RNA barcodes enable high-speed mapping of connections in the brain

Comingling RNA barcodes, each correlating to a neuron, indicate where neurons connect in the brain, letting researchers map neural connection with speed, scale and resolution.
Illustration Credit: Michael Vincent.

Scientific Frontline: Extended "At a Glance" Summary: Connectome-seq

The Core Concept: Connectome-seq is a high-throughput brain-mapping platform that employs unique RNA "barcodes" to tag individual neurons, facilitating the simultaneous mapping of thousands of neural connections at single-synapse resolution.

Key Distinction/Mechanism: Traditional brain mapping relies on labor-intensive tissue slicing and microscopic imaging, while older sequencing-based techniques only trace a neuron's general trajectory without identifying its specific synaptic partners. In contrast, Connectome-seq translates spatial connectivity into a sequencing problem. It uses specialized proteins to transport and anchor unique RNA barcodes directly at the synapse. By isolating these synaptic junctions and utilizing high-throughput sequencing, researchers can read which barcode pairs colocalize, precisely revealing which neurons are connected.

Major Frameworks/Components:

• RNA Barcoding: The assignment of unique molecular identifiers to distinctly tag individual neuron cells within a network.
• Synaptic Anchoring: The deployment of specialized transport proteins to carry RNA barcodes from the neuron's cell body and secure them at the synaptic junctions.
• High-Throughput Sequencing: The computational and molecular process of isolating synaptic junctions and sequencing the localized RNA to read out connected barcode pairs at scale.
• Pontocerebellar Circuit Mapping: The initial validation of the platform, which successfully mapped over 1,000 neurons in a specific mouse brain circuit and uncovered previously unknown connectivity patterns between cell types.

What Is: Connectomics

Scientific Frontline: Extended "At a Glance" Summary: Brain Wiring Explained

The Core Concept: Connectomics is the production, study, and comprehensive analysis of connectomes—the exquisitely detailed, complete wiring diagrams of an organism's nervous system. It represents a paradigm shift that models the brain not as a collection of isolated regions, but as a dense, dynamic, and interconnected network in order to uncover the physical substrate of consciousness, memory, and behavior.

Key Distinction/Mechanism: Unlike traditional neuroscience, which typically examines isolated cellular fragments or low-resolution functional regions, connectomics merges systems biology with big data and artificial intelligence. It cross-references static structural anatomy (the physical "wires") with functional connectivity (synchronized electrical activity) to trace precise neural circuitry and network communication patterns.

Origin/History: The field's foundation was laid in 1986 with the mapping of the Caenorhabditis elegans nematode (302 neurons). The connectome concept was globally popularized in 2010 by computational neuroscientist Sebastian Seung. The field recently achieved unprecedented scaling milestones, including the 2024 complete mapping of the adult fruit fly brain (over 50 million synaptic connections) by the FlyWire Consortium, and the 2026 "H01" petascale reconstruction of a cubic millimeter of the human temporal cortex by Harvard University and Google Research.

Deciphering the secrets of the brain

Adrian Wanner is delighted with the exceptional international recognition from the US National Institute of Health (NIH).
Photo Credit: Scanderbeg Sauer Photography

Scientific Frontline: Extended "At a Glance" Summary: Mapping the Brain's Connectome

The Core Concept: Mapping the brain's connectome is the process of creating a comprehensive structural wiring diagram of the brain's billions of neurons and their synaptic connections to understand how information is processed.

Key Distinction/Mechanism: Unlike traditional methodologies that rely on fragile, ultra-thin tissue slices prone to physical handling errors, this advanced approach utilizes thicker tissue sections. It employs a multi-beam scanning transmission electron microscope combined with broadband ion beam polishing—a technique adapted from microchip manufacturing—to iteratively remove nanometer-thin layers. This highly stable process generates superior high-resolution data, allowing artificial intelligence (AI) algorithms to reconstruct 3D neuronal networks far more accurately.

