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Category: computing – Page 8

How silver iodide triggers ice formation at the atomic level

No one can control the weather, but certain clouds can be deliberately triggered to release rain or snow. The process, known as cloud seeding, typically involves dispersing small silver iodide particles from aircraft into clouds. These particles act as seeds on which water molecules accumulate, forming ice crystals that grow and eventually become heavy enough to fall to the ground as rain or snow.

Until now, the microscopic details of this process have remained unclear. Using and , researchers at TU Wien have investigated how interacts with water at the .

Their findings, published in Science Advances, reveal that silver iodide exposes two fundamentally different surfaces, but only one of them promotes . The discovery deepens our understanding of how clouds form rain and snow and may guide the design of improved materials for inducing precipitation.

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.

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 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 .

New diode chain could be used to develop high-power terahertz technologies

Electromagnetic waves with frequencies between microwave and infrared light, also known as terahertz radiation, are leveraged by many existing technologies, including various imaging tools and wireless communication systems. Despite their widespread use, generating strong and continuous terahertz signals using existing electronics is known to be challenging.

To reliably generate terahertz signals, engineers often rely on frequency multipliers, that can distort an , to generate an with a desired frequency. Some of these circuits are based on Schottky barrier diodes, devices in which the junction between a metal and semiconductor form a one-way electrical contact.

While some frequency multipliers based on Schottky barrier diodes have achieved promising results, devices based on individual diodes can only handle a limited amount of energy. To increase the energy they can manage, engineers can use several diodes arranged in a chain. However, even this approach can have its limitations, as the distribution of the electromagnetic field between the diodes in a chain often becomes uneven.

Neuronal hyperactivity and broader tuning linked to altered sound processing in autism model rats

People with autism spectrum disorders commonly have difficulty processing sensory information, which can make busy, bright or loud settings—such as schools, airports and restaurants—stressful or even painful. The neurological causes for altered sound processing are complex, and researchers are interested in better understanding them to make life better for people with autism.

In a study that combines behavioral tests, computer models and electrophysiological recordings of neuron activity, researchers have found that hyperactivity of neurons in the auditory cortex and the reaction of these neurons to an unusually broad range of frequencies contribute to this altered processing in rat models. The research is published in the journal PLOS Biology.

“One of the things we thought wasn’t being looked at enough was this idea of sensory discrimination: being able to distinguish between different features in our environment,” said Benjamin Auerbach, a professor of molecular and integrative physiology at the University of Illinois Urbana-Champaign.

After distractions, rotating brain waves may help thought circle back to the task

As sure as the brain is prone to distraction, it can also return its focus to the task at hand. A new study in animals by scientists at the Picower Institute for Learning and Memory of MIT shows how that seems to happen: Coordinated neural activity in the form of a rotating brain wave puts thought back on track.

“The rotating waves act like herders that steer the cortex back to the correct computational path,” said study senior author Earl K. Miller, Picower Professor in the Picower Institute and MIT’s Department of Brain and Cognitive Sciences.

Picower Institute postdoc Tamal Batabyal is the lead author of the study published in the Journal of Cognitive Neuroscience.

A Practitioner’s Guide to Kolmogorov-Arnold Networks

Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional Multilayer Perceptrons (MLPs), inspired by the Kolmogorov-Arnold representation theorem. Unlike MLPs, which use fixed activation functions on nodes, KANs employ learnable univariate basis functions on edges, offering enhanced expressivity and interpretability. This review provides a systematic and comprehensive overview of the rapidly expanding KAN landscape, moving beyond simple performance comparisons to offer a structured synthesis of theoretical foundations, architectural variants, and practical implementation strategies. By collecting and categorizing a vast array of open-source implementations, we map the vibrant ecosystem supporting KAN development. We begin by bridging the conceptual gap between KANs and MLPs, establishing their formal equivalence and highlighting the superior parameter efficiency of the KAN formulation. A central theme of our review is the critical role of the basis function; we survey a wide array of choices, including B-splines, Chebyshev and Jacobi polynomials, ReLU compositions, Gaussian RBFs, and Fourier series, and analyze their respective trade-offs in terms of smoothness, locality, and computational cost. We then categorize recent advancements into a clear roadmap, covering techniques for improving accuracy, efficiency, and regularization. Key topics include physics-informed loss design, adaptive sampling, domain decomposition, hybrid architectures, and specialized methods for handling discontinuities. Finally, we provide a practical “Choose-Your-KAN” guide to help practitioners select appropriate architectures, and we conclude by identifying current research gaps. The associated GitHub repository https://github.com/AmirNoori68/kan-review complements this paper and serves as a structured reference for ongoing KAN research.

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