Monthly Archives: September 2021

How gravitational waves can lead us to the holy grail of modern physics – Aviation Analysis Wing

Posted: September 12, 2021 at 9:49 am

Equipment in the gravitational wave detector Virgo in Italy.Build Lab / Virgo Cooperation

It keeps you grounded, makes apples fall from trees and directs the cosmic dance between celestial bodies like the earth, sun and moon. However, gravity is perhaps the most unfortunate force in modern physics.

In recent decades, the search for the true nature of gravity has been shown to be the holy grail of physics. Whoever truly understands gravity takes a steady step towards a deeper understanding of the reality around us.

Against this background, three prominent theoretical physicists, including Nobel Prize winner Frank Wilczek, have launched a tantalizing new idea. In the prestigious Physics Journal physical review messages They write that the deeper nature of gravity may be hidden in so-called gravitational waves, the vibrations of space and time that arise, among other things, when heavy objects such as black holes collide in the depths of the universe.

Fundamental forces of nature

First take a step back. Physics distinguishes four fundamental forces of nature. In addition to gravity, this is the electromagnetic force responsible for light and electricity, among other things, the strong nuclear force that ensures that atoms do not disintegrate, and the weak interaction that causes heavier particles to decay into lighter ones. grains.

And while the last three may seem esoteric, its these factorsnot the familiar gravitythat physicists understand best. They are described in the so-called Standard Model of particle physics, the mathematical model that captures all the building blocks of reality and the forces associated with them into a formula that fits in a T-shirt or coffee mug.

In this description, each force has a force-carrying particle a boson, in technical terms that makes the force work in practice. As for the electromagnetic force, this is, for example, a photon, a light particle. This is why many physicists believe that gravity must also contain such a boson. And although no one has seen this particle before, it does indeed have a name: the graviton.

In fact, no one doubts that such a graviton really exists, says theoretical physicist Eric Verlinde (University of Amsterdam). But as in science, youll want to see it for a while. This is where Wilczyk and colleagues new paper comes in. According to them, it should be possible to find the signature of gravitons in gravitational waves.

Noise behind the waves

Back to this standard form. Above all, this uses quantum theory, the set of natural laws that describe the crazy behavior of the particle world. Only: a quantum theory of gravity does not exist yet. One of the main reasons is that the level of energy at which the quantum effect on gravity begins to appear is so ridiculously high that this rarely happens in practice. Except for cosmic collisions that make space and time tremble so that you can measure the gravitational waves generated on Earth.

These physicists I myself sometimes work with first author Molek Baric, with whom I discussed this idea before have a very interesting idea: How many gravitons would be present in such gravitational waves and how would you measure them? says Verlind. , who was not directly involved in the research.

In the quantum world, reality at the most complex level is not smooth, but grainy a vibrant environment completely alien to our senses, where particles flash in and out of reality. According to the new article, these quantum fluctuations should cause a characteristic behavior of the graviton whose signature remains in the measured gravitational waves. It has to appear as a distinct kind of noise, Verlind says. If you measure exactly this noise in several detectors at the same time, you can be sure that it is the signal you are looking for.

According to the authors, the signals should be visible in current Ligo gravitational wave detectors, at two locations in the United States, and Virgo in Italy. However, Verlinde has doubts about whether you can make such a difficult measurement. I think there is only a small chance that something like this will work. I think the chance is greater with the planned new generation of gravitational wave detectors, which can be measured more accurately.

He emphasizes that this does not mean that experimenters should not research. If you are spontaneously trying to find these signals, you develop methods that can make measurements with existing detectors more accurate, he says.

A gravitational wave detector tunnel at the Maiden Tower near Pisa, Italy.Colorbox picture

hard evidence

It is very rare to test theoretical ideas about quantum gravity in experiments. Whereas experiences are the cornerstone of our physical knowledge: only when you measure something in the real world do you know for sure that it exists. Thats why Im part of a consortium with Barrick, among others, thinking about measurable signals from quantum gravity, Verlind says. We believe such signals are detectable. More and more people are taking it seriously now. Finding the expected noise behind gravitational waves is a good first step, Verlind says. This will be the first definitive proof that gravity is in fact quantum mechanical, he says.

If so, it is only a matter of time until physicists can finally complete the formula on their cups and T-shirts with an accurate description of gravity.

How gravitational waves can lead us to the holy grail of modern physics - Aviation Analysis Wing

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Controlling the Phase Transition in Superfluid Helium-3 – Physics

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September 8, 2021• Physics 14, 122

Researchers demonstrate that they can suppress the formation of defects that appear in superfluid helium-3 when it undergoes a continuous phase transition, allowing them to influence the form of the systems final phase.

When a system that can be described by the 2D Ising model cools, it transitions from having a paramagnetic phase to having a ferromagnetic one via a continuous phase transition. During such a phase transition, magnetic defects can form in the material, creating a nonuniform final ferromagnetic phase. Juho Rysti of Aalto University, Finland, and colleagues now show that they can suppress the formation of these defects in superfluid helium-3when it undergoes a 3D continuous phase transitionby applying a symmetry-breaking bias field to the material [1]. This technique could also be applied to materials undergoing quantum phase transitions, where the appearance of defects can demolish quantum states prepared by adiabatic evolution.

The high-temperature paramagnetic and low-temperature ferromagnetic phases of the 2D Ising model differ by their symmetry: The paramagnetic phase is symmetricthe phase looks the same if the pointing direction of its spins are simultaneously reversedwhile the two ferromagnetic phases of the model are symmetry broken. As a 2D Ising system cools from its paramagnetic phase to a ferromagnetic one, it has to choose which of the two ferromagnetic phases it will transition to, and the evolution of the system slows down near the critical point as the system tries to make this choice.