Origin/History: The foundational milestone in connectomics was the manual mapping of the nematode C. elegans (comprising just 302 nerve cells), a rigorous process completed in 1986. Building upon this history, the US National Institutes of Health (NIH) BRAIN Initiative recently awarded a $2.6 million grant to researchers at the Paul Scherrer Institute (PSI) and the Francis Crick Institute to modernize, scale, and automate this process for the mouse brain.

Network neuroscience theory best predictor of intelligence

U. of I. Professor Aron Barbey, pictured, and co-author Evan Anderson found that taking into account the features of the whole brain – rather than focusing on individual regions or networks – allows the most accurate predictions of intelligence.     
Photo Credit: Fred Zwicky

Scientific Frontline: Extended "At a Glance" Summary: Network Neuroscience Theory

The Core Concept: Network neuroscience theory posits that human general intelligence and problem-solving capabilities emerge from the global architecture of the brain rather than from isolated regions. It suggests that cognitive aptitude is a product of systemwide neural network efficiency and flexibility.

Key Distinction/Mechanism: While historical models localized intelligence to specific brain regions (such as the prefrontal cortex) or focused on isolated neural pathways, this theory evaluates the entire brain configuration. It accounts for both "strong" connections (highly connected hubs used for familiar tasks) and "weak" connections (flexible linkages utilized for adaptive, novel problem-solving).

Major Frameworks/Components: 

• Connectome-Based Predictive Modeling: An analytical framework used to systematically compare how well different theories predict intelligence based on connectivity data.
• Resting-State Functional MRI (fMRI): Brain imaging utilized to map the intrinsic biological infrastructure of the mind while active at rest.
• Intrinsic Brain Networks: Foundational systems assessed in the research, including the frontoparietal network (cognitive control), the dorsal attention network (spatial awareness), and the salience network (stimuli direction).
• Global Information Processing: The overarching mechanism indicating that overall whole-brain coordination is superior at overcoming cognitive challenges than localized processing.

Disrupted flow of brain fluid may underlie neurodevelopmental disorders

The addition of a magenta tracer molecule illustrates the flow of fluid around the brain, revealing that neurons in the hippocampus (cyan), the brain’s memory center, are awash in fluid. Researchers at Washington University School of Medicine in St. Louis have discovered that this fluid flows to areas critical for normal brain development and function, suggesting that disruptions to its circulation may play an underrecognized role in neurodevelopmental disorders.
Photo Credit: Shelei Pan and Peter Yang/School of Medicine

The brain floats in a sea of fluid that cushions it against injury, supplies it with nutrients and carries away waste. Disruptions to the normal ebb and flow of the fluid have been linked to neurological conditions including Alzheimer’s disease and hydrocephalus, a disorder involving excess fluid around the brain.

Researchers at Washington University School of Medicine in St. Louis created a new technique for tracking circulation patterns of fluid through the brain and discovered, in rodents, that it flows to areas critical for normal brain development and function. Further, the scientists found that circulation appears abnormal in young rats with hydrocephalus, a condition associated with cognitive deficits in children.

The findings, available online in Nature Communications, suggest that the fluid that bathes the brain — known as cerebrospinal fluid — may play an underrecognized role in normal brain development and neurodevelopmental disorders.

The dialogue happening in our heads: New study decodes how regions in the brain communicate with each other

Snapshot of the constantly changing signal flow in the human brain.
Image Credit: © e-Lab

