Look inside the brain of someone learning. You just might be lucky enough to spy a new bridge between two nerve cells pop into existence. Called a synapse, this bridge cements new knowledge into the brain. As new information arrives, some synapses form and strengthen. At the same time, others weaken. But that’s okay. This makes way for more new connections.
You might see more subtle changes, too. These could include changes in the levels of signaling molecules. You might even glimpse slight boosts in the activity of nerve cells, also known as neurons.
Over the last few decades, scientists have zoomed in on these microscopic changes that happen as brains learn. That detailed scrutiny has revealed a lot about the synapses that wire our brains. But it isn’t enough. Brain scientists still lack a complete picture of how brains learn.
Some scientists now think that maybe they have just been looking too closely. When it comes to the science of learning, zeroing in on synapse action risks missing the forest for the trees.
A new, zoomed-out approach attempts to make sense of large-scale brain changes that underlie learning. By studying the shifting interactions between many different brain areas over time, scientists are beginning to grasp how the brain takes in new information — and holds onto it.
Such studies rely on powerful math. Brain scientists are turning to approaches developed in other network-based sciences. They also are borrowing tools that reveal in precise, numerical terms the shape and function of the brain-signaling pathways that shift as people learn.
Danielle Bassett is one of these network neuroscientists. She works at the University of Pennsylvania in Philadelphia. “When you’re learning, it doesn’t just require a change in activity in a single region,” she notes. “It really requires many different regions to be involved.” Her whole-brain approach asks: “What’s actually happening in your brain while you’re learning?” Bassett is charging ahead to both define this new field of “network neuroscience” and =to push its boundaries.
Such work “is very promising,” says Olaf Sporns. He’s a neuroscientist at Indiana University in Bloomington. Bassett’s research, he says, holds the potential to bridge gaps between what brain-imaging studies show and what scientists understand about how learning occurs. “I think she’s very much on the right track.”
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Already, Bassett and others have found hints that the brains that learn best have flexible networks. By that she means that they are able to rewire connections on the fly. This allows new knowledge in. Some brain regions almost always communicate with the same neural partners. Others show great flexibility. They can quickly swap who they’re talking to. Think of them like people who can send a holiday-party invite to neighbors and friends on their e-mail lists, then moments later shoot off a memo to colleagues at work.
In a few studies, researchers have witnessed this flexibility in action. They put volunteers into brain scanners and then taught them something new. As the scan recorded their brain activity, the scientists could watch networks rewire themselves. Such network flexibility may aid in several types of learning. Too much flexibility, however, could signal certain types of brain disease, other studies suggest.
Not surprisingly, some researchers are rushing to apply this new information. They are testing ways to boost brain flexibility for those of us who may be too rigid in our neural (nerve cell) connections.
“These are pretty new ideas,” says Raphael Gerraty. He’s a cognitive neuroscientist at Columbia University in New York City. The math and computer tools required for this type of research didn’t exist until recently, he notes. So people hadn’t been thinking about learning from such a network-scale perspective. There was simply a technological roadblock, he says. But the road at last is clear and “people can now explore.”
It takes a neural village
That conceptual path is more of a map. It is made of countless neural roads. Even when someone learns something very simple, large swaths of the brain jump in to help. Consider learning an easy sequence of movements, like tapping out a brief tune on a keyboard. This prompts activity in a part of the brain that directs finger movements. The action also calls into play brain areas involved in vision, decision-making, memory and planning. And finger taps are a pretty basic type of learning. In many situations, learning calls up even more brain areas. It gets information from multiple sources to weave together, Gerraty says.
He and his colleagues have seen glimpses of such interactions by scanning the brains of people who had learned to associate two faces. Only one of the faces was paired with a reward. In later experiments, the researchers tested whether people could figure out that the halo of good fortune linked with that one face also extended to the face it had been partnered with earlier. This process is known as “transfer of learning.” And it is something that people do all the time (such as when someone may be wary of the salad at a restaurant that recently served tainted cheese).