This critical slowing down causes different parts of the system to move out of thermal equilibrium with each other, something that allows different parts of the system to make independent choices of their magnetization. If the different parts can communicate with each other, the choices can be coordinated, which is more likely for slower cooling rates. Slower cooling rates thus lead to larger domains of one or other of the ferromagnetic phases, with the size of the domains being quantifiable using the Kibble-Zurek-mechanism theory [24]. That said, after the phase transition occurs, the final ferromagnetic phase of the system is almost never uniform but is rather a mosaic of domains of the two ferromagnetic phases (Fig. 1).

The outcome of the phase transition can be made more uniform by applying a magnetic field to the system. For example, if this field points upward as the system cools, the decision will be biased toward the ferromagnetic phase that has spins pointing up. The bias is ineffective for very fast cooling rates because there is not enough time for the field to leave its imprint on the phase of the system. So how slow should the cooling rate be for the bias to be effective in ensuring a uniform ferromagnetic phase? The answer comes again from a generalization of the Kibble-Zurek-mechanism theory, which predicts that the maximal cooling rate scales with the bias strength [5]. The new experiment from Rysti and colleagues shows that when the cooling rate is slow enough, the final phase of the system is an equilibrium ferromagnetic one without any domainsthe first time that has been seen experimentally.

Rysti and his colleagues study a continuous symmetry-breaking phase transition of superfluid helium-3 [1]. Superfluid helium-3 has more complex magnetic behavior than that of the 2D Ising model: Its spins can point in a continuum of directions rather than just up and down, and they can wind into quantized vortices. The nonequilibrium ferromagnetic phase of superfluid helium-3 is a tangle of such vortices, whose density scales with a power of the cooling rate.

In their experiments, the team investigated this scaling behavior by cooling the superfluid using a 3D cryostat and then detecting the orientation of its spins using nuclear magnetic resonance (NMR) coils. In the space between the NMR coils, where the superfluid helium-3 is held, they placed an array of long, thin columns (they call them solid strands), which trap the superfluids vortices.

The experiment shows that when a bias is applied to the systemthe team use both a magnetic field for the bias and also spin-orbit couplingthe power law relating the density of vortices to the cooling rate can break down. Specifically, Rysti and colleagues find that this breakdown happens when the cooling rate falls below a threshold value that is proportional to a power of the bias, with the exponent of the power law being a combination of the universal critical exponents for the transition. Cooling at rates below this threshold value, they find that the density of vortices decays exponentially with cooling time such that the final phase becomes a uniform, equilibrium one.

The team found that the 1-mT bias that they apply is effective only near the phase transitions critical temperature where the system is most susceptible to small perturbations, and even the tiniest of biases can influence the orientation of the spins. They also found that the transition is adiabatic, and as such, they show that cooling with a bias is an efficient way to achieve an adiabatic transition with a finite cooling rate, something that could allow use of the method for adiabatic quantum state preparation in an adiabatic quantum simulator, for example.

The idea of such a simulator is to evolve a system adiabatically from a simple ground state to a more interesting one that cannot be calculated analytically or with a classical computer. If successfully prepared in a quantum simulator, the properties of such a state could simply be measured. Unfortunately, these two ground states are often different enough that to move the system from one to the other requires that the system goes through a quantum phase transition. That means that any adiabatic simulator must be able to evolve a system that is close to its quantum critical point.

This evolution can be described by a quantum generalization of the Kibble-Zurek-mechanism theory, which predicts that, because of a closing of the energy gap of the system at the quantum critical point, excitation of the system is inevitable [6, 7]. It is predicted, however, that in symmetry-breaking transitions these excitations can be suppressed by applying a bias while the system is crossing the quantum critical point [5]. The bias is too weak to affect the properties of the final ground state but is large enough to prevent excitations that would destroy the ground state. The new demonstration by Rysti and colleagues shows that this should be experimentally possible, opening the door to many future experiments on this topic.

Jacek Dziarmaga is a professor at the Jagiellonian University, Poland, where he also obtained his Ph.D. Dziarmaga studies the dynamics of quantum phase transitions. He also develops tensor network algorithms to simulate time evolution of strongly correlated systems in two dimensions.

Researchers demonstrate lighter, smaller optics and vacuum components for cold-atom experiments that they hope could enable the development of portable quantum technologies. Read More

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Could This 40 Year Old Formula Be The Key To Going Beyond The Standard Model? – Forbes

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The quarks, antiquarks, and gluons of the standard model have a color charge, in addition to all the ... [+] other properties like mass and electric charge that other particles and antiparticles possess. All of these particles, to the best we can tell, are truly point-like, and come in three generations. At higher energies, it is possible that still additional types of particles will exist, but they go beyond the Standard Model's description.

When it comes to the nature of matter in the Universe, the Standard Model describes the known elementary particles perfectly well and without exception, at least so far. There are two classes of fundamental particles:

The fermions come in three generations and are split between the six types of quarks and leptons, while among the bosons, there are no generations, but merely different numbers of them, depending on the nature of the force being mediated. Theres just one boson (the massless photon) for the electromagnetic force, three (the massive W-and-Z bosons) for the weak force, eight (massless gluons), and one (massive) Higgs boson.

All told, the Standard Model provides the framework for all of the known and discovered fundamental particles, but has no way of providing expected values for what masses each particle should possess. In fact, of the fundamental constants needed to describe our Universe, a full 15 of them more than half belong to the rest masses of these particles. And yet, a very simple formula appears to relate many of them to one another, with no explanation as to why. Heres the puzzling story of the Koide formula.

The final results from many different particle accelerator experiments have definitively showed that ... [+] the Z-boson decays to charged leptons about 10% of the time, neutral leptons about 20%, and hadrons (quark-containing particles) about 70% of the time. This is consistent with 3 generations of particles and no other number.

