Birmingham FES project to improve life for amputees – The Engineer

A project led by Birmingham University aims to improve quality of life for amputees through development of a novel functional electrical stimulation (FES) device.
The researchers hope to meet currently unmet needs of amputees through their new assistive technology, with potential benefits to include improved function, pain management and mitigated risk of complications.
“Annually, there are more than one million amputations worldwide as a result of vascular diseases, trauma and cancer,” said principal investigator Dr Ziyun Ding, from Birmingham’s Department of Mechanical Engineering.
“With the increasing rate of diabetes and the population ageing, the amputee population is expected to double by 2050. A major limb amputation inevitably impairs mobility. In addition, amputees may suffer from chronic pain and the loss of muscle mass, which altogether in turn will [further diminish] their mobility.”
Ding described the team’s approach to using FES — a device to deliver small amounts of electrical current to muscles, providing additional amounts of muscle excitations for fulfilling functional tasks — as ‘ground-breaking’. 
It involves maintaining a computational musculoskeletal model of the body to predict an optimal solution for amputees, she explained, which could prescribe the values of unknowns such as which muscles to stimulate, the amount and the timing of stimulation in a functional task.
“Our bodies have a great deal of redundancy: there are many ways to accomplish a task we ask our muscles to do,” Ding said. “That is a good thing: if one or several muscles are amputated, others can pick up the slack by working harder than they were before with an amputation.
“With the improved understanding of our bodies, especially the improved understanding of the relationship between the amounts we excite our muscles and the resulting motions of our bodies, we believe that we could help amputees regain their mobility.
“Simply speaking, if amputees could walk faster and longer with the assistance of prostheses as well as the functional electrical stimulation, this will be able to reduce other effects, typically pain and cardiovascular disease.”
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Ding added that the team’s approach to modelling the human musculoskeletal system involves: model preparation for measuring movement and imaging data from patients; model construction to calibrate and estimate model parameters and incorporate clinical treatment plans in the model; and model utilisation to collect post-treatment movement and imaging data from patients and validate the model.
“Few labs throughout the world have reached the point of being able to apply such an approach to solve a mobility-related clinical problem,” she said. “The advances made through the research project could quickly improve the amputee healthcare provision in approximately three years’ time.”
The project will be delivered in partnership with Rice University in the US and involves collaboration with physiotherapists, amputee consultants and FES consultants from the West Midlands Rehabilitation Centre in Birmingham. 
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The Genetics of Aleesha Young: Effort Counts, But Often Nature Decides – Muscle & Fitness

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People giving training advice often talk about exercises that change the shape of muscles. For example, some trainers claim you can develop longer muscles with Pilates or yoga compared to weight training. The problem is, this is not true. You can change the size and volume of muscles depending on what exercises you do, but the shape is determined by genetics.
Here is an illustration: Suppose you have some children’s balloons. You blow up one and it is a long, cylinder shape. Another is very round. You can keep blowing up each type and making them bigger, but the cylinder-shaped balloon will never turn into a round one and vice-versa. The shape is determined by how the balloon was manufactured and that can’t be altered.
The same is true for muscles. Some are designed to be long, cylinder shapes, other full and round and some might be somewhere in between. You can make these muscles bigger, but their genetic shape says mostly the same.
If you don’t believe in the tyranny of genetics, try getting taller.
If you want an example of a female bodybuilder with muscles that are really round and full just look at Aleesha Young. She is a perfect example of this kind of body type. By contrast, the legendary Sharon Bruneau, who had big and aesthetic muscles, did not have this kind of genetics. Part of her appeal was her long and elegant muscle structure, that of a former fashion model. This body type made it almost impossible for her to defeat somebody in competition like Lenda Murray, whose muscles were genetically fuller and rounder.
Of course, even the amazing Lenda didn’t have quite the degree of incredibly round and full muscle structure of Aleesha Young. But aside from size and fullness, Aleesha is also beautiful and highly aesthetic. Qualities necessary in become a champion, pro female bodybuilder.
Aleesha won the NPC USA Championships in 2014 and then turned pro. Gaining mass was never a problem for her. At her largest, her biceps measured over 18 in (457 mm) and her quads over 28 in (711 mm).
Aleesha says she inherited excellent genes, because she comes from an athletic family. Her father is a retired bodybuilding competitor, her brother plays American football and ice hockey, and her sister plays ice hockey. Young herself first pursued her interest in softball, cheerleading, basketball and soccer, and didn’t begin to do bodybuilding training until the age of 15, alongside her father.
After turning pro, she quickly took advantage of the contests being held by Jake Wood and the Wings of Strength organization. In 2019 she placed first at the WOS Chicago Pro Championships, after which she set her sights on the Rising Phoenix World Championships.
“Building muscle is one thing,” Aleesha says, “but diet and contest prep something very different. The quality of the top competitors at Wings contest is awe-inspiring. I felt I had pretty much found the formula when I won in Chicago and was very confident about my chances in Phoenix in 2019. But, as they say, life is what happens to you when you are making other plans.”
What life had in stored for Aleesha was a fairly serious auto accident. She didn’t suffer any permanent, lasting injury, but she was pretty banged up, which seriously interfered with her training schedule. “I was not able to be anywhere need my best,” she admits. “But I’d made a commitment to Jake Wood and Wings, so I entered the Rising Phoenix anyway.
After the contest, Aleesha agreed to drive out to the desert with me for a photo shoot. I picked Death Valley, Ca. as a location because I wanted somewhere powerful and dramatic enough to match Aleesha’s overpowering body and physical presence. The landscape was “larger than life” and so was Aleesha. We got out into the sand dunes at dawn. That choice of time was important. We had sun but the temperature in DV, statistically the hottest place on earth, was very tolerable. And as we wrapped a few hours later, we saw a change in the weather. It became overcast, with a sharp, hot wind. We had really lucked out in having the right kind of weather circumstances for our photo shoot.
But we had the photos we needed, some of which we are sharing here with you. In 2020, Aleesha is heading back to the Rising Phoenix, this time injury free. And perhaps the Ms. Olympia immediately after. In any event, she will remain a perfect example of a full-bodied, shapely, metamorphic and aesthetic champion female bodybuilder.
Stay tuned for a great future for Aleesha in the sport.
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Discovery about cellular 'batteries' could open the door to better treatments for many diseases – News-Medical.Net

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A top exercise researcher at the University of Virginia School of Medicine has revealed how our bodies ensure the proper functioning of the powerhouses of our cells. The findings could open the door to better treatments for many common diseases, including Alzheimer’s and diabetes.
The new research from UVA’s Zhen Yan, PhD, and colleagues reveals how our cells sense problems and perform quality control on cellular “batteries” known as mitochondria. Yan has spent many years seeking to better understand the workings of mitochondria, and he calls the new discovery the most exciting of his career.
Mitochondria are the center of universe to me since literally all cells in our body rely on mitochondria for energy production and must have a bulletproof system to ensure the powerhouses are functioning properly. Chronic diseases, also known as noncommunicable diseases, such as diabetes, heart failure and Alzheimer’s disease that catastrophically impact so many individuals, families and the whole society are caused by problems of the mitochondria in the cells.”
Zhen Yan, Director, Center for Skeletal Muscle Research, UVA’s Robert M. Berne Cardiovascular Research Center
Yan and his team discovered special sensors on the outer membrane surrounding the mitochondria in various tissues in both mice and humans. These sensors detect “energetic stress,” such as caused by exercise or fasting, and signal for damaged mitochondria to be degraded and removed. This essential cleanup process is known as “mitophagy,” and its existence was first suggested more than 100 years ago. But how it works has never been fully understood. Yan’s new research offers long-sought answers.
Yan and his colleagues found that the mitochondrial sensors, known as “mitoAMPK,” exist in slightly different forms in different tissues. For example, one type seemed particularly active in skeletal muscle. In a new scientific paper outlining their findings, the researchers describe the variety of sensors as “unexpectedly complex.” They go on to outline how these sensors provide a vital damage-control system that safeguards our cellular energy supply.
One finding of the study that Yan finds extremely exciting: Treating mice with  metformin, the most effective, first-line anti-diabetes drug, activates mitoAMPK in skeletal muscles without activating AMPK in the other parts of the cells. The finding is the best illustration of the importance of activating mitoAMPK and mitochondrial quality control in treatment of a common chronic disease that is known to be caused by accumulation of dysfunctional mitochondria in our body. It also explains why regular exercise is so powerful in preventing and treating such diseases.
The new insights gained into mitochondrial quality control will boost efforts to develop new treatments for non-communicable diseases that have reached pandemic proportions and are estimated to cause 71% of all deaths.
Yan, who is part of UVA’s Division of Cardiovascular Medicine, says it will be important for doctors to better understand how specific diseases interfere with mitochondrial function. And his new findings set the stage for that.
“We have developed genetic models for pinpointing the key steps of mitoAMPK activation and are on our way to discover the magic molecules that are controlled by mitoAMPK,” Yan said. “The findings taught us a lot about the beauty of the sensor system in our body. Society should definitely take advantage of these findings to promote regular exercise for health and disease prevention and develop effective exercise-mimetic drugs.”
The researchers have published their findings in the scientific journal PNAS. The research team consisted of Joshua C. Drake, Rebecca J. Wilson, Rhianna C. Laker, Yuntian Guan, Hannah R. Spaulding, Anna S. Nichenko, Wenqing Shen, Huayu Shang, Maya V. Dorn, Kian Huang, Mei Zhang, Aloka B. Bandara, Matthew H. Brisendine, Jennifer A. Kashatus, Poonam R. Sharma, Alexander Young, Jitendra Gautam, Ruofan Cao, Horst Wallrabe, Paul A. Chang, Michael Wong, Eric M. Desjardins, Simon A. Hawley, George J. Christ, David F. Kashatus, Clint L. Miller, Matthew J. Wolf, Ammasi Periasamy, Gregory R. Steinber, D. Grahame Hardie and Yan.
The research was supported by National Institutes of Health grants R01-AR050429, R00-AG057825, R01-AG067048 and T32 HL007284-37; American Heart Association post-doctoral fellowship 14POST20450061 and grant 114PRE20380254; Canadian Institutes of Health Research Foundation Grant 201709FDN-CEBA-116200; Diabetes Canada Investigator Award DI-5-17-5302-GS; and a Tier 1 Canada Research Chair and the J. Bruce Duncan Endowed Chair in Metabolic Diseases. As part of their work, the researchers used a UVA Keck Center Zeiss 780 multiphoton FLIM-FRET microscope and Leica SP5X confocal supported by the NIH.
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Andrew Wiggins shares he's put on 'a couple of pounds of muscle' during Warriors offseason – Warriors Wire