Scientific Frontline: "At a Glance" Summary

• Main Discovery: The human hippocampus and amygdala actively broadcast signals to the cerebral cortex during both sleep and wakefulness, contrary to previous rodent models that suggested a reversal of signal flow during sleep.
• Methodology: Researchers utilized intracranial EEG measurements from temporarily implanted electrodes in human subjects, applying short, imperceptible electrical impulses to track causal signal flow between deep brain regions and the cerebral cortex.
• Key Data: Observations recorded over a continuous 24-hour period from 15 adult patients demonstrated that deep brain emotion and memory centers transmit approximately twice as many signals as they receive, tracking movement with millisecond accuracy.
• Significance: The findings establish a dynamic map of structural brain connectivity, enabling direct and causal measurement of signal directionality rather than relying on time-averaged or indirect simultaneous activity metrics.
• Future Application: Insights from this research aim to facilitate the development of highly precise neurostimulation devices and targeted brain therapies to intervene in dysfunctional networks associated with epilepsy and neuropsychiatric disorders.
• Branch of Science: Neuroscience and Neurology
• Additional Detail: The research represents the first systematic mapping of directed cortico-limbic dialogue in the human brain, fundamentally confirming that memory and emotion centers disseminate, rather than just process, information.

Study maps the role of a master regulator in early brain development

Image Credit: Scientific Frontline

Scientific Frontline: "At a Glance" Summary

• Main Discovery: The gene HNRNPU functions as a central orchestrator in early human brain development, coordinating essential processes such as gene expression, RNA processing, protein synthesis, and epigenetic regulation.
• Methodology: Researchers employed human induced pluripotent stem cell-derived neural models and applied advanced proteomics, RNA-mapping, and genome-wide DNA methylation profiling to assess the impact of reduced HNRNPU levels on cellular function.
• Key Data: Analysis revealed hundreds of molecules interacting with HNRNPU and identified 19 specific genes affected at multiple regulatory levels—including RNA binding and DNA methylation—that are vital for neuronal growth and migration.
• Significance: The study elucidates the mechanism behind severe neurodevelopmental disorders associated with HNRNPU variants, demonstrating that its absence disrupts methylation patterns at gene promoters and hinders the transition of neural cells into mature states.
• Future Application: The 19 identified downstream genes and the mapped molecular landscape serve as concrete targets for future mechanistic studies and therapeutic interventions aimed at mitigating the effects of HNRNPU deficiency.
• Branch of Science: Molecular Neuroscience and Epigenetics
• Additional Detail: A critical interaction was observed between HNRNPU and the SWI/SNF (BAF) chromatin-remodeling complex, a group of proteins known to govern gene activation during brain development.

Discrimination alters brain-gut ‘crosstalk,’ prompting poor food choices and increased health risks

Illustration Credit: julientromeur

People frequently exposed to racial or ethnic discrimination may be more susceptible to obesity and related health risks in part because of a stress response that changes biological processes and how we process food cues. These are findings from UCLA researchers conducting what is believed to be the first study directly examining effects of discrimination on responses to different types of food as influenced by the brain-gut-microbiome (BGM) system.

The changes appear to increase activation in regions of the brain associated with reward and self-indulgence – like seeking “feel-good” sensations from “comfort foods” – while decreasing activity in areas involved in decision making and self-control.

“We examined complex relationships between self-reported discrimination exposure and poor food choices, and we can see these processes lead to increased cravings for unhealthy foods, especially sweet foods, but also manifested as alterations in the bidirectional communication between the brain and the gut microbiome,” said Arpana Gupta, PhD, a researcher and co-director of the UCLA Goodman-Luskin Microbiome Center and the UCLA G. Oppenheimer Center for Neurobiology of Stress and Resilience.

Different pediatric brain tumors originate from the same type of cell

Miao Zhao and Fredrik Swartling have shown that pediatric brain tumors from different parts of the brain share the same biological origin.
Photo Credit: Anjali Sivakumar

Scientific Frontline: Extended "At a Glance" Summary: Common Cellular Origin of Pediatric Brain Tumors

The Core Concept: Severe pediatric brain tumors that develop in entirely distinct anatomical regions—such as the pineal gland, retina, and cerebellum—actually arise from the same type of immature precursor cell containing photoreceptor features.