The early 1980s were an extremely successful time for particle physics. The final pieces of the Standard Model had recently been put into place, with the Higgs mechanism, electroweak symmetry breaking, and asymptotic freedom having all been worked out theoretically. On the experimental side, the advent of powerful new colliders had recently revealed the (tau) lepton as well as the charm and bottom quarks, providing empirical evidence for a third generation of particles. With the Main Ring running at Fermilab and the Super Proton Synchrotron collecting the data that would lead to the discovery of the W-and-Z bosons in 1983, the Standard Model was nearing completion.

The quarks are only observable indirectly: as parts of bound states making up mesons (quark-antiquark pairs), baryons (three-quark combinations), and anti-baryons (three-antiquark combinations), requiring a sophisticated theoretical toolkit to extract their rest masses. The leptons, however, are observable directly, and their rest masses were easily reconstructed from the energy and momenta of their decay products. For the three charged leptons, their masses are:

It might appear, on the surface, that theres no relationship between these three masses, but in 1981, physicist Yoshio Koide suggested that there might be one, after all.

A geometrical interpretation of the Koide formula, showing the relative relationship between the ... [+] three particles that obey its particular mathematical relationship. Here, as was its original intent, it's applied to the charged leptons: the electron, muon, and tau particles.

The electron is the lightest charged particle in the Standard Model, and the lightest of all massive particles except for the neutrinos. The muon, its heavier cousin, is identical in terms of electric charge, spin, and numerous other quantum properties, but its mass is ~207 times greater, and its fundamentally unstable, with a mean decay lifetime of ~2.2 microseconds. The tau the third-generation counterpart of the electron and muon is similar but even heavier and shorter lived, with a mass thats about 17 times the muons mass and a mean lifetime of just ~290 femtoseconds, surviving less than one-millionth the amount of time a muon lives for.

No relation, right?

Thats where Koide came in. Perhaps its just a numerical coincidence, but its well known at least, in quantum physics that whenever two particles have identical quantum numbers, theyre going to mix together at some level; youll have a mixed state instead of a pure state. Although this isnt necessarily applicable to the masses of the charged leptons (or any particles at all), its a possibility that might be worth exploring. And its that same mathematical structure that Koide leveraged when he proposed a very simple formula:

which mathematically must lie between and 1. In the case of these charged leptons, it just happens to itself be a simple fraction: , almost exactly.

The Koide formula, as applied to the masses of the charged leptons. Although any three numbers could ... [+] be inserted into the formula, guaranteeing a result between 1/3 and 1, the fact that the result is right in the middle, at 2/3 to the limit of our experimental uncertainties, suggests that there might be something interesting to this relation.

Now, there are many, many relations that one can cook up between various numbers or values that arent actually representative of an underlying relationship, but merely appear as a numerical coincidence. In the early days, people thought the fine-structure constant might be exactly equal to 1/136; a little later, that was revised to 1/137. Today, however, its measured to be 1/137.0359991, and its known to increase in strength at higher energies: up to ~1/128 at electroweak scales. Plenty of suggestive, tantalizing relationships have turned out to be nothing more than coincidences.

And yet, we have precisely measured values for not only the charged leptons, but for each of the quarks as well: the up, down, strange, charm, bottom, and top quarks. The first three are the lightest quarks, the latter three are the heaviest quarks. Using the best data presently available, their masses (shown without uncertainties) are:

Interestingly enough, we can attempt to apply the Koide formula to these six masses in two separate groupings to see what comes out.

The rest masses of the fundamental particles in the Universe determine when and under what ... [+] conditions they can be created, and also describe how they will curve spacetime in General Relativity. The properties of particles, fields, and spacetime are all required to describe the Universe we inhabit.

Remarkably enough, for the up, down, and strange quarks, you get a value of approximately 0.562, which is very close to another simple fraction: 5/9, or 0.55555..., and is allowable within the published uncertainties.

Similarly, we can do a comparable analysis for the charm, bottom, and top quarks together as well, yielding a value of 0.669, which is again very close to a simple fraction of 2/3: 0.666666..., with the exact value, again, allowed within the published uncertainties.

And, if we wanted to be extremely bold, we could move over to the bosons, and check out what the relationship is between the only three massive bosons we have:

Applying the same formula to these three masses yields a value of 0.3362, which appears to be consistent with a simple fraction of 1/3: 0.33333..., which once again seems like a remarkable, almost-perfect coincidence, although in this case, the errors are small enough that the exact relationship cannot be saved.

The particles of the standard model, with masses (in MeV) in the upper right. The Fermions make up ... [+] the left three columns; the bosons populate the right two columns. While all particles have a corresponding antiparticle, only the fermions can be matter or antimatter.

Its important to recognize that these values are only for the pole masses, which is the equivalent of rest mass in relativity. In quantum physics, the only measurements you can make are based on interactions between various quanta, and those interactions always occur at a particular energy thats greater than zero. However, by appropriately applying the correct theoretical techniques, you can disentangle what the pole mass is from the inferred mass that your measurements give you. While the measured masses will change or run with increased energy, the zero-energy limit remains the same.

In fact, although the uncertainties in the measured values of neutrino masses has only yielded constraints on their masses, with everything dependent on the yet-unmeasured particulars of how the various neutrino states mix together, there is reason to believe that there exists some sort of hierarchy between the mass states of the three different types of neutrinos: electron, muon, and tau. Its eminently possible, once those masses can be inferred, that they will also yield an interesting and simple value for the Koide formula.

We haven't yet measured the absolute masses of neutrinos, but we can tell the differences between ... [+] the masses from solar and atmospheric neutrino measurements. A mass scale of around ~0.01 eV appears to fit the data best, and four total parameters (for the mixing matrix) are required to understand neutrino properties. The LSND and MiniBooNe results, however, are incompatible with this simple picture, and should be either confirmed or contradicted in the coming months.