During the Golden State Warriors extended offseason period, multiple videos and photos were shared of Andrew Wiggins working in the gym. The former Rookie of the Year was practicing his drives to the bucket, long-distance shooting and more. 
When Wiggins wasn’t on the court refining his game, it looks like the 25-year-old was hitting the weights. On Wednesday, the Warriors shared a bevy of photos as players return to Chase Center for the start of preseason training camp. 
In one photo, it’s easy to spot the layer of new muscles on Wiggins’ arms. In a press conference with Bay Area media, the small forward was asked about his offseason workout plan. Wiggins admitted to gaining “a couple of” pounds of muscle. 
I put on a couple of pounds of muscle. Just a couple of pounds. Just a few. I definitely feel stronger. I feel faster, stronger. I feel good. Coming into the season, I feel the best I’ve ever felt ever. 
Via @warriors on Twitter: 
back in business pic.twitter.com/6zHsv88vp6
— Golden State Warriors (@warriors) December 3, 2020

Listen to his full pre-training camp interview with media via Warriors SoundCloud
Due to the coronavirus pandemic, Wiggins’ first run of action with the Golden State Warriors was limited to only 12 games. During that span, Wiggins averaged 19.4 points on 45.7% shooting from the field with 4.6 boards, 3.6 assists, 1.4 blocks and 1.3 steals per contest. 
With Klay Thompson set to miss the entire season with a torn Achilles, the Warriors will likely lean on Wiggins over his first full season in the Bay Area. 
Wiggins will have the rest of training camp to build chemistry with Steph Curry, Draymond Green, Kelly Oubre Jr., and James Wiseman before the season begins on Dec. 22 against the Brooklyn Nets. 
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Chin-ups vs. pull-ups: Major differences and muscles worked – INSIDER

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Chin-ups and pull-ups are highly beneficial bodyweight exercises that target your entire upper body. And while you may use the terms interchangeably, the two moves are actually quite distinct.
The big difference comes in how you grip the bar. Put most simply, chin-ups are performed with your palms facing toward your body, and pull-ups are performed with your palms facing away from you.
The change in grip position results in a large difference in muscle activation and grip strength, says Andy Sobuta, a physical therapist at Spaulding Rehabilitation Center, which is an official teaching partner of the Harvard Medical School Department of Physical Medicine and Rehabilitation. 
Here’s what you need to know about the difference between chin-ups and pull-ups, which muscles they target, and how to add them to your workout routine. 
A chin-up is a strength training exercise that uses your entire body weight, with a special focus on your upper body and core. 
While it requires a great deal of strength, the move is rather straightforward: 
In general, the chin-up may be better for someone new to a body-weight move, because it is typically the easier of the two movements, says Sobuta. Furthermore, those lacking in upper back flexibility may have an easier time with the chin-up. 
This is because chin-ups put your arms in a more natural position, which reduces injury risk to your shoulders. Doing chin-ups with proper form will also improve your grip strength and posture.
Chin-ups work your upper back and arm muscles, specifically the biceps, forearms, shoulders, and latissimus dorsi, or “lats.” Like pull-ups, chin-ups also engage your abdominal muscles throughout the move.
However, Sobuta says chin-ups differ from pull-ups in one major way. The underhand grip position of the chin-up activates the anterior chain muscles, which are located in the front of your body, such as the biceps and pectorals — while the pull-up focuses on the posterior chain muscles in your back. 
Doing a pull-up is similar to doing a chin-up. But besides the slight variations in your grip and stance, there are also differences in how your body responds to the move.
These are the steps to properly do a pull-up: 
One common issue with pull-ups is strain on your shoulders. To avoid this, it’s important to ensure you’re using proper form by pulling your shoulders down and back before bending your elbows to pull up. 
Pull-ups target your back muscles primarily, specifically your lats, but also your chest and shoulder muscles. Compared to a chin-up, pull-ups better engage the lower trapezius muscles in your back, between your shoulder blades. 
The overhand grip of the pull-up improves posterior chain activation, says Sobuta. Posterior chain refers to the muscles on the back side of your body, which are key for everyday movements.
“Overhead athletes, such as pitchers and volleyball players, may benefit more from the pull-up due to overuse of the biceps and pectorals during sport,” says Sobuta. “By training the posterior chain over the anterior chain, this may assist them long-term with preventing injury and improving overall shoulder health.”
Chin-ups and pull-ups are both powerful strength moves that use your entire body weight. The main differences come down to slight variations in position and preference. Ultimately, both are great ways to work your entire upper body and engage your core. 

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Pro Bodybuilder Victor Martinez Is Now a US Citizen – BarBend

 
IFBB Professional Bodybuilder Victor Martinez has won several titles in the course of his near two decade career, but on December 11 he added another one that has nothing to do with bodybuilding: United States Citizen.

Only thank you and gratitude to @sal.nyc esq for walking into my gym a long time ago and saying if you don’t change this plead in your case you will never be a citizen. To George Crimarco esq and his staff @mellienbrax and Cristiane Laurenco in #miami , a judge can want to kick you out of the country, but they must follow the rule of law that says otherwise for the rights of citizens and immigrants alike. Sorry for driving you guys nuts @mellienbrax .Thank you. To Kieth and Abby Gordon on getting me Crimarco law. Thank you. To @schwarzenegger thank you for looking out and writing me that letter to the judge and everyone else who did @cristianriverafoundation . Thank you.To Gerard Dente and Steve Blechman for holding me down during hard ass times. To @timalexesq and @paula_zwiren esq for the visits and helping me fight the long fight. To my family, especially my brothers and sisters,for always being in suspense and pulling hairs waiting to see what’s next for me. To all the good immigrants on lockdown with me ,hope you guys won your cases. To all the cool customs agents that always rooted for me. To my wife @normacarrasquilla I love you. To @no cnewsonlineofficialpage and @ifbb_pro_league for standing by me. My trainer @victormunoz_proedge “For a green card I cut him up real nice”-Scarface. To my all my beautiful kids ,how can I quit when I have you counting on me? Can’t get rid of me now..Never! My friends you know who you are ..And last ,but definitely not least my fans thank you. Dominican Dominator for life. Now I go train. #legalalien #citizenvic #dominican #american 🇺🇸🇩🇴
A post shared by Victor Martinez (@dominicandominator) on Dec 11, 2019 at 5:03pm PST

The 2007 Arnold Classic winner shared the news on his Instagram page for his 612,000 followers to see. Martinez has had a history of issues regarding his residency and visa in the United States, so for him, this was certainly a noteworthy development.
At the turn of the century, Martinez was considered an athlete that had a lot of potential to take over the sport. Many of his supporters felt that praise was validated when he won the NPC Nationals championship in 2000 to earn his pro status.
He won his first contest in 2003, which was the Night of Champions (now known as the New York Pro). He faced his first of several legal problems later on that year when he was convicted of selling anabolic steroids and had to serve 90 days in jail.   
Upon his release in 2004, he resumed his career and won the Show of Strength show. He also placed 9th in the Mr. Olympia that year. He would continue to rise in the pro ranks until 2007 which would be his pinnacle year in the sport. He won the Arnold Classic that year and six months later placed a very controversial second place at the Mr. Olympia to champion Jay Cutler. Many fans and experts believed Martinez was in better shape than Cutler and deserved the championship.
The next major title Martinez would win would be the Arnold Classic Europe in 2011, but he also faced another major legal issue while returning to the United States from that contest. He would be met at the airport by officers because his permanent resident card had expired and his past steroid case (a felony) was on his record. So he was detained and held in jail until a trial took place in April 2012. 
Between that arrest and the trial, Martinez received support from many in the bodybuilding industry, including Arnold Schwarzenegger, who was the Governor of California at the time. He wrote a letter to the judge in support of Martinez. At the trial, the judge determined that Martinez could remain in the U.S. and was released.
The process from this release to citizenship lasted over seven years, but “The Dominican Dominator” now has his citizenship. Praise for Martinez was shared on his post by many notable people including reigning Mr. Olympia Brandon Curry, Kai Greene, and Busta Rhymes. 
At 46 years old, he is in the second half of his bodybuilding career and he may not step onstage again. He hasn’t made any public acknowledgements about future competitions or retirement. His last contest was the 2019 Arnold Classic where he placed 10th. He is still a part of the sport as an ambassador, promoter, and is still active in the gym.
Featured Image: Instagram/ifbbvictormartinez

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Mitochondrial Mysteries Solved by Discovery of Energetic Stress Sensors – Genetic Engineering & Biotechnology News

