The Neuroscience of Holding It

Wherever you are right now: squeeze your glutes. Feel that? You just also contracted your pelvic floor too, whether you wanted to or not.

Scientists studying the source of chronic abdominal and pelvic floor pain found an unexpected connection in the brain between the pelvic floor – the muscle responsible for, among other things, keeping you from peeing your pants – and various muscles throughout the body. They’ve found some evidence for a link as far away as the toes (try tapping a toe and see if you feel the clench), but the strongest link so far is with the glutes.

“We knew that pelvic floor muscles contract involuntarily in healthy people to make sure they don’t accidently urinate, but we didn’t know what part of the nervous system was doing this,” said Jason Kutch, corresponding author on a study about the research and an assistant professor in the Division of Biokinesiology & Physical Therapy at the USC Ostrow School of Dentistry. “Now we know that there are specific brain regions controlling involuntary pelvic floor contraction.”

Kutch collaborated with colleagues at USC Ostrow, the Keck School of Medicine of USC, and Loma Linda University on the research. Their findings were published on October 8 in the Journal of Neuroscience.

The team used electromyographic recordings – which measure the activation of muscle tissue – to show that pelvic floor activation occurred in conjunction with the activation of certain muscles (like the glutes), but not others (like fingers).

They then used functional magnetic image resonance (fMRI) imaging to show that a specific part of the brain (the medial wall of the precentral gyrus – a part of the primary motor cortex) activates both when the pelvic floor contracts and when the glutes are squeezed – but not when fingers move.

“We hope that this vein of research will help us to find the causes of chronic pelvic floor pain, which disproportionately affect women, and may even yield information that could help people struggling with incontinence,” Kutch said.

Broadly, the finding speaks to the interconnected nature of our bodies and brains, and all of the hard work going on in the pelvic floor muscles – without us even know it.

Using the brain to forecast decisions

You’re waiting at a bus stop, expecting the bus to arrive any time. You watch the road. Nothing yet. A little later you start to pace. More time passes. “Maybe there is some problem”, you think. Finally, you give up and raise your arm and hail a taxi. Just as you pull away, you glimpse the bus gliding up. Did you have a choice to wait a bit longer? Or was giving up too soon the inevitable and predictable result of a chain of neural events?

In research published on 09/28/2014 in the journal Nature Neuroscience, scientists show that neural recordings can be used to forecast when spontaneous decisions will take place. “Experiments like this have been used to argue that free will is an illusion,” says Zachary Mainen, a neuroscientist at the Champalimaud Centre for the Unknown, in Lisbon, Portugal, who led the study, “but we think that interpretation is mistaken.”

The scientists used recordings of neurons in an area of the brain involved in planning movements to try to predict when a rat would give up waiting for a delayed tone. “We know they were not just responding to a stimulus, but spontaneously deciding when to give up, because the timing of their choice varied unpredictably from trial to trial” said Mainen. The researchers discovered that neurons in the premotor cortex could predict the animals’ actions more than one second in advance. According to Mainen, “This is remarkable because in similar experiments, humans report deciding when to move only around two tenths of a second before the movement.”

However, the scientists claim that this kind of predictive activity does not mean that the brain has decided. “Our data can be explained very well by a theory of decision-making known as an ‘integration-to-bound’ model” says Mainen. According to this theory, individual brain cells cast votes for or against a particular action, such as raising an arm. Circuits within the brain keep a tally of the votes in favor of each action and when a threshold is reached it is triggered. Critically, like individual voters in an election, individual neurons influence a decision but do not determine the outcome. Mainen explained: “Elections can be forecast by polling, and the more data available, the better the prediction, but these forecasts are never 100% accurate and being able to partly predict an election does not mean that its results are predetermined. In the same way, being able to use neural activity to predict a decision does not mean that a decision has already taken place.”

The scientists also described a second population of neurons whose activity is theorized to reflect the running tally of votes for a particular action. This activity, described as “ramping”, had previously been reported only in humans and other primates. According to Masayoshi Murakami, co-author of the paper, “we believe these data provide strong evidence that the brain is performing integration to a threshold, but there are still many unknowns.” Said Mainen, “what is the origin of the variability is a huge question. Until we understand that, we cannot say we understand how a decision works”.

EEG Study Findings Reveal How Fear is Processed in the Brain

An estimated 8% of Americans will suffer from post traumatic stress disorder (PTSD) at some point during their lifetime. Brought on by an overwhelming or stressful event or events, PTSD is the result of altered chemistry and physiology of the brain. Understanding how threat is processed in a normal brain versus one altered by PTSD is essential to developing effective interventions. 

New research from the Center for BrainHealth at The University of Texas at Dallas published online today in Brain and Cognition illustrates how fear arises in the brain when individuals are exposed to threatening images. This novel study is the first to separate emotion from threat by controlling for the dimension of arousal, the emotional reaction provoked, whether positive or negative, in response to stimuli. Building on previous animal and human research, the study identifies an electrophysiological marker for threat in the brain.