There have also been attempts to extend the Koide formula in various ways, including to all six quarks or leptons simultaneously, with varying successes: you can get a simple relationship for the quarks, but not for the leptons. Others have tried to tease out deeper mathematical relationships that could underpin the rest masses of the fundamental particles, but at this point, these relationships were only knowable after-the-fact, and could not have been used to accurately predict any unknown masses at any point in time.

However, these patterns most definitely persist across applications, from the charged leptons to the light quarks to the heavy quarks to, quite possibly, the massive bosons and the neutrinos as well. It leads to a remarkable question whose answer is not yet known: is the Koide formula something of great importance, and does it provide a hint of some novel structure that might underlie some property of nature that the Standard Model cannot explain? Or, alternatively, is it simply a combination of numerical coincidence (or worse, a near-coincidence) and the human penchant for seeing patterns, even where none exist?

The particles and forces of the Standard Model. Dark matter isn't proven to interact through any of ... [+] the "standard" forces except gravitationally, and is one of many mysteries that the Standard Model cannot account for, along with the matter-antimatter asymmetry, dark energy, and the values of the fundamental constants.

This latter option should be seriously taken into account before we over-invest in this idea. The fine-structure constant is just one example of a numerical relationship that looks promising when you look at it coarsely, but falls apart when you look at things in greater detail. Early attempts at using quark mixing properties to predict the masses of the top quark gave an initial estimate of ~14 GeV/c2 as the mass, whereas its actual mass turned out to be more than 12 times as large as that value.

A little over a decade ago, an attempt was made to use asymptotically safe gravity to predict the mass of the Higgs boson, a few years before it was actually discovered at the Large Hadron Collider. The prediction was astonishingly precise: a mass of ~126 GeV/c2, with an uncertainty of just ~1-2 GeV/c2 in that energy. When the actual discovery was announced, with a value of ~125 GeV/c2, it seemed to vindicate the calculation, but there was a catch: in the intervening time, a number of parameters in the Standard Model were better measured, and that asymptotically safe calculation instead now yielded a value closer to 129-130 GeV/c2. Despite the fact that the original prediction wound up being borne out by experiment, the reasoning behind it no longer holds up.

The first robust, 5-sigma detection of the Higgs boson was announced a few years ago by both the CMS ... [+] and ATLAS collaborations. But the Higgs boson doesn't make a single 'spike' in the data, but rather a spread-out bump, due to its inherent uncertainty in mass. Its mean mass value of 125 GeV/c^2 is a puzzle for theoretical physics, but experimentalists need not worry: it exists, we can create it, and now we can measure and study its properties as well.

This puts us in a particularly precarious position. We have a formula simple in structure that appears to work anywhere from marginally well to extremely well in providing a relationship between a certain fundamental property of matter, rest mass, that cannot be predicted by any theoretical means known today. In many ways, weve reached the limit of the Standard Model of particle physics, as every meaningful prediction that can be extracted from the theory concerning observable quantities has already been teased out.

And yet, the mysterious nature of mass exhibits these approximate relationships. Is there some fundamental reason why the fermions in our Universe come in exactly three copies? Is there a reason why the bosons dont? Is there a reason why the heavy quarks and the charged leptons give the same constant of 2/3 for the Koide formula, but the light quarks are closer to 5/9 and the massive bosons are closer to (but inconsistent with exactly) a value of 1/3? And just what, precisely, are the fundamental masses of the neutrinos, and what sort of hierarchy do they display?

A logarithmic scale showing the masses of the Standard Model's fermions: the quarks and leptons. ... [+] Note the tininess of the neutrino masses. With the latest KATRIN results, the electron neutrino is less than 1 eV in mass, while from data from the early Universe, the sum of all three neutrino masses can be no greater than 0.17 eV. These are our best upper limits for neutrino mass.

By taking the sum of any three numbers, while simultaneously dividing them by the square of the sum of each of their square roots, youll always get a number between 1/3 and 1, without exception. When all three numbers are equal, you get 1/3; if one number is much, much greater than the other two, you get 1. In the Standard Model, we have precisely three generations of fermions. So why is it, then, for both the charged leptons and the three heaviest quarks, that we get a value precisely between those two: of 2/3, while the light quarks give 5/9 and the massive bosons give us a value just a tiny bit larger than 1/3?

At this point, we have no idea. It could all be a simple numerical coincidence, with no rhyme or reason beyond the fact that these values only approximately match the implied correlation. Or, just maybe, its a 40-year-old hint of what might underpin or even take us beyond the Standard Model: a possible mass relation between fundamental particles that the Standard Model itself offers no explanation for. One of the greatest mysteries in physics is why particles have the properties they do. If the Koide formula turns out to be somehow connected to the property of rest mass, we just might have seen an impeccable hint to guide us down the unknown road that lies before us.

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Could This 40 Year Old Formula Be The Key To Going Beyond The Standard Model? - Forbes

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Whats Eating the Universe? Review: A Pocket Guide to the Cosmos – The Wall Street Journal

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As the pandemic ebbed and flowed this summer, we watched the spectacle of billionaires racing to the edge of space. Shortly after reaching an altitude of 53 miles in his rocket plane, Richard Branson heralded the dawn of a new space age, while Jeff Bezoswho flew more than 10 miles higher nine days latersaid he wanted to build a road to space so our kids, and their kids, can build the future. While Mr. Branson dreams of an orbiting hotel, Mr. Bezos of a base on the moon and Elon Musk a colony on Mars, the physicist Paul Davies explores a far wider canvas in his introduction to cosmology, Whats Eating the Universe? This scientific detective story, Mr. Davies tells us, travels from the very edge of time itself, through our own epoch, into the infinite future and weaves together the vastness of space with the innermost recesses of subatomic matter.

