Learning Through Dreams

Researchers at Harvard University and Harvard Medical School conducted an experiment that indicates that dreaming during non-REM (rapid eye movement) sleep after performing a difficult task helps participants complete the activity more successfully after waking. (Scientists have only observed learning during non-REM sleep and not during REM sleep.) The researchers’ results also indicate that just thinking about the activity after first performing it does not help in later attempts to complete the task. These findings support earlier research indicating that sleep improves memory and learning.

“Task-related dreams may get triggered by the sleeping brain’s attempt to consolidate challenging new information and to figure out how to use it,” Dr. Robert Stickgold, study co-author, told ScienceNews about their results.

Researchers recruited 99 college students between the ages of 18 and 30 to participate in the study. For the experiment, the volunteers spent 60 minutes working individually to solve a 3-D virtual maze on a computer. During the activity, the participants performed several trials, and started the maze at a different location each time. In addition, while solving the maze, the participants were told to memorize the location of a specific tree’s location in the puzzle.

After spending an hour working on the maze, the participants were given a five-hour break. Half of the participants were instructed to take a nap, and the other half of participants were told to take part in quiet activities, such as reading or watching a video. For the nap group, the researchers fitted each participant with scalp sensors to monitor their brain activity while asleep. In addition, members of the napping group were asked about the content of their dreams just before they fell asleep, one minute after non-REM sleep, and at the end of their nap. Of the 50 participants in the nap group, four recounted dreaming about the maze activity. For the participants in the quiet activity group, each members was asked what they were thinking about at the beginning, middle, and end of the activity period.

After a lunch break and another period of quiet activity in which both groups of participants took part, the volunteers were asked to repeat the virtual maze activity. Those participants in the nap group who recalled dreaming about the maze in their sleep performed better the second time around in the maze activity and also found the tree that they had been told to remember quicker than other participants. All of the members of the nap group had been relatively unsuccessful in their attempts to complete the maze in the earlier session. The study authors suggest that tasks that are difficult and/or important to complete provoke memory processes in the brain required for learning to activate during sleep.

The scientists plan to continue their research into the connection between dreaming and learning. Future research plans include having study participants navigate through a more “exciting” virtual maze. The researchers are also interested in determining whether participants that have REM dreams about the maze during a normal full night’s sleep are able to better navigate the maze the next day.

The results of the scientists’ research were published in the April 22, 2010 online edition of the journal Current Biology. Study authors included Erin J. Wamsley, Matthew Tucker, Jessica D. Payne, Joseph A. Benavides, and Robert Stickgold.

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Brain Function Differs for Morning People and Night Owls

Researchers at the University of Alberta in Canada have discovered that there really is a difference between those who describe themselves as “morning people” and those who consider themselves “night owls.” Those self-described as “morning people” tend to wake up early and feel most productive in the morning hours. “Night owls,” on the other hand, are the opposite–they tend to feel more productive during the night and do not prefer waking up early in the morning.

A total of 18 people participated in the study. After completing a questionnaire about their habits, the study participants were broken into two equal groups–one group of nine consisted of those who considered themselves morning people and the other group of nine was made up of those who considered themselves night owls. In their experiment, the scientists:

  • measured how much muscle force could be generated during maximum contractions
  • applied electrical stimulation to a nerve in the back of the participant’s knee to assess pathways through the spinal cord
  • used trans-cranial magnetic stimulation to stimulate brain cells to send a signal to different muscles in the body

The most interesting result from the study was that the scientists discovered that there is a significant difference in brain function between morning people and night owls. For morning people, cortical excitability (also referred to as brain activity and inhibition) was the highest in the morning and decreased throughout the day, while for night owls, cortical excitability increased throughout the day and was highest around 9 p.m.. The researchers also found that morning people and night owls both showed an increase in spinal-cord excitability (which is related to muscle reflex response) throughout the day. A third finding was that night owls did better on the maximum muscle force test, meaning they got stronger throughout the day, while morning people showed no change in their maximum muscle force throughout the day.

The scientists who conducted this research were quite intrigued by the results and have already begun to consider future experiments. The researchers are interested to find out whether it is possible to switch someone from being a morning person to being a night owl, and vice versa, and how long such a switch might take. The scientists are also interested in determining how the results from this study may be applied in terms of work efficiency and performance, especially in relation to those who work very early and very late shifts.

The results of the scientists’ research were published in the June edition of the Journal of Biological Rhythms. Scientists who contributed to the research included Dave Collins, Olle Lagerquist, Alex Ley, and Alex Tamm.

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Researchers Link Circadian Rhythms to Learning and Memory

A properly-working circadian system helps Siberian hamsters remember things, such as where to find food sources. (Credit: Eric Wong/Shutterstock)

Researchers at Stanford University, led by senior research scientist Norman Ruby, recently discovered a link between circadian rhythms and learning and memory. The subject of the researchers’ study was the Siberian hamster (also called the dwarf hamster). Their research indicated that a correctly-functioning circadian system is necessary for the hamsters’ ability to remember what they have learned. Hamsters that had their circadian systems disabled were unable to consistently recall objects in their environment as compared to hamsters with working circadian systems.

