Your brain is currently expending about a fifth of your body’s energy, and almost none of that is being used for what you’re doing right now. Reading these words, feeling the weight of your body in a chair – all of this together barely changes the rate at which your brain consumes energy, perhaps by as little as 1%.

The other 99% is used on the activity the brain generates on its own: neurons (nerve cells) firing and signalling to each other regardless of whether you’re thinking hard, watching television, dreaming, or simply closing your eyes.

Even in the brain areas dedicated to vision, the visuals coming in through your eyes shape the activity of your neurons less than this internal ongoing action.

In a paper just published in Psychological Review, we argue that our imagination sculpts the images we see in our mind’s eye by carving into this background brain activity. In fact, imagination may have more to do with the brain activity it silences than with the activity it creates.

Imagining as seeing in reverse

Consider how “seeing” is understood to work. Light enters the eyes and sparks neural signals. These travel through a sequence of brain regions dedicated to vision, each building on the work of the last.

The earliest regions pick out simple features such as edges and lines. The next combine those into shapes. The ones after that recognise objects, and those at the top of the sequence assemble whole faces and scenes.

Neuroscientists call this “feedforward activity” – the gradual transformation of raw light into something you can name, whether it’s a dog, a friend, or both.

In brain science, the standard view is that visual imagination is this original seeing process run in reverse, from within your mind rather than from light entering your eyes.

So, when you hold the face of a friend in mind, you start with an abstract idea of them – a memory or a name, pulled from the filing cabinet of regions that sit beyond the visual system itself.

That idea travels back down through the visual sequence into the early visual areas, which serve as your brain’s workshop where a face would normally be reconstructed from its parts – the curve of a jawline, the specific shade of an eye. These downward signals are called “feedback activity”.

A signal through the static

However, prior research shows this feedback activity doesn’t drive visual neurons to fire in the same way as when you actually see something.

At least in the brain regions early in the vision process, feedback instead modulates brain activity. This means it increases or decreases the activity of the brain cells, reshaping what those neurons are already doing.

Even behind closed eyes, early visual brain areas keep producing shifting patterns of neural activity resembling those the brain uses to process real vision.

Imagination doesn’t need to build a face from scratch. The raw material is already there. In the internal rumblings of your visual areas, fragments of every face you know are drifting through at low volume. Your friend’s face, even now, is passing through in pieces, scattered and unrecognised. What imagining does is hold still the currents that would otherwise carry those pieces away.

All that’s needed is a small, targeted suppression of neurons that are pulled by brain activity in a different direction, and your friend’s face settles out of the noise, like a signal carving its way through static.

Steering the brain

In mice, artificially switching on as few as 14 neurons in a sensory brain region is enough for the animal to notice it and lick a sugar-water spout in response. This shows how small an intervention in the brain can be while still steering behaviour.

While we don’t know how many neurons are needed to steer internal activity into a conscious experience of imagination in humans, growing evidence shows the importance of dampening neural activity.

In our earlier experiments, when people imagined something, the fingerprint it left on their behaviour matched suppression of neuronal activity – not firing. Other researchers have since found the same pattern.

Other lines of evidence strengthen our theory, too. About one in 100 people have aphantasia, which means they can’t form mental images at all. One in 30 form these images so vividly they approach the intensity of images we actually see, known as hyperphantasia.

Research has found that people with weaker mental imagery have more excitable early visual areas, where neurons fire more readily on their own. This is consistent with a visual system whose spontaneous patterns are harder to hold in shape.

Taking all this together, the spontaneous activity reshaping hypothesis – our new theory that imagination carves images out of the steady stream of ongoing brain activity – explains why imagination usually feels weaker than sight. It also explains why we rarely lose track of which is which.

Visual perception arrives with a strength and regularity the brain’s own internal patterns don’t match. Imagination works with those patterns rather than against them, reshaping what is already there into something we can almost see.

Source: UTS

The cosmological constant has been a problem in physics since Einstein, but new research may show why it takes the value that it does despite quantum fluctuations that should make its value practically infinite.

The Hubble Space Telescope showed that distant galaxies are moving away from Earth faster than those nearby, a sign that the universe’s expansion is increasing at rate described by the cosmological constant. That value of that constant is one of the great mysteries of modern physics. Credit: NASA.