Mr. Davies starts with the astonishing discoveries of the 20th century, discoveries now so well established that despite their extraordinary nature they are steadily making the transition into common sense. The universe is 13.8 billion years old, a vast, expanding menagerie of stars complete with exotic beasts such as quasars, supernovas and black holes. In its early history, the universe was hot and densea fact that can be read in the faint remnants that fill the skies. This cosmic microwave background, which was first mapped by the Cosmic Background Explorer satellite in 1990, shows traces of the subtle variations that seeded galaxies, stars and planets. As the missions lead scientist, George Smoot, declared: It was like looking into the face of God.

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Whats Eating the Universe? Review: A Pocket Guide to the Cosmos - The Wall Street Journal

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Interdisciplinarity is not about the humanities aping the sciences – Times Higher Education (THE)

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Nicholas Dirks is by no means the first academic or administrator to learn from their own history, but it is notable that such a senior figure has become the latest.

In his recent article for Times Higher Education, Dirks proffers a goal of disciplinary unification as if nothing had transpired since physical chemist and novelist C. P. Snows anachronistic The Two Cultures and the Scientific Revolution of 1959. Dirks a historian and former chancellor of the University of California, Berkeley ignores numerous inter- and cross-disciplinary collaborations across the arts, humanities, social sciences and natural sciences.

Not that these collaborations have always been celebrated. For decades, regardless of qualifications or research foundations, academics have spoken out loudly for but also against one notion or another of interdisciplinarity. The specific form of interdisciplinarity (or transdisciplinarity, multidisciplinarity and so on) is seldom defined or understood critically, in its historical context, and proponents rarely address each other. But these strong statements revolve around a common trope: the centrality of science as a model either to avoid or, more often, to emulate or imitate.

Science has a long and contradictory allure to humanists and social scientists and a chequered legacy. Following science has an intellectual appeal, but the urge to do so also stems from inaccurate, stereotypical or outdated ideas about sciences status, recognition and funding.

On the one hand, certain models of science contributed to successful developments in many subjects, including social science history, historical demography, new political history and economic history, analytical bibliography, digital humanities, reader-response theories, and much more.

On the other hand, science can be a false and misleading goal/god. This is particularly true when academics imitate an image of science uncritically and outside its historical and intellectual context. Consider these examples.

First is the persisting confusion of interdisciplinarity as rhetoric and metaphor, as opposed to conceptualisation, methodology and analytical practice. For instance, one of the long-standing leaders of the Association for Interdisciplinary Studies, Julie Thompson Klein, conflates interdisciplinarity with a whole roster of related but distinct concepts within the span of several pages in one article in the associations in-house journal. These include integration, transdisciplinary, multidisciplinary, transcendent interdisciplinary, interaction, intersection, relationality and translation, professionalisation, interprofessionalism, expansion, holistic and multilevelled, problem-solving, policy studies and team science. None of these terms is defined, but it is clear that some relate to concepts while others relate to practice.

A second example is quantum social science, a newly minted enthusiasm replete with summer boot camps. Among its contradictions is its misunderstanding of both the historical origins of modern social science at the turn of the 20thcentury and the meaning of the term quantum in the context of the transformative quantum revolution and the shifting subsequent status of quantum physics in that discipline.

So often in the history of the humanities and social sciences, envy of the hard sciences exerts a superficial appeal to academics who suffer from an inferiority complex. This cultural phenomenon is also evident in my own field of literacy studies, with its proliferation of new literacies, such as blogging or podcasting. There, too, science is called into play in a number of the exaggerated claims of the uniqueness and power of each proclaimed new literacy.

Quantum social science, meanwhile, finds a rival in neuroscientific literary criticism. This is another metaphorical not theoretical or analytic misapplication from the sciences. As Deborah G. Rogers wrote last month in a review of Angus Fletchers new book on the topic, When science wags literary criticism, the results are unfortunate...literature becomes a form of psychotherapy that releases oxytocin and cortisol. Reading stimulates neurotransmitters... unfortunately, most of these neurological claims are unsubstantiated and unsupported.

To the contrary, Rogers advocates sound interdisciplinary research and interpretation, alongside knowledgeable interchanges between the humanities and the sciences. She emphasises relevant scholarly research and literary criticism, including cognitive theory-of-mind approaches and reader-response/reception theory.

We exist at a moment of suspended animation. Despite at least two generations of ground-breaking interdisciplinarity that draws on the sciences when relevant, scholars in the humanities and social sciences continue to succumb to the temptation of imitating reductionist and/or outdated conceptions of science without regard to their exemplars current status.

This is faux interdisciplinarity. These professors do not do investigate the basics of their subject and alternative approaches to it. Crooked paths advance without signage or road maps, as if the past half century were absent or if their advocates could not visualise or locate the history.

As for the non-debate over interdisciplinarity versus disciplinarity, the compelling question for our own times is how best they can cooperate and collaborate. This differs in fundamental ways from the much earlier two cultures debates, from which scholars must finally move on.

Harvey J. Graff is professor emeritus of English and history at Ohio State University. He is the author of many books on social history, including Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century (Johns Hopkins University Press, 2015).

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Ministry of Sound celebrates 30th anniversary with trance, UKG and house parties – DJ Mag

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London's Ministry of Sound will celebrate its 30th anniversary with a series of trance, UKG and house parties next weekend.

The iconic Elephant & Castle club, which featured in this year's Top 100 Clubs poll, is celebrating three decades of music on Friday 17th & Saturday 18th September, hosting three parties as part of a marathon weekender.

Kicking things off on Friday night, Part 1 will see trance legend Paul van Dyk perform at the London club, joined by the likes of Aly & Fila, Judge Jules, Tall Paul and Lottie, with SISTER and HD Life curating the Baby Box and Loft line-ups.

Scheduled for Saturday daytime, a UKG special will see DJ Zinc, Matt Jam Lamont, Zed Bias and Heartless Crew take over the main room, joined by DJ Mag UK's July cover star,Todd Edwards, who'll play B2B with Majestic.

The celebrations are set to close out on Saturday evening, with Ministry of Sound favourite Armand van Helden, Groove Armada, Bellaire, Fat Tony and Arielle Free all soundtracking the end of another era for the club.

