Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 1 through 15 of 99 found.

, . Van Schependom, Jeroen, et al. Neurophysiological avenues to better conceptualizing adaptive cognition. Communications Biology. 7/626, 2024.. Communications Biology. 7/626, 2024. Vrije Universiteit Brussel, Oxford University, CNR Istituto dei Sistemi Complessi, Italy and Technical University Dresden neuroscientists achieve another deeply quantified notice and expression of a reciprocal balance between coincident opposites of more or less coherence, conservation or creativity. Once again a semblance of a critically organized “sweet spot” appears as a natural optimum preference. We write on June 28 and wonder how can these robust, universal scientific findings ever make it to an academe stuck in mechanist denials of anything going on at all. We respectfully offer herein a Planatural PhiloSophia family mind and a PediaPedia Earthica.

We delve into the human brain’s deep capacity for adaptability and cognitive functioning, which are often seen as an executive domain. In regard, the neural bases that enable the navigation between transient thoughts without detracting from overarching goals form our article. We discuss the concept of “metacontrol,” which proposes a dynamic balancing of core processes depending on situational demands. This approach leads to the role of oscillatory processes in electrophysiological activity at different phases of desynchronization and synchronization in supporting adaptive behavior. These cognitive and neurophysiological avenues can thereby contribute to a more nuanced comprehension and its neural basis in both health and disease. (Excerpt)

Our central focus lies in exploring cognitive processing along a continuum characterized by its two polar phases: “persistence” and “flexibility.” We propose to use signal-processing methods to characterize this continuum connecting neurophysiology, physics, and cognitive science. (2)

Castro, Daniel. et al. In and Out of Criticality? State-Dependent Scaling in the Rat Visual Cortex. PRX Life. 2/023008, 2024. In this new Physical Review journal, eight Universidade Federal de Pernambuco, Recife, Brazil and University of Minho, Braga, Portugal system physicians add a latest appreciation of how our cerebral processes indeed do seem to bounce around a best performance balance.

A presumed proximity to a critical point is believed to endow the brain with scale-invariant statistics to confer advantages for information processing, storage, and transmission. To assess scaling and cortical states, we apply a renormalization group method to data recordings from the anesthetized rat's visual cortex. Under anesthesia, cortical states shift across synchronization levels defined by population spiking rate variability. We find that scaling signatures only appear as spiking frequency surpasses a threshold. Our results suggest that a wide range of cortical states corresponds to small deviations around a critical point, with the system fluctuating in and out of criticality, spending roughly three-quarters of the experiment duration within a scaling regime. (Abstract excerpt)

Planatural Genesis: A 21st Century PhiloSophia, EarthTwinity, Ecosmic WumanKinder EditionVersion

Rosen, Robert. Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life. New York: Columbia University Pres, 2005. The author (1934 - 1998) was a professor of theoretical biophysics at Dalhousie University in Halifax, Nova Scotia but his lifetime project was to move beyond, decades ago, an olden machine fixation by articulating how all manner of organisms are living systems, along with the whole natural world. In regard, Predrag Slijepčević new book Biocivilisations: A New Look at the Science of Life (Chelsea Green, 2023) takes up Rosen’s mission. And I once met spoke with RR in 1987 at a Boston University Philosophy of Science conference.)

Bruckner, David and Gasper Tkacik. Bruckner, David and Gasper Tkacik. Information content and optimization of self-organized developmental systems.. PNAS. 121/23, 2024. Institute of Science and Technology (ITSA), Austria physicists introduce a novel framework to study self-organized, reaction-diffusion patterning as a stochastic dynamical system. As the quotes say, their proof of principle is the way cells form, migrate and combine in. embryonic development. See also then Waves, patterns, bifurcations: the vertebrate segmentation clock by Paul Francois and Victoria Mochulska in Physics Reports (Volume 1080, 2024) and Precise and scalable self-organization in mammalian pseudo-embryos by Melody Merle and Leah Friedman in Nature Structural & Molecular Biology. (31/896, 2024) for similar, concurrent reports of the same theoretical basis.

Altogether this year, along with many other entries, our 21st century, 2020s prodigious revolution has reached a robust wide and deep observance of a phenomenal universe to pediaverse catalytic spontaneity which now seems to require its own aware, selective realization. An awesome consequence then accrues for our Earthuman observance. We valiant, survivor peoples may well be the actual SELVES whom altogether are meant to respectfully take up, vitalize, engender and continue to arrange a universal procreativity.