The cosmological constant is the mathematical description of the energy that drives the ever-accelerating expansion of the cosmos. It’s also the source of one of the most enduring and confounding problems in modern physics.

The constant’s observed value is fundamentally at odds with quantum field theory (QFT), the leading theory describing the elementary particles and forces that make up the universe. QFT predicts that quantum fluctuations in the vacuum of space should make the value of the constant enormous — practically infinite. But its observed value is a tiny fraction of that prediction.

Researchers at Brown University have proposed a provocative new answer for why that is.

The scientists show that math underlying the simplest formulation of quantum gravity bears a striking resemblance to the math describing the quantum Hall effect, an exotic state of matter in which electricity flows with uncanny precision. In the quantum Hall state, electrical conductance is held steady, regardless of any imperfections in the conducting material, by the system’s topology — the mathematical “shape” of the quantum state. The researchers show that there’s an analogous topology in what’s known as the Chern-Simons-Kodama state, a proposed ground state of quantum gravity.

“What we’ve shown is that if space-time has this non-trivial topology, then it resolves one of the deadliest problems of the cosmological constant,” said study co-author Stephon Alexander, a professor of physics at Brown. “All the quantum perturbations that should blow up the value of the cosmological constant are rendered inert by this topology, which keeps the constant’s value stable.”

The research, which Alexander co-authored with Brown Theoretical Physics Center colleagues Aaron Hui and Heliudson Bernardo, is published in Physical Review Letters.

The “ugly” term

The cosmological constant first appeared as a term in the equations describing Einstein’s canonical theory of space, time and gravity, known as general relativity. Einstein was forced to introduce the term to make his mathematical universe stable. It represented a repulsive force, present in the vacuum of space, that counteracted the force of gravity and kept the universe from collapsing on itself.

In 1929, however, the cosmological constant was dealt an existential blow. Astronomer Edwin Hubble discovered that the universe was not as stable as Einstein had assumed. Rather than holding static, it was expanding. That discovery allowed Einstein to remove the stabilizing term from his equations, which he did with some relief. He had long viewed it as “ugly” and is purported to have called it his “biggest blunder.”

Following Hubble’s discovery, the cosmological constant spent about a half-century on the scientific scrap heap. That changed in 1998, however, when scientists discovered that the universe’s expansion is not happening at a constant rate; it’s accelerating. That discovery once again made the cosmological constant necessary to describe the increasing speed of the universe’s expansion.

Not only was Einstein’s ugly term back, it was uglier than ever. During the constant’s exile, quantum field theory had become the backbone of the Standard Model of particle physics. According to QFT, empty space is not empty at all. Rather, it’s a boiling soup of elementary particles constantly popping in and out of existence. All that activity should cause the vacuum energy of space — the energy described by the cosmological constant — to be practically infinite. Yet its observed value, which is estimated by the rate of cosmic expansion, is most definitely not infinity. An infinite value would cause the universe to expand far too quickly to allow the formation of things like galaxies, planets or physicists.

Experiments with elementary particles have shown QFT to be among the most precise and successful theories in all of science, which makes its seemingly errant predictions about the cosmological constant all the more puzzling.

Topologically protected

Alexander has spent years studying Chern-Simons-Kodama (CSK) theory, a proposed state of quantum gravity that grows out of quantum field theory. Scientists have yet to settle on a quantum theory of gravity — a theory that explains how gravity works at the tiniest scales — but the CSK state is one of the more straightforward candidates, according to Alexander.

“It’s a really conservative approach to quantizing gravity,” he said. “This is the approach used by people like Dirac, Schrödinger and Wheeler. It’s just good, old-fashioned quantization.”

Alexander had been aware of some mathematical similarities between CSK and the math behind the quantum Hall effect, but he wasn’t entirely sure what to make of them. That’s when he turned to Hui, an assistant professor at Brown who specializes in topological systems like those that emerge in the quantum Hall effect.

“This is the beauty of the Brown Theoretical Physics Center,” Alexander said. “We want to be a place where there’s a mixing of lots of perspectives, and this is us practicing what we preach — a cosmologist working closely with a condensed matter theorist.”