Key Distinction/Mechanism: While historically tumors like pineoblastoma, retinoblastoma, and medulloblastoma were viewed as biologically independent due to their varied anatomical locations, advanced molecular profiling demonstrates they share a unified origin in light-sensitive precursor cells. This mechanism distinguishes them biologically from other, unassociated tumors developing within those exact same brain regions.

Major Frameworks/Components: 

• Single-Cell Analysis: The use of advanced molecular mapping to profile and compare the biological origins of diverse patient tumors.
• Photoreceptor Signature: The identification of specific proteins associated with light-sensitive cells that are preserved from evolutionary biology and act as drivers for tumor development across distinct central nervous system regions.
• CRISPR/Cas9 Validation: The utilization of genetic scissors in mouse models to block photoreceptor activity, successfully halting tumor growth and confirming the biological target.

Misplaced Neurons Reveal the Brain’s Adaptability

Image Credit: Scientific Frontline / AI generated (Gemini)

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Neurons positioned in the wrong location, known as heterotopias, can successfully integrate into brain circuits and take over the functional role of the normal cerebral cortex, defying the assumption that precise anatomical placement is required for function.
• Methodology: Researchers utilized a mouse model with induced heterotopias and performed functional mapping during a sensory task requiring the distinction of whiskers; they employed targeted deactivation to isolate the contributions of normal versus misplaced neurons.
• Key Data: Mice continued to perform sensory tasks normally when the healthy cortex was deactivated; however, the specific inhibition of the misplaced neuronal clusters resulted in immediate and complete failure of the task.
• Significance: This study fundamentally alters the understanding of brain plasticity, demonstrating that cellular identity and connectivity can override spatial positioning to maintain neurological function.
• Future Application: These findings validate the potential of regenerative therapies, such as neuronal grafts and brain organoids, suggesting they can be effective treatments without needing to perfectly replicate natural brain architecture.
• Branch of Science: Neuroscience (Neurodevelopment and Plasticity).
• Additional Detail: Analysis revealed that these stray neurons formed neural circuits almost identical to those in the healthy cortex, establishing correct connections with both the rest of the brain and the spinal cord.

Nature-inspired computers are shockingly good at math

Researchers Brad Theilman, center, and Felix Wang, behind, unpack a neuromorphic computing core at Sandia National Laboratories. While the hardware might look similar to a regular computer, the circuitry is radically different. It applies elements of neuroscience to operate more like a brain, which is extremely energy-efficient.
Photo Credit: Craig Fritz

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Neuromorphic (brain-inspired) computing systems have been proven capable of solving partial differential equations (PDEs) with high efficiency, a task previously believed to be the exclusive domain of traditional, energy-intensive supercomputers.
• Methodology: Researchers at Sandia National Laboratories developed a novel algorithm that utilizes a circuit model based on cortical networks to execute complex mathematical calculations, effectively mapping brain-like architecture to rigorous physical simulations.
• Theoretical Breakthrough: The study establishes a mathematical link between a computational neuroscience model introduced 12 years ago and the solution of PDEs, demonstrating that neuromorphic hardware can handle deterministic math, not just pattern recognition.
• Comparison: Unlike conventional supercomputers that require immense power for simulations (such as fluid dynamics or electromagnetic fields), this neuromorphic approach mimics the brain's ability to perform exascale-level computations with minimal energy consumption.
• Primary Implication: This advancement could enable the development of neuromorphic supercomputers for national security and nuclear stockpile simulations, significantly reducing the energy footprint of critical scientific modeling.
• Secondary Significance: The findings suggest that "diseases of the brain could be diseases of computation," providing a new framework for understanding neurological conditions by studying how these biological-style networks process information.