“We are trying to find where thought exists in the mind,” explained John Hart, Jr., M.D., Medical Science Director at the Center for BrainHealth. “We know that groups of neurons firing on and off create a frequency and pattern that tell other areas of the brain what to do. By identifying these rhythms, we can correlate them with a cognitive unit such as fear.”

Utilizing electroencephalography (EEG), Dr. Hart’s research team identified theta and beta wave activity that signifies the brain’s reaction to visually threatening images. 

“We have known for a long time that the brain prioritizes threatening information over other cognitive processes,” explained Bambi DeLaRosa, study lead author. “These findings show us how this happens. Theta wave activity starts in the back of the brain, in it’s fear center – the amygdala – and then interacts with brain’s memory center - the hippocampus – before traveling to the frontal lobe where thought processing areas are engaged. At the same time, beta wave activity indicates that the motor cortex is revving up in case the feet need to move to avoid the perceived threat.” 

For the study, 26 adults (19 female, 7 male), ages 19-30 were shown 224 randomized images that were either unidentifiably scrambled or real pictures. Real pictures were separated into two categories: threatening (weapons, combat, nature or animals) and non-threatening (pleasant situations, food, nature or animals). 

While wearing an EEG cap, participants were asked to push a button with their right index finger for real items and another button with their right middle finger for nonreal/scrambled items. Shorter response times were recorded for scrambled images than the real images. There was no difference in reaction time for threatening versus non-threatening images. 

EEG results revealed that threatening images evoked an early increase in theta activity in the occipital lobe (the area in the brain where visual information is processed), followed by a later increase in theta power in the frontal lobe (where higher mental functions such as thinking, decision-making, and planning occur). A left lateralized desynchronization of the beta band, the wave pattern associated with motor behavior (like the impulse to run), also consistently appeared in the threatening condition.

This study will serve as a foundation for future work that will explore normal versus abnormal fear associated with an object in other atypical populations including individuals with PTSD.

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)

Stop and Listen: Study Shows How Movement Affects Hearing

When we want to listen carefully to someone, the first thing we do is stop talking. The second thing we do is stop moving altogether. This strategy helps us hear better by preventing unwanted sounds generated by our own movements.

This interplay between movement and hearing also has a counterpart deep in the brain. Indeed, indirect evidence has long suggested that the brain’s motor cortex, which controls movement, somehow influences the auditory cortex, which gives rise to our conscious perception of sound.

A new Duke study, appearing online August 27 in Nature, combines cutting-edge methods in electrophysiology, optogenetics and behavioral analysis to reveal exactly how the motor cortex, seemingly in anticipation of movement, can tweak the volume control in the auditory cortex.

The new lab methods allowed the group to “get beyond a century’s worth of very powerful but largely correlative observations, and develop a new, and really a harder, causality-driven view of how the brain works,” said the study’s senior author Richard Mooney Ph.D., a professor of neurobiology at Duke University School of Medicine, and a member of the Duke Institute for Brain Sciences.

The findings contribute to the basic knowledge of how communication between the brain’s motor and auditory cortexes might affect hearing during speech or musical performance. Disruptions to the same circuitry may give rise to auditory hallucinations in people with schizophrenia.

In 2013, researchers led by Mooney first characterized the connections between motor and auditory areas in mouse brain slices as well as in anesthetized mice. The new study answers the critical question of how those connections operate in an awake, moving mouse.

"This is a major step forward in that we’ve now interrogated the system in an animal that’s freely behaving," said David Schneider, a postdoctoral associate in Mooney’s lab.

Mooney suspects that the motor cortex learns how to mute responses in the auditory cortex to sounds that are expected to arise from one’s own movements while heightening sensitivity to other, unexpected sounds. The group is testing this idea.

"Our first step will be to start making more realistic situations where the animal needs to ignore the sounds that its movements are making in order to detect things that are happening in the world," Schneider said.

In the latest study, the team recorded electrical activity of individual neurons in the brain’s auditory cortex. Whenever the mice moved — walking, grooming, or making high-pitched squeaks — neurons in their auditory cortex were dampened in response to tones played to the animals, compared to when they were at rest.

To find out whether movement was directly influencing the auditory cortex, researchers conducted a series of experiments in awake animals using optogenetics, a powerful method that uses light to control the activity of select populations of neurons that have been genetically sensitized to light. Like the game of telephone, sounds that enter the ear pass through six or more relays in the brain before reaching the auditory cortex.

"Optogenetics can be used to activate a specific relay in the network, in this case the penultimate node that relays signals to the auditory cortex," Mooney said.