The scientists developed a non-invasive procedure to disable the hamsters’ circadian systems by manipulating the hamsters’ exposure to light. First, the hamsters were exposed to two hours of bright light late at night. Next, the hamsters’ normal cycle of light/dark was delayed by three hours. After the treatment–the single treatment is enough to destroy the hamsters’ circadian system the hamsters’ normal cycle of light and dark was resumed. To test the hamsters’ memory and learning ability, the researchers used a standard test called a “novel object recognition task.” This technique takes advantage of a hamsters’ innate interest in exploring its environment.

The Novel Object Recognition Task

In this technique, two objects are placed in the opposite corners of a box. A hamster is then placed in the box. (As shown in the box marked “A”.) The hamster will typically examine the objects in its environment, spending an equal amount of time with the two objects. After a period of five minutes, the hamster is removed from the box, and one of the objects in the box is replaced with a new one. The hamster is then placed back into the box. (As shown in the box marked “B”.) A normal hamster with an unimpaired circadian system will spend time examining both objects, but will spend twice the amount of time at the new object. In comparison, a hamster with an impaired circadian system will spend the same amount of time at both objects, as it does not remember seeing one of the objects before.

This illustration shows the two steps of the novel object recognition task.

Previous research indicates that learning retention depends on the amount of a neurochemical called GABA in the brain. GABA controls brain activity. The biological clock manages an animal’s daily cycle of sleep and alertness by inhibiting different parts of the brain through the release of GABA. The hippocampus is the part of the brain that stores memories. When the hippocampus is over-inhibited by the release of too much GABA, the hippocampus becomes overwhelmed, and memories aren’t stored correctly.

Research Implications for Human Diseases

This research has implications for several diseases that impact learning and memory. For example, those affected with Down Syndrome don’t perform well on cognitive tests due to an over-inhibited brain during development. People with Alzheimer’s disease could also benefit from this study, as memory loss is also linked with an over-inhibited brain. In addition, as people age, their circadian systems begin to degrade and break down. This breakdown could explain short-term memory loss in the elderly.

In two separate studies focused on Down Syndrome and Alzheimer’s disease, mice exhibiting the symptoms of each were given pentylenetetrazole (PTZ), a GABA antagonist. PTZ works in the brain by blocking GABA from binding to synapses, which lets them continue to fire. This continual firing of the synapses keeps the brain in an excited state. In the mice, the PTZ counteracted the inhibitory affects of GABA, and improved their ability to learn and retain memories.

Ruby and his colleagues hypothesized that giving PTZ to hamsters with impaired circadian systems would see a similar improvement. The results of their experiment confirmed the researchers’ hypothesis–after being given PTZ, the impaired hamsters showed a definite improvement in their learning and memory skills.

The results of this study were published online October 1 in an early edition of the journal Proceedings of the National Academy of Sciences. Other researchers who contributed to the paper include co-authors H. Craig Heller, Calvin Hwang, Colin Wessells, Fabian Fernandez, Pei Zhang, and Robert Sapolsky.

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Researchers Learn How Brain Represents Meaning

In the past, scientists who study brain function have used functional magnetic resonance imaging (fMRI) to determine which areas of the brain are activated when an individual is instructed to think about a certain word. Now, researchers at Carnegie Mellon University in Pittsburgh, Pennsylvania have developed a computer model that can predict the unique brain activation connected with concrete nouns–words for things that you sense through sight, sound, touch, taste, or odor. This computer model is helping brain scientists understand how the brain codes the meanings of certain words.

The computer model was developed by a team of researchers led by Tom M. Mitchell, a computer scientist, and Marcel Just, a cognitive neuroscientist. The results of their research were recently published in the journal Science.

We believe we have identified a number of basic building blocks that the brain uses to represent meaning, said Mitchell. Coupled with computational methods that capture the meaning of a word by how it is used in text files, those building blocks can be assembled to predict neural activation patterns for any concrete noun. And we have found that these predictions are quite accurate for words where fMRI data is available to test them.

Through their research, the team of scientists found that the brain represents the meaning of a concrete noun in places in the brain connected with how it is sensed or used.

The meaning of an apple, for instance, is represented in brain areas responsible for tasting, for smelling, for chewing, said Just. An apple is what you do with it.

The researchers also discovered that some words are connected to areas of the brain associated with planning and long-term memory. For example, thinking about an apple may trigger a persons memory of going to an orchard to pick apples.

The scientists are excited to continue their research. In the future, they plan to study the brain activation patterns for adjective-noun combinations, prepositional phrases, and simple nouns and concepts. The research team also plans to further their study of noun-connections by researching how the brain represents abstract nouns and concepts.

