Now online! Li et al. apply base-pair resolution Micro Capture-C ultra to map chromatin contacts between individual motifs within cis-regulatory elements and reveal a unified model of biophysically mediated enhancer-promoter communication.
Category: mapping
Mapping a new frontier with AI-integrated geographic information systems
Over the past 50 years, geographers have embraced each new technological shift in geographic information systems (GIS)—the technology that turns location data into maps and insights about how places and people interact—first the computer boom, then the rise of the internet and data-sharing capabilities with web-based GIS, and later the emergence of smartphone data and cloud-based GIS systems.
Now, another paradigm shift is transforming the field: the advent of artificial intelligence (AI) as an independent “agent” capable of performing GIS functions with minimal human oversight.
In a study published in Annals of GIS, a multi-institutional team led by geography researchers at Penn State built and tested four AI agents in order to introduce a conceptual framework of autonomous GIS and examine how this shift is redefining the practice of GIS.
When speaking out feels risky: New study maps hidden dynamics of self-censorship
In an era when social media blurs the line between public and private speech, how do people decide whether to speak their minds or stay silent?
A new study from researchers at Arizona State University and the University of Michigan, published in the Proceedings of the National Academy of Sciences, offers a groundbreaking look at the strategic trade-offs individuals make when facing the threat of punishment for dissent.
The work, co-authored by Professor Stephanie Forrest and Assistant Professor Joshua J. Daymude in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at ASU, and Robert Axelrod from the University of Michigan, introduces a mathematical model to explain when people choose to express dissent or self-censor.
Functional ultrasound neuroimaging reveals mesoscopic organization of saccades in the lateral intraparietal area
An amazing paper (link:) where functional ultrasound imaging (fUSI) is used to explore how brain activity in the lateral intraparietal cortex (LIP) can predict visual saccades (eye movements) in two monkeys. An impressive array of computational analyses are used to extract insights from the imaged regions. Indeed, predictive models developed by the authors remained fairly stable over the course of up to 900 days! I happen to know two of the authors (Sumner L Norman and Mikhail Shapiro): congratulations to them and their colleagues on this excellent publication!
Our results demonstrate that PPC contains subregions tuned to different directions. These tuned voxels were predominately within LIP and grouped into contiguous mesoscopic subpopulations. Multiple subpopulations existed within a given coronal plane, i.e., there were multiple preferred directions in each plane. A rough topography exists where anterior LIP had more voxels tuned to contralateral downwards saccades and posterior LIP had more voxels tuned to contralateral upwards saccades. These populations remained stable across more than 100–900 days.
We observed large effect sizes with changes in CBV on the order of 10–30% from baseline activity (Fig. 3). This is much larger than observed with BOLD fMRI where the effect size was ~0.4–2% on similar saccade-based event-related tasks27,32. Our results support a growing evidence base that establishes fUSI as a sensitive neuroimaging technique for detecting mesoscopic functional activity in a diversity of model organisms, including pigeons, rats, mice, nonhuman primates, ferrets, and infant and adult humans23,24,25,33,34,35,36,37,38,39,40.
Several studies have reported a patchiness in direction selectivity with many neighboring neurons tuned to approximately the same direction followed by an abruption to a patch of a different preferred direction13,14,41. These results match very closely with the results observed in this study where we found clusters within LIP tightly tuned to one direction with differently tuned clusters in close proximity within a given plane. These results further emphasize the high spatial resolution of fUSI for functional mapping of neuronal activity. These results also closely match a previous study that used fUSI to identify the tonotopic mapping of the auditory cortex and inferior colliculus in awake ferrets where the authors found a functional resolution of 100 µm for voxel responsiveness and 300 µm for voxel frequency tuning34.