Together, the researchers were able to show that the cosmological constant has a similar “topological protection” in the CSK state as electrical conductivity has in the quantum Hall effect. The quantum Hall effect emerges when electricity flows through very thin materials in the presence of a magnetic field. Imagine a flat, two-dimensional piece of metal cut into a rectangular strip with an electric current running longways down the strip. Introducing a magnetic field produces a second voltage that runs perpendicular to the original current. This is known as a Hall voltage (named after Edwin Hall, who discovered it).

At room temperature and under relatively weak magnetic fields, the Hall voltage increases linearly as the strength of the magnetic field increases. But at very cold temperatures, where the rules of quantum mechanics dominate, and under very strong magnetic fields, the phenomenon changes. Rather than increasing linearly with magnetic field strength, the Hall voltage starts to increase in discrete (or quantized) steps and plateaus. The steps and plateaus are incredibly precise and consistent, taking the exact same values regardless of the type of metal used as a conductor or whether there happen to be any imperfections in it.

That precision and consistency arise because of the system’s topology. In these extreme conditions, electrons enter a highly correlated state of collective behavior. It’s the mathematical structure of that collective state — its topology — that locks the values of the steps and plateaus into place. The system is topologically protected from perturbations from the material and its imperfections, so the steps and plateaus always have the same value.

The researchers show that a very similar topological protection is present in the equations describing the CSK state. Just as the topology of the electron states locks the Hall voltage into place, the topology of space-time itself locks the cosmological constant into place, even in the face of quantum fluctuations in the vacuum of space.

“What we find is that this quantization of the electrical conductance in quantum Hall has an analog with the cosmological constant,” Hui said. “It also ends up becoming quantized for topological reasons. There turn out to be constraints in the theory that force the cosmological constant to take certain allowed quantized values.”

There’s much more work to be done to fully flesh out a topological solution to the cosmological constant problem, Alexander says. But finding a potential solution to the gravitational aspect of the problem is a crucial start. At the very least, he says, the work bolsters the profile of the CSK state as a candidate for a long-sought theory of quantum gravity.

“We took something old, which is this conservative, canonical approach to quantum gravity, and discovered something new that had been there all along,” Alexander said. “Now we’re working on a bigger picture of how this phenomenon works.”

Source: Brown University

Scientists at UCLA have created one of the first cellular-resolution molecular maps detailing how Down syndrome alters human brain development before birth — a resource that resolves longstanding contradictions in the field and could lay the groundwork for future therapeutic strategies.

The study, published in Science, analyzed more than 100,000 nuclei from human prenatal neocortex samples collected across 26 pre-genotyped donors during gestational weeks 13 to 23 — the only window during which all the cortical neurons a person will carry for their entire life are generated. The findings suggest that Down syndrome disrupts the developmental sequence of that process, creating shifts that may help explain later differences in cognition, learning and sensory processing.

“There’s a new level of detail here that had never existed before,” said Luis de la Torre-Ubieta, senior author of the study and a member of the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at UCLA. “For the first time, we can really try to understand systematically what’s going on in the developing brain of individuals with Down syndrome.”

Filling a critical gap

The Down syndrome research field has historically focused on two areas: the adult brain and the disorder’s connection to neurodegeneration. The link is striking — the vast majority of people with Down syndrome will develop Alzheimer’s disease, typically by their 60s.

What remained largely unexamined, despite clear indicators that Down syndrome is a developmental condition — such as smaller brain volumes detectable by MRI and cognitive differences apparent as early as 6 months to one year of age — was how the condition shapes the developing brain itself.

“No one had looked at the developing human brain in Down syndrome directly using single-cell genomics,” said de la Torre-Ubieta, an assistant professor of psychiatry and biobehavioral sciences. “Mouse models and in vitro models are important tools, but don’t really give you a gold standard of what’s happening in the human brain — and actually, they have led to different results and some confusion in the field.”

These inconsistencies are due in part to differences in how mice and human brains develop, and the fact that in vitro models don’t fully represent all the cell types and tissues present in the brain.

The new study, de la Torre-Ubieta said, can serve as that gold standard resource.

A disrupted developmental sequence and its impact on brain size

The development of the prenatal neocortex typically follows a tightly orchestrated sequence. Progenitor cells — the brain’s stem cells — must first divide repeatedly to expand their own pool, building up a sufficient base for all future neurons. Only then do they begin differentiating into neurons, starting with deep-layer cell types and progressing toward upper-layer cells in a carefully timed order.