Particular brain signatures showed up in study participants who were good at applying knowledge about one thing — in this case, a face — to a separate thing. It’s something that Gerraty and his colleagues reported three years ago in the Journal of Neuroscience. They looked at links between the hippocampus (a brain structure important for memory) and the ventromedial prefrontal cortex (involved in self-control and decision making). Those links were weaker in good learners than in people who struggled to learn. Brain scans performed several days after the learning task revealed differences between those brains, the researchers say. The experiment also turned up differences in the neural networks among these regions and in larger-scale networks that span the whole brain.
Vinod Menon is a neuroscientist at Stanford University in California. In 2015, he scanned the brains of children who have difficulty learning math. And his team turned up unexpected brain connectivity in them. Compared to kids without these problems, the math-challenged kids had more neural connections. This showed up particularly within regions of their brains involved in solving math problems.
That overconnectivity was a surprise, Menon says.
Earlier work had suggested that the math-related networks were too weak to process information well. But the new data suggest an alternative explanation. Too many links may create a system that can't handle too much new information. In the end, he says, the result may be that “it’s not going to be as responsive.” His team described its findings in Developmental Science.
There needs to be a balance, Menon says. Neural pathways that are too weak can’t carry necessary information. Pathways that are too connected don’t allow new information in. But there’s more to the problem than that. It seems that connections in some areas are more important than in others. And which ones matter seem to depend on the task.
Neural networks need to shuttle information around quickly and smoothly. To really get a sense of this movement — as opposed to snapshots frozen in time — scientists need to watch the brain as it learns. “The next stage is to figure out how the networks actually shift,” Menon says. “That’s where the studies from Dani Bassett and others will be very useful.”
Flexing in real time
In a 2015 study, Bassett and her colleagues described changes to networks as people learned. They gave volunteers simple sequences to tap out on a keyboard. This happened while each person was undergoing a functional MRI scan. This technology can study changes in the brain as people are doing things. The study scanned people on and off over a six week period as they learned the new task. And those scans showed that learning seemed to shift around some of the neural networks in their brains.
Some connections strengthened. Others weakened.
Bassett and her team reported their findings in Nature Neuroscience.
People who learned quickly to tap the correct sequence of keys showed an interesting neural trait. As they learned, they shed certain connections between two areas of their brains. One was the frontal cortex. This is the outermost layer of the brain toward the front of the head. The other area is the cingulate. It sits toward the middle of the brain.
A connection between these brain areas has been linked with the ability to direct attention, set goals and make plans. These are skills that may be important for the early stages of learning but not for later ones, the researchers now suspect. Compared with slow learners, fast learners were more likely to have shed these connections. And this may have made their brains more efficient.
Flexibility seems to be important for other kinds of learning too, Gerraty, Bassett and others reported online May 30 at bioRxiv.org. One example: reinforcement learning. This is where right answers get a thumbs up and wrong answers are called out. This network comprises many points in two areas of the brain. One is the cortex, the brain’s outer layer. The other is a deeper structure known as the striatum (Stry-AY-tum). Last year, Bassett and her colleagues published a paper showing that some brain regions involved in language comprehension also have the ability to quickly form and break connections.
Such studies that watch a brain in action, Gerraty says, show how changeable its networks are during learning. Certain parts disconnect from partners and quickly join new ones. In other words, the act of learning takes flexibility.
But too much flexing may be bad.
Schizophrenia is a disabling mental disorder in which people may feel they lose touch with the outer world. They can suffer from hallucinations or delusions. They may think people are out to get them (when they aren’t). They may have memory problems or trouble paying attention to things. They may not express emotions. They may have trouble making good decisions (ones that are in their best interests). It’s a very serious disease. And while performing a memory task in a scanner, people with schizophrenia show higher flexibility among neural networks across the brain than did healthy people. Bassett and her colleagues reported this, last year, in the Proceedings of the National Academy of Sciences.
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Just how this flexibility arises, and what controls it, is unknown.
Push for more
For now, some researchers are charging ahead, looking for signs that neural flexibility might offer a way to boost one's ability to learn new things.
After researchers stimulated a region of the brain known as a “memory circuit,” people were better able to recall lists of words. Scientists described their success with this May 8 in Current Biology. If stimulation can boost memory, some scientists now argue, the way it works may involve enhancing that network flexibility. It might also aid in learning things in the first place.