You can get tickets for the events here.

Earlier this year,Ministry of Sound partnered with sleep and meditation app Calm for a new series of chillout-focused mixes.

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Ministry of Sound celebrates 30th anniversary with trance, UKG and house parties - DJ Mag

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Chle Says Her ‘Have Mercy’ Video Is ‘All About Ass, But In An Artistic Way’ – MTV.com

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The road to Chle Bailey's debut solo single "Have Mercy" was long, arduous, and sometimes even plagued by toxic comments from strangers who refused to let her own her confidence. But with a wildly bold and inventive new video directed by Karena Evans that lets Chle present herself precisely how she wants the world to see her, she's truly arrived.

As she tells MTV News ahead of the debut performance of "Have Mercy" at the 2021 VMAs on Sunday, September 12, executing her vision as she saw it was paramount to the song's rollout. "Men can glorify ass in their videos. I want to do it with this in an artful, really fun, beautiful way," she tells MTV News correspondent Dometi Pongo. "I think it's so great how women can claim ownership of their bodies and not let the world do it. We get to do it in the way that we want to."

In the dizzying clip, a dominating Chle steals every moment of spotlight as she fills the frame in look after look on sorority row, all while a loose narrative of missing men plays throughout. By the end, it's clear she's turning these guys (boys, really) to stone. But the cornerstone of the entire concept resides in simple shots of Chle in front of pink backgrounds.

The visual found its origins in that color, which led to the idea of Greek life, and Chle herself suggested the darker twist of the "modern-day Medusa" tale, epitomized by a series of frightening and erratic choreography by Chle bathed in harsh nightmare lighting.

"I wanted to make it all about ass, but in an artistic way," she says. "I think it's so cool how women have this incredible power. They can leave men in a trance with their bodies and their spirits and the way they carry themselves."

She felt like a different person on set, and throughout her interview, the difference between the protagonist of "Have Mercy" and the gentler Chle we knew are palpable. That said, she's happy to keep the experience of embodying such a confident and sexual persona in her own personal reserves she never knows when she might need to "tap back into" it. Part of her positivity about the shoot comes from the "family vibe" they established thanks to director Evans, her creative lead, Andrew Makadsi, and even a quick cameo from Beyonc's mom, Tina Knowles-Lawson.

"I think it's amazing how Karena gets it because she's a woman, she's a Black woman, and there's some things that I didn't even have to really explain because she knows it by living life," she says. "You get to see the power that we hold within the music video. I felt sexy doing it, but it's also very empowering."

"Have Mercy" will likely appear on Chle's forthcoming debut album, the solid roots of which took hold in 2020. After her and sister Halle embarked on their so-called "backyard tour" for their 2019 album Ungodly Hour, Halle went into production on Disney's The Little Mermaid update. Chle, meanwhile, dove right into her solo music. Of the estimated 100 songs she recorded for possible inclusion, Chle currently has it narrowed down to about 30 and in a streaming era marked by much longer albums, maybe she only has to lose about 10 to make it work.

So far, it seems like it'll span pop and R&B, as both "Have Mercy" and her Chloe x Halle work have. Although, she's teasing that we haven't quite heard what she's fully capable of. "I love how my tone sounds on pop records, which you guys really haven't even heard yet," she says.

What we have heard? "Have Mercy," though we still haven't seen what Chle will do with it when she debuts it live at the VMAs. If the video is any indication of where her head is at now, we're in for a ride. "I'm going to be honest: I'm very scared," she says of the showcase moment. "But I'm really grateful... [to] finally show the world who I am completely."

‘All of a sudden, the room echoed a collective gasp’: Former teacher looks back on 9/11 – The Gardner News

Posted: at 9:48 am

Mike Richard| Special for The Gardner News

It seems as though every generation experiences its own significant day of infamy.

For my parents, it occurred on Dec. 7, 1941, with the bombing of Pearl Harbor and the entrance of the United States into World War II.

For me, it occurred in Dallas on Nov. 22, 1963, with the assassination of President John F. Kennedy.

For my children, it was 9/11; so significant that it needs only those numbers and no other explanation.

Tuesday, Sept. 11, 2001, started out like every other day, early in the school year at Gardner High School. It was crisp and sunny; just a picture-perfect late summer day if there ever was one.

I had a free period and was making my way through the schools main office when the secretaries had the TV monitor tuned to a breaking news story out of New York City.

It seemed as though an airplane had struck the World Trade Center.

My mind quickly flashed back to an event I had read about from 1945, when a B-25 Mitchell bomber flew into the Empire State Building; the pilot misjudging his whereabouts in a heavy fog.

However, if the skies over New York were as bright and clear as those over Gardner, that couldnt have been the cause.

All of a sudden, the room echoed a collective gasp as the TV showed a second airplane crashing into the other Twin Tower.

We quickly realized this was no accident.

The bell ending the second period and heralded the beginning of homeroom which occurred on Tuesdays around 9:30 snapped us back into reality.

Before long, the students were made aware of the terrorist attacks on our country, as news began to filter in about another plane crashing into the Pentagon and a fourth plane downed in a field in Shanksville, Pennsylvania.

As I stood before a room full of freshmen my daughter, Lindsey, among them who were in their second full week of high school, it was nearly impossible to attempt to assuage their emotions of fear and uncertainty.

For generations, students have looked to their teachers in the quest of getting right answers.

I had none.

The rest of the day went by in a blur with a pall cast over the assembled student body who ambled through the school session in a trance-like existence. It was quite impossible to try to get high school kids in my English class to focus on their studies.

No doubt, anyone else who can recall that day and their own experiences in the workplace can relate.

After school, the football team practiced, half-heartedly going the motions in preparation for Friday nights game at Fitchburg.

