An international team of researchers has developed new analytical techniques that consider interactions between three or more regions of the brain – providing a more in-depth understanding of human brain activity than conventional analysis. Led by Andrea Santoro at the Neuro-X Institute in Geneva and Enrico Amico at the UK’s University of Birmingham, the team hopes its results could help neurologists identify a vast array of new patterns in human brain data.

To study the structure and function of the brain, researchers often rely on network models. In these, nodes represent specific groups of neurons in the brain and edges represent the electrical connections between neurons using statistical correlations.

Within these models, brain activity has often been represented as pairwise interactions between two specific regions. Yet as the latest advances in neurology have clearly shown, the real picture is far more complex.

“To better analyse how our brains work, we need to look at how several areas interact at the same time,” Santoro explains. “Just as multiple weather factors – like temperature, humidity, and atmospheric pressure – combine to create complex patterns, looking at how groups of brain regions work together can reveal a richer picture of brain function.”

Higher-order interactions

Yet with the mathematical techniques applied in previous studies, researchers have not confirmed whether network models incorporating these higher-order interactions between three or more brain regions could really be more accurate than simpler models, which only account for pairwise interactions.

To shed new light on this question, Santoro’s team built upon their previous analysis of functional MRI (fMRI) data, which identify brain activity by measuring changes in blood flow.

Their approach combined two powerful tools. One is topological data analysis. This identifies patterns within complex datasets like fMRI, where each data point depends on a large number of interconnected variables. The other is time series analysis, which is used to identify patterns in brain activity which emerge over time. Together, these tools allowed the researchers to identify complex patterns of activity occurring across three or more brain regions simultaneously.

To test their approach, the team applied it to fMRI data taken from 100 healthy participants in the Human Connectome Project. “By applying these tools to brain scan data, we were able to detect when multiple regions of the brain were interacting at the same time, rather than only looking at pairs of brain regions,” Santoro explains. “This approach let us uncover patterns that might otherwise stay hidden, giving us a clearer view of how the brain’s complex network operates as a whole.”

Just as they hoped, this analysis of higher-order interactions provided far deeper insights into the participants’ brain activity compared with traditional pairwise methods. “Specifically, we were better able to figure out what type of task a person was performing, and even uniquely identify them based on the patterns of their brain activity,” Santoro continues.

Distinguishing between tasks

With its combination of topological and time series analysis, the team’s method could distinguish between a wide variety of tasks in the participants: including their expression of emotion, use of language, and social interactions.

By building further on their approach, Santoro and colleagues are hopeful it could eventually be used to uncover a vast space of as-yet unexplored patterns within human brain data.

By tailoring the approach to the brains of individual patients, this could ultimately enable researchers to draw direct links between brain activity and physical actions.

“Down the road, the same approach might help us detect subtle brain changes that occur in conditions like Alzheimer’s disease – possibly before symptoms become obvious – and could guide better therapies and earlier interventions,” Santoro predicts.

The research is described in Nature Communications.

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From tumour-killing quantum dots to proton therapy firsts, this year has seen the traditional plethora of exciting advances in physics-based therapeutic and diagnostic imaging techniques, plus all manner of innovative bio-devices and biotechnologies for improving healthcare. Indeed, the Physics World Top 10 Breakthroughs for 2024 included a computational model designed to improve radiotherapy outcomes for patients with lung cancer by modelling the interaction of radiation with lung cells, as well as a method to make the skin of live mice temporarily transparent to enable optical imaging studies. Here are just a few more of the research highlights that caught our eye.

Marvellous MRI machines

This year we reported on some important developments in the field of magnetic resonance imaging (MRI) technology, not least of which was the introduction of a 0.05 T whole-body MRI scanner that can produce diagnostic quality images. The ultralow-field scanner, invented at the University of Hong Kong’s BISP Lab, operates from a standard wall power outlet and does not require shielding cages. The simplified design makes it easier to operate and significantly lower in cost than current clinical MRI systems. As such, the BISP Lab researchers hope that their scanner could help close the global gap in MRI availability.