Certain drugs also show promise. One, known as DXM, is found in some cough medicines. It blocks certain proteins in the brain, helping to control nerve-cell chatter. The compound appears to do this in healthy people by making some of their brain regions more flexible and better able to rapidly switch partners. Bassett’s team reported this last year in the Proceedings of the National Academy of Sciences.
Neural flexibility may also be connected to mood. On March 31 in Scientific Reports, Bassett and her team described analyses of one person: a neuroscientist. He submitted to three brain scans a week for a year. Each time, he described his mood. The standout result: When this man was happiest, his brain was most flexible. The reasons aren’t yet clear. (Flexibility was lowest when he was surprised.)
This research is just getting started. But already, insights on learning are coming quickly from the small group of researchers who are viewing the brain as a matrix of nodes and links — ones that deftly shift, swap and rearrange themselves. The initial findings on network flexibility and learning,” Bassett says, suggest “a whole new set of hypotheses and new ways of testing them.”
brain scan A technique to view structures inside the brain, typically with X-rays or a magnetic resonance imaging (or MRI) machine. With MRI technology — especially the type known as functional MRI (or fMRI) — the activity of different brain regions can be viewed during an event, such as viewing pictures, computing sums or listening to music.
cell The smallest structural and functional unit of an organism. Typically too small to see with the unaided eye, it consists of a watery fluid surrounded by a membrane or wall. Depending on their size, animals are made of anywhere from thousands to trillions of cells. Most organisms, such as yeasts, molds, bacteria and some algae, are composed of only one cell.
circuit A network that transmits electrical signals. In the body, nerve cells create circuits that relay electrical signals to the brain. In electronics, wires typically route those signals to activate some mechanical, computational or other function.
cognitive A term that relates to mental activities, such as thinking, learning, remembering and solving puzzles.
colleague Someone who works with another; a co-worker or team member.
compound (often used as a synonym for chemical) A compound is a substance formed when two or more chemical elements unite (bond) in fixed proportions. For example, water is a compound made of two hydrogen atoms bonded to one oxygen atom. Its chemical symbol is H2O.
cortex The outermost layer of neural tissue of the brain.
developmental (in biology) An adjective that refers to the changes an organism undergoes from conception through adulthood. Those changes often involve chemistry, size and sometimes even shape.
disorder (in medicine) A condition where the body does not work appropriately, leading to what might be viewed as an illness. This term can sometimes be used interchangeably with disease.
field An area of study, as in: Her field of research was biology. Also a term to describe a real-world environment in which some research is conducted, such as at sea, in a forest, on a mountaintop or on a city street. It is the opposite of an artificial setting, such as a research laboratory.
hippocampus (pl. hippocampi) A seahorse-shaped region of the brain. It is thought to be the center of emotion, memory and the involuntary nervous system.
insight The ability to gain an accurate and deep understanding of a situation just by thinking about it, instead of working out a solution through experimentation.
link A connection between two people or things.
microscopic An adjective for things too small to be seen by the unaided eye. It takes a microscope to view objects this small, such as bacteria or other one-celled organisms.
molecule An electrically neutral group of atoms that represents the smallest possible amount of a chemical compound. Molecules can be made of single types of atoms or of different types. For example, the oxygen in the air is made of two oxygen atoms (O2), but water is made of two hydrogen atoms and one oxygen atom (H2O).
nerve A long, delicate fiber that transmits signals across the body of an animal. An animal’s backbone contains many nerves, some of which control the movement of its legs or fins, and some of which convey sensations such as hot, cold or pain.
network A group of interconnected people or things. (v.) The act of connecting with other people who work in a given area or do similar thing (such as artists, business leaders or medical-support groups), often by going to gatherings where such people would be expected, and then chatting them up. (n. networking)
neural network A computer program designed to work in a way similar to the human brain. The programs can “learn” from examples, just as the brain does.
neuron An impulse-conducting cell. Such cells are found in the brain, spinal column and nervous system.
neuroscience The field of science that deals with the structure or function of the brain and other parts of the nervous system. Researchers in this field are known as neuroscientists.
node A person or thing in a network.
numerical Having to do with numbers.
prefrontal cortex A region containing some of the brain’s gray matter. Located behind the forehead, it plays a role in making decisions and other complex mental activities, in emotions and in behaviors.