Fragile X study uncovers brain wave biomarker bridging humans and mice

Caption:Picower Professor Mark Bear (left) and postdoc Sara Kornfeld-Sylla discovered a brainwave biomarker of fragile X syndrome that is shared between mice and human patients. “Identifying this biomarker could broadly impact future translational neuroscience research,” Kornfeld-Sylla says.
Photo Credit: Courtesy of the Bear Lab/Picower Institute

Scientific Frontline: "At a Glance" Summary: Fragile X Syndrome Brainwave Biomarker

• Main Discovery: Researchers identified a specific, cross-species biomarker in low-frequency brain waves shared between humans with fragile X syndrome and mice modeling the disorder.
• Methodology: The team measured EEG activity over the occipital lobe in humans and the visual cortex in mice, isolating periodic power fluctuations and comparing them directly without relying on traditional frequency band groupings to reveal shared patterns.
• Key Data: In adult men and adult mice with the condition, the peak power of low-frequency waves shifted to a significantly slower frequency, while boys and juvenile mice displayed a notable reduction in that same peak power.
• Significance: This provides a non-invasive, objective physiological metric to evaluate underlying neurobiological deficits, specifically linking the brainwave alterations to reduced GABA receptivity and altered somatostatin interneuron activity.
• Future Application: The biomarker will allow researchers to directly test the efficacy and optimal dosing of candidate therapies in preclinical mouse models with a direct mapping to human physiological responses before clinical trials.
• Branch of Science: Translational Neuroscience, Neurobiology, and Electrophysiology.
• Additional Detail: Testing with the candidate drug arbaclofen successfully increased the power of the key subpeak in juvenile fragile X mice, proving the biomarker is highly sensitive to acute pharmacological intervention.

Zebrafish are smarter than we thought

A new study from MIT and Harvard University suggests that the brains of the seemingly simple zebrafish are more sophisticated than previously thought. The researchers found that larval zebrafish can use visual information to create three-dimensional maps of their physical surroundings.
Photo Credit: Petr Kuznetsov

A new study from MIT and Harvard University suggests that the brains of the seemingly simple zebrafish are more sophisticated than previously thought. The researchers found that larval zebrafish can use visual information to create three-dimensional maps of their physical surroundings — a feat that scientists didn’t think was possible.

In the new study, the researchers discovered that zebrafish can move around environmental barriers while escaping predators. The findings suggest that zebrafish are “much smarter than we thought,” and could be used as a model to explore many aspects of human visual perception, the researchers say.

“These results show you can study one of the most fundamental computational problems faced by animals, which is perceiving a 3D model of the environment, in larval zebrafish,” says Vikash Mansinghka, a principal research scientist in MIT’s Department of Brain and Cognitive Sciences and an author of the new study.

Andrew Bolton, an MIT research scientist and a research associate at Harvard University, is the senior author of the new study, which appears in the journal Current Biology. Hanna Zwaka, a Harvard postdoc, and Olivia McGinnis, a recent Harvard graduate who is now a graduate student at the Oxford University, are the paper’s lead authors.

How Does the Brain Make Decisions?

Image Credit: Generated by HM News with AI in Adobe Firefly

Scientific Frontline: Extended "At a Glance" Summary: Neural Circuitry of Decision-Making

The Core Concept: The brain finalizes decisions through a structural process where selecting one option actively suppresses the neural pathways associated with alternative options. This mechanism involves specific sequences of neuronal activation that lock in a choice and prevent a change of mind.

Key Distinction/Mechanism: During navigational decision-making, a specific set of excitatory neurons associated with a chosen action (e.g., turning right) fires and subsequently activates a targeted set of inhibitory neurons. These inhibitory cells then curb the activity of the neurons associated with the opposite action (e.g., turning left). This functional architecture within the posterior parietal cortex serves to stabilize the committed decision.

Major Frameworks/Components:

• Connectomics: The comprehensive structural mapping of the wiring and connections between neurons using powerful microscopy.
• Functional Behavioral Analysis: The use of virtual reality mazes to record real-time neuronal activity and decision-making dynamics in active subjects.
• Posterior Parietal Cortex: The specific brain region studied, functioning as an "integrative hub" that receives and processes multisensory information to guide navigational choices.
• Synaptic Wiring Motifs: The specific, rule-based interactions between excitatory and inhibitory neurons that provide the foundation for the brain’s computational processes.