Moving from ultralow- to ultrahigh-field instrumentation, a team headed up by David Feinberg at UC Berkeley created an ultrahigh-resolution 7 T MRI scanner for imaging the human brain. The system can generate functional brain images with 10 times better spatial resolution than current 7 T scanners, revealing features as small as 0.35 mm, as well as offering higher spatial resolution in diffusion, physiological and structural MR imaging. The researchers plan to use their new NexGen 7 T scanner to study underlying changes in brain circuitry in degenerative diseases, schizophrenia and disorders such as autism.

Meanwhile, researchers at Massachusetts Institute of Technology and Harvard University developed a portable magnetic resonance-based sensor for imaging at the bedside. The low-field single-sided MR sensor is designed for point-of-care evaluation of skeletal muscle tissue, removing the need to transport patients to a centralized MRI facility. The portable sensor, which weighs just 11 kg, uses a permanent magnet array and surface RF coil to provide low operational power and minimal shielding requirements.

Proton therapy progress

Alongside advances in diagnostic imaging, 2024 also saw a couple of firsts in the field of proton therapy. At the start of the year, OncoRay – the National Center for Radiation Research in Oncology in Dresden – launched the world’s first whole-body MRI-guided proton therapy system. The prototype device combines a horizontal proton beamline with a whole-body MRI scanner that rotates around the patient, a geometry that enables treatments both with patients lying down or in an upright position. Ultimately, the system could enable real-time MRI monitoring of patients during cancer treatments and significantly improve the targeting accuracy of proton therapy.

Also aiming to enhance proton therapy outcomes, a team at the PSI Center for Proton Therapy performed the first clinical implementation of an online daily adaptive proton therapy (DAPT) workflow. Online plan adaptation, where the patient remains on the couch throughout the replanning process, could help address uncertainties arising from anatomical changes during treatments. In five adults with tumours in rigid body regions treated using DAPT, the daily adapted plans provided target coverage to within 1.1% of the planned dose and, in over 90% of treatments, improved dose metrics to the targets and/or organs-at-risk. Importantly, the adaptive approach took just a few minutes longer than a non-adaptive treatment, remaining within the 30-min time slot allocated for a proton therapy session.

Bots and dots

Last but certainly not least, this year saw several research teams demonstrate the use of tiny devices for cancer treatment. In a study conducted at the Institute for Bioengineering of Catalonia, for instance, researchers used self-propelling nanoparticles containing radioactive iodine to shrink bladder tumours.

Upon injection into the body, these “nanobots” search for and accumulate inside cancerous tissue, delivering radionuclide therapy directly to the target. Mice receiving a single dose of the nanobots experienced a 90% reduction in the size of bladder tumours compared with untreated animals.

At the Chinese Academy of Sciences’ Hefei Institutes of Physical Science, a team pioneered the use of metal-free graphene quantum dots for chemodynamic therapy. Studies in cancer cells and tumour-bearing mice showed that the quantum dots caused cell death and inhibition of tumour growth, respectively, with no off-target toxicity in the animals.

Finally, scientists at Huazhong University of Science and Technology developed novel magnetic coiling “microfibrebots” and used them to stem arterial bleeding in a rabbit – paving the way for a range of controllable and less invasive treatments for aneurysms and brain tumours.

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The plant kingdom is full of intriguing ways to distribute seeds such as the dandelion pappus effortlessly drifting on air currents to the ballistic nature of fern sporangia.

Not to be outdone, the squirting cucumber (Ecballium elaterium), which is native to the Mediterranean and is often regarded as a weed, has its own unique way of ejecting seeds.

When ripe, the ovoid-shaped fruits detach from the stem and as it does so explosively ejects seeds in a high-pressure jet of mucilage.

The process, which lasts just 30 milliseconds, launches the seeds at more than 20 metres per second with some landing 10 metres away.

Researchers in the UK have, for the first time, revealed the mechanism behind the squirt by carrying out high-speed videography, computed tomography scans and mathematical modelling.

“The first time we inspected this plant in the Botanic Garden, the seed launch was so fast that we weren’t sure it had happened,” recalls Oxford University mathematical biologist Derek Moulton. “It was very exciting to dig in and uncover the mechanism of this unique plant.”

The researchers found that in the weeks leading up to the ejection, fluid builds up inside the fruits so they become pressurised. Then just before seed dispersal, some of this fluid moves from the fruit to the stem, making it longer and stiffer.

