Scientists Discover Why Learning Tasks Can Be Difficult

Learning a new skill is easier when it is related to an ability we already have. For example, a trained pianist can learn a new melody easier than learning how to hit a tennis serve.

Scientists from the Center for the Neural Basis of Cognition (CNBC) — a joint program between Carnegie Mellon University and the University of Pittsburgh — have discovered a fundamental constraint in the brain that may explain why this happens. Published as the cover story in the Aug. 28, 2014, issue of Nature, they found for the first time that there are limitations on how adaptable the brain is during learning and that these restrictions are a key determinant for whether a new skill will be easy or difficult to learn. Understanding the ways in which the brain’s activity can be “flexed” during learning could eventually be used to develop better treatments for stroke and other brain injuries.

Lead author Patrick T. Sadtler, a Ph.D. candidate in Pitt’s Department of Bioengineering, compared the study’s findings to cooking.

"Suppose you have flour, sugar, baking soda, eggs, salt and milk. You can combine them to make different items - bread, pancakes and cookies — but it would be difficult to make hamburger patties with the existing ingredients," Sadtler said. "We found that the brain works in a similar way during learning. We found that subjects were able to more readily recombine familiar activity patterns in new ways relative to creating entirely novel patterns."

For the study, the research team trained animals to use a brain-computer interface (BCI), similar to ones that have shown recent promise in clinical trials for assisting quadriplegics and amputees.

"This evolving technology is a powerful tool for brain research," said Daofen Chen, program director at the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), which supported this research. "It helps scientists study the dynamics of brain circuits that may explain the neural basis of learning."

The researchers recorded neural activity in the subject’s motor cortex and directed the recordings into a computer, which translated the activity into movement of a cursor on the computer screen. This technique allowed the team to specify the activity patterns that would move the cursor. The test subjects’ goal was to move the cursor to targets on the screen, which required them to generate the patterns of neural activity that the experimenters had requested. If the subjects could move the cursor well, that meant that they had learned to generate the neural activity pattern that the researchers had specified.

The results showed that the subjects learned to generate some neural activity patterns more easily than others, since they only sometimes achieved accurate cursor movements. The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning.

"We wanted to study how the brain changes its activity when you learn, and also how its activity cannot change. Cognitive flexibility has a limit — and we wanted to find out what that limit looks like in terms of neurons," said Aaron P. Batista, assistant professor of bioengineering at Pitt.

Byron M. Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon, believes this work demonstrates the utility of BCI for basic scientific studies that will eventually impact people’s lives.

"These findings could be the basis for novel rehabilitation procedures for the many neural disorders that are characterized by improper neural activity," Yu said. "Restoring function might require a person to generate a new pattern of neural activity. We could use techniques similar to what were used in this study to coach patients to generate proper neural activity."

(Image: Fotolia)

(Image caption: This image shows an artificial connection that connects brain to spinal circuits. Credit: © Yukio Nishimura)

Bypass commands from the brain to legs through a computer

Gait disturbance in individuals with spinal cord injury is attributed to the interruption of neural pathways from brain to the spinal locomotor center, whereas neural circuits locate below and above the lesion maintain most of their functions. An artificial connection that bridges the lost pathway and connects brain to spinal circuits has potential to ameliorate the functional loss. A Japanese research group led by Shusaku Sasada, research fellow and Yukio Nishimura, associate professor of the National Institute for Physiological Sciences (NIPS), National Institutes of Natural Sciences (NINS) has successfully made an artificial connection from the brain to the locomotion center in the spinal cord by bypassing with a computer interface. This allowed subjects to stimulate the spinal locomotion center using volitionally-controlled muscle activity and to control walking in legs. This result was published online in The Journal of Neuroscience on August 13, 2014.

Neural networks in the spinal cord, locomotion center are capable of producing rhythmic movements, such as swimming and walking, even when isolated from the brain. The brain controls spinal locomotion center by sending command to the spinal locomotion center to start, stop and change waking speed. In most cases of spinal cord injury, the loss of this link from the brain to the locomotion center causes problems with walking.

The research group came up with bypassing the functioning brain and locomotion center with the computer to compensate lost pathways as a way to enable individuals with spinal cord injury to regain walking ability.

Since the arm movement associate with leg movement when we walk they used muscle activity of arm to sarogate the brain activity. The computer interface allowed subjects to control magnetic stimulator that drive to the spinal locomotion center non-invassively using volitionally-controlled muscle activity and to control walking in legs. As a results of experiments in people who are neurologically intact, the subjects were asked to make own legs relaxed and passively controlled via computer interface that was controlled by arm muscle, walking behavior in legs was induced and subjects could control the step cycle volitionally as well. However without bypassing with the computer interface, the legs did not move even if the arms muscle was volitionally acivated.