AI helps explain how covert attention works and uncovers new neuron types

Image Credit: Scientific Frontline / AI generated

Shifting focus on a visual scene without moving our eyes — think driving or reading a room for the reaction to your joke — is a behavior known as covert attention. We do it all the time, but little is known about its neurophysiological foundation. Now, using convolutional neural networks (CNNs), UC Santa Barbara researchers Sudhanshu Srivastava, Miguel Eckstein and William Wang have uncovered the underpinnings of covert attention and, in the process, have found new, emergent neuron types, which they confirmed in real life using data from mouse brain studies. 

“This is a clear case of AI advancing neuroscience, cognitive sciences and psychology,” said Srivastava, a former graduate student in the lab of Eckstein, now a postdoctoral researcher at UC San Diego. 

Neurobiologists Hack Brain Circuits Tied to Placebo Pain Relief

Fluorescent images of a key brain circuit involved in placebo pain relief in mice. Pain-regulating neurons located in the ventrolateral periaqueductal gray (vlPAG) are labeled in green, with their cell bodies visible as green spots and their wire-like axons extending to the brainstem to suppress pain.
 Image Credit: Janie Chang-Weinberg

Scientific Frontline: Extended "At a Glance" Summary: The Neurobiology of Placebo Pain Relief

The Core Concept: Placebo pain relief is a phenomenon where the brain generates its own painkilling response—specifically through the release of endogenous opioid neuropeptides—without the administration of active pharmaceutical treatments. It is an expectancy-driven process that empowers the brain to produce broad-spectrum pain reduction on demand.

Key Distinction/Mechanism: Unlike traditional opioid painkillers (like morphine) that flood the system and carry a high risk of addiction and off-target side effects, placebo pain relief relies on precise, native neural circuits linking the cortex to the brainstem and spinal cord. The mechanism centers on the activation of endogenous opioid signaling within a specific brain region known as the ventrolateral periaqueductal gray (vlPAG).

Major Frameworks/Components: 

• Reverse Translation Method: An experimental framework where human placebo conditioning protocols are adapted for murine models, bridging the gap between human clinical data and foundational neurobiology.
• Ventrolateral Periaqueductal Gray (vlPAG): The anatomical hub in the brain identified as the critical site for pain signaling and the release of native opioids during placebo trials.
• Endogenous Opioid Neuropeptides: Naturally occurring endorphins that act as the brain's internal painkillers.
• Photoactivatable Naloxone (PhNX): An innovative light-activated drug technology used to precisely control and block opioid receptors in real-time, verifying that internal opioid signaling is the primary driver of placebo relief.

Researchers create simple method for viewing microscopic fibers

Computational scattered light imaging shows the orientation and organization of tissue fibers at micrometer resolution. The colors represent different fiber orientations.
Image Credit: Marios Georgiadis

Every tissue in the human body contains a network of microscopic fibers. Muscle fibers direct mechanical forces, intestinal fibers are involved in gut mobility, and brain fibers transmit signals and form the communication network to drive cognition. Together, these fibers shape how organs function and help maintain their structure.

Likewise, almost all diseases involve some form of degeneration or disruption of these fiber networks. In the brain, this translates to disturbances in neural connectivity that are found in all neurological disorders.

Despite their biological importance, these microscopic fibers have been difficult to study, as scientists have struggled to visualize their orientations within tissues.

Now, Stanford Medicine researchers and their colleagues have developed a simple, low-cost approach that makes those hidden structures visible in remarkable detail.