New research from UVA’s Zhen Yan, PhD, and colleagues reveals how cells sense problems and perform quality control on mitochondria. Yan has spent years seeking to better understand the workings of mitochondria, and he calls the new discovery the most exciting of his career. [Dan Addison/UVA Health]
University of Virginia (UVA) School of Medicine scientists report a major advance in understanding the way our bodies ensure the proper functioning of mitochondria. The findings could open the door to better treatments for many common diseases, including Alzheimer’s and diabetes, according to Zhen Yan, PhD, and colleagues, who describe (“Mitochondria-localized AMPK responds to local energetics and contributes to exercise and energetic stress-induced mitophagy“) in PNAS how cells sense problems and perform quality control on mitochondria.
“Mitochondria are the center of universe to me since literally all cells in our body rely on mitochondria for energy production and must have a bulletproof system to ensure the powerhouses are functioning properly,” said Yan, the director of the Center for Skeletal Muscle Research at UVA’s Robert M. Berne Cardiovascular Research Center. “Chronic diseases, also known as noncommunicable diseases, such as diabetes, heart failure and Alzheimer’s disease that catastrophically impact so many individuals, families and the whole society are caused by problems of the mitochondria in the cells.”
Yan and his team discovered special sensors on the outer membrane surrounding the mitochondria in various tissues in both mice and humans. These sensors detect “energetic stress,” such as that caused by exercise or fasting, and signal for damaged mitochondria to be degraded and removed. This essential cleanup process (mitophagy) and its existence was first suggested more than 100 years ago. But how it works has never been fully understood. Yan’s new research offers long-sought answers.
“Mitochondria form a complex, interconnected reticulum that is maintained through coordination among biogenesis, dynamic fission, and fusion and mitophagy, which are initiated in response to various cues to maintain energetic homeostasis. These cellular events, which make up mitochondrial quality control, act with remarkable spatial precision, but what governs such spatial specificity is poorly understood,” write Yan and his team of investigators.
“…we demonstrate that specific isoforms of the cellular bioenergetic sensor, 5′ AMP-activated protein kinase (AMPKα1/α2/β2/γ1), are localized on the outer mitochondrial membrane, referred to as mitoAMPK, in various tissues in mice and humans. Activation of mitoAMPK varies across the reticulum in response to energetic stress, and inhibition of mitoAMPK activity attenuates exercise-induced mitophagy in skeletal muscle in vivo.
“Discovery of a mitochondrial pool of AMPK and its local importance for mitochondrial quality control underscores the complexity of sensing cellular energetics in vivo that has implications for targeting mitochondrial energetics for disease treatment.”
The researchers found that the mitochondrial sensors (mitoAMPK) exist in slightly different forms in different tissues. For example, one type seemed particularly active in skeletal muscle. In a new scientific paper outlining their findings, the researchers describe the variety of sensors as “unexpectedly complex.” They go on to outline how these sensors provide a vital damage-control system that safeguards our cellular energy supply.
One finding of the study that Yan finds extremely exciting: Treating mice with  metformin, the most effective, first-line anti-diabetes drug, activates mitoAMPK in skeletal muscles without activating AMPK in the other parts of the cells. The finding illustrates the importance of activating mitoAMPK and mitochondrial quality control in treatment of a common chronic disease that is known to be caused by accumulation of dysfunctional mitochondria in our body. It also explains why regular exercise is so powerful in preventing and treating such diseases.
The new insights gained into mitochondrial quality control could boost efforts to develop new treatments for non-communicable diseases that have reached pandemic proportions and are estimated to cause 71% of all deaths.
Yan, who is part of UVA’s Division of Cardiovascular Medicine, says it will be important for doctors to better understand how specific diseases interfere with mitochondrial function. And his new findings set the stage for that.
“We have developed genetic models for pinpointing the key steps of mitoAMPK activation and are on our way to discover the magic molecules that are controlled by mitoAMPK,” notes Yan. “The findings taught us a lot about the beauty of the sensor system in our body. Society should definitely take advantage of these findings to promote regular exercise for health and disease prevention and develop effective exercise-mimetic drugs.”
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Increasing and decreasing interregional brain coupling increases and decreases oscillatory activity in the human brain – pnas.org

