TL;DR

• Even without a central brain, jellyfish can learn from past experiences like humans, mice, and flies, scientists report for the first time. They trained Caribbean box jellyfish (Tripedalia cystophora) to learn to spot and dodge obstacles. The study challenges previous notions that advanced learning requires a centralized brain and sheds light on the evolutionary roots of learning and memory.
• People differ significantly in their memory performance. Researchers at the University of Basel have now discovered that certain brain signals are related to these differences.
• Inflammation is the sign that our body is defending itself against aggression. But when this response escalates, for example in the brain, it can lead to serious neurological or psychiatric diseases. A team investigated a marker protein targeted by medical imaging to visualize cerebral inflammation, but whose interpretation was still uncertain. The team reveals that a large quantity of this protein goes hand in hand with a large quantity of inflammatory cells, but its presence is not a sign of their overactivation. These results pave the way for optimal observation of neuroinflammatory processes and a re-reading of previous studies on the subject.
• Research reveals new non-coding genetic variants associated with Alzheimer’s disease functioning in microglia — brain cells already implicated in the progression of this often-fatal neurodegenerative condition.
• New research finds fruit flies make decisions based on their expectations about the likelihood of a reward and pinpoints the site in the fly brain where these value adjustments are made, enabling researchers to directly test a theory about how the brain enables this behavior on the level of neural circuits.
• Scientists have revealed that the outer part of our brain (the cortex) is skilled at managing all the info it gets from the outside world thanks to special groups of nerve connections called modules, which work together but also independently.
• New research has identified an alternative signaling pathway in the brain of mice that relieves pain, even in animals that have developed tolerance to opioids. The study also showed that pain relief through this route did not induce tolerance, did not create withdrawal symptoms after treatment was stopped, and did not activate reward systems, limiting the risk for addiction and making it a viable path to developing effective, non-opioid pain relief.
• A new study sheds new light on the origins of modern brain cells. Researchers find evidence that specialized secretory cells found in placozoans, tiny sea creatures the size of a grain of sand, have many similarities to the neuron, such as the genes required to create a partial synapse. From an evolutionary point of view, early neurons might have started as something like these cells, eventually gaining the ability to create a complete synapse, form axons and dendrites and create ion channels that generate fast electrical signals — innovations that gave rise to the neuron in more complex animals such as jellyfish. Though the complete story of how the first neuron appeared remains to be told, the study demonstrates that the basic building blocks for our brain cells were forming in the ancestors of placozoans grazing inconspicuously in the shallow seas of Earth around 800 million years ago.
• Monash University Engineering researchers have successfully used “bioinks” containing living nerve cells (neurons) to print 3D nerve networks that can grow in the laboratory and transmit and respond to nerve signals.
• A research team has found that worms start moving at an unusually high speed when stimulated with alternating current. Because of its several characteristics, the team considered that this phenomenon may be triggered by primitive “emotion”.

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The latest news and research

Associative learning in the box jellyfish Tripedalia cystophora

by Jan Bielecki, Sofie Katrine Dam Nielsen, Gösta Nachman, Anders Garm in Current Biology

Even without a central brain, jellyfish can learn from past experiences like humans, mice, and flies, scientists report for the first time on September 22 in the journal Current Biology. They trained Caribbean box jellyfish (Tripedalia cystophora) to learn to spot and dodge obstacles. The study challenges previous notions that advanced learning requires a centralized brain and sheds light on the evolutionary roots of learning and memory.

No bigger than a fingernail, these seemingly simple jellies have a complex visual system with 24 eyes embedded in their bell-like body. Living in mangrove swamps, the animal uses its vision to steer through murky waters and swerve around underwater tree roots to snare prey. Scientists demonstrated that the jellies could acquire the ability to avoid obstacles through associative learning, a process through which organisms form mental connections between sensory stimulations and behaviors.

“Learning is the pinnacle performance for nervous systems,” says first author Jan Bielecki of Kiel University, Germany. To successfully teach jellyfish a new trick, he says “it’s best to leverage its natural behaviors, something that makes sense to the animal, so it reaches its full potential.”

The team dressed a round tank in gray and white stripes to simulate the jellyfish’s natural habitat, with gray stripes mimicking mangrove roots that would appear distant. They observed the jellyfish in the tank for 7.5 minutes. Initially, the jelly swam close to these seemingly far stripes and bumped into them frequently. But by the end of the experiment, the jelly increased its average distance to the wall by about 50%, quadrupled the number of successful pivots to avoid collision and cut its contact with the wall by half. The findings suggest that jellyfish can learn from experience through visual and mechanical stimuli.

“If you want to understand complex structures, it’s always good to start as simple as you can,” says senior author Anders Garm of the University of Copenhagen, Denmark. “Looking at these relatively simple nervous systems in jellyfish, we have a much higher chance of understanding all the details and how it comes together to perform behaviors.”

The researchers then sought to identify the underlying process of jellyfish’s associative learning by isolating the animal’s visual sensory centers called rhopalia. Each of these structures houses six eyes and generates pacemaker signals that govern the jellyfish’s pulsing motion, which spikes in frequency when the animal swerves from obstacles.