Development relies on the ability of cells to self-organize into patterns of different cell types that underlie the formation of tissues and organs. But how to generically quantify the patterning performance of different biological self-organizing systems has remained unclear. Here, we develop an information-theoretic framework to analyze a wide range of models of self-organization. Our approach can be used to define the information content of observed patterns, assess the importance of regulatory motifs, and predict optimal operating regimes for self-organizing systems. In regard, this framework achieves a unifying mathematical language to describe the actual presence of biological self-organization across diverse systems. (Significance)

Self-organizing patterning processes generate, transmit, transform, and distribute information in space and time. Much as physics equips us with a formalism to describe how the flows of matter take shape, information theory provides a formal language to quantify statistical structures. This approach has previously been applied to formalize the notion of “positional information” in developmental systems, where inputs are the maternally provided morphogen gradients. However, for self-organizing patterns a more general approach is needed to quantify their information content. Here, we address this challenge by proposing an information-theoretic measure of self-organization performance in embryonic development. (2)

New mathematical framework sheds light on how cells communicate to form an embryo
Biological processes depend on puzzle pieces coming together and interacting. Interestingly, the mammalian embryo develops similarly. In nature, self-organization is all around us: We can observe it in fish schools, bird flocks, or insect collectives, and even in microscopic processes regulated by cells. "Information theory is a universal language to quantify structure and regularity in statistical ensembles, which are a collection of replicates of the same process. Embryonic development can be seen as such a process that reproducibly generates functional organisms that are very similar but not identical," says Gašper Tkaèik, professor at ISTA and expert in this field. (ITSA News)

Cech, Thomas. The Catalyst: RNA and the Quest to Unlock Life's Deepest Secrets. New York: Norton, 2024. The 1989 Nobel chemist has been at the center of a revolutionary shift in genetic science from an original emphasis on DNA to its companion biomolecule ribonucleic acid RNA. The thematic story is about realizations of a wide array of features which have given it a significant role in many metabolic functions. A recent merit is to provide a vaccine base during the COVID pandemic. But our interest also lies with the title concept which can identify life’s deep propensity to consistently initiate and perpetuate its own procreative course, seemingly within a catalytic ecosmos.

As an example of current advances on this frontier, we cite BEACON: Benchmark for Comprehensive RNA Tasks and Language Models by Yuchen Ren, et al at arXiv:2406.10391 and RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching by Divya Nori and Wengong Jin at arXiv:2405.18768.

For over half a century, DNA has reigned in the popular imagination as the “secret of life.” But over the past decades, a quiet revolution has taken place. The biochemist Thomas Cech and a diverse cast of scientists have revealed that RNA, long overlooked as the passive servant of DNA, sits at the center of biology. In The Catalyst, Cech finally brings together years of research to demonstrate that RNA is the true key to understanding life on Earth, from its very origins to our future in the twenty-first century. The Catalyst moves from the early experiments to Cech’s own findings that it can catalyze cellular reactions and on to novel biotechnologies. The work glimpses how RNA-powered therapies such as CRISPR that can RNA rewrite the code of life and mRNA vaccines that have saved millions during the pandemic. BOOK

I tell the story of RNA in two parts: the first is how RNA revealed itself as life’s great catalyst. We begin in the 1950s with the experiments that un covered how RNA orchestrates the construction of the proteins that perform most of the essential functions in living organisms. Then we see how RNA is responsible for helping us humans do so much with our DNA jnformation. From there, the story takes a personal turn. I recount how my team discovered catalyric RNA called riboenzynes. (13)

Thomas Robert Cech (born December 8, 1947) is an American chemist who shared the 1989 Nobel Prize in Chemistry with Sidney Altman, for their discovery of the catalytic properties of RNA. He is also the president of Howard Hughes Medical Institute.

Kogut, Alan, et al. Kogut, Alan, et al. The Primordial Inflation Explorer (PIXIE): Mission Design and Science Goals. arXiv:2405.20403. We note this posting by seventeen astroscientists from across the USA, onto the UK, France and beyond led by NASA Goddard which detailed project plans as Earthropo sapiens proceeds apace with the task of astronomic self-quantification. See also The SKA Galactic Centre Survey: A White Paper at arXiv:2406.04022. Along with many similar endeavors, what a grand scenario is altogether revealed whence our unique knowsphere commences on an intrinsic course of (multi)universal self-quantification, representation, and select affirmation.

The Primordial Inflation Explorer (PIXIE) mission concept plans to measure the energy spectrum and linear polarization of the cosmic microwave background (CMB). PIXIE opens a broad discovery space for the origin, contents, and evolution of the universe. Measurements of small distortions from a CMB blackbody spectrum provide a robust determination of the mean electron pressure and temperature in the universe while constraining processes including dissipation of primordial density perturbations, black holes, and the decay or annihilation of dark matter. We describe the PIXIE instrument sensitivity, foreground subtraction, and anticipated science return from both the baseline 2-year mission and a potential extended mission. (Excerpt)

Sole, Ricard, et al.. Fundamental Constraints to the Logic of Living Systems.. C:/Users/Author/Downloads/preprints202406.0891.v1.pdf.. his June 13, 2024 preprint is so notable that it merits the full list of coauthors who are RS, Christopher Kempes, Bernat Corominas-Murtra, Manlio De Domenico, Artemy Kolchinsky, Michael Lachmann, Eric Libby, Serguei Saavedra, Eric Smith and David Wolpert (search each). Their postings include Universitat Pompeu Fabra, Barcelona, MIT, the Santa Fe Institute, University of Graz, Earth-Life Science Institute, Tokyo, Umea University, Sweden and the University of Padua.