The aging brain: protein mapping furnishes new insights

Stained mouse microvessels under the fluorescence microscope (green: vascular endothelium, red: cell nuclei). 
Image Credit: © Dichgans Lab

For the neurons in the brain to work smoothly and be able to process information, the central nervous system needs a strictly regulated environment. This is maintained by the blood-brain barrier, whereby specialized brain endothelial cells lining the inner walls of blood vessels regulate the exchange of molecules between the circulatory and nervous systems. Earlier studies have shown that various functions that are dependent on these cells, such as the integrity of the blood-brain barrier or the regulation of blood supply to the brain, decline over the course of a person’s life. This dysregulation leads to a dysfunction of the brain vasculature and is therefore a major contributor to medical conditions such as strokes and dementia.

However, the molecular changes that underlie this loss of function have remained largely obscure. To improve our mechanistic understanding, researchers carry out molecular profiling studies to investigate the different components of brain endothelial cells and collect their findings in large databases. “The transcriptome – that is to say, the RNA contained in endothelial cells – has since been quite comprehensively mapped,” says LMU professor Martin Dichgans, Director of the Institute for Stroke and Dementia Research at University of Munich Hospital and Principal Investigator at the SyNergy Cluster of Excellence. “What has been lacking is corresponding data on the complete set of proteins in the cells, the proteome.” A study recently published in the journal Nature Aging, which had major contributions by researchers from LMU and SyNergy, has now closed this knowledge gap.

With navigating nematodes, scientists map out how brains implement behaviors

Caption:Scientists curious about how brains produce behaviors were able to image the movements and simultaneous neural activity of a C. elegans nematode as it navigated to avoid aversive odors. Here, a worm is turning around.
Image Credit: Flavell Lab/PIcower Institute

Scientific Frontline: Extended "At a Glance" Summary: Brain Mapping of Nematode Navigation

The Core Concept: A comprehensive mapping of the neural circuits in C. elegans nematodes that details exactly how their brains process environmental odors to generate purposeful, sequential movement.

Key Distinction/Mechanism: Rather than ambling randomly until reaching a desired location, the worms utilize a precise sequence of neural activation—driven by a cohort of about 10 specific neurons—to detect odors, calculate advantageous turn angles, and shift movement states. This mechanism relies heavily on the neuromodulator tyramine to synchronize the neural "shifting of gears" between forward and reverse navigation.

Origin/History: The open-access research was published in Nature Neuroscience in April 2026 by scientists at MIT’s Picower Institute for Learning and Memory, led by senior author Steven Flavell and former graduate student Talya Kramer.

Flies Navigate Using Complex Mental Math

Scientists can image the brains of flies to study how they navigate. Here, a fly walks in place inside a visual arena that makes the fly feel as if it is traveling in various directions.
Credit: Maimon Lab

The treadmills in Rachel Wilson’s laboratories at Harvard Medical School aren’t like any you’ll find at a gym. They’re spherical, for one, and encased in bowling ball–sized plastic bubbles. They’re also built for flies.

Inside these bubbles, fruit flies walk in place as they navigate a 360-degree virtual reality environment.

A similar scene unfolds 200 miles away, in Gaby Maimon’s lab at the Rockefeller University, where flies attached to tiny tethers browse their own virtual worlds. By monitoring the flies’ brain signals, researchers in these two labs have discovered a key mechanism behind insect navigation.

These little flies, with brains the size of poppy seeds, navigate the world using mathematics that most of us mere mortals forgot after high school. The feat requires performing calculations with data gleaned from the senses and using geometry to compute the body’s traveling direction. Howard Hughes Medical Institute Investigators Wilson and Maimon and their colleagues report the work in two new studies released together December 15, 2021, in the journal Nature.

Researchers had previously located the fly brain’s compass – a set of neurons arrayed in a donut-shaped structure that keeps track of which direction the fly is facing. But scientists didn’t understand how flies knew which way they were traveling, Maimon says. “Not which way their body is facing, but which way they are moving in the real world.” The new papers identify for the first time which neurons in the brain are tracking both body movement and orientation, and how the signals combine to track a path through the environment.