The team showed the stationary rhopalium moving gray bars to mimic the animal’s approach to objects. The structure did not respond to light gray bars, interpreting them as distant. However, after the researchers trained the rhopalium with weak electric stimulation when the bars approach, it started generating obstacle-dodging signals in response to the light gray bars. These electric stimulations mimicked the mechanical stimuli of a collision. The findings further showed that combining visual and mechanical stimuli is required for associative learning in jellyfish and that the rhopalium serves as a learning center.

Next, the team plans to dive deeper into the cellular interactions of jellyfish nervous systems to tease apart memory formation. They also plan to further understand how the mechanical sensor in the bell works to paint a complete picture of the animal’s associative learning.

“It’s surprising how fast these animals learn; it’s about the same pace as advanced animals are doing,” says Garm. “Even the simplest nervous system seems to be able to do advanced learning, and this might turn out to be an extremely fundamental cellular mechanism invented at the dawn of the evolution nervous system.”

Neurofunctional underpinnings of individual differences in visual episodic memory performance

by Léonie Geissmann, David Coynel, Andreas Papassotiropoulos, Dominique J. F. de Quervain in Nature Communications

People differ significantly in their memory performance. Researchers at the University of Basel have now discovered that certain brain signals are related to these differences.

While it is well known that certain brain regions play a crucial role in memory processes, so far it has not been clear whether these regions exhibit different activities when it comes to storing information in people with better or worse memory performance.

Having investigated this matter, a research team led by Professor Dominique de Quervain and Professor Andreas Papassotiropoulos has now published its results in the journal Nature Communications.

In the world’s largest functional imaging study on memory, they asked nearly 1,500 participants between the ages of 18 and 35 to look at and memorize a total of 72 images. During this process, the researchers recorded the subjects’ brain activity using MRI. The participants were then asked to recall as many of the images as possible — and as in the general population, there were considerable differences in memory performance among them.

In certain brain regions including the hippocampus, the researchers found a direct association between brain activity during the memorization process and subsequent memory performance. Individuals with a better memory showed a stronger activation of these brain areas. No such association was found for other memory-relevant brain areas in the occipital cortex — they were equally active in individuals with all levels of memory performance.

Statistical brain map of the group-based positive subsequent memory effects. For illustrative purposes, coordinates were placed in left-hemispheric brain regions: A inferior lateral occipital cortex (t = 13.96), B caudal anterior cingulate (t = 35.28), C hippocampus (t = 17.15), D superior lateral occipital cortex/angular gyrus (t = 28.74), E PCC (t = 32.28), F intracalcarine cortex (t = 28.85). The images are corrected for multiple comparisons at the whole brain level (two-sided t-test, p-FWE-corrected <0.05, t-FWE-corrected = 4.848).

The researchers were also able to identify functional networks in the brain that were linked to memory performance. These networks comprise different brain regions that communicate with each other to enable complex processes such as the storage of information.

“The findings help us to better understand how differences in memory performance occur between one individual and another,” said Dr. Léonie Geissmann, the study’s first author, adding that the brain signals of a single individual do not allow for any conclusions to be drawn about their memory performance, however.

According to the researchers, the results are of great importance for future research aimed at linking biological characteristics such as genetic markers to brain signals.

Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases

by Erik Nutma, Nurun Fancy, Maria Weinert, Stergios Tsartsalis, Manuel C. Marzin, Robert C. J. Muirhead, Irene Falk, Marjolein Breur, Joy de Bruin, David Hollaus, Robin Pieterman, Jasper Anink, David Story, Siddharthan Chandran, et al in Nature Communications

Inflammation is the sign that our body is defending itself against an aggression. But when this response escalates, for example in the brain, it can lead to serious neurological or psychiatric diseases. A team from the University of Geneva (UNIGE), the University Hospitals of Geneva (HUG), Imperial College London and Amsterdam UMC, investigated a marker protein targeted by medical imaging to visualise cerebral inflammation, but whose interpretation was still uncertain. The team reveals that a large quantity of this protein goes hand in hand with a large quantity of inflammatory cells, but its presence is not a sign of their overactivation. These results, published in Nature Communications, pave the way for optimal observation of neuroinflammatory processes and a re-reading of previous studies on the subject.

Inflammation is a natural defensive reaction initiated by the immune system. It enables our cells to fight off aggression, such as injury or infection. But this response can also get out of control and lead to the onset of serious pathologies. When it occurs in the brain — in which case it is known as neuroinflammation — this overactivation can play a part in the mechanisms of neurodegenerative diseases (Alzheimer’s, amyotrophic lateral sclerosis, multiple sclerosis) and psychiatric diseases (schizophrenia, bipolar disorder, depression).

In the brain, microglial cells play an important role in inflammation and its potential overactivation. They can be ‘’activated’’ when dysfunction occurs, phagocytize pathological cells or proteins and even produce protective substances. Currently, in medical imaging, only one marker can be used to locate and measure microglia non-invasively and in vivo: the TSPO protein, which is present in these cells. This protein can be observed by Positron Emission Tomography (PET), a common imaging technique.

‘’Hundreds of studies have used PET scans of this protein to explore and quantify microglia. However, no study has succeeded in precisely interpreting the significance of its quantity in the context of an inflammatory reaction,’’ explains Stergios Tsartsalis, senior clinical associate in the Department of Psychiatry at the UNIGE Faculty of Medicine.

