context came last, people would have to input gate everything they saw into working memory, making all the real thinking a matter of output gating. If the context cue came last, they would carry a higher load of characters in working memory. To address this disparity, the experimenters created two more conditions in which a global context indicator, “3,” required people to keep everything they saw in working memory whether it came before the sequence or after.
With this experimental design the researchers could measure performance and monitor brain activity with subjects who had distinct moments of input and output gating, regardless of the character load in working memory.
People accomplished the tasks with a range of speeds, which the researchers regarded as a proxy for the amount of cognitive work volunteers had to do. People were slowest in making a selection when they got the context cue last and then had to gate just one specific symbol out of memory (e.g., they saw the sequence, then saw a 1, and then had to choose the option with a wingding they had seen). People were fastest at making a selection when they were given the context first and then had to pick the one character of that kind that they saw (e.g., they saw a “2,” then the sequence in which only letters mattered, and then had to choose the option with a letter they had seen).
In analyzing the results, Chatham and his co-authors found that the caudate and the dorsal anterior premotor cortex, contributed distinctly to the reaction times they saw. These separate roles in the partnership agree with computational models of how the brain works.
“The division of labor that’s specifically posited by these computational models is one in which there is a basically a context being represented in the prefrontal cortex that determines the overall efficiency of going from stimulus to response – like a route,” Chatham said. “The striatum is involved in the actual gating of that flow of information,” he said, “like traffic lights along the route.”
So the cortex interprets the context, while the striatum implements the gating. When the context is unhelpfully general and the gating is very specific, for example, the task takes a lot of time.
The findings help advance studies of how cognition works in the brain and could help psychiatrists analyze behavior in people where those areas of the brain have been injured, the researchers said. It also highlights how similar brain circuits can execute different functions – motion and working memory gating.
Navigational ability is visible in the brain
The brains of people who immediately know their way after travelling along as a passenger are different from the brains of people who always need a GPS system or a map to get from one place to another. This was demonstrated by Joost Wegman, who will defend his thesis at Radboud University Nijmegen, the Netherlands on the 27th of November.
Wegman demonstrates that good navigators store relevant landmarks automatically on their way. Bad navigators on the other hand, often follow a fixed procedure or route (such as: turn left twice, then turn right at the statue).
Anatomical differences
Wegman also found that there are detectable structural differences between the brains of good and bad navigators. ‘These anatomical differences are not huge, but we found them significant enough, because we had a lot of data’, the researcher explains. ‘The difference is in the hippocampus. We saw that good navigators had more so-called gray matter. In the brain’s gray matter information is processed. Bad navigators, on the other hand, have more white matter - which connects gray matter areas with each other - in a brain area called the caudate nucleus. This area stores spatial actions with respect to oneself. For example, to turn right at the record store’, Wegman describes.
Questionnaires
For his research, Wegman combined data from several studies done by the Radboud University research group Neural Correlates of Spatial Memory at the Donders Institute for Brain, Cognition and Behaviour.
Wegman: ‘We always give participants extensive questionnaires in our studies. This allows us to explain possible differences in behaviour afterwards. People generally have a good insight into their ability to find their way, so these questions provide a feasible way to assess these abilities. I have coupled the answers of these questionnaires with the brain scans we have collected over the years, which allowed us to detect these differences’.
Objects in space - the neural basis of landmark-based navigation and individual differences in navigational ability (PhD defence)
Wednesday 27 November 2013, promotors: prof. dr. L.T.W. Verhoeven, prof. dr. P. Hagoort,
copromotor: dr. G. Janzen
The papers to which this article refers are both included in Joost Wegman’s thesis:
1. Wegman, J. & Janzen, G. Neural encoding of objects relevant for navigation and resting state correlations with navigational ability. Journal of Cognitive Neuroscience 23, 3841-3854 (2011).
2. Wegman, J. et al. Gray and white matter correlates of navigational ability in humans. Human Brain Mapping (in press).
Simple Dot Test May Help Gauge the Progression of Dopamine Loss in Parkinson’s Disease
A pilot study by a multi-disciplinary team of investigators at Georgetown University suggests that a simple dot test could help doctors gauge the extent of dopamine loss in individuals with Parkinson’s disease (PD). Their study is being presented at Neuroscience 2013, the annual meeting of the Society for Neuroscience.
“It is very difficult now to assess the extent of dopamine loss — a hallmark of Parkinson’s disease — in people with the disease,” says lead author Katherine R. Gamble, a psychology PhD student working with two Georgetown psychologists, a psychiatrist and a neurologist. “Use of this test, called the Triplets Learning Task (TLT), may provide some help for physicians who treat people with Parkinson’s disease, but we still have much work to do to better understand its utility,” she adds.
Gamble works in the Cognitive Aging Laboratory, led by the study’s senior investigator, Darlene Howard, PhD, Davis Family Distinguished Professor in the department of psychology and member of the Georgetown Center for Brain Plasticity and Recovery.
The TLT tests implicit learning, a type of learning that occurs without awareness or intent, which relies on the caudate nucleus, an area of the brain affected by loss of dopamine.
The test is a sequential learning task that does not require complex motor skills, which tend to decline in people with PD. In the TLT, participants see four open circles, see two red dots appear, and are asked to respond when they see a green dot appear. Unbeknownst to them, the location of the first red dot predicts the location of the green target. Participants learn implicitly where the green target will appear, and they become faster and more accurate in their responses.
Previous studies have shown that the caudate region in the brain underlies implicit learning. In the study, PD participants implicitly learned the dot pattern with training, but a loss of dopamine appears to negatively impact that learning compared to healthy older adults.
“Their performance began to decline toward the end of training, suggesting that people with Parkinson’s disease lack the neural resources in the caudate, such as dopamine, to complete the learning task,” says Gamble.
In this study of 27 people with PD, the research team is now testing how implicit learning may differ by different PD stages and drug doses.
“This work is important in that it may be a non-invasive way to evaluate the level of dopamine deficiency in PD patients, and which may lead to future ways to improve clinical treatment of PD patients,” explains Steven E. Lo, MD, associate professor of neurology at Georgetown University Medical Center, and a co-author of the study.
They hope the TLT may one day be a tool to help determine levels of dopamine loss in PD.
(Source: explore.georgetown.edu)