Topographical sparse mapping: A neuro-inspired sparse training framework for deep learning models
AI models have been expanding dramatically in size and the number of trainable parameters. This rapid growth has introduced many challenges, including increased computational costs and inefficiencies. Dynamic sparse training has emerged as a novel approach to address overparameterization and achieve energy-efficient artificial neural network (ANN) architectures. The highly efficient neuro-inspired sparse design remains underexplored compared to the significant focus on random topology searches. We propose the Topographical Sparse Mapping (TSM) method, inspired by the vertebrate visual system and convergent units. TSM introduces a sparse input layer for MLPs, significantly reducing the number of parameters.
Holographic optogenetics could enable faster brain mapping for new discoveries
Recent technological advances have opened new possibilities for neuroscience research, allowing researchers to map the brain’s structure and synaptic connectivity (i.e., the junctions via which neurons communicate with each other) with increasing precision.
Despite these developments, most widely employed methods to image synaptic connectivity are slow and fail to precisely record changes in the connections between neurons in vivo, or in other words, while animals are awake and engaging in specific activities.
Two different research groups, one based at Columbia University and UC Berkeley, and the other at the Vision Institute of Sorbonne University in Paris, introduced a promising approach to study synapses in vivo. Their proposed mapping strategies, outlined in two Nature Neuroscience papers, combine holographic optogenetics, a method to selectively and precisely stimulate or silence specific neuron populations, with computational techniques.
The In Situ Structure of T-Series T1 Reveals a Conserved Lambda-Like Tail Tip
It is estimated that over 60% of known tailed phages are siphophages, which are characterized by a long, flexible, and non-contractile tail. Nevertheless, entire high-resolution structures of siphophages remain scarce. Using cryo-EM, we resolved the structures of T-series siphophage T1, encompassing its head, connector complex, tail tube, and tail tip, at near-atomic resolution. The density maps enabled us to build the atomic models for the majority of T1 proteins. The T1 head comprises 415 copies of the major capsid protein gp47, arranged into an icosahedron with a triangulation number of seven, decorated with 80 homologous trimers and 60 heterotrimers along the threefold and quasi-threefold axes of the icosahedron. The T1 connector complex is composed of two dodecamers (a portal and an adaptor) and two hexamers (a stopper and a tail terminator).
Astronomers Create First 3D Map of an Exoplanet’s Atmosphere
“Eclipse mapping allows us to image exoplanets that we can’t see directly, because their host stars are too bright,” said Dr. Ryan Challener.
What can a 3D map of an exoplanet’s atmosphere teach astronomers about the planet’s formation, evolution, and composition? This is what a recent study published in Nature Astronomy hopes to address as a team of scientists presented a first-time 3D map of an exoplanet’s atmosphere based on temperature. This study has the potential to help scientists better understand the formation and evolution of exoplanet atmospheres while opening the doors for developing better methods of studying them.
For the study, the researchers used data obtained from NASA’s James Webb Space Telescope to develop a new method called 3D eclipse mapping on WASP-18b, which is located just over 400 light-years from Earth and whose radius is slightly more than Jupiter’s while have ten times its mass. WASP-18b is known as an “ultra-hot” Jupiter, as it orbits extremely close to its star at 0.02024 astronomical units (AU) while completing one orbit in only 0.9 days. For context, the planet Mercury orbits our Sun at 0.387 AU and completes one orbit in 88 days. WASP-18b is also tidally locked to its star like our Moon is tidally locked to Earth.
In the end, the researchers found that WASP-18b’s “dayside” features variations in temperature and chemical composition while also exhibiting a circular “hotspot” where the largest amount of starlight hits the atmosphere. Additionally, the team found this hotspot is surrounded by a colder “ring” closer to the limbs of the planet, or the outer edges where the shape of the planet is visible.
Imaging technique maps fleeting intermediates in hydrogen electrocatalysis
Electrocatalytic transformations not only require electrical energy—they also need a reliable middleman to spark the desired chemical reaction. Surface metal-hydrogen intermediates can effectively produce value-added chemicals and energy conversion, but, given their low concentration and fleeting lifespan, they are difficult to characterize or study in depth, especially at the nanoscale.