Does a large quantity of TSPO correspond to a large quantity of inflammatory cells? Is it a sign of their overactivation? Together with researchers from Imperial College London (Dr David Owen) and Amsterdam UMC (Prof Sandra Amor), Stergios Tsartsalis and members of Prof Philippe Millet’s team from the HUG’s Laboratory of translational imaging in psychiatric neuroscience and the UNIGE’s Group of molecular neuroimaging in psychiatry set out to find out.

The international research team worked on the brains of mouse models of Alzheimer’s disease, amyotrophic lateral sclerosis and multiple sclerosis, and on post-mortem brain samples from patients affected by the same diseases.

‘’We discovered that a high density of TSPO protein is indeed an indicator of a high density of microglia. On the other hand, the observation of TSPO does not allow us to say whether or not the inflammatory cells are overactivated,’’ explains the UNIGE researcher, co-first author of the study.

TSPO gene expression and epigenetic profile in human and mouse macrophages. a, b Forest plot of the meta-analysis for TSPO expression in a mouse and b human myeloid cells treated with a pro-inflammatory stimulus. Statistical significance for individual dataset was done using linear model, the meta-analysis was performed using random-effect model (black square; logFC, horizontal lines; 95% CI, diamond; pooled logFC). c, d Fold change of TSPO mRNA in macrophages after stimulation indicating increases in tspo expression in mice but not in TSPO expression in humans. e, f An increase is observed in tspo expression after stimulation of mouse microglia but not in TSPO in human microglia. g TSPO mRNA count data from RNA sequencing of human monocytes isolated from healthy volunteers (with C/C and T/T genotype at the rs6971 locus) exposed to 100 ng/mL LPS for 24 h shows no effect of genotype on TSPO mRNA. h, i ChIP-seq data, generated from h mouse and i human myeloid cells treated with IFNγ, visualisation of histone modification peaks (H3K27Ac, K4me1) and PU.1 binding peaks at TSPO loci in IFNγ-treated (blue) and baseline (pink) conditions. Yellow vertical shading corresponds to the TSS along with promoter and light blue shading corresponds to the enhancer region of the loci. Biologically independent samples were used for all experiments (c–f n = 3 for all conditions, g n = 5 C/C and n = 6 T/T genotype). Statistical significance in (c–g) was determined by one-way ANOVA or Kruskal–Wallis test when not normally distributed or by a two-tailed unpaired t-test or two-tailed Mann–Whitney U-test when not normally distributed. Bar graphs indicate the mean ± SEM. Box and whiskers mark the 25th to 75th percentiles and min to max values, respectively, with the median indicated.

This discovery highlights the value of medical imaging of TSPO: it makes it possible to identify cases where the neuroinflammatory disease is linked to deregulation in the number of glial cells. In addition, scientists have identified two markers of the state of microglia activation in humans — the LCP2 and TFEC proteins — which pave the way for new medical imaging approaches.

‘’These results represent a further step towards understanding the role of microglia in neuroinflammation. They will help to optimise the focus of future studies and also to review the conclusions of previous research,’’ enthuses Stergios Tsartsalis.

Combined with the significant development of molecular imaging at the UNIGE and the HUG, this study, supported by the Swiss National Science Foundation and the Prof Dr Max Cloëtta Foundation, set the scene for effective observation of the immune mechanisms of neurological and psychiatric diseases, within the two Geneva institutions and beyond.

Functional characterization of Alzheimer’s disease genetic variants in microglia

by Xiaoyu Yang, Jia Wen, Han Yang, Ian R. Jones, Xiaodong Zhu, Weifang Liu, Bingkun Li, Claire D. Clelland, Wenjie Luo, Man Ying Wong, Xingjie Ren, Xiekui Cui, Michael Song, Hongjiang Liu, Cady Chen, Nicolas Eng, Mirunalini Ravichandran, Yang Sun, David Lee, Eric Van Buren, Min-Zhi Jiang, Candace S. Y. Chan, Chun Jimmie Ye, Rushika M. Perera, Li Gan, Yun Li, Yin Shen in Nature Genetics

Scientists studying Alzheimer’s disease (AD) have identified thousands of genetic variants in the genome in the development of this progressive neurodegenerative disease.

These variants are predominantly located in genomic regions that do not code for proteins, making it difficult to understand which variants confer individuals’ risk of AD. Non-coding variants were once thought to be “junk DNA” by scientists. In recent years, these variants have been appreciated for playing crucial roles in controlling gene expression across tissues and cell types. However, linking these non-coding variants to the genes they regulate and effects on AD-related functions is a daunting task.

Now, researchers at the University of North Carolina at Chapel Hill and The University of California, San Francisco, have identified the connections of risk variants with functions in microglia and then how they may contribute to AD.

“Microglia are brain’s immune cells and are critically important for AD,” said Yun Li, professor of genetics and biostatistics in the UNC School of Medicine and UNC Gillings School of Global Public Health. “Our study focuses squarely on the critical genomic regions that are important for regulating microglia cells. These variants and regions we’ve uncovered will serve as a great starting point for conducting further experiments in microglia.”