"We hope that this technology would compensate for the interrupted pathways’ function by sending an intentionally encoded command to the preserved spinal locomotor center and regain volitionally-controlled walking in indviduals with paraplegia. However, the major challenge that this technology does not help them to dodge obstacles and to maintain posture. We are carefully working toward clinical application in near future", Nishimura said.

New prosthetic arm controlled by neural messages

This design hopes to identify the memory of movement in the amputee’s brain to translate to an order allowing manipulation of the device.

Controlling a prosthetic arm by just imagining a motion may be possible through the work of Mexican scientists at the Centre for Research and Advanced Studies (CINVESTAV), who work in the development of an arm replacement to identify movement patterns from brain signals.

First, it is necessary to know if there is a memory pattern to remember in the amputee’s brain in order to know how it moved and, thus, translating it to instructions for the prosthesis,” says Roberto Muñoz Guerrero, researcher at the Department of Electrical Engineering and project leader at Cinvestav.

He explains that the electric signal won’t come from the muscles that form the stump, but from the movement patterns of the brain. “If this phase is successful, the patient would be able to move the prosthesis by imagining different movements.”

However, Muñoz Guerrero acknowledges this is not an easy task because the brain registers a wide range of activities that occur in the human body and from all of them, the movement pattern is tried to be drawn. “Therefore, the first step is to recall the patterns in the EEG and define there the memory that can be electrically recorded. Then we need to evaluate how sensitive the signal is to other external shocks, such as light or blinking.”

Regarding this, it should be noted that the prosthesis could only be used by individuals who once had their entire arm and was amputated because some accident or illness. Patients were able to move the arm naturally and stored in their memory the process that would apply for the use of the prosthesis.

According to the researcher, the prosthesis must be provided with a mechanical and electronic system, the elements necessary to activate it and a section that would interpret the brain signals. “Regarding the material with which it must be built, it has not yet been fully defined because it must weigh between two and three kilograms, which is similar to the missing arm’s weight.”

The unique prosthesis represents a new topic in bioelectronics called BCI (Brain Computer Interface), which is a direct communication pathway between the brain and an external device in order to help or repair sensory and motor functions. “An additional benefit is the ability to create motion paths for the prosthesis, which is not possible with commercial products,” says Muñoz Guerrero.

A Mexican Scientist Just Invented a ‘Telekinesis’ Helmet

A researcher just made a remarkable breakthrough in the area of brain-computer interfaces—creating a rig that allows a user to operate machines with thought alone, almost literally granting a form of ‘telekinesis’ over attached devices.

Brain-computer interfaces are a rapidly expanding area of research and industry. Though the technology to read brainwaves from the head’s surface has been around for decades, scientists and engineers have only recently created numerous systems to read signals directly from the brain and translate them into commands that control computers.

In the future, these technologies could allow people with physical disabilities to control their environment through thought alone—the brain-computer interface effectively grants users a form of telekinesis. With an increasingly digital world, brain-computer interfaces (BCIs) could allow future generations to interact with technology telepathically. Many of the early BCI studies were promising, but the technology was difficult to use and mentally exhausting.

Read more

Scientists discover how to restore ability to grasp in paralysed hand

Pioneering research by scientists at a North East university could help people who have been paralysed to re-gain the use of their hands.

The researchers at Newcastle University have been able to restore the ability to grab objects with a paralysed hand using spinal cord stimulation.

The work, which has been funded by the Wellcome Trust, could help stroke and spinal injury victims as the research has shown that by connecting the brain to a computer and then the computer to the spinal cord, it is possible to restore movement.

The discovery opens up the possibility of new treatments within the next few years which could help stroke victims or those with spinal cord injuries regain some movement in their arms and hands as currently there is no cure for upper limb paralysis.

The work, led by Dr Andrew Jackson, Research Fellow at Newcastle University and Dr Jonas Zimmermann, now at Brown University in America, is published in the journal Frontiers in Neuroscience.

Read more

Researchers reveal more about how our brains control our arms

Ready, set, go.

Sometimes that’s how our brains work. When we anticipate a physical act, such as reaching for the keys we noticed on the table, the neurons that control the task adopt a state of readiness, like sprinters bent into a crouch.

Other times, however, our neurons must simply react, such as if someone were to toss us the keys without gesturing first, to prepare us to catch.

How do the neurons in the brain control planned versus unplanned arm movements?

Krishna Shenoy, a Stanford professor of electrical engineering, neurobiology (by courtesy) and bioengineering (affiliate), wanted to answer that question as part of his group’s ongoing efforts to develop and improve brain-controlled prosthetic devices.