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Edited by Peter L. Strick, University of Pittsburgh, Pittsburgh, PA, and approved July 21, 2021 (received for review January 12, 2021)
Oscillatory activity is prominent in the brain, and one hypothesis is that it is, in part, due to the nature of coupling or interaction patterns between brain areas. We tested this hypothesis by manipulating the strength of coupling between two brain regions (ventral premotor cortex, PMv, and motor cortex, M1) in two directions (increase or decrease) while carefully controlling for the impact each manipulation had on activity in each area. We looked at the PMv–M1 connection because it is the major cortical route by which prefrontal cortex might influence, inhibit, and curtail action-related activity in M1. Manipulating PMv–M1 coupling in accordance with Hebbian-like spike-timing–dependent plasticity resulted in changes in beta and theta frequencies linked to action control.
The origins of oscillatory activity in the brain are currently debated, but common to many hypotheses is the notion that they reflect interactions between brain areas. Here, we examine this possibility by manipulating the strength of coupling between two human brain regions, ventral premotor cortex (PMv) and primary motor cortex (M1), and examine the impact on oscillatory activity in the motor system measurable in the electroencephalogram. We either increased or decreased the strength of coupling while holding the impact on each component area in the pathway constant. This was achieved by stimulating PMv and M1 with paired pulses of transcranial magnetic stimulation using two different patterns, only one of which increases the influence exerted by PMv over M1. While the stimulation protocols differed in their temporal patterning, they were comprised of identical numbers of pulses to M1 and PMv. We measured the impact on activity in alpha, beta, and theta bands during a motor task in which participants either made a preprepared action (Go) or withheld it (No-Go). Augmenting cortical connectivity between PMv and M1, by evoking synchronous pre- and postsynaptic activity in the PMv–M1 pathway, enhanced oscillatory beta and theta rhythms in Go and No-Go trials, respectively. Little change was observed in the alpha rhythm. By contrast, diminishing the influence of PMv over M1 decreased oscillatory beta and theta rhythms in Go and No-Go trials, respectively. This suggests that corticocortical communication frequencies in the PMv–M1 pathway can be manipulated following Hebbian spike-timing–dependent plasticity.
The origins of oscillatory activity in the brain are currently an area of active debate, but common to many accounts is the idea that they partly reflect interaction or communication between brain areas (1, 2). Here, we directly test this possibility in the human brain by using manipulations that either increase or decrease the influence of one cortical area, the ventral premotor cortex (PMv), on another cortical area, the primary motor cortex (M1). Importantly we do this by carefully controlling for the impact on each component area when altering the strength of the pathway between them.
The PMv–M1 pathway is an ideal pathway in which to examine the effects of manipulating connection strength; it is well established that PMv exerts a powerful influence over M1 and that changes in connectivity are functionally relevant and correlated with motor control (39). Moreover, the pathway can be examined in humans; by stimulating PMv shortly (6 to 8 ms) before the stimulation of M1, it is possible to influence how activity in M1 evolves (812). Even though the impact of the first pulse in PMv is spatially circumscribed (13), it alters the activity in PMv neurons that project to M1 (3, 4, 6). When this is done repeatedly, the influence that PMv exerts over M1 is strengthened (7, 14, 15). Such a procedure is referred to as paired associative stimulation (PAS) or corticocortical PAS (ccPAS) when, as in this case, the two regions stimulated are areas of cortex. The evoked effects have been described as Hebbian in nature (16, 17, 18). If exactly the same amount of stimulation is applied to the same two areas but in the opposite temporal order, then the influence of PMv over M1 is, instead, diminished (14, 15). These effects have been established by examining changes in the coupling of blood oxygen level–dependent (BOLD) signals in PMv and M1 before and after ccPAS (15). From such experiments, it is clear that the increases and decreases in coupling that result from the two types of ccPAS are prominent between the stimulated areas themselves—PMv and M1—but they also extend to other motor association areas with which PMv and M1 are closely interconnected in the frontal and parietal cortex. The impact of ccPAS can also be visualized by measuring M1 excitability, which can be done by measuring motor-evoked potentials (MEPs) in hand muscles when single pulses of transcranial magnetic stimulation (TMS) are applied to M1 (14, 15). When this is done before and after ccPAS, M1 excitability increases in contexts, such as movement production, in which PMv normally exerts an excitatory influence over M1 (14, 15). Such effects are, however, context dependent, and in other settings in which PMv inhibits M1, it is this inhibitory action that is augmented by ccPAS (14).
CcPAS may, therefore, be an ideal tool for looking at the impact of manipulating coupling between two brain areas; if the effects of two different ccPAS protocols are compared, then it should be possible to establish the effect of increasing or decreasing coupling between the two areas while holding constant the total amount of stimulation to each component area. We therefore examined the impact of either increasing or decreasing PMv–M1 coupling on electroencephalogram (EEG) oscillatory activity while human participants performed a simple Go/No-Go motor task in two blocks (referred to as Baseline and Expression blocks; Fig. 1). In participant group A, we applied 15 min of ccPAS over PMv followed by M1 (PMv–M1-ccPAS; each PMv pulse was followed by an M1 pulse at either 6- or 8-ms interpulse interval [IPI]). Before and after ccPAS, participants performed a Go/No-Go task in which participants responded to “Go” stimuli (blue square) and withheld responses to “No-Go” stimuli (red square). Furthermore, we investigated whether changes in oscillatory activity were dependent on ccPAS stimulation order by reversing the order of ccPAS stimulation (participant group B), that is, applying the first paired pulse over M1 and the second pulse over PMv (Fig. 1). Exactly the same number of pulses were applied to PMv and M1 in both participant groups A and B.
Representation of the set up for groups A and B and individual subject scalp hotspot for rM1 and rPMv. (Top) Experimental design and setup for both experimental groups. The ccPAS period was preceded (Baseline) and followed (Expression) by Go/No-Go task blocks. EEG activity was recorded during the task blocks. (Bottom) Individual subject scalp hotspot (filled circles) and 95% group confidence ellipses for rM1 (red) and rPMv (blue) locations for the main and preliminary experiments in standardized MNI space.
The use of a Go/No-Go task enabled us to look at a range of oscillatory effects in the EEG. Power increases in the beta range, called post-movement beta rebound, are related to activity in M1, and closely interconnected areas as movements are completed and should be observable on Go trials (19, 20). By contrast, activity in the theta range should be prominent on No-Go trials as in other situations that require the reorienting of behavior such as stopping an action from being made (2125). Beta and theta band activity occurs in medial and lateral frontal and centroparietal areas that interact with PMv and adjacent inferior frontal cortex during action inhibition (10, 2628). It is also possible to record activity in the alpha band in the EEG, although task-related modulations of alpha were less anticipated in a Go/No-Go task of this type. Given the difficulty of recording reliable gamma-band activity using EEG, we did not attempt to examine activity at this frequency.
In experimental groups A (n = 16) and B (n = 17), we investigated, respectively, whether increasing or decreasing coupling across motor and motor association areas led to modulation of either fast (transient) or slow (sustained) EEG oscillatory dynamics associated with action control. We contrasted the effects of the two types of ccPAS, repeated paired stimulation of PMv followed by M1 (group A) or, vice versa, M1 followed by PMv (group B) on time-frequency oscillatory responses (computed as Expression–Baseline block separately for Go and No-Go trials), recorded in a simple motor task.
Prior to starting the main experiment, in a preliminary investigation probing M1 excitability, we carried out two initial checks to ensure the effectiveness of the TMS protocol in the context of the current behavioral task (SI Appendix; Fig. S5A). First, we compared MEPs when we applied either single-pulse TMS (spTMS) over right M1 (16, 29) or paired-pulse TMS (ppTMS) over right PMv (conditioning pulse) followed by right M1 (8, 9, 14, 15). We recorded MEPs from the left first dorsal interosseus (FDI) muscle while participants performed Go trials in the Go/No-Go task. We demonstrated that PMv TMS did indeed alter the impact of M1 pulses on Go trials, confirming that the paired pulse procedure allowed us to probe the PMv–M1 pathway (SI Appendix; Fig. S5B). Second, we examined the impact of repeatedly inducing PMv activity either just before or just after inducing M1 activity during ccPAS. Again, we did this by measuring MEPs recorded in response to single pulses of M1 TMS on Go trials, but we did so before and after a 15-min period of ccPAS. Here, we demonstrated that we could manipulate the pathway’s connectivity; the two ccPAS protocols used in groups A and B did indeed exert distinct effects on Go trials. While PMv–M1-ccPAS significantly enhanced the cortical excitability of M1 in Go trials, this M1 excitability remained the same after M1–PMv-ccPAS (SI Appendix; Fig. S5C).
Next, we examined the impact of the ccPAS in the EEG in groups A and B. We first compared the two groups of participants in the two groups before examining the changes occurring in each group in more detail. We focused on motor-relevant frequency bands theta, alpha, and beta (4 to 30 Hz) in frontocentral and centroparietal electrodes (EEG Recording and Analysis) known to reflect top-down control of motor processes likely to be relevant for performance of the Go/No-Go task (1922, 30, 31). Because ccPAS can affect the motor system both ipsilaterally (14) and contralaterally (10), we examined a bilateral group of electrodes spanning both hemispheres.
We used cluster-based nonparametric permutation analysis procedures for identifying statistically significant clusters in the time, frequency, and spatial domain (EEG Recording and Analysis) (3234). This revealed that ccPAS had a significant impact on motor-related beta and theta bands but little impact on the alpha band. Moreover, ccPAS effects significantly differed for Go and No-Go trials, and they diverged between the two participant groups (group A versus B—see Materials and Methods for a detailed explanation of analysis procedure). The significant effects of ccPAS were identified by the cluster-based permutation test as occurring in frequency bands typically regarded as being within the beta band range (19 to 24 Hz; Monte Carlo P value = 0.018) and within the theta band range (4 to 10 Hz; Monte Carlo P value = 0.008) between 0.15 and 1.2 s after the Go/No-Go stimulus onset.
Following these results, we contrasted the ccPAS effect, testing the difference across the two participant groups, for Go and No-Go trials separately, by subtracting EEG responses recorded at Baseline from Expression and contrasting this difference across groups (group A versus B) in the two types of trials. In the beta band, post hoc between-subject Student’s t tests showed that the PMv–M1-ccPAS in group A led to an increase in beta synchronization only for Go trials (0.7 to 1.2 s after “Go” stimulus onset, consistent with the time of the post-movement beta rebound, PMBR) in the Expression versus the Baseline block. However, the opposite effects were found in Go trials when the ccPAS order was reversed in group B (Monte Carlo P value = 0.002, Fig. 2 A, Left). Note that, as we describe below, these differences could not be an indirect consequence of changes in reaction time because no changes in reaction time were apparent (SI Appendix, Table S2 and Behavioral Results). No significant differences in the beta band were observed for No-Go trials in the between-subject Student’s t test analyses (Monte Carlo P value > 0.05) (Fig. 2 A, Right). In addition, we contrasted the ccPAS effects on beta activity recorded in the Baseline versus the Expression block for Go and No-Go trials separately for group A and B. The results of this within-subject Student’s t test analysis revealed a late increase in beta synchronization after (versus before) PMv–M1-ccPAS for Go trials only (0.9 to 1.2 s after Go stimulus onset; Monte Carlo P value = 0.002, SI Appendix, Fig. S1, Left). By contrast, when the ccPAS order was reversed, changes in beta power were only observed in No-Go trials; beta responses first decreased before increasing in a later time window (0.3 to 1.1 s after No-Go stimulus onset; Monte Carlo P value = 0.0009, SI Appendix, Fig. S1, Right). No significant differences were seen in the beta band when comparing Baseline and Expression blocks for No-Go trials in group A, PMv–M1-ccPAS, nor for Go trials in group B, M1–PMv-ccPAS (Monte Carlo P value > 0.05). Furthermore, control analysis confirmed that the beta changes after the ccPAS manipulation in Go trials were not driven by group differences at baseline. Additional details of the results (mainly the data for each condition as opposed to the contrasts between conditions) and control analysis are shown in SI Appendix, Fig. S1 and SI Appendix.
EEG time-frequency responses in the beta band in frontocentral sites for Go and No-Go trials (n = 33). (A and B) EEG time-frequency responses (TFR) in the beta band (15 30 Hz) in frontocentral sites (C4, CZ, FC2, CP2, FCZ, C1, C2, FC4, CP4, and CPz; electrodes highlighted in white in Top Right topoplot) time locked to the onset of the Go/No-Go stimuli, computed as (A) the difference between Expression and Baseline blocks, (B) the mean of Baseline and Expression blocks collapsing across groups A + B. While B shows the PMBR effect was especially prominent in the Go trials, A illustrates how this changed as a function of the two types of ccPAS used in groups A and B. The dashed red square in A indicates the time window (0.7 to 1.2 s) in which significant modulation in beta responses after ccPAS were found. Dashed red line in B indicates the mean RT across Baseline and Expression for Go trials in both participant groups (mean = 352.36 s). (C) Mean beta frequency increase (PMv – M1 ccPAS) and decrease (M1 − PMv ccPAS) computed as the difference between Expression and Baseline in Go trials in the 0.7- to 1.2-s time window. Error bars represent SEM, single dots represent individual data points. In A, EEG TFR represent percentage change in power computed by subtracting the Baseline from the Expression block (0 = no percentage change). In C, EEG TFR represent relative percentage change in power with respect to the prestimulus interval (1 = no percentage change).
The PMBR may reflect a short-lasting state of deactivation or “resetting” of premotor–motor networks after movement completion (35). The increased PMBR observed in Go trials during Expression may reflect an augmentation of active inhibition from PMv over M1 following strengthening of PMv’s influence over M1 through ccPAS. The projections from PMv to M1 are excitatory, but many of these projections are onto inhibitory interneurons in M1 (36). Thus, PMv exerts both inhibitory and facilitatory influences over M1, and both of these influences can be augmented by PMv–M1-ccPAS (14). Moreover, the observation of the opposite effects on beta synchronization on Go trials, when reversing the order of the ccPAS stimulation in group B, are in line with previous evidence showing contrasting effects of reversed versus forward order ccPAS on M1 cortical excitability as well as on functional connectivity in motor networks (14, 15).