Li and Yin Shen, PhD, associate professor at the Institute of Human Genetics and the Department of Neurology at UC-San Francisco, and their teams performed a detailed analysis in microglia of potential functional regions harboring genetic variants associated with AD. They discovered 181 new regions of interest containing 308 prioritized variants, which were previously not considered to play a role in Alzheimer’s disease.

Li and her colleagues started from 37 genetic loci associated with AD to prioritize risk variants and their residing potential functional regions — termed candidate cis-regulatory regions (cCRE) — in microglia, they performed a process called fine-mapping. One locus at a time, they studied the associated variants with a special consideration of epigenetic signatures and 3D genome interaction annotations indicating their likelihood of functioning in microglia.

After prioritizing variants that are most likely to exert their effect on AD through gene regulatory function in microglia, they performed CRISPR interference (CRISPRi) screening experiments to nail down the exact regions that affect microglia gene expression using human pluripotent stem cell differentiated microglia.

Using this epigenomic editing technology, the researchers can “perturb” candidate regions to see whether any tested genomic regions can impact downstream gene expression. They found that turning off one region can often impact a “whole neighborhood” of genes, much like a blackout on a power grid.

“We have been asking the wrong question,” said Li. “We should be asking what the targeting gene or genes of these variants are affecting the microglia. Sometimes, one variant may affect the expression of multiple genes in the neighborhood.”

Additionally, each region could contain several AD-associated genetic variants. Researchers then needed to pinpoint which variants are causal among the many that were identified through genetic analysis. Such precision is crucial for understanding the mechanisms by which non-coding variants contribute to the development of AD.

The team employed a cutting-edge genome editing technique — prime editing, which allows them to introduce one single DNA base substitution at a time and to assess individual variant function at the TSPAN14 AD risk locus. Through this method, they were able to identify one specific variant, differentiating it from another which is almost perfectly correlated and in the same cCRE region, to be responsible for TSPAN14 expression.

More importantly, the responsible variant further negatively affected a cascade of downstream cellular processes, including the maturation of ADAM10 protein and soluble TREM2 shredding in microglia. Since all three aforementioned genes are known to be risk genes for AD, the study successfully links an AD non-coding variant to functions in microglia beyond control of gene expression.

Their research findings, Li said, will serve as a new foundation from which other researchers can discover more causal variants of AD, predict disease risks, and develop more effective therapies. This work was also made possible in collaboration with Li Gan’s group from the Helen and Robert Appel Alzheimer’s Disease Research Institute, Weill Cornell Medical College.

Reward expectations direct learning and drive operant matching in Drosophila

by Adithya E. Rajagopalan, Ran Darshan, Karen L. Hibbard, James E. Fitzgerald, Glenn C. Turner in Proceedings of the National Academy of Sciences

Like many collectors of L.P. records, James Fitzgerald’s brother-in-law has a favorite store where he consistently finds the best vinyl for his collection. But there are times when he spends hours at the store and comes up empty. He also knows that occasionally he should venture to the record store on the other side of town, where he sometimes scores a hard-to-find gem that was stocked since his last visit.

Fitzgerald’s brother-in-law is making a calculation: weighing probable outcomes to guide his behavior. His favorite record store rewards him more frequently, so he visits that store the most. The second-tier store is less likely to reward him, so he visits that store only occasionally.

Glenn Turner, who like Fitzgerald is a neuroscientist and group leader at HHMI’s Janelia Research Campus, says this “record foraging” habit is a perfect example of a type of behavior called matching that is pervasive in the animal kingdom. Instead of vinyl, non-hipster animals like mice and flies forage for food, using sensory cues like odors to evaluate food quality from a distance.

But, while matching has been observed in everything from pigeons to mice to humans, it was unclear how the brain carried out this value-based decision-making. Researchers had previously proposed a theory for how that might happen, but the idea hadn’t been tested in the real world.

Now, a team of Janelia researchers that includes Fitzgerald, Turner, Janelia Graduate Scholar Adithya Rajagopalan, former Janelia Fellow Ran Darshan and Research Specialist Karen Hibbard has confirmed that the proposed theory works. Rajagopalan’s experiments showed that, like Fitzgerald’s brother-in-law, fruit flies can make decisions based on their expectations about the likelihood of a reward. The team also pinpointed the site in the fly brain where these value adjustments are made, enabling them to directly test this theory on the level of neural circuits.

“We found that flies are using expectation to assign value to their world,” Turner says. “It also really nicely connects back to this theoretical work that was so elegant and explains this widespread phenomenon.”

Uncovering how the fly brain carries out this ubiquitous behavior could help scientists better understand how similar decision-making happens in the brains of larger animals, including humans. Decision-making goes awry in diseases like addiction, so understanding how this process works in simpler brains has broad value, according to the researchers.

“The kinds of ideas and the theoretical framework that we have identified in this paper feel like a seed for evolution to build on in larger organisms, where more layers are added to allow for more complex behaviors,” says Rajagopalan, the first author of a new paper describing the work.

Fruit flies, whose brains have been well studied and mapped, were an appealing choice for examining matching and its underlying mechanisms. But first, the team had to design a way to observe fruit fly decisions.