Proceedings of the National Academy of Sciences A prestigious journal publishing original scientific research, begun in 1914. The journal's content spans the biological, physical, and social sciences. Each of the more than 3,000 papers it publishes each year, now, are not only peer reviewed but also approved by a member of the U.S. National Academy of Sciences.
protein A compound made from one or more long chains of amino acids. Proteins are an essential part of all living organisms. They form the basis of living cells, muscle and tissues; they also do the work inside of cells. Among the better-known, stand-alone proteins are the hemoglobin (in blood) and the antibodies (also in blood) that attempt to fight infections. Medicines frequently work by latching onto proteins.
reinforcement learning An approach to teaching in which an animal or a person learns to perform a specific task to achieve a desired reward.
reward (In animal behavior) A stimulus, such as a tasty food pellet, that is offered to an animal or person to get them to change their behavior or to learn a task.
scanner A machine that runs some sort of light (which includes anything from X-rays to infrared energy) over a person or object to get a succession of images. When a computer brings these images together, they can provide a motion picture of something or can offer a three-dimensional view through the target. Such systems are often used to see inside the human body or solid objects without breaching their surface.
schizophrenia A serious brain disorder that can lead to hallucinations, delusions and other uncontrolled behaviors.
signaling molecule A substance created by an organism and released into the environment. In organisms that use quorum sensing, signaling molecules are used to broadcast an individual’s presence to similar organisms nearby.
subtle Some feature that may be important, but can be hard to see or describe. For instance, the first cellular changes that signal the start of a cancer may be visible but subtle — small and hard to distinguish from nearby healthy tissues.
synapse The junction between neurons that transmits chemical and electrical signals.
tissue Made of cells, any of the distinct types of materials that make up animals, plants or fungi. Cells within a tissue work as a unit to perform a particular function in living organisms. Different organs of the human body, for instance, often are made from many different types of tissues.
trait A characteristic feature of something.
Journal: D. Bassett and M.G. Mattar. A network neuroscience of human learning: Potential to inform quantitative theories of brain and behavior. Trends in Cognitive Sciences. Vol. 21, April 2017, p. 250-264. doi: 10.1016/j.tics.2017.01.010.
Journal: L. R. Chai et al. Functional network dynamics of the language system. Cerebral Cortex. November 2016, p. 4148. doi: 10.1093/cercor/bhw238
Journal: D. S. Bassett et al. Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences. Vol. 188, May 3, 2011. doi: 10.1073/pnas.1018985108
Journal: D. S. Bassett et al. Learning-induced autonomy of sensorimotor systems. Nature Neuroscience. Vol. 18, May, 2015. doi:10.1038/nn.3993
Journal: R. F. Betzel et al. Positive affect, surprise, and fatigue are correlates of network flexibility. Scientific Reports. Published online March 31, 2017. doi: 10.1038/s41598-017-00425-z
Journal: U. Braun et al. Dynamic brain network reconfiguration as a potential schizophrenia genetic risk mechanism modulated by NMDA receptor function. Proceedings of the National Academy of Sciences. Vol. 113, November 1, 2016. doi: 10.1073/pnas.1608819113
Journal: Y. Ezzyat et al. Direct brain stimulation modulates encoding states and memory performance in humans. Current Biology. Vol. 27, May 8, 2017, p. 1251. doi: 10.1016/j.cub.2017.03.028
Journal: R. T. Gerraty et al. Transfer of learning relates to intrinsic connectivity between hippocampus, ventral prefrontal cortex and large-scale networks. The Journal of Neuroscience. Vol. 34, August 20, 2014, p. 11297. doi: 10.1523/JNEUROSCI.0185-14.2014
Journal: R. T. Gerraty et al. Dynamic flexibility in striatal-cortical circuits supports reinforcement learning. www.BioRXiv.org, posted May 30, 2017. doi: 10.1101/094383
Journal: M. Rosenberg-Lee et al. Brain hyper-connectivity and operation-specific deficits during arithmetic problem solving in children with developmental dyscalculia. Developmental Science. Vol. 18, May, 2015. doi: 10.1111/desc.12216