While the PMv–M1-ccPAS effects in the beta frequency occurred on Go trials, the theta effects occurred in No-Go trials in both groups. In No-Go trials, post hoc Student’s t test analyses revealed that PMv-M1-ccPAS in group A led to a significant increase in theta power, whereas theta power decreased after reversed-order M1–PMv-ccPAS in group B (Monte Carlo P value = 0.002; 0.15 to 1.2 s after stimuli onset) (Fig. 3). In the same vein, the results of the post hoc within-subjects Student’s t test analysis contrasting the ccPAS effects on theta activity between Baseline and Expression blocks revealed that the PMv-M1-ccPAS in group A led to a late increase of theta activation in No-Go trials (0.8 to 1.2 s after No-Go stimulus onset; Monte Carlo P value = 0.0009, SI Appendix, Fig. S2, Top Right), whereas the opposite effects in early theta activation were observed for No-Go trials after reversing ccPAS in group B (0.15 to 0.65 s after No-Go stimulus onset; Monte Carlo P value = 0.001, SI Appendix, Fig. S2, Bottom Right). Several findings have linked increased theta power in midfrontal regions to top-down executive control and action reprogramming during response conflict and motor inhibition, for example, after a No-Go command (21, 22). Notably, theta oscillatory changes increase with the level of response conflict, reflecting a larger top-down influence over motor circuits (31). It is clear that the inhibition of a specific action is associated with a series of interactions between medial frontal cortex areas such as the presupplementary motor area and PMv and possibly immediately adjacent tissue in the posterior inferior frontal cortex (10, 26, 27). Therefore, the increased theta power in No-Go trials after PMv–M1-ccPAS observed in experimental group A suggests augmentation of oscillatory activity associated with top-down motor control in response conflict, whereas the reversed-order M1–PMv-ccPAS suggests diminution of the same oscillatory activity in the same No-Go trials in experimental group B. No ccPAS effects on theta power were found in Go trials (Monte Carlo P value > 0.05) (Fig. 3). Moreover, control analysis confirmed that the theta changes after the ccPAS manipulation in No-Go trials were not driven by group differences at baseline. Further details of the results (mainly the data for each condition) and control analysis are shown in SI Appendix, Fig. S2 and SI Appendix.
EEG time-frequency responses in the theta band in frontocentral sites for Go and No-Go trials (n = 33). (A and B) EEG time-frequency responses in the theta band (4 to 15 Hz) in frontocentral sites (C3, C4, CZ, FC1, FC2, FCZ, C1, C2, FC3, FC4, CP4, and CPZ; electrodes highlighted in white in Top Left topoplot) time locked to the onset of the Go/No-Go stimuli, computed as (A) the difference between Expression and Baseline blocks, (B) the mean of Baseline and Expression blocks collapsing across groups A + B. While B shows the theta effect that was especially prominent in the No-Go trials, A illustrates how this changed as a function of the two types of ccPAS used in groups A and B. The dashed red square in A indicates the time window (0.15 to 1.2 s) in which a significant modulation in theta responses after ccPAS was found. The dashed red line in B indicates the mean RT across Baseline and Expression for Go trials in both participant groups (mean = 352.36 s). (C) Mean theta frequency increase (PMv – M1 ccPAS) and decrease (M1 − PMv ccPAS) computed as the difference between Expression and Baseline in No-Go trials in the 0.15- to 1.2-s time window. Error bars represent SEM, single dots represent individual data points. In A, EEG time-frequency responses represent percentage change in power computed by subtracting the Baseline from the Expression block (0 = no percentage change). In C, EEG time-frequency responses represent relative percentage change in power with respect to the prestimulus interval (1 = no percentage change).
We performed additional analyses to investigate the effects of ccPAS on nonstate-dependent oscillatory responses irrespective of motor state (i.e., collapsing across Go and No-Go trials). When contrasting the effects of PMv–M1-ccPAS in group A versus reversed M1–PMv-ccPAS in group B on cortical entrained motor activity (computed as the “Expression-minus-Baseline” difference), we found a lack of significant differences between the ccPAS manipulations (Monte Carlo P value > 0.05). This lack of difference between group A and B suggest that the direction of the stimulation, that is, PMv to M1 versus M1 to PMv, is ultimately driving the state-dependent effects observed in Go and No-Go trials. Furthermore, we investigated the absolute effect of PMv–M1- and reversed M1–PMv-ccPAS on activity recorded in Baseline versus Expression blocks. The analyses revealed that the ccPAS manipulation had a significant impact on motor-related theta, alpha, and beta (PMv–M1-ccPAS: 0.25 to 1.2 s after stimulus onset; 4 to 15 Hz; Monte Carlo P value = 0.004; M1–PMv-ccPAS: 0.25 to 1.1 s after stimulus onset; 9.9 to 14 Hz; Monte Carlo P value = 0.008; channels: C3, C4, CZ, FC1, FC2, CP1, CP2, FCZ, C1, C2, FC3, FC4, CP3, CP4, and CPZ). These results corroborate the absolute effect of the ccPAS manipulation on nonstate-dependent activations.
Oscillatory signals can reflect both transient, evoked activity and sustained, induced neural oscillations. Evoked responses are phase locked to external stimuli, whereas induced oscillations are not. PMv–M1-ccPAS manipulation led to long-latency oscillatory changes, whereas the reverse order led to frequency changes with an early onset. Thus, it is possible that these beta and theta modulations occurring after ccPAS reflect changes in either one or other neurophysiological mechanism or even a mixture of both mechanisms. In order to understand the nature of the ccPAS modulations, we carried out an analysis to identify any evoked oscillatory effects by computing the phase coherence across trials (i.e., intertrial linear coherence—ITLC) for each condition. First, we determined which parts of the Go/No-Go cue-related activity were evoked or sustained regardless of ccPAS. We observed phase coherence across all frequencies tested (4 to 30 Hz; Monte Carlo P value = 0.001) from 0.15 to 1.2 s after stimulus onset, but this was particularly obvious in the theta range during an early short-lived period around 0.3 s after stimulus presentation (SI Appendix, Fig. S3–yellow area in Right). In comparison to Go trials, No-Go trials were associated with stronger, transient, evoked activity in the theta band accompanied by milder sustained changes in alpha and beta activity (SI Appendix, Fig. S3—ITLC for all conditions tested). This analysis shows that some EEG changes are likely to be evoked responses that are phase locked to external stimuli even if later effects were likely to reflect induced oscillatory activity. We, therefore, next examined the impact of ccPAS to determine whether it affected only one type of activity or the other. We found that it modulated the amplitude of both early-evoked components as well as sustained changes of the theta oscillations in No-Go trials (Fig. 3 A, Right, dashed red line) and sustained changes in beta oscillations in Go trials (Fig. 2 A, Left, dashed red area). However, it did not modulate the phase consistency either in the theta or the beta band (SI Appendix, Fig. S3, comparable phase coherence between Baseline and Expression, before and after ccPAS, for Go/No-Go trials; Monte Carlo P value > 0.05). In summary, it is clear that the effects of ccPAS are not limited to an impact on evoked neural activity but include a clear effect on induced neural oscillations in both beta and theta bands. In the same vein, there were no significant differences in ccPAS effects on event-related potential (ERP) data between group A and B (EEG Recording and Analysis and SI Appendix, Fig. S4).
The application of TMS pulses to PMv prior to TMS pulses to M1 evoke synchronous pre- and postsynaptic activity in the PMv-to-M1 pathway and alters the manner in which activity in M1 evolves (812, 3739). Moreover, repeated paired stimulation of PMv followed by M1, PMv–M1-ccPAS leads to a subsequent state-dependent augmentation of PMv’s influence over M1 expressed during action control (7, 14, 15). However, the same effects are not observed when M1 is stimulated prior to PMv in M1–PMv-ccPAS, and instead, such a protocol may even lead to a reduced influence of PMv over M1. These observations were replicated in the context of the current task (SI Appendix, Fig. S5). This means that ccPAS can be used to increase the interactions between two brain areas in order to examine the impact of connectivity change on oscillatory activity associated with the motor system. Importantly, the control ccPAS procedure, M1–PMv-ccPAS, comprises the same amount and intensity of both PMv and M1 stimulation as PMv–M1-ccPAS, and thus, it has the same impact on the component elements of the PMv–M1 circuit, but because of its different temporal patterning, it is associated with no augmentation of the influence of PMv over M1. This means that any change in oscillatory activity that is induced by PMv–M1-ccPAS that is not present with, or reversed with, M1–PMv-ccPAS cannot be attributed to the activation of either PMv or M1 but only to the manipulation of the connectivity between them.
Our results demonstrate that ccPAS delivered at rest leads to task-related changes in beta and theta oscillatory activity during action control. PMv–M1-ccPAS led to increased beta power in the PMBR in Go trials. Decreases and increases in beta frequency oscillations have, respectively, been linked to action initiation and cessation (40, 41), and the route between right PMv and adjacent inferior frontal cortex and M1 has been linked to both action initiation and inhibition (10, 11, 14, 26). In addition, PMv–M1-ccPAS led to increased theta power when there was greater demand for motor control in No-Go trials. While the changes occurred principally in the theta band, the fact that they occurred between 4 to 10 Hz meant that they extended into the low alpha band. Theta band activity occurs in medial and lateral frontal areas that interact with PMv and the adjacent inferior frontal cortex during action inhibition (10, 21, 22, 26, 27). These areas include the pre–supplementary motor area in the dorsal frontomedial cortex, PMv, the immediately adjacent cortex in the inferior frontal cortex, and M1 (10, 26, 27). It is increasingly clear that neurons concerned with the control of hand movements are present not just in PMv itself but in the inferior frontal cortex anterior to PMv (42) and that PMv receives a strong monosynaptic projection from many parts of prefrontal cortex including inferior frontal regions (43, 44).
By contrast, the opposite beta and theta patterns were seen after reversed-order M1–PMv stimulation in group B. The reversed-order M1–PMv stimulation protocol is unlikely to lead to simultaneous pre- and postsynaptic activity in the PMv–M1 pathway; as a result, connectivity in the pathway should either remain constant or, more likely, decrease (14, 15). More generally, according to the principles of Hebbian-like spike timing–dependent plasticity (16), the firing of presynaptic cells before postsynaptic cells leads to long-term potentiation, whereas the firing of postsynaptic activity before presynaptic activity usually induces long-term depression. In tandem, results from group A and B demonstrate that it is possible to entrain the cortical oscillatory dynamics of action control by repeated stimulation of a directed projection in a specific motor circuit. They also suggest that transmission of causal influences between PMv and M1 is linked to state-dependent channels of communication tuned to specific frequencies, specifically, the beta rhythm for action initiation and cessation on Go trials and the theta rhythm for action inhibition on No-Go trials. Different cortical rhythms in the beta and theta range are associated with distinct functional roles in motor control and inhibition (23, 25).
PMv–M1-ccPAS selectively modulated induced beta oscillatory activity at the time of movement completion (there was no evidence for stimulus-locked evoked beta responses). This suggests that PMv exerts an influence over M1 that is associated with resonant activity in the beta range (19, 20). In contrast, reversed-order M1–PMv-ccPAS led to moderate PMBR reductions. Although there are strong projections from PMv to M1, projections from M1 to PMv also exist (43). The moderate decrease of PMBR after M1–PMv-ccPAS may, therefore, reflect not just a reduction in influence exerted by PMv over M1 but a change in the projections in the opposite direction. Interestingly, the beta band effects of ccPAS were most apparent at the time of increased synchronization when movements were completed rather than at the time of desynchronization when movements were being initiated. Similar to neurons in M1, neurons in PMv also project directly to the spinal cord (45). Therefore, the increased synchronization at the time of movement completion may reflect not only plasticity changes in the motor cortex but also changes on the descending projections to the spinal cord. Future studies should investigate the potential premotor origin of these PMBR after the ccPAS manipulation. In addition to induced neural oscillations in the beta range, it is possible that ccPAS also affects short-lasting beta-burst activity only visible on single trials during movement initiation (46). Further research in the future might investigate the effects of ccPAS on the trial-to-trial dynamics of action control.
Theta band power increases have been suggested as spectral fingerprints of top-down executive control (2125, 30, 31, 47). Here, we observed increased theta oscillations in No-Go trials after PMv–M1-ccPAS, suggesting greater top-down motor control during response conflict as a result of entrainment of PMv–M1 connections. Opposite effects on theta oscillations are observed after reversed-order M1–PMv-ccPAS, suggesting decreased executive control over motor output. Notably, while the ccPAS may cause some changes in early-evoked and later-induced theta activity (Fig. 3), these modulations cannot be explained by changes in phase-locked responses (SI Appendix, Fig. S3) or in ERP components (SI Appendix, Fig. S4). Instead, the ccPAS appears to affect the amplitude of oscillatory activity linked to response inhibition. The results are also consistent with previous investigations emphasizing theta oscillatory activity in integrative mechanisms and as mediators of information transfer between prefrontal and motor areas in decision-making and action control (2325).
Given the clear influence of ccPAS on beta and theta oscillations during action performance and inhibition, changes in task performance might, therefore, also have been expected. Changes in task performance after ccPAS have been reported in both the visual and motor system (7, 48). Despite conducting a number of analyses (Behavioral Analysis), we were unable to find robust evidence for such changes in the current study (SI Appendix, Behavioral Results). The task was chosen for its simplicity, and it is possible that ccPAS-induced changes in performance might only have been seen in more demanding tasks as has been previously reported (7). Another possibility is that the effects of the ccPAS manipulation on behavior might not be most apparent immediately after the stimulation. Further future studies should investigate the possibility of longer-term influence of ccPAS on either speed or accuracy rates. As it stands, however, the oscillatory changes induced by ccPAS in the current setting can be interpreted as a direct result of the ccPAS rather than a secondary consequence of ccPAS-induced changes in task performance. The current findings complement previous evidence of oscillatory changes at rest after ccPAS (49) and of selective enhancement of functional specific pathways outside the PMv–M1 network (50)
It is notable that the ccPAS procedure induced a suite of changes that were apparent at several different points in time after Go and No-Go cues. The modulatory effect of ccPAS on a beta oscillatory activity and theta oscillatory were apparent 700 and 150 ms after Go and No-Go stimuli, respectively, approximately during the same period when beta and theta oscillations appeared most robustly in the baseline state in our study (Figs. 2 and 3). The ccPAS also produced changes in MEPs following application of spTMS to M1 125 ms after Go cues (SI Appendix, Fig. S5C). The 125-ms time point was examined because it is close to times at which PMv has been shown to influence M1 in previous studies (10, 11, 37), but it is possible that additional effects might have been observed had we tested other time points after the Go cue.
In summary, corticocortical communication frequencies in the human PMv–M1 pathway can be manipulated, leading to state-dependent changes during action control. The frequency-specific patterns of oscillatory activity change found after different types of ccPAS on Go versus No-Go trials reflects spectral fingerprints of augmentation versus reduction of top-down PMv influence over M1. The patterns are consistent with Hebbian-like (16) spike timing–dependent long-term potentiation and depression and with hierarchical models of action control in which top-down motor control occurs in tandem with oscillations with specific resonant properties in the beta and theta frequency ranges (23, 25).
A total of 36 healthy, right-handed adults participated across the two experimental groups. Three participants were excluded due to excessive noise in the EEG signal, resulting in 33 participants—16 in group A (23.75 ± 4.59; 10; 0.81 ± 0.17) and 17 in group B (22.64 ± 2.31; 5; 0.93 ± 0.13) (where numbers correspond to mean age ± SD; number of female participants, handiness mean ± SD; as measured by the Edinburgh handedness inventory, adapted from ref. 51). All participants had no personal or familial history of neurological or psychiatric disease, were right handed (except for one participant—handiness score 0.045), were screened for adverse reactions to TMS and risk factors by means of a safety questionnaire, and received monetary compensation for their participation. Participants underwent high-resolution, T1-weighted structural MRI scans. Sample sizes were determined based on previous studies that have used the same ccPAS protocol to measure the influence of PMv over M1 cortical excitability (14, 15) and studies that have used the Go/No-Go paradigm to investigate oscillatory responses during action control in humans. All participants gave written informed consent, and all the experimental procedures were approved by the Medical Science Interdivisional Research Ethics Committee (Oxford, No. R29477/RE004).