Rajagopalan, who came to the Turner Lab through a joint graduate program with Johns Hopkins University, spearheaded the project. He designed an experiment where a single fly enters one arm of a symmetrical Y-shaped arena. Odors are pumped into the other two arms of the Y. The fly chooses to follow one odor or the other and is rewarded — in this case by having its sugar-sensing neurons activated — but with different probabilities: One odor might translate into a reward 80 percent of the time, while the other odor might yield a reward 20 percent of the time.

The researchers found that the fly learned to expect the rewards in the same proportions they were presented and then made its choice based on those expectations. These actions give the matching behavior its name: 80 percent of the time, the fly chose the odor that gives 80 percent of the rewards. And 20 percent of the time, it chose the odor that yields 20 percent of the rewards.

The team tracked the behavior to specific synapses in the mushroom body, a region of the fly brain responsible for learning and memory. This enabled them to create a model of how the brain carries out this behavior, based on the theory of matching. In this theory, the values associated with different choices are learned through changes in synaptic strength: Synaptic connections are strengthened or weakened in proportion to the difference between expected and received reward. The team’s model based on this theory and the fly’s behavior allowed them to demonstrate how individual synapses are changing to enable value-based decision-making.

The new work emphasizes the important interplay between experiment and theory, converging on a description of the rules governing how an animal learns — an outcome that the researchers say is satisfying on both a conceptual and mechanistic level.

“To be able to see that you can get these sophisticated economic decisions through this simple mechanistic explanation about how synapses are changing is a great illustration of what mechanistic cognitive neuroscience can mean,” Fitzgerald says. “We’re taking this universal property and using the strengths of these small animals to really nail it mechanistically.”

Modular architecture facilitates noise-driven control of synchrony in neuronal networks

by Hideaki Yamamoto, F. Paul Spitzner, Taiki Takemuro, Victor Buendía, Hakuba Murota, Carla Morante, Tomohiro Konno, Shigeo Sato, Ayumi Hirano-Iwata, Anna Levina, Viola Priesemann, Miguel A. Muñoz, Johannes Zierenberg, Jordi Soriano in Science Advances

Scientists have found that the outer cortex of the mammalian brain is able to maintain control over all the external inputs it receives because of how its nerve networks are organized into interconnected but independently functioning ‘modules.’ The finding was the result of a unique experimental system that grew neurons, the functional elements of the brain, on microfabricated glass surfaces. Computational models then described the experimental observations. The work, by an international team of researchers led by Hideaki Yamamoto from Tohoku University and Jordi Soriano from the University of Barcelona, was published in the journal Science Advances.

The cortex is the outer layer of the brain that contains a large number of neurons responsible for functions such as sensory perception, motor control, and higher-order computation. “Neuronal networks, like those in the mammalian cortex, need to be able to segregate inputs from specialized circuits, and to integrate inputs from multiple circuits,” says Yamamoto. But it has not been clear how the cortex is able to support these two very different processing paradigms.

To study this, the researchers guided cortical neurons to form a network containing multiple sub-groups, or modules. The lab-grown neurons were engineered to express light-sensitive proteins so they could be stimulated using a specific wavelength of light.

The team found that the more well-formed modular networks had large responses to localized light stimulation, while those with less ‘modularity’ responded to all stimulus in an excessively synchronized way.

For this effect to happen, the applied light stimulation was delivered to different parts of the network at different times, to mimic the real-life inputs to the cortex from subcortical parts of the brain. However, when the overall excitability of the entire network was raised simultaneously, by increasing potassium concentration across the entire network, this did trigger a synchronous, coordinated activity response across the entirety of the networks.

Optogenetic stimulation on modular neuronal cultures increases the variability in collective network dynamics. (A) Phase-contrast image of a representative single-bond modular network. Neurons appear as dark round objects with a white contour. Ten neurons were selected from the bottom module pair (orange box) and optogenetically targeted in a random manner. (B) Representative fluorescence traces and inferred spike events (dots) of three neurons along 1 min. © Sketch of the experimental setup. Neuronal cultures were transfected with ChrimsonR for optogenetic stimulation (orange arrow) and GCaMP6s for simultaneous activity monitoring (blue and green arrows). (D) Pre-stimulation raster plot (top panel) of network spontaneous activity, with neurons grouped according to their module, and the corresponding population activity (bottom). (E) Corresponding data upon optogenetic stimulation, wherein population activity markedly increases in variability. Targeted modules are marked as orange bands. (F) Spontaneous activity post-stimulation, with a return to strong network-wide bursting. (G) Representative snapshots of calcium imaging recordings for the above data. All modules activate synchronously without stimulation. Upon stimulation, activity events extend over individual neurons, multiple modules, or all modules. (H and I) Raster plot and population activity before and during chemical stimulation. Chemical stimulation increases the frequency of events but maintains the network-wide activity. (J) Effect of optogenetic and chemical stimulation on bursting median event sizes, median correlation coefficients, and functional complexity (paired-sample t test, two-sided). For chemical stimulation with N = 4, no test was performed.

“This balance between locally segregated activity and globally integrated activity is thought to be important for the brain to be able to expand its capacity for information representation with limited resources,” explains Yamamoto.

The discovery not only helps scientists understand the interplay between structure and function of the mammalian brain but can also help improve the development of artificial neural networks for use in machine learning research.