In a paper published today in the journal Neuron, Shenoy and first author Katherine Cora Ames, a doctoral student in the Neurosciences Graduate Program, present a mathematical analysis of the brain activity of monkeys as they make anticipated and unanticipated reaching motions.

Monitoring the neurons

The experimental data came from recording the electrical activity of neurons in the brain that control motor and premotor functions. The idea was to observe and understand the activity levels of these neurons during experiments in which the monkeys made planned or reactive arm movements. What the researchers found is that when the monkeys knew what arm movement they were supposed to make and were simply waiting for the cue to act, electrical readings showed that the neurons went into what scientists call the prepare-and-hold state – the brain’s equivalent of ready, set, waiting for the cue to go.

But when the monkeys made unplanned or unexpected movements, the neurons did not go through the expected prepare-and-hold state. “This was a surprise,” Ames said.

Before the experiment, the researchers had believed that a prepare-and-hold state had to precede movement. In short, they thought the neurons had to go into a “ready, set” crouch before acting on the “go” command. But they discovered otherwise in three variations of an experiment involving similar arm movements.

Experimental design

In all three cases, the monkeys were trained to touch a target that appeared on a display screen.

During each motion, the researchers measured the electrical activity of the neurons in control of arm movements.

In one set of experiments, the monkeys were shown the target but were trained not to touch it until they got the “go” signal. This is called a delayed reach experiment. It served as the planned action.

In a second set of experiments the monkeys were trained to touch the target as soon as it appeared. This served as the unplanned action.

In a third variant, the position of the target was changed. It briefly appeared in one location on the screen. The target then reappeared in a different location. This required the monkeys to revise their movement plan.

Monkey see, then monkey do

Ames said that, in all three instances, the first information to reach the neurons was awareness of the target.

“Perception always occurred first,” Ames said.

Then, about 50 milliseconds later, some differences appeared in the data. When the monkeys had to wait for the go command, the brain recordings showed that the neurons went into a discernable prepare-and-hold state. But in the other two cases, the neurons did not enter the prepare-and-hold state.

Instead, roughly 50 milliseconds after the electrical readings showed evidence of perception, a change in neuronal activity signaled the command to touch the target; it came with no apparent further preparation between perception and action. “Ready, set” was unnecessary. In these instances, the neurons just said, “Go!”

Applications

“This study changes our view of how movement is controlled,” Ames said. “First you get the information about where to move. Then comes the decision to move. There is no specific prepare-and-hold stage unless you are waiting for the signal to move.”

These nuanced understandings are important to Shenoy. His lab develops and improves electronic systems that can convert neural activity into electronic signals in order to control a prosthetic arm or move the cursor on a computer screen.

One example of such efforts is the BrainGate clinical trial here at Stanford, now being conducted under U.S. Food & Drug Administration supervision, to test the safety of brain-controlled, computer cursor systems – “think-and-click” communication for people who can’t move.

“In addition to advancing basic brain science, these new findings will lead to better brain-controlled prosthetic arms and communication systems for people with paralysis,” Shenoy said.

Novel Rehabilitation Device Improves Motor Skills after Stroke

Using a novel stroke rehabilitation device that converts an individual’s thoughts to electrical impulses to move upper extremities, stroke patients reported improvements in their motor function and ability to perform activities of daily living. Results of the study were presented today at the annual meeting of the Radiological Society of North America (RSNA).

"Each year, nearly 800,000 people suffer a new or recurrent stroke in the United States, and 50 percent of those have some degree of upper extremity disability," said Vivek Prabhakaran, M.D., Ph.D., director of functional neuroimaging in radiology at the University of Wisconsin-Madison. "Rehabilitation sessions with our device allow patients to achieve an additional level of recovery and a higher quality of life."

Dr. Prabhakaran, along with co-principal investigator Justin Williams, Ph.D., and a multidisciplinary team, built the new rehabilitation device by pairing a functional electrical stimulation (FES) system, which is currently used to help stroke patients recover limb function, and a brain control interface (BCI), which provides a direct communication pathway between the brain and this peripheral stimulation device.

In an FES system, electrical currents are used to activate nerves in paralyzed extremities. Using a computer and an electrode cap placed on the head, the new BCI-FES device (called the Closed-Loop Neural Activity-Triggered Stroke Rehabilitation Device) interprets electrical impulses from the brain and transmits the information to the FES.

"FES is a passive technique in that the electrical impulses move the patients’ extremities for them," Dr. Prabhakaran said. "When a patient using our device is asked to imagine or attempt to move his or her hand, the BCI translates that brain activity to a signal that triggers the FES. Our system adds an active component to the rehabilitation by linking brain activity to the peripheral stimulation device, which gives the patients direct control over their movement."