In Down syndrome, that sequence appears to break down. The study found that progenitor cells appear to rush prematurely into neuron production, depleting their own pool and skewing the balance of neuron types generated. Specifically, the researchers observed a relative increase in upper-layer intratelencephalic neurons and a reduction in deep-layer corticothalamic neurons.

Those two cell populations play fundamentally different roles: CT neurons project outward from the cortex — connecting to brain structures and to the spinal cord to govern sensation and movement; IT neurons wire within the cortex, connecting the two hemispheres and contributing to information processing. This finding offers a new hypothesis for how early developmental changes might contribute to the cognitive profile of the condition.

The finding also offers a new answer to a longstanding question in the field: Why do people with Down syndrome tend to have smaller brains? Earlier theories centered on elevated rates of cell death. The current study found less evidence of widespread neuronal death and instead points to the depletion of the progenitor pool.

A systems-level view of a systems-level disorder

The study employed paired single-nucleus multi-omics, a technology that measures both gene expression and chromatin accessibility in the same individual cell. Chromatin accessibility reveals which regions of the genome are open and active — the enhancers and promoters that regulate gene expression — offering a layer of information beyond which genes are simply switched on or off.

By combining these two readouts, the researchers were able to reconstruct not just a snapshot of which cells are present, but the regulatory programs that guide cell fate — and how those programs are disrupted in Down syndrome. Systems-level approaches also led them to uncover alterations in cell metabolism and changes in how the vasculature interacts with the developing nervous system, both of which could speed up neuron production.

Implications beyond Down syndrome

The study’s significance extends beyond Down syndrome. The researchers specifically tested for overlap between the molecular disruptions they identified and the genetic risk signatures associated with other neurodevelopmental and neuropsychiatric conditions, including autism, epilepsy and developmental delay. They found substantial convergence, particularly in the gene-regulatory networks governing the specification of IT versus CT neurons.

“Down syndrome could be a model to understand intellectual disability and neuropsychiatric disorders more broadly,” de la Torre-Ubieta said. “Also to uncover the shared biology underlying these conditions — because the mechanisms are often still unknown.”

Two papers, one story

The publication coincides with a companion paper from researchers at the University of Wisconsin-Madison, appearing in the same issue of Science. While the UCLA study focuses on the prenatal period, the Wisconsin team examined the postnatal brain, studying Down syndrome between approximately one and five years of age.

When the two groups shared preliminary findings, they discovered striking parallels: many of the changes identified prenatally by the UCLA team appear to persist into early childhood.

Together, the two papers provide a continuous molecular view of Down syndrome brain development from mid-gestation through infancy — a resource that did not previously exist and that the researchers expect will serve as a reference for their field for years to come.

A foundation for future therapies

While the researchers are careful to emphasize that the findings do not point to a near-term clinical application, the study provides the clearest picture yet of the cellular and molecular events that distinguish the Down syndrome brain during development, and a framework for identifying future therapeutic targets.

“We are finding targets that could be actionable down the line if you generate drugs for specific pathways,” de la Torre-Ubieta said. “And you could conceive of a gene therapy based on that, to suppress the expression of particular drivers and restore development closer to its normal course.”

UCLA authors Celine K. Vuong and Alexis Weber led this work, along with Patrick Seong, Yu-Jen Chen, Jordan Peyer, Shahab Younesi, Angelo Salinda, Daniel Gomez, Gabriella Rivas, Abril Morales, Beck Shafie, Pan Zhang, Susanne Nichterwitz, Le Qi, Nolan T. Fernandez, Emily Friedman, Daniel H. Geschwind and William E. Lowry. Nana Matoba, Michael I. Love, Michael J. Gandal and Jason L. Stein contributed to this study.

The research was supported by the National Institute of Child Health and Human Development, the National Institute of Mental Health, the UCLA Broad Stem Cell Research Center, including a Rose Hills Foundation Innovator Grant and a post-doctoral training grant, the UCLA Health Jonsson Comprehensive Cancer Center and UCLA Broad Stem Cell Research Center Ablon Scholars Program, the California Institute for Regenerative Medicine and the National Institutes of Health Biomedical Big Data Training Program.

Source: UCLA