A cholinergic circuit that relieves pain despite opioid tolerance

by Shivang Sullere, Alissa Kunczt, Daniel S. McGehee in Neuron

The opioid epidemic in the United States has exacted an incalculable toll on individuals and communities, creating an urgent need for alternative painkillers. The search for non-opioid treatments is crucial, not only to mitigate the risks of addiction and overdose, but also to develop pain management tools that remain effective without inducing tolerance and other challenging side effects in patients.

New research from the University of Chicago identified an alternative signaling pathway in the brain of mice that relieves pain, even in animals that have developed tolerance to opioids. The study, published in Neuron in September, also showed that pain relief through this route did not induce tolerance, did not create withdrawals symptoms after treatment was stopped, and did not activate reward systems, limiting risk for addiction and making it a viable path to developing effective, non-opioid pain relief.

“There are multiple categories of non-opioid treatments, but the bad news is that nothing currently compares to opioids for the level of pain relief,” said Daniel McGehee, PhD, Professor of Anesthesia and Critical Care at UChicago and senior author of the new study. “Any alternative is a welcome option, and we have found pain control circuitry here that can produce relief similar to what we see with opioid activity, without the downsides.”

The ventrolateral periaqueductal gray (vlPAG) is an area of the brain that serves as an important crossroads of systems that control pain. Previous research has shown that electrical stimulation and pharmacological treatments targeting this region can relieve pain, although the non-opioid circuits that alter pain through changes in activity in this part of the brain are less well-studied. One of these circuits involves the neurotransmitter acetylcholine, which affects activity in multiple parts of the brain. Targeting acetylcholine receptors can change pain responses, but the mechanisms by which naturally produced acetylcholine regulates pain control circuitry in the vIPAG had not been explored.

McGehee and Shivang Sullere, PhD, a previous graduate student in the Committee on Neurobiology at UChicago, now a postdoctoral scholar at the Harvard Medical School and the new study’s first author, investigated the dynamics of how acetylcholine is released in this area of the brain under various pain states, like inflammation, chronic neuropathy, or acute pain. McGehee’s lab published a paper in 2017 showing that targeting an acetylcholine receptor in the vIPAG called alpha-7 (⍺7) produced an analgesic effect. One might expect that the body would take advantage of this and release more acetylcholine in a painful scenario, but instead, the researchers saw the opposite effect — it was being suppressed. The team then set out to understand how and why this was happening.

The ⍺7 receptor is usually an excitatory receptor, meaning that it generates more activity in the nervous system. But when the researchers injected a drug that stimulates ⍺7 into the mice, the cells’ initial excited state quickly gave way to a prolonged quiet state, producing an analgesic effect that lasted for several hours.

“That was a huge and extremely unexpected outcome,” McGehee said. “Persistent inhibition was not on our radar at all. It was always a conundrum to me, but we saw that there is recruitment of another signaling pathway that is altering potassium channel function and causing these cells to shut down.”

When the team tested the effects of boosting acetylcholine in mice that had tolerance to opioids, they saw the same long-lasting analgesic effects. That’s because the acetylcholine receptor is part of a different pathway than that used by opioids — the two operate independently, and if tolerance develops in the opioid circuits, acetylcholine’s effects are not altered. The animals also didn’t show signs of dependence or preference for environments where they received the drug that stimulated more acetylcholine in the absence of pain, which is a good sign that it doesn’t have addictive properties.

Separate imaging experiments also showed that higher levels of activity in cells that express ⍺7 correlated with higher levels of pain experienced by the animals: when those same cells were suppressed, pain was reduced as well.

“Not only do these cells relieve pain, they also accurately mirror the pain state of the organism. Through imaging methods, we can reproducibly monitor these neurons and acetylcholine in the vlPAG. This provides us a valuable biomarker for the pain state of an organism,” Sullere said. “This unexplored role of acetylcholine also points towards its potential involvement in the central sensitization processes that contribute to the development of chronic pain conditions. Modifying acetylcholine signaling provides an opportunity to relieve pain and prevent the establishment of the chronic pain state.”

The results of this work point to multiple opportunities to develop new pain-relieving drugs, either by stimulating the release of acetylcholine or targeting ⍺7 receptors. McGehee said medications targeting these receptors have been tested for multiple diseases, but not yet as painkillers.

“This is a potentially valuable target for new development of analgesics,” he said. “We see that inhibiting these cells is important in terms of controlling pain, and it’s a very profound mechanism that works beautifully and to a similar degree to what we see with opioids.”

Stepwise emergence of the neuronal gene expression program in early animal evolution

by Sebastián R. Najle, Xavier Grau-Bové, Anamaria Elek, Cristina Navarrete, Damiano Cianferoni, Cristina Chiva, Didac Cañas-Armenteros, Arrate Mallabiabarrena, Kai Kamm, Eduard Sabidó, Harald Gruber-Vodicka, Bernd Schierwater, Luis Serrano, Arnau Sebé-Pedrós in Cell

A study in the journal Cell sheds new light on the evolution of neurons, focusing on the placozoans, a millimetre-sized marine animal. Researchers at the Centre for Genomic Regulation in Barcelona find evidence that specialized secretory cells found in these unique and ancient creatures may have given rise to neurons in more complex animals.