The Wisconsin team conducted a small clinical trial of their rehabilitation device, enlisting eight patients with one hand affected by stroke. The patients were also able to serve as a control group by using their normal, unaffected hand. Patients in the study represented a wide range of stroke severity and amount of time elapsed since the stroke occurred. Despite having received standard rehabilitative care, the patients had varying degrees of residual motor deficits in their upper extremities. Each underwent nine to 15 rehabilitation sessions of two to three hours with the new device over a period of three to six weeks.

The patients also underwent functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) before, at the mid-point of, at the end of, and one month following the rehabilitation period. fMRI is able to show which areas of the brain are activated while the patient performs a task, and DTI reveals the integrity of fibers within the white matter that connects the brain’s functional areas.

Patients who suffered a stroke of moderate severity realized the greatest improvements to motor function following the rehabilitation sessions. Patients diagnosed with mild and severe strokes reported improved ability to complete activities of daily living following rehabilitation.

Dr. Prabhakaran said the results captured throughout the rehabilitation process—specifically the ratio of hemispheric involvement of motor areas—related well to the behavioral changes observed in patients. A comparison of pre-rehabilitation and post-rehabilitation fMRI results revealed reorganization in the regions of the brain responsible for motor function. DTI results over the course of the rehabilitation period revealed a gradual strengthening of the integrity of the fiber tracts.

"Our hope is that this device not only shortens rehabilitation time for stroke patients, but also that it brings a higher level of recovery than is achievable with the current standard of care," Dr. Prabhakaran said. "We believe brain imaging will be helpful in both planning and tracking a stroke patient’s therapy, as well as learning more about neuroplastic changes during recovery."

A Blueprint for Restoring Touch with a Prosthetic Hand

New research at the University of Chicago is laying the groundwork for touch-sensitive prosthetic limbs that one day could convey real-time sensory information to amputees via a direct interface with the brain.

The research, published early online in the Proceedings of the National Academy of Sciences, marks an important step toward new technology that, if implemented successfully, would increase the dexterity and clinical viability of robotic prosthetic limbs.

“To restore sensory motor function of an arm, you not only have to replace the motor signals that the brain sends to the arm to move it around, but you also have to replace the sensory signals that the arm sends back to the brain,” said the study’s senior author, Sliman Bensmaia, PhD, assistant professor in the Department of Organismal Biology and Anatomy at the University of Chicago. “We think the key is to invoke what we know about how the brain of the intact organism processes sensory information, and then try to reproduce these patterns of neural activity through stimulation of the brain.”

Bensmaia’s research is part of Revolutionizing Prosthetics, a multi-year Defense Advanced Research Projects Agency (DARPA) project that seeks to create a modular, artificial upper limb that will restore natural motor control and sensation in amputees. Managed by the Johns Hopkins University Applied Physics Laboratory, the project has brought together an interdisciplinary team of experts from academic institutions, government agencies and private companies.

Bensmaia and his colleagues at the University of Chicago are working specifically on the sensory aspects of these limbs. In a series of experiments with monkeys, whose sensory systems closely resemble those of humans, they indentified patterns of neural activity that occur during natural object manipulation and then successfully induced these patterns through artificial means.

The first set of experiments focused on contact location, or sensing where the skin has been touched. The animals were trained to identify several patterns of physical contact with their fingers. Researchers then connected electrodes to areas of the brain corresponding to each finger and replaced physical touches with electrical stimuli delivered to the appropriate areas of the brain. The result: The animals responded the same way to artificial stimulation as they did to physical contact.

Next the researchers focused on the sensation of pressure. In this case, they developed an algorithm to generate the appropriate amount of electrical current to elicit a sensation of pressure. Again, the animals’ response was the same whether the stimuli were felt through their fingers or through artificial means.

Finally, Bensmaia and his colleagues studied the sensation of contact events. When the hand first touches or releases an object, it produces a burst of activity in the brain. Again, the researchers established that these bursts of brain activity can be mimicked through electrical stimulation.

The result of these experiments is a set of instructions that can be incorporated into a robotic prosthetic arm to provide sensory feedback to the brain through a neural interface. Bensmaia believes such feedback will bring these devices closer to being tested in human clinical trials.

“The algorithms to decipher motor signals have come quite a long way, where you can now control arms with seven degrees of freedom. It’s very sophisticated. But I think there’s a strong argument to be made that they will not be clinically viable until the sensory feedback is incorporated,” Bensmaia said. “When it is, the functionality of these limbs will increase substantially.”