Both experimental groups started with a Baseline block, followed by a ccPAS period, and an Expression block (Fig. 1). During Baseline and Expression blocks, participants performed a visual Go/No-Go task. Trials started with the presentation of either a blue (Go trials—70% of trials) or a red (No-Go trials) square (1.8 × 1.8 cm) displayed for 500 ms. These were followed by a yellow fixation cross (1.3 × 1.3 cm) presented centrally on the screen for a time interval between 2 and 3 s. There was a total of 304 trials per block (equal number of trials in the Baseline and the Expression blocks) with a short break halfway through the block. Blocks always started with four consecutive Go trials. Participants were instructed to press a button with their left index finger as soon as the blue square was presented and to withhold the response when the red square appeared on the screen. Reaction times and accuracy were recorded. During the task, participants were seated at ∼50 cm from the screen in a sound and electrically shielded booth.
In the two experimental groups, the ccPAS period that intervened between Baseline and Expression blocks consisted of 15 min of ccPAS over PMv and M1 applied at 0.1 Hz (90 total stimulus pairings) with an IPI of either 6 or 8 ms. Both resting-state and task-state interactions between M1 and PMv, and adjacent areas, emerge at 6- to 8-ms intervals (8, 9, 14, 15). Precise interpulse timing is critical if both PMv and M1 pulses are to produce coincident influences on corticospinal activity. Therefore, we employed an IPI of 8 ms when testing half of the participants in group A and in group B and an IPI of 6 ms in the other half of participants in each group. The impact of this difference in the experimental manipulation was tested by a repeated-measures ANOVA with within-subject factors block (Baseline, Expression) and trial type (Go, No-Go), between-subject factor ccPAS order (PMv–M1-ccPAS, M1–PMv-ccPAS), and the IPI (8 ms, 6 ms) as a covariate. No effects of the 6-ms IPI versus 8-ms IPI was seen even when the analysis focused on the time window and frequency bands in which the key effects of ccPAS on neural oscillations had been found (Monte Carlo P values > 0.05). Because these analyses found no effect of the 2-ms difference, we do not consider this difference in IPI further. In the experimental group A, the pulse applied to PMv always preceded the pulse over M1, while the opposite was true in experimental group B, which served as an active control.
ccPAS was applied using two Magstim 200 stimulators, each connected to 50-mm figure eight–shaped coils. The M1 “scalp hotspot” was the scalp location where the TMS stimulation evoked the largest left FDI MEP amplitude. This scalp location was projected onto high-resolution, T1-weighted MRIs of each volunteer’s brain using frameless stereotactic neuronavigation (Brainsight; Rogue Research). In contrast to the scalp hotspot, the right M1 “cortical hotspot” was the mean location in the cortex where the stimulation reached the brain for all participants in Montreal Neurological Institute (MNI) coordinates (X = 41.03 ± 6.59, Y = −16.74 ± 9.35, Z = 63.69 ± 8.20; Fig. 1—cortical coordinates computed using Brainsight stereotactic neuronavigation for each participant; mean cortical coordinates computed by averaging all individual’s cortical coordinates). These coordinates were similar to that reported previously (9, 11, 14, 15). The PMv coil location was determined anatomically as follows. A marker was placed on each individual’s MRI and adjusted with respect to individual sulcal landmarks to a location immediately anterior to the inferior precentral sulcus. The mean MNI cerebral location of the PMv stimulation was at X = 59.66 ± 3.41, Y = 17.07 ± 6.28, Z = 14.85 ± 8.50 (Fig. 1) and lies within the region defined previously as human PMv (rostral part) and the adjacent inferior frontal gyrus (posterior/mid part) (52), more precisely over areas 44d and 44v of the pars opercularis within the inferior frontal gyrus (53), which resembles parts of macaque PMv in cytoarchitecture and connections (54, 55).
Resting motor threshold (RMT) of the right M1 (mean ± SD, 43.13 ± 7.22% stimulator output) was determined as described previously (56). As in previous ccPAS studies (14, 15), PMv TMS was proportional to RMT—110% (47.76 ± 7.35). M1 stimulation intensity during the experiment was set to elicit single-pulse MEPs of ±1 mV (47.23 ± 7.58% stimulator output). TMS coils were positioned tangential to the skull, with the M1 coil angled at ∼45° (handle pointing posteriorly) and the PMv coil at ∼0° relative to the midline (handle pointing anteriorly). The PMv coil was fixed in place with an adjustable metal arm and monitored throughout the experiment. The M1 coil was held by the experimenter. Left FDI electromyography activity was recorded with bipolar surface Ag-AgCl electrode montages. Responses were band-pass filtered between 10 and 1.000 Hz, with additional hardwired 50-Hz notch filtering (CED Humbug), sampled at 5,000 Hz, and recorded using a CED D440-4 amplifier, a CED micro1401 Mk.II A/D converter, and PC running Spike2 (Cambridge Electronic Design). All trials with muscle preactivation between Go/No-Go onset and TMS pulse were offline discarded.
EEG was recorded with sintered Ag/AgCl electrodes from 64 scalp electrodes mounted equidistantly on an elastic electrode cap (64Ch-Standard-BrainCap for TMS with Multitrodes; EasyCap). All electrodes were referenced to the right mastoid and re-referenced to the average reference offline. Continuous EEG was recorded using NuAmps digital amplifiers (Neuroscan, 1000-Hz sampling rate).
Offline EEG analysis was performed using FieldTrip (33). The data were down sampled to 500 Hz and digitally band-pass filtered between 1 to 40 Hz. Bad/missing channels were restored using a FieldTrip-based spline interpolation. Next, the data were segmented into 3.5-s intervals starting from 1.4 s before stimulus onset. This was done for Go and No-Go trials separately, and incorrect trials and trials in which reaction times (RTs) were too slow or too fast (± 2SD) were excluded from the analysis. Automatic artifact rejection was performed excluding trials and channels whose variance (z-scores) across the experimental session exceeded a threshold of 10. This was combined with visual inspection for all participants eliminating large technical and movement-related artifacts. Physiological artifacts such as eye blinks and saccades were corrected by means of independent component analysis (RUNICA, logistic Infomax algorithm) as implemented in the FieldTrip toolbox. Those independent components (7.22 on average across participants; 4.8 SD) whose timing and topography resembled the characteristics of the physiological artifacts were removed. For the ERP analysis, the signal was re-referenced to the arithmetic average of all electrodes, and segments were baseline corrected using an interval from 500 to 100 ms before the stimulus onset.
For the time-frequency analysis, single-subject activations for each block (Baseline, Expression) and trial type (Go, No-Go) were averaged and submitted to a complex multitaper time-frequency transformation from 4 to 30 Hz in steps of 1 Hz, with a fixed Hanning window of 0.75 s. A relative Baseline normalization was performed using a time window from −1.1 to 0 s in respect to stimulus onset. To estimate the effects of the ccPAS protocol on neural responses of action control in the Go/No-Go task, time-frequency activations time locked to stimulus onset were computed at the group level using a nonparametric randomization test controlling for multiple comparisons (32). Investigations of the neural dynamics of cognitive and motor control processes highlight the functional significance of both low- and high-frequency oscillations in action performance and inhibition. Theta (4 to 8 Hz), alpha (9 to 12 Hz), and beta (13 to 30 Hz) spectrums have all been linked to aspects of action control. Therefore, in the statistical analyses, no frequency bands were selected a priori. Instead, the statistical analyses were performed on all motor-relevant frequency bands (4 to 30 Hz) and across the entire time window in which oscillatory changes associated with motor control have been observed—0.2 to 1.2 s after stimulus onset. Statistical analyses were restricted to 15 electrodes distributed over frontocentral and centroparietal areas, that is, FC3, FC1, FCZ, FC2, FC4, C3, C1, CZ, C2, C4, CP3, CP1, CPZ, CP2, and CP4, where the neural phenomena linked to motor control are typically distributed (5759).
To test if the ccPAS protocol influenced cortical correlates of action control and if this influence happened in a state-dependent manner (Go versus No Go), we used a cluster-based permutation approach as implemented in FieldTrip (see below). Since this method allows the comparison of only two conditions, we first computed the “cortical entrained effect” (calculated by the subtraction of each frequency at each time point of activity recorded in Baseline from the Expression block) for Go and No-Go trials separately. We then calculated the difference of the cortical entrained effect between No-Go trials versus Go trials. Thereafter, we contrasted the “No-Go-minus-Go cortical entrained effect” recorded from the participants that received PMv–M1-ccPAS (group A; n = 16) versus the participants that received reverse-order M1–PMv-ccPAS (group B; n = 17) by means of between-subject nonparametric cluster-based permutation analysis. A nonparametric cluster-based permutation approach is an efficient way of dealing with the multiple comparison problem that prevents biases in preselecting time windows or frequency bands avoiding inflation of type I error rate (32, 60). Time-frequency responses in all conditions are represented in SI Appendix, Fig. S1 (beta band) and SI Appendix, Fig. S2 (theta band). In addition, we used the same cluster-based permutation approach to investigate the effect of ccPAS on all trial types, irrespectively of the motor state (i.e., across Go and No-Go trials), by contrasting activity recorded in the Baseline and Expression period for experimental group A and B.
Subject-wise time-frequency courses were extracted at the selected electrodes and were passed to the statistical analysis procedure in FieldTrip, the details of which are described by Maris and Oostenveld (32). Subject-wise time-frequency courses were compared to identify statistically significant clusters in the time, frequency, and spatial domain using a FieldTrip-based analysis across all time points and frequency bands focusing on frontocentral and centroparietal sites described above (33). FieldTrip uses a nonparametric method (34) to address the multiple comparison problem. T-values of adjacent temporal and frequency points whose P values were less than 0.05 were clustered by adding their t-values, and this cumulative statistic is used for inferential statistics at the cluster level. This procedure, that is, the calculation of t-values at each temporal point followed by clustering of adjacent t-values, was repeated 5,000 times, with randomized swapping and resampling of the subject-wise time-frequency activity before each repetition. This Monte Carlo method results in a nonparametric estimate of the P value representing the statistical significance of the identified cluster.
In addition, to rule out the possibility that changes in oscillatory activity after ccPAS were linked to phase-locked responses to stimulus presentation, we computed the phase coherence across trials (ITLC) for each condition (SI Appendix, Fig. S3). We tested the effects of ccPAS on ITLC, mimicking the cluster-based permutation analysis performed on time-frequency oscillatory responses across all time points and frequency bands focusing on the 15 electrodes distributed over frontocentral and centroparietal areas, that is, FC3, FC1, FCZ, FC2, FC4, C3, C1, CZ, C2, C4, CP3, CP1, CPZ, CP2, and CP4.
For the ERP analysis, single-subject ERPs for each block (Baseline, Expression) and trial type (Go, No-Go) were calculated and used to compute ERP grand averages across subjects (SI Appendix, Fig. S4). The analysis on the ERP data mimicked the time-frequency analysis. In brief, ERP activations time locked to stimulus onset were computed at the group level using a nonparametric randomization test controlling for multiple comparisons (32). To test the effects of ccPAS on ERPs related to action control, we first computed the ccPAS effect on ERPs (by the subtraction of each time point of the trials in the Baseline block from the Expression block) for Go and No-Go trials. We then computed the difference of the ccPAS effect between No-Go and Go trials. Finally, we contrasted the “No-Go-minus-Go ccPAS effect” between the two participant groups (PMv–M1-ccPAS group versus reversed-order PMv–M1-ccPAS group) by means of between-subject nonparametric cluster-based permutation analysis. Statistical analyses were done across the entire time window in which the N2-P3 component typically takes place, this is, 0.2 to 0.6 s (28), and it was restricted to 15 electrodes distributed over frontocentral and centroparietal areas (see above). Subject-wise activation time courses were extracted at the selected electrodes and were passed to the analysis procedure of FieldTrip (32). The cluster-based permutation analysis on the ERP data did not find any significant differences in the cortical entrained effect between the participant groups A and B at any electrode cluster when contrasting either Go or No-Go trials (Monte Carlo P values > 0.05). These results demonstrated that 1) the effects of ccPAS on the PMv–M1 circuit are frequency specific and only affect particular oscillatory bands linked to action control, that is, beta and theta bands, and 2) the changes observed in the slow-frequency band theta cannot be explained by changes in the ERP components. There was, however, a significant difference between Go versus No-Go trials across both groups, confirming that the action control manipulation was effective (Monte Carlo P value = 0.001; electrode sites—C4, C3, CZ, FC1, FC2, CP1, CP2, FCZ, C1, C2, FC3, CP3, CP4, and CPZ; between 0.20 and 0.50 s after stimulus onset; SI Appendix, Fig. S4).
Behavioral performance measures comprised median RTs (excluding trials with RT ± 2SD from the mean, 3.9%) and accuracy (excluding omission errors in Go trials, 5%, and commission errors to No-Go trials, 12%). We tested the effect of the ccPAS protocol on RTs and accuracy measures. A repeated-measures ANOVA using the within-subject factors of block (Baseline, Expression) and trial type (Go, No-Go) and the between-subject factor of ccPAS order (PMv–M1-ccPAS, M1–PMv-ccPAS) was used to analyze the behavioral data of groups A and B. No main effects or interactions in accuracy or reaction time were found (all Ps > 0.05). We also examined if the difference in IPI (6 ms IPI versus 8 ms) influenced RTs and accuracy measures. We used the same ANOVA with the same variables and added the IPI (6 ms IPI versus 8 ms) as a covariate. We did not find an influence of IPI difference on RTs or accuracy (all Ps > 0.05). Moreover, we tested the effects of ccPAS on overall accuracy across all Go and No-Go trials in two Student’s t tests (Baseline versus Expression) separately for group A and B. Again, no effects of ccPAS on overall accuracy was found (all Ps > 0.05)
In addition, we explored the possibility that EEG modulations (computed as the difference between Baseline and Expression blocks for Go and No-Go trials separately) could be linked to participants’ performances (median RT in Go trials and accuracy rates in Go and No-Go trials) at Baseline. No relationship was found between participants’ median RT/accuracy and EEG changes between the Baseline versus Expression blocks neither in group A nor group B (Monte Carlo P value > 0.05). We also tested if undergoing ccPAS influenced the aftereffects of No-Go trials on subsequent Go trials. We found that there were aftereffects of No-Go trials on subsequent Go trials represented by slower median RTs in the Expression versus Baseline period for both experimental groups A and B (F(1,31) = 7.746, P = 0.009, ηp2 = 0.2), possibly due to fatigue.
Anonymized human brain, physiological, and behavioral data have been deposited in Open Science Framework (DOI: 10.17605/OSF.IO/6VTFB) (61).
This study was funded by the Bial Foundation to A.S. (Grant 44/16), John Templeton Foundation Prime Award (15464/ Subaward Ref. SC14), and Wellcome Trust: WT100973AIA to M.F.S.R. We would like to thank Nadescha Trudel for her help in data collection.
Author contributions: A.S. and M.F.S.R. designed research; A.S., K.A., and R.D. performed research; A.S., L.V., M.C.K.-F., and M.F.S.R. contributed new reagents/analytic tools; A.S., L.V., K.A., R.D., and M.C.K.-F. analyzed data; L.V., M.C.K.-F., and M.F.S.R. made comments on the paper; and A.S. and M.F.S.R. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2100652118/-/DCSupplemental.
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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Snap a photo at these amazing murals across the United States – USA Today 10Best