Placozoans are tiny animals, around the size of a large grain of sand, which graze on algae and microbes living on the surface of rocks and other substrates found in shallow, warm seas. The blob-like and pancake-shaped creatures are so simple that they live without any body parts or organs. These animals, thought to have first appeared on Earth around 800 million years ago, are one of the five main lineages of animals alongside Ctenophora (comb jellies), Porifera (sponges), Cnidaria (corals, sea anemones and jellyfish) and Bilateria (all other animals).

The sea creatures coordinate their behaviour thanks to peptidergic cells, special types of cells that release small peptides which can direct the animal’s movement or feeding. Driven by the intrigue of the origin of these cells, the authors of the study employed an array of molecular techniques and computational models to understand how placozoan cell types evolved and piece together how our ancient ancestors might have looked and functioned.

The researchers first made a map of all the different placozoan cell types, annotating their characteristics across four different species. Each cell type has a specialised role which comes from certain sets of genes. The maps or ‘cell atlases’ allowed researchers to chart clusters or ‘modules’ of these genes. They then created a map of the regulatory regions in DNA that control these gene modules, revealing a clear picture about what each cell does and how they work together. Finally, they carried out cross-species comparisons to reconstruct how the cell types evolved.

The research showed that the main nine cell types in placozoans appear to be connected by many “in-between” cell types which change from one type to another. The cells grow and divide, maintaining the delicate balance of cell types required for the animal to move and eat. The researchers also found fourteen different types of peptidergic cells, but these were different to all other cells, showing no in-between types or any signs of growth or division.

Surprisingly, the peptidergic cells shared many similarities to neurons — a cell type which didn’t appear until many millions of years later in more advanced animals such as and bilateria. Cross-species analyses revealed these similarities are unique to placozoans and do not appear in other early-branching animals such as sponges or comb jellies (ctenophores).

The similarities between peptidergic cells and neurons were threefold. First, the researchers found that these placozoan cells differentiate from a population of progenitor epithelial cells via developmental signals that resemble neurogenesis, the process by which new neurons are formed, in cnidaria and bilateria.

Second, they found that peptidergic cells have many gene modules required to build the part of a neuron which can send out a message (the pre-synaptic scaffold). However, these cells are far from being a true neuron, as they lack the components for the receiving end of a neuronal message (post-synaptic) or the components required for conducting electrical signals.

Finally, the authors used deep learning techniques to show that placozoan cell types communicate with each other using a system in cells where specific proteins, called GPCRs (G-protein coupled receptors), detect outside signals and start a series of reactions inside the cell. These outside signals are mediated by neuropeptides, chemical messengers used by neurons in many different physiological processes.

“We were astounded by the parallels,” says Dr. Sebastián R. Najle, co-first author of the study and postdoctoral researcher at the Centre for Genomic Regulation. “The placozoan peptidergic cells have many similarities to primitive neuronal cells, even if they aren’t quite there yet. It’s like looking at an evolutionary stepping stone.”

The study demonstrates that the building blocks of the neuron were forming 800 million years ago in ancestral animals grazing inconspicuously in the shallow seas of ancient Earth. From an evolutionary point of view, early neurons might have started as something like the peptidergic secretory cells of today’s placozoans. These cells communicated using neuropeptides, but eventually gained new gene modules which enabled cells to create post-synaptic scaffolds, form axons and dendrites and create ion channels that generate fast electrical signals — innovations which were critical for the dawn of the neuron around one hundred million years after the ancestors of placozoans first appeared on Earth.

However, the complete evolutionary story of nerve systems is still to be told. The first modern neuron is thought to have originated in the common ancestor of cnidarians and bilaterians around 650 million years ago. And yet, neuronal-like cells exist in ctenophores, although they have important structural differences and lack the expression of most genes found in modern neurons. The presence of some of these neuronal genes in the cells of placozoans and their absence in ctenophores raises fresh questions about the evolutionary trajectory of neurons.

“Placozoans lack neurons, but we’ve now found striking molecular similarities with our neural cells. Ctenophores have neural nets, with key differences and similarities with our own. Did neurons evolve once and then diverge, or more than once, in parallel? Are they a mosaic, where each piece has a different origin? These are open questions that remain to be addressed,” says Dr. Xavier Grau-Bové, co-first author of the study and postdoctoral researcher at the Centre for Genomic Regulation.

3D Functional Neuronal Networks in Free‐Standing Bioprinted Hydrogel Constructs

by Yue Yao, Harold A. Coleman, Laurence Meagher, John S. Forsythe, Helena C. Parkington in Advanced Healthcare Materials

Monash University Engineering researchers have successfully used “bioinks” containing living nerve cells (neurons) to print 3D nerve networks that can grow in the laboratory and transmit and respond to nerve signals.

Using a tissue engineering approach, and bioprinting with two bioinks containing living cells and non-cell materials respectively, the researchers were able to mimic the arrangement of grey matter and white matter seen in the brain.

Professor John Forsythe of the Department of Materials Science and Engineering, who is leading the research, said while two-dimensional nerve cell cultures have previously been used to study the formation of nerve networks and disease mechanisms, those relatively flat structures don’t reflect the way neurons grow and interact with their surroundings.