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Molecular Manager of Memory Pathway Construction

Researchers at Northwestern University’s Feinberg School of Medicine have identified the protein that acts as the foreman in the construction and support of neurons. Kalirin-7 and its construction projects are what allow us to remember and learn.

Kalirin-7 is found in high concentrations in the spines of dendrites, the signal-receiving ends of synapses between neurons. Kalirin-7 is also involved in the construction of cell cytoskeletons. These two facts suggested to physiology professor Peter Penzes and his colleagues at Northwestern that kalirin-7 might be involved in building and maintaining the dendritic spines that are so important in transmission between nerve cells. If true, it would mean kalirin-7 helps build and reinforce the network that allows us to learn and remember.

To test their hypothesis, Penzes and his colleagues cultured neurons in the lab and subjected them to neurotransmitters. They found that when neurons were activated, kalirin-7 molecules triggered the growth of the spines along the dendrites, thereby making them more likely to receive further transmissions at full strength. They also saw that kalirin-7 controlled the number of receptors on dendritic spines, which in turn controlled the strength of the nerve signals. The overall trend was that the more activity the neurons had, the more kalirin-7 triggered further growth and development. “Synaptic activity turns on the function of kalirin-7, and kalirin-7 in turn makes synapses larger and stronger,” Dr. Penzes explained. “A synapse is like a volume dial between two cells. If you turn up the volume, communication is better. Kalirin makes the synaptic spines grow.”

In addition to determining the identity and role of this protein, this discovery could pave the way for treatments of cognitive diseases and disorders such as Alzheimer’s, autism, drug addiction, and mental retardation, all of which involve defects or degradations of the receptors of neurons. “If kalirin-7 can be activated or enhanced, perhaps neural circuitry could be healed or rewired. The extension of this is that maybe we can make drugs and thereby fortify the synapses and perhaps delay or reverse some of these cognitive diseases,” Penzes said.

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Adult Brains Can Rewire after a Stroke

A child’s brain has an amazing ability to adapt and change to new experiences it is very plastic. Over the past 25 years, researchers have found that an adults brain also has plasticity. Many times, its plasticity helps an adult master a new skill or adapt to a changing environment. Sometimes, the plasticity makes up for an injury.

A case study of a stroke patient adds to evidence proving that adult brains are capable of creating new neural pathways. The victim, known as BL, had a stroke that left him with a blind area in his upper left visual field. BL described how objects looked distorted in the lower left visual field, right below his blind area. Neuroscientists from Johns Hopkins University and Massachusetts Institute of Technology hypothesized that these distortions were caused by rewiring in the visual cortex, the part of the brain that processes visual information, to compensate for the stroke.

Dr. Daniel Dilks of MIT, and his colleagues tested their hypothesis. BL was shown basic shapes while he stared at another object. When they presented the shapes in his upper left visual field, he recorded seeing nothing. But when they presented the shapes just below his blind area, he recorded something different. Triangles appeared pencil-like. Circles appeared cigar-like. Squares appeared like rectangles. The shapes extended up into his blind area. His brain had rewired to use the part of the visual cortex that no longer received direct visual information.

The fMRI studies confirmed that the deprived visual cortex began to assume new properties that led to the visual distortions. “We discovered that it (the visual cortex) takes on new functional properties, and BL (the stroke victim) sees differently as a consequence of that cortical reorganization,” Dr. Daniel Dilks said.

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Intelligence Is in the Network

When it comes to intelligence, it is all about the connections. Richard Haier of the University of California, Irvine, and Rex Jung of the University of New Mexico compiled evidence that human intelligence is related to how well information travels among intelligence hubs along certain pathways of the brain.

In 2004, Haier and Jung found that general intelligence areas are throughout the brain. Now, they have a more sophisticated view of intelligence works. Haier and Jung reviewed 37 brain imaging studies and identified brain areas, or stations, most related to intelligence. From their analysis, Haier and Jung developed their Parieto-Frontal Integration Theory (P-FIT) model. The P-FIT model identifies areas of the frontal and parietal lobes of the brain as stations of the brain network related to intelligence. Based on the evidence, Haier and Jung think that intelligence levels might be based on how efficient the parietal-frontal networks process information.

The P-FIT model is not dependent on one type of intelligence testing. Regardless of how an individuals intelligence is measured, the P-FIT model identifies similar stations of intelligence. “In every single study that we reviewed, there was a different measure of intelligence,” Haier said. “There’s controversy about what is the best measure of intelligence. There’s controversy over how broad or narrow the definition of intelligence should be. Our work really goes beyond those questions and basically says that irrespective of the definition of intelligence you use in neuroimaging studies, you find a similar result.”

Earl Hunt, a psychologist from the University of Washington says they (Haier and Jung) can take the far more sophisticated view that individual differences in intelligence depend, in part, upon individual differences in specific areas of the brain and in the connections between them.

Haier and Jung hope that their model will provide a basis on which new hypotheses on intelligence can be tested.

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