July 13, 2021 // By
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July 13, 2021
Courtney Montague sits in front of the Wynwood Walls mural in MiamiPhoto courtesy of Kelsey Montague
Mural art has a rich history that stretches back thousands of years, with many murals found within ancient Egyptians tombs. Contemporary street art as we know it stemmed from New York City’s graffiti boom that grew significantly in the 1960s and 1970s.
Street art has continued to flourish, and with the wild popularity of social media, a lot of murals are interactive. They’re designed to be posed with and shared on social media. See how many you want to pose with! 
This gorgeous mural is located at the main branch of the New York Public LibraryPhoto courtesy of Kurt Boone
Prolific and gifted mural artist Konstance Patton created this vivid, lovely mural at the main branch of the New York Public Library at 455 5th Avenue. It was completed on November 7, 2020.
Called “Goddezz Sisters June, Meechie and Blue Enjoy Their Favorite Book,” the mural depicts Konstance and her two sisters Kendra Silverman and Kira Patton. They are holding the books that encouraged them to be dreamers. People who come here for a selfie often hold their own favorite books for the photo. 
The Best Friends Roadhouse mural pays tribute to animals who have been special to the sanctuaryPhoto courtesy of Best Friends Roadhouse and Mercantile
The Best Friends Roadhouse and Mercantile features a gorgeous mural by Utah artist Benjamin Wiemeyer. The 300-foot-long mural was made with spray paint and aerosol in the summer of 2019. It spans the rear length of the roadhouse, and it was inspired by special animals from Best Friends Animal Society’s past.
Animals represented on the mural include a dog, a cat, a pig and even a hummingbird. It also features local flora and fauna. 
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Adrian Wilson's Gayte Pride mural is joyousPhoto courtesy of Adrian Wilson
Adrian Wilson‘s Gayte Pride mural was created in June 2021 for Pride month. Located in the NoLita neighborhood of Manhattan at 246 Bowery, it was painted on a long-closed storefront that’s managed by The LISA Project. It celebrates the LGBTQIA2S+ community, and it also serves as a tribute to iconic New York City artist Keith Haring.
Wilson explained to us, “When Keith Haring was dying, he explained that though he knew his physical life was coming to an end, his art would live on forever and inspire others. This mural is proof of that.”
The Lubbock and Sunrise mural inspires a lot of creative selfiesPhoto courtesy of Visit Lubbock
Located at CASP Studios at 1106 5th Street in Lubbock, Texas, this mural depicts a striking sunrise that has inspired many selfies. You may opt to stand right in the center of the sunrise or sit in front of the mural. Either way, the selfie is sure to be radiant and cheerful.
The Charles Adams Studio Project (CASP) is a non-profit organization that’s dedicated to nurturing a working artists’ community in Lubbock.
The Rescue! Adopt! mural helps spread a powerful message to New Yorkers who often pose with itPhoto courtesy of Praxis
Created in June 2021, the Rescue! Adopt! mural by Praxis was created in collaboration with LISA Project NYC. It’s located on Avenue A between 2nd Avenue and 3rd Avenue in Manhattan. The eye-catching, two-part piece is not only beautiful to look at, but it also has a deep meaning. It implores passersby to rescue animals and adopt when they can.
Artist Praxis uses art as a force for social change. People often stand on either side of the mural or in between the pieces for their selfie.
Mary Thiefels and Danijel Matanic created this inspiring mural in Ann ArborPhoto courtesy of Destination Ann Arbor
It would be difficult to find a midwestern city that’s more vibrant and creative than Ann Arbor, Michigan, so this colorful mural seems just perfect for visitors who are eager to snap a special selfie. It’s located on the 10-story tall wall of Courthouse Square at 100 South 4th Avenue.
Called the “Challenge Everything. Create Anything.” mural by its creators Mary Thiefels and Danijel Matanic, it’s an inspiring work of art that’s a bit like peeking into the whirlwind of the creative mind.
The cupcake mural offers a lot of opportunities for fun posesPhoto courtesy of Bunnie Cakes
Located at 8450 NW 53rd Street in Doral, Florida, this cute and endearing mural is located outside the bakery Bunnie Cakes. What’s not to love about the pastel array of sweet treats? They include a rainbow cake, cupcakes and cake slices. Also included in the mural are rainbows, balloons, hearts and geometric designs.
People often stop and show off their aesthetically pleasing treats with a selfie.
Nashville's rainbow mural was created by Kelsey MontaguePhoto courtesy of Courtney Montague
Located at the Publix at 1010 Martin Luther King, Jr. Boulevard, Kelsey Montague’s cheerful rainbow mural was created to honor frontline workers such as grocery store associates. With the artist’s gratitude for how frontline workers kept the United States going throughout the Covid-19 pandemic, this mural was painted on the back, street-facing side of Publix.
The mural embodies a great sense of hope for putting the pandemic in the past, and it serves as a reminder that better days are coming.
A memorial wall mural pays tribute to those who lost their lives from Covid-19Photo courtesy of Courtney Montague
Kelsey Montague created this memorial wall mural to honor the more than 600 residents of Knoxville who died from Covid-19. Each bird in the mural is unique and represents a person who lost their life to the pandemic. After quiet reflection, Kelsey encourages people to stand in front of the mural and appear to be releasing the flock to the heavens.
In the tradition of people turning to art to help them process grief and other complex emotions, the artist created this piece with the hope that it would be cathartic and to honor those who died from Covid-19.
The Finding Tomorrow mural in Richmond, VirginiaPhoto courtesy of Brenda Soque
Located at 511 N. Adams Street in Richmond, Virginia, the Finding Tomorrow mural honors artist Lorna Pinckney. She was a writer, singer, graphic designer and business owner who was dedicated to empowering her fellow writers and artists.
She passed away at the young age of 43, but she’ll “be remembered as a creative visionary force,” according to Richmond Magazine. She elevated the local culture by starting such projects as Tuesday Verses, the city’s enduring, open mic poetry series. This mural was a joint creation of Hamilton Glass and Eli McMullen.
The Save Them mural inspires city dwellers to help save endangered wildlifePhoto courtesy of Praxis
The Save Them mural was created by Praxis at 28 Avenue A in the charming East Village neighborhood of Manhattan. Since it has two panels with equally impactful imagery, people often pose in the middle of the two murals for their selfie. This isn’t just a casual selfie spot, though. It encourages people to respect and take steps to save wildlife each time it’s shared. 
The striking Abraham Lincoln mural is unforgettable.Photo courtesy of VisitLEX
Created by acclaimed Brazilian street artist Eduardo Kobra, the Lincoln mural is a colorful kaleidoscope depiction of the nation’s 16th president. It’s located on the back wall of the Kentucky Theatre at 214 E. Main Street in Lexington, Kentucky. It’s a bit of a meta art piece because it doesn’t just depict Abraham Lincoln; it’s also an artistic rendering of the Lincoln Memorial in Washington, D.C., another presidential work of art.
Lexington is filled with interesting street art. For the past few years, this has been bolstered by VisitLEX’s Mural Challenge which features dozens of street art installations around the city’s downtown area. 
The hotel lobby of the Surfjack Hotel & Swim Club has an impressive muralPhoto courtesy of Surfjack Hotel & Swim Club
The Surfjack Hotel & Swim Club in Honolulu, Hawaii boasts an incredible mural in its lobby. Iconic Hawaii artists Matthew and Roxanne Ortiz go by the artist name of Wooden Wave, and they created this special mural called “Our Treehouse.” It depicts what the hotel might look like if it was a treehouse-style hotel, and the creative imagination of this artist duo is on full display here.
Taking a selfie with this hotel mural is a tradition for plenty of Honolulu travelers. 
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Konstance Patton created a triumph with her mural Goddezz Kendra of Healing and GigglesPhoto courtesy of Konstance Patton
Located at 47 Howard Street in the SoHo neighborhood of Lower Manhattan, the mural Goddezz Kendra of Healing and Giggles was created by Konstance Patton. It depicts her sister Kendra, a physician’s assistant, and the artist observed that, like her sister, the mural was healing and brought a spirit of laughter to the community.
People often take selfies in pairs at this mural, standing on each side of Kendra. 
This mural invites you to step into a secret garden oasisPhoto courtesy of Courtney Montague
Kelsey Montague was honored to have been asked by Goldman Global Arts to create a piece at Wynwood Walls in 2019. This piece is her secret garden and encourages people to step into a hidden oasis. Its swing and door invite each visitor into a colorful, imaginative world that’s fun and quite photogenic for selfies.
You can pose in a variety of ways with the garden, whether you want to sit and take it all in or stop at the swing.
Cache created this cartoon mural with an important messagePhoto courtesy of Cache for PETA
The End Speciesism mural by artist Cache provides animal lovers with a fun photo opportunity. It’s located on the Bob Barker building at PETA in Los Angeles, California.
For decades as the host of “The Price Is Right,” legendary entertainer Bob Barker would sign off by asking viewers to please have their pets spayed or neutered. He educated millions of fans on how to best protect their companion animals and help control the pet population, so it’s fitting that this mural is on the building that’s named in his honor.
This colorful mural has a deep and important meaningPhoto courtesy of Nashville Convention & Visitors Corp.
Music City has a lot of awesome street art. Artist Adrien Saporiti created the Kind Comments mural at 209 3rd Avenue North in Nashville, Tennessee. It was commissioned as part of Instagram’s #KindComments campaign in support of the LGBTQIA2S+ community. 
With its many gorgeous colors, you may be inspired to stare at the piece for a while. This mural honors Pride Month, but it also is a great stop for selfies and solidarity any time of the year. 
Praxis created this mural as part of the Wellington Court Mural ProjectPhoto courtesy of Praxis
The Adopt mural by Praxis is part of the the Wellington Court Mural Project. This impressive and historical community beautification project has been going strong since it started in 2009. Aptly calling itself “a beautiful collective statement of integrating positive social change via the culture of street art,” the Wellington Court Mural Project transformed its neighborhood into one that’s now much sought-after for residents and visitors.
The Adopt mural helps spread the word about the importance of adopting companion animals from shelters.
Kelsey Montague created these muscle arms to offer an interactive fitness muralPhoto courtesy of Courtney Montague
Kelsey Montague‘s Muscle Arms mural makes people smile and want to interact with some fun selfie poses. Whether you’re a fitness buff or simply want a photo that reminds you of your inner strength, this mural is picture-perfect. It’s located at Lululemon in the Garden City Center in Cranston, Rhode Island. 
MISS CHELOVE's mural inspires many people to take selfies with the hotel frontPhoto courtesy of Mike Schwartz Photography
Artist Cita Sadeli, also known as MISS CHELOVE, created this awe-inspiring mural on the exterior of the new Hotel Zena. It can be seen prominently at Thomas Circle in downtown Washington, D.C.
Called the Guardians of the Four Directions, this bold work of art depicts a pair of determined and strong sentinel women warriors. They have come to protect Mother Earth. This four-story mural was created to celebrate female empowerment. 