“The networks grown in this research closely replicated the 3D nature of circuits in a living brain, where nerve cells extend processes called neurites to form connections between different layers of the cortex,” said Professor Forsythe.

“We found that the projections growing from neurons in the printed ‘grey matter’ or cellular layer readily grew through the ‘white matter’ layer and used it as a ‘highway’ to communicate with neurons in other layers.

“Not only were we able to construct a basic layout similar to what we see in regions of the brain, we found that the neurons actually behaved and performed in a similar manner.”

Sensitive electrophysiological measurements confirmed spontaneous nerve-like activity taking place in the 3D neuronal networks in addition to responses evoked by electrical and drug stimulation.

The presence of detectable electrical activity in tissue engineered 3D networks represents a significant step forward in the field of neuroscience and bioprinting.

Bioprinted 3D neural networks are likely to be a promising platform for studying how nerves and nerve networks form and grow, investigating how some diseases affect neurotransmission, and screening drugs for their effects on nerve cells and the nervous system.

Bioprinted cortical neurons and astrocytes after in vitro culture at 7 DIV. A) Cross-section view of bioprinted structure consisting of cellular (green) and acellular (grey) strands. B) Maximum intensity projection of patterned structure: cellular (left), acellular (middle), and cellular (right) strands. Neurons (NeuN, green), astrocytes (GFAP, red), and nuclei (DAPI, blue) were colocalized and developed complex structures. Axons (Tuj1, green) originating from the left and right cellular strands projected across the central acellular strand. C) Depth-coding of Tuj1/NeuN showed the development of axonal projections across strands. White arrows indicate neurites that projected across the acellular strand. D) Depth-coding of DAPI showed localization of cell nuclei. E) Confocal image in 3D. Depth-coding was shown using a color bar: white, closest to the glass substrate, and purple, 193 µm away from the substrate. Scale bar, 100 µm.

Electric shock causes a fleeing-like persistent behavioral response in the nematode Caenorhabditis elegans

by Tee LF, Young JJ, Maruyama K, et al. . Barrios A, ed GENETICS

Researchers have found that worms start moving at an unusually high speed when stimulated with alternating current.

Brain research is one of the most crucial fields in modern life sciences, and “emotion” is one of its major topics. Studying emotions in animals has long been considered challenging with limited research mostly focused on ‘fear’ in mice and rats. However, since the 2010s, it has been increasingly reported in scientific papers that even crayfish and flies may have brain functions resembling emotions by focusing on several characteristics of their behavior, such as persistence and valence. For instance, when an animal experiences a dangerous situation like being attacked by a predator (a negative valence) even for a short period, the animal’s behavior may be to stay in a safe place, ignoring normally attractive smells of food even if hungry, for a certain length of time (persistence), which can be regulated by a primitive form of emotion. However, the details of these fundamental “emotion mechanisms” remain largely undisclosed.

An international research team from Nagoya City University (Japan) and Mills College at Northeastern University (USA) has revealed the possibility that the roundworm Caenorhabditis elegans possesses basic “emotions.” They used the worms because worms have been used for detailed analysis of basic functions such as perception, memory, and even decision-making at cellular and genetic levels. The team initially discovered that when worms are subjected to alternating current stimulation, worms start moving at an unexpectedly high speed. Interestingly, the team also found that this “running” response persisted for 1–2 minutes even after the electrical stimulation for a few seconds was terminated. In animals in general, when a stimulus is stopped, the response to that stimulus usually ceases immediately. (Otherwise, the perception of stimuli such as sounds or visual scenes would linger.) Therefore, the reaction of “continuing to run even after the stimulus stops” is exceptional.

Furthermore, during and after the electric stimulation, the team found that the worms ignore their food bacteria, which provide crucial environmental information. This suggests that while the presence or absence of their food bacteria is usually crucial, the danger posed by electrical shocks, a survival-threatening stimulus, is even more important. In other words, when worms sense the dangerous stimulus of an electrical shock, their highest survival priority is to escape from that location. To achieve this, the brain’s functioning seems to persistently change, including ignoring the usually significant “food” in order to escape danger. This suggests that the phenomenon of “worms continuing to run due to short-term electrical stimulation” reflects basic “emotions.”

Furthermore, through genetic analysis, particularly leveraging the advantages of worms, the team revealed that mutants unable to produce neuropeptides, equivalent to our hormones, exhibited a longer duration of continuous running in response to electrical stimulation compared to normal worms. This result indicates that the continuous state in response to danger is regulated to end at the appropriate time. Indeed, if we experience excitement or fear that persists for a very long period, it disrupts our daily lives. Therefore, the findings suggest that our emotions, such as “excitement,” “happiness,” or “sadness,” induced by stimuli, may not be naturally destined to fade away with time, but are controlled by an active mechanism involving genes.

This study demonstrates that using worms can offer detailed insights into the genetic mechanisms underlying primitive “emotions”. Many of the genes at work in worms are known to have counterparts in humans and other organisms, so studying worms can offer significant clues about the genes involved in the basis of “emotions.” Specifically, conditions like depression, classified as mood disorders, can be interpreted as states where negative emotions are excessively and persistently maintained due to the inability to effectively process experienced stimuli. If novel genes related to emotions are discovered through worm research, these genes could potentially become targets for new treatments of emotional disorders.

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