Suddenly, everyone on the practice field froze in place and looked skyward as a medical helicopter from UMass Memorial zipped above toward its customary landing spot on the field at nearby Mount Wachusett Community College.

All air travel had been grounded that day, and the appearance of the emergency Medivac caused an unexplained panic among everyone on the ground.

Airports, IDs, privacy: Here's what changed after 9/11 that probably now seems normal

Upon arriving home that evening, I had the urge to just burrow into my living room chair and gather the family around me to take in the full scope of what happened that day.

However, we had dropped our son, Casey, off at Providence College just prior to Labor Day, and having that void in the family felt like an empty hole to me.

Then I realized the empty holes that many other families were experiencing that night, having lost one or more of their own members to the terrorist attack.

We kept vigil by our television, so reminiscent of the bleak weekend back in November of 1963 when our country experienced all of the details of the Kennedy assassination on our black and white sets.

More from Mike Richard: Once again, someone has put our columnist's good name in 'Jeopardy'

A few days later, Gardner would make the national news.

The Federal Aviation Administration indicated that the hijackers aboard American Airlines Flight 11 out of Logan Airport had gained control of the flight over Gardners airspace.

American Airlines Flight 11 had left Logan Airport in Boston and was en route to Los Angeles, the Associated Press dispatch reported. According to the controller, it was first noticed that Flight 11 was having difficulties when its transponder suddenly shut off while in the Gardner area.

As the weeks progressed and a nation tried to heal, students of Gardner High did their own small part to help the families whose lives were so devastated that day.

For several Saturdays through the months of October and November, students organized and volunteered for a program they called De-leaf for Relief.

20 years after 9/11, New Englanders reflect on a defining moment

Residents of Gardner who wanted students to assist with raking the leaves in their yard paid a pre-arranged fee to have the job completed; the money going to a New York City relief fund.

Later that fall, a busload of those same students took the trip to New York City to deliver a large donation from their efforts. It was a unique kindness that was typical of students at Gardner High in that era helping them heal, as the nation tried to heal as well.

Eventually, the world would get back to normal; a new normal.

However, on that crisp and sunny September day 20 years ago, life as we knew it and the innocence we also once knew was robbed from a generation.

Comments and suggestions for The Gardner Scene can be sent to Mike Richard at mikerichard0725@gmail.com or in writing to Mike Richard, 92 Boardley Road, Sandwich, MA 02563.

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'All of a sudden, the room echoed a collective gasp': Former teacher looks back on 9/11 - The Gardner News

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More than a TMS, Alvys spares carriers from needing multiple software solutions – FreightWaves

Posted: at 9:47 am

Logistics providers have one goal in mind: Ensure shipments arrive on time and in one piece. But its easier said than done, as growth can often be a double-edged sword.

When demand surpasses the capabilities of a business, growing pains make it difficult to scale operations. This is the case for many carriers as well as shippers and 3PLs with growth in mind.

The juggling act of sourcing, fulfillment and management often distracts logistics providers from the business at hand, as each department requires more attention. Solutions are available to manage each task, but this siloed approach makes cross-platform synchronization nearly impossible and ultimately creates friction between departments.

There are systems that do those individual things for you, but you still end up putting a lot of effort into moving data from one system to another making sure theyre synchronized, said Nick Darmanchev, Alvys founder and CEO. That kind of defeats the entire purpose of using technology because youre spending more time managing the technology instead of reaping its benefits.

What the industry needs is a single platform to satisfy all stakeholders, and Alvys has answered the call.

The Denver-based logistics software provider simplifies logistics and transportation workflows, carrier procurement, dispatch, and relationship management, starting at the ground level with small and midsize carriers the industrys most overlooked segment.

Alvys offers something beyond the conventional functions of a TMS. Unique among TMS offerings, it focuses on workflow. Its TMS levels the playing field through affordable add-scale technology that integrates a variety of management systems into one intuitive dashboard.

Darmanchev expounded on the platforms affordability and convenience, noting that Alvys builds its technology around customers business.

Ask an Alvys user what they think about the system and theyll tend to say that it feels like its designed for what theyre doing and to exactly support the workflow theyre engaged in, as opposed to the other way around, where theyve got to try to fit workflows into the technology, Darmanchev said.

Igor Balorda, CEO of Colorado-based motor carrier Skyline Transportation, made the switch to Alvys earlier this year and said the platform has provided a breath of fresh air.

Alvys has really checked all the boxes on our end as far as what we want from a truck management software, Balorda said.

As a midsized company, Skylines 35-truck fleet has experienced rapid growth, which had become a bit too much for its current operating systems to handle. Balorda said that its biggest challenge was data entry and dispatching challenges, conflicting with day-to-day operations. But after joining Alvys, managing truckings nitty-gritty tasks became a lot less challenging.

My team absolutely loves the drag-and-drop feature for rate confirmations, Balorda said. Alvys automatically generates an invoice for us and puts in all the pertinent information that the driver needs. This differs from before, when Skyline spent hours building out loads every day.

Smaller carriers, especially those operating on thin margins, found themselves unable to afford such technology before discovering Alvys. However, carriers are no longer expected to shell out a lot of money for a sophisticated TMS or develop software in-house.

We promise logistics service providers that well help them move from point A to point B faster, meaning from one phase of the company to another, said Alvys co-founder and CTO Leo Gorodinski. It takes a different strategy tool to manage a five-truck operation versus a 20-truck, and Alyvs has the tools in our TMS to incorporate these different phases.

Poor visibility inevitably leads to frustration. Gorodinski said that communication gaps are common for carriers operating disparate platforms. He explained that a dispatcher snagging a load from a DAT load board at 9 a.m., for example, may go ahead and book a noon pickup for a specific trailer sitting idle at the receiver. The dispatcher is under the impression that the trailer has already been unloaded and is ready for pickup due to the GPS showing inactivity, but unbeknown to the dispatcher, the trailer has yet to be unloaded and will probably miss its noon scheduling.