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Biomedical Engineers Grow 3D Bioprinted Blood Vessel – Texas A&M Today – Texas A&M University Today

 
Vascular diseases such as aneurysms, peripheral artery disease and clots inside blood vessels account for 31% of global deaths. Despite this clinical burden, cardiovascular drug advancements have slowed over the past 20 years. The decrease in cardiovascular therapeutic development is attributed to the lack of efficiency in converting possible treatments into approved methods, specifically due to the discrepancy between studies that take place outside the body compared to inside.
Researchers at Texas A&M University aim to remodel current methodologies to minimize this gap and improve the translatability of these techniques by directing 3D bioprinting toward vascular medicine.
A team in the Department of Biomedical Engineering, led by Akhilesh Gaharwar, associate professor, and Abhishek Jain, assistant professor, has designed a 3D-bioprinted model of a blood vessel that mimics the native vascular function and disease response. Gaharwar is a biomaterials expert and has developed novel bioinks that offer unprecedented biocompatibility and control of mechanical properties needed to print blood vessels, whereas Jain’s expertise lies in creating biomimetic models of vascular and hematological diseases. This interdisciplinary and collaborative project was recently published in the journal Advanced Healthcare Materials.
Bioprinting in 3D is an advanced manufacturing technique capable of producing unique, tissue-shaped constructs in a layer-by-layer fashion with embedded cells, making the arrangement more likely to mirror the native, multicellular makeup of vascular structures. A range of hydrogel bioinks was introduced to design these structures; however, there is a limitation in available bioinks that can mimic the vascular composition of native tissues. Current bioinks lack high printability and are unable to deposit a high density of living cells into complex 3D architectures, making them less effective.
To overcome these shortcomings, Gaharwar and Jain developed a new nanoengineered bioink to print 3D, anatomically accurate, multicellular blood vessels. Their approach offers improved real-time resolution for both macro-structure and tissue-level micro-structure, something that currently is not possible with available bioinks.
“A remarkably unique characteristic of this nanoengineered bioink is that regardless of cell density, it demonstrates a high printability and ability to protect encapsulated cells against high shear forces in the bioprinting process,” Gaharwar said. “Remarkably, 3D-bioprinted cells maintain a healthy phenotype and remain viable for nearly one month postfabrication.”
Leveraging these unique properties, the nanoengineered bioink is printed into 3D cylindrical blood vessels, consisting of living co-cultures of endothelial cells and vascular smooth muscle cells, which provides researchers the opportunity to model vascular function and disease impact.
This 3D-bioprinted vessel provides a potential tool to understand vascular disease pathophysiology and assess therapeutics, toxins or other chemicals in preclinical trials.
Other project collaborators include Dr. John Cooke from the Houston Methodist Research Institute and Javier Jo from the University of Oklahoma. This research is funded through grants from the National Institutes of Health, the National Science Foundation and the Texas A&M President’s Excellence Fund.
This article originally appeared on the College of Engineering website.
Texas A&M researchers are developing biosensors to detect acute kidney injuries, which could help clinicians provide more effective treatment.
The microdevice can be used to observe how cancer cells interact with vascular and blood cells and test novel ways to treat the disease.
Texas A&M research lays the groundwork toward building electrical stimulation implants.
Eight Aggies recount how they did their part in a time of crisis.
A Texas A&M physician says both flu and COVID-19 vaccines are needed.
Texas A&M researchers will lead the hub to minimize the socio-economic impact of hazards to historically underrepresented communities along the Northern Gulf Coast.
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