About half of the suppression during movement was found to originate within the auditory cortex itself. “That says a lot of modulation is going on in the auditory cortex, and not just at earlier relays in the auditory system” Mooney said.

More specifically, the team found that movement stimulates inhibitory neurons that in turn suppress the response of the auditory cortex to tones.

The researchers then wondered what turns on the inhibitory neurons. The suspects were many. “The auditory cortex is like this giant switching station where all these different inputs come through and say, ‘Okay, I want to have access to these interneurons,’” Mooney said. “The question we wanted to answer is who gets access to them during movement?”

The team knew from previous experiments that neuronal projections from the secondary motor cortex (M2) modulate the auditory cortex. But to isolate M2’s relative contribution — something not possible with traditional electrophysiology — the researchers again used optogenetics, this time to switch on and off the M2’s inputs to the inhibitory neurons.

Turning on M2 inputs reproduced a sense of movement in the auditory cortex, even in mice that were resting, the group found. “We were sending a ‘Hey I’m moving’ signal to the auditory cortex,” Schneider said. Then the effect of playing a tone on the auditory cortex was much the same as if the animal had actually been moving — a result that confirmed the importance of M2 in modulating the auditory cortex. On the other hand, turning off M2 simulated rest in the auditory cortex, even when the animals were still moving.

"I couldn’t contain my excitement when we first saw that result," said Anders Nelson, a neurobiology graduate student in Mooney’s group.

Modelling how neurons work together

Sleep After Learning Strengthens Connections Between Brain Cells and Enhances Memory

In study published today in Science, researchers at NYU Langone Medical Center show for the first time that sleep after learning encourages the growth of dendritic spines, the tiny protrusions from brain cells that connect to other brain cells and facilitate the passage of information across synapses, the junctions at which brain cells meet. Moreover, the activity of brain cells during deep sleep, or slow-wave sleep, after learning is critical for such growth.

The findings, in mice, provide important physical evidence in support of the hypothesis that sleep helps consolidate and strengthen new memories, and show for the first time how learning and sleep cause physical changes in the motor cortex, a brain region responsible for voluntary movements. 

“We’ve known for a long time that sleep plays an important role in learning and memory. If you don’t sleep well you won’t learn well,” says senior investigator Wen-Biao Gan, PhD, professor of neuroscience and physiology and a member of the Skirball Institute of Biomolecular Medicine at NYU Langone Medical Center. “But what’s the underlying physical mechanism responsible for this phenomenon? Here we’ve shown how sleep helps neurons form very specific connections on dendritic branches that may facilitate long-term memory. We also show how different types of learning form synapses on different branches of the same neurons, suggesting that learning causes very specific structural changes in the brain.”

On the cellular level, sleep is anything but restful: Brain cells that spark as we digest new information during waking hours replay during deep sleep, also known as slow-wave sleep, when brain waves slow down and rapid-eye movement, as well as dreaming, stops. Scientists have long believed that this nocturnal replay helps us form and recall new memories, yet the structural changes underpinning this process have remained poorly understood.

To shed light on this process, Dr. Gan and colleagues employed mice genetically engineered to express a fluorescent protein in neurons. Using a special laser-scanning microscope that illuminates the glowing fluorescent proteins in the motor cortex, the scientists were then able to track and image the growth of dendritic spines along individual branches of dendrites before and after mice learned to  balance on a spin rod. Over time mice learned how to balance on the rod as it gradually spun faster. “It’s like learning to ride a bike,” says Dr. Gan. “Once you learn it, you never forget.”

After documenting that mice, in fact, sprout new spines along dendritic branches, within six hours after training on the spinning rod, the researchers set out to understand how sleep would impact this physical growth. They trained two sets of mice: one trained on the spinning rod for an hour and then slept for 7 hours; the second trained for the same period of time on the rod but stayed awake for 7 hours. The scientists found that the sleep-deprived mice experienced significantly less dendritic spine growth than the well-rested mice. Furthermore, they found that the type of task learned determined which dendritic branches spines would grow.

Running forward on the spinning rod, for instance, produced spine growth on different dendritic branches than running backward on the rod, suggesting that learning specific tasks causes specific structural changes in the brain.

“Now we know that when we learn something new, a neuron will grow new connections on a specific branch,” says Dr. Gan. “Imagine a tree that grows leaves (spines) on one branch but not another branch. When we learn something new, it’s like we’re sprouting leaves on a specific branch.”

Finally, the scientists showed that brain cells in the motor cortex that activate when mice learn a task reactivate during slow-wave deep sleep. Disrupting this process, they found, prevents dendritic spine growth. Their findings offer an  important insight into the functional role of neuronal replay—the process by which the sleeping brain rehearses tasks learned during the day—observed in the motor cortex.

“Our data suggest that neuronal reactivation during sleep is quite important for growing specific connections within the motor cortex,” Dr. Gan adds.

(Image: Shutterstock)

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.

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