Gorodinski noted that this situation couldve easily been avoided if the dispatcher and driver had a direct communication channel. The Alvys mobile Driver App allows drivers to provide check-in and checkout updates at every stop. Drivers can also issue comcheck and EFS checks for lumpers and advances, as well as upload bills of lading and proof of deliveries at each load level.

Imagine if drivers are empowered with a mobile application where theyre obligated to actually register their check-in and checkout time activity? Gorodinski said. If the checkout was not yet registered from the mobile application, then the dispatcher wouldve known for sure that the truck had not been unloaded. Therefore, the dispatcher wouldnt have bothered talking with the broker.

The Alvys app helps managers keep fleets in shape by sending drivers confirmation requests and schedules instantly without hassle. Skyline has enjoyed its improved communication capabilities, as it found corresponding with drivers through email and text messages to be a tedious task. In fact, Balorda said that the driver app has inadvertently reduced the amount of messages drivers send while in transit, ultimately reducing distracted driving.

Alvys streamlines the accounting process too, through its integration with QuickBooks and other accounting software. Users can automate invoices, upload instantly to a preferred factoring company, manage customer aging reports, and even generate drivers pay stubs almost instantaneously.

For instance, a driver traveling an additional 200 miles for truck repairs would understandably want to be paid for the trouble. But if dispatch fumbles the payment request and forgets to tell accounting, all while the driver assumes the payment is being processed, things get heated pretty quickly.

If that driver was able to report the extra 200 miles on his own, then accounting would only need to check with the dispatcher, Gorodinski said. The dispatcher would then confirm, therefore posting that extra 200 miles on his pay stub; the driver is happy, retained, and so on and so forth.

Alvys end-to-end platform saves carriers from the hassle of using multiple software solutions. Gorodinski reasons that carriers benefit from incorporating appointments automatically with shippers and receivers within the TMS, where all parties can stay up to date instead of tediously drafting yet another set of dull spreadsheets.

I dont know of any carrier that uses a TMS only; they use a TMS and a bunch of spreadsheets on top of other softwares in order to do their work, Gorodinski said. The question is, why do they even have a TMS? Why not incorporate the entire end-to-end workflow, and make the lives of all logistics stakeholders easier?

Click for more FreightWaves content by Jack Glenn.

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More than a TMS, Alvys spares carriers from needing multiple software solutions - FreightWaves

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Increasing and decreasing interregional brain coupling increases and decreases oscillatory activity in the human brain – pnas.org

Posted: at 9:47 am

Significance

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 PMvM1 connection because it is the major cortical route by which prefrontal cortex might influence, inhibit, and curtail action-related activity in M1. Manipulating PMvM1 coupling in accordance with Hebbian-like spike-timingdependent 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 PMvM1 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 PMvM1 pathway can be manipulated following Hebbian spike-timingdependent 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 PMvM1 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 leveldependent (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 themselvesPMv and M1but 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 PMvM1 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 (PMvM1-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 ExpressionBaseline 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 PMvM1 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 pathways connectivity; the two ccPAS protocols used in groups A and B did indeed exert distinct effects on Go trials. While PMvM1-ccPAS significantly enhanced the cortical excitability of M1 in Go trials, this M1 excitability remained the same after M1PMv-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 Bsee 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 Students t tests showed that the PMvM1-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 Students 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 Students t test analysis revealed a late increase in beta synchronization after (versus before) PMvM1-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, PMvM1-ccPAS, nor for Go trials in group B, M1PMv-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 premotormotor 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 PMvs 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 PMvM1-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 PMvM1-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 Students 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 M1PMv-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 Students 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 PMvM1-ccPAS observed in experimental group A suggests augmentation of oscillatory activity associated with top-down motor control in response conflict, whereas the reversed-order M1PMv-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 PMvM1-ccPAS in group A versus reversed M1PMv-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 PMvM1- and reversed M1PMv-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 (PMvM1-ccPAS: 0.25 to 1.2 s after stimulus onset; 4 to 15 Hz; Monte Carlo P value = 0.004; M1PMv-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. PMvM1-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 coherenceITLC) 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. S3yellow 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. S3ITLC 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, PMvM1-ccPAS leads to a subsequent state-dependent augmentation of PMvs 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 M1PMv-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, M1PMv-ccPAS, comprises the same amount and intensity of both PMv and M1 stimulation as PMvM1-ccPAS, and thus, it has the same impact on the component elements of the PMvM1 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 PMvM1-ccPAS that is not present with, or reversed with, M1PMv-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. PMvM1-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, PMvM1-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 presupplementary 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 M1PMv stimulation in group B. The reversed-order M1PMv stimulation protocol is unlikely to lead to simultaneous pre- and postsynaptic activity in the PMvM1 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 timingdependent 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).

PMvM1-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 M1PMv-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 M1PMv-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 PMvM1-ccPAS, suggesting greater top-down motor control during response conflict as a result of entrainment of PMvM1 connections. Opposite effects on theta oscillations are observed after reversed-order M1PMv-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 PMvM1 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 PMvM1 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 timingdependent 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 participants16 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 participanthandiness 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 trials70% 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 (PMvM1-ccPAS, M1PMv-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 eightshaped 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 volunteers 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. 1cortical coordinates computed using Brainsight stereotactic neuronavigation for each participant; mean cortical coordinates computed by averaging all individuals 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 individuals 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 RMT110% (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 observed0.2 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 PMvM1-ccPAS (group A; n = 16) versus the participants that received reverse-order M1PMv-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 (PMvM1-ccPAS group versus reversed-order PMvM1-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 PMvM1 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 sitesC4, 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 (PMvM1-ccPAS, M1PMv-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 Students 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, p2 = 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.

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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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Increasing and decreasing interregional brain coupling increases and decreases oscillatory activity in the human brain – pnas.org

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