This process crucially causes the fruit to rotate from being vertical to close to an angle of 45 degrees, improving the launch angle for the seeds.

During the first milliseconds of ejection, the tip of the stem holding the fruit then recoils away causing the fruit to counter-rotate and detach. As it does so, the pressure inside the fruit causes the seeds to eject at high speed.

By changing certain parameters in the model, such as the stiffness of the stem, reveals that the mechanism has been fine-tuned to ensure optimal seed dispersal. For example, a thicker or stiffer stem would result in the seeds being launched horizontally and distributed over a narrower area.

According to Manchester University physicist Finn Box, the findings could be used for more effective drug delivery systems “where directional release is crucial”.

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Optical traps and tweezers can be used to capture and manipulate particles using non-contact forces. A focused beam of light allows precise control over the position of and force applied to an object, at the micron scale or below, enabling particles to be pulled and captured by the beam.

Optical manipulation techniques are garnering increased interest for biological applications. Researchers from Massachusetts Institute of Technology (MIT) have now developed a miniature, chip-based optical trap that acts as a “tractor beam” for studying DNA, classifying cells and investigating disease mechanisms. The device – which is small enough to fit in your hand – is made from a silicon-photonics chip and can manipulate particles up to 5 mm away from the chip surface, while maintaining a sterile environment for cells.

The promise of integrated optical tweezers

Integrated optical trapping provides a compact route to accessible optical manipulation compared with bulk optical tweezers, and has already been demonstrated using planar waveguides, optical resonators and plasmonic devices. However, many such tweezers can only trap particles directly on (or within several microns of) the chip’s surface and only offer passive trapping.

To make optical traps sterile for cell research, 150-µm thick glass coverslips are required. However, the short focal heights of many integrated optical tweezers means that the light beams can’t penetrate into standard sample chambers. Because such devices can only trap particles a few microns above the chip, they are incompatible with biological research that requires particles and cells to be trapped at much larger distances from the chip’s surface.

With current approaches, the only way to overcome this is to remove the cells and place them on the surface of the chip itself. This process contaminates the chip, however, meaning that each chip must be discarded after use and a new chip used for every experiment.

Trapping device for biological particles

Lead author Tal Sneh and colleagues developed an integrated optical phased array (OPA) that can focus emitted light at a specific point in the radiative near field of the chip. To date, many OPA devices have been motivated by LiDAR and optical communications applications, so their capabilities were limited to steering light beams in the far field using linear phase gradients. However, this approach does not generate the tightly focused beam required for optical trapping.

In their new approach, the MIT researchers used semiconductor manufacturing processes to fabricate a series of micro-antennas onto the chip. By creating specific phase patterns for each antenna, the researchers found that they could generate a tightly focused beam of light.

Each antenna’s optical signal was also tightly controlled by varying the input laser wavelength to provide an active spatial tuning for tweezing particles. The focused light beam emitted by the chip could therefore be shaped and steered to capture particles located millimetres above the surface of the chip, making it suitable for biological studies.

The researchers used the OPA tweezers to optically steer and non-mechanically trap polystyrene microparticles at up to 5 mm above the chip’s surface. They also demonstrated stretching of mouse lymphoblast cells, in the first known cell experiment to use single-beam integrated optical tweezers.

The researchers point out that this is the first demonstration of trapping particles over millimetre ranges, with the operating distance of the new device orders of magnitude greater than other integrated optical tweezers. Plasmonic, waveguide and resonator tweezers, for example, can only operate at 1 µm above the surface, while microlens-based tweezers have been able to operate at 20 µm distances.

Importantly, the device is completely reusable and biocompatible, because the biological samples can be trapped and undergo manipulation while remaining within a sterile coverslip. This ensures that both the biological media and the chip stay free from contamination without needing complex microfluidics packaging.

The work in this study provides a new type of modality for integrated optical tweezers, expanding their use into the biological domain to perform experiments on proteins and DNA, for example, as well as to sort and manipulate cells.

The researchers say that they hope to build on this research by creating a device with an adjustable focal height for the light beam, as well as introduce multiple trap sites to manipulate biological particles in more complex ways and employ the device to examine more biological systems.

The optical trap is described in Nature Communications.

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