Akin to the early 2020s recognition of a teleological course because its presence became so strong, herein it is said that evidence for an insistent evolutionary convergence is so profound that it is suggestive of an inherent, independent source which repeats in kind wherever it can. As the quotes say, this admitted observance can reveal companion properties such as universal recurrences across emergent life’s milieu from proteins to cells, metabolisms and onto ecosystems. With these common patterns in place, a further notice of complex self-organized criticalities everywhere can be achieved. As I write in mid July, a growing number of entries are beginning to consider an independent, mathematic, exemplary realm in effect, which altogether can imply something phenomenal going on by itself. May we begin to glimpse the very idea of an imminent revolutionary scientific discovery of a greater, abiding genesis universe, with our Earth once again be its temporal center

It has been said that the historical nature of evolution makes it a path-dependent process. Under this view, the outcome of evolutionary dynamics could have resulted in organisms with different forms and functions. At the same time, there is much evidence that convergence and constraints limit what life’s evolution can achieve. Here, we argue that such fundamental domain occasions are associated with the logic of animate matter. We illustrate this by thermodynamic properties, molecular information, multicellularity and development, computational cognitive systems, and viable ecosystems. In all these examples, we present past and recent evidential proof and suggest pathways towards a well-defined theoretical formulation. (Abstract)

Nonetheless, there are several major reasons to expect convergence. First, all evolutionary trajectories occur under generic selective margins due to the laws of mathematics, physics, and chemistry, which should lead to universal features. Second, many of these spaces are not explored randomly. The percolating nature of genotype spaces favours success in evolutionary search. Moreover, some intrinsic properties of chemical and physical nature channel the repertoires of molecular structures because only a small fraction of protein folds are realizable. (4)

Here, we discuss some fundamental limits to the space of evolutionary outcomes. We start with some core thermodynamic vectors along with molecular information carriers, cellular reproduction, cognitive architectures, and ecosystems. Finally, we consider the concept of phase transitions as a paradigm for the emergence of living complexity. In our view, such predictions strongly infer a universality which fits within the broader goal of finding general theories that transcend the specifics of life on Earth. (5) Moreover, despite the enormous variation of climate and resource conditions, all ecosystems essentially display the same properties from Antarctica to the Sahel. We can also reconstruct fossil phases, the so-called “paleo food webs” and again find universal patterns shared with modern ecological networks. (25)

Some of our case studies are deeply connected with the emergence of innovations in evolution. These major transitions refer to critical points in the history of life where new levels of biological organisation (cells, groups or language) and complexity emerged. It has been suggested that these events as a marked shift from a qualitative level of organization to a new one, can be mapped into the concept of phase transitions from statistical physics. (28)

Along with evolutionary innovations and phase transitions, critical points play another role. Criticality refers to the state of a system poised between dual ordered and disordered states. The idea that criticality has desirable properties has been advanced within the context of nonlinearity and chaos, computation, genetic codes, neuroscience and ecology. There are good reasons because critical states often enhance information transfer and sensitivity to external signals. (30)

Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Actual Factual Knowledge

Sante, Andrea, et al. Applying machine learning to Galactic Archaeology. arXiv:2405.00102. Five Liverpool John Moores University astroscientists consider whether the ancient timeline origin of stars in the Milky Way can be presently quantified by virtue of these novel AI data dense facilities. And once again, one might reflect on the whole scenario of a creative ecosmos whose regnant life evolves to a collaborative sapience on an infinitesimal bioplanet that is able to achieve such nascent self-representations. We wonder what kind of universe reality seems to require its own observance, recognition and aware admission to bring itself into full existence. See also A Census of Sun's Ancestors and their Contributions to the Solar System Chemical Composition by F. Fiore, et al at 2406.08036 and Presolar Grains by Nan Liu at 2406.14694.

We survey machine learning (ML) models developed to separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These methods, which include examples from artificial neural networks, decision trees and dimensionality reduction techniques, are trained on a sample of disc-like, Milky Way-mass galaxies. We find that the input parameters consist of stellar positions, kinematics, chemical abundances and photometric properties. The general applicability bodes well for application to identify accreted substructures in the Milky Way. (Excerpt)

Huh, Minyoung, et al.. Huh, Minyoung, et al. The Platonic Representation Hypothesis. . Neural networks, trained with different objectives on different data and modalities, are converging to a shared statistical model of reality in their representation spaces. We cite this May entry by MIT computer scientists including Phillip Isola as an example of how these many large language models could be altogether seen as coming to their own planetary universion discovery. See also Learning and Leveraging World Models in Visual Representation Learning by Quentin Garrido, et al at arXiv:2403.00504. As incendiary conflicts worsen, the novel presence of an intelligent sapiensphere, aka an actual global brain, learning on her/his own could bring a salutary alternative we so need.

We argue that representations in AI models by way of deep neural networks, are in a convergence stage. First, we survey many examples in the literature over time and across multiple domains. Next, we demonstrate common trends across data modalities: as vision and language models get larger, they measure distance between datapoints in similar forms. We propose that this convergence is heading toward a shared statistical model of the world, akin to Plato's concept of an ideal reality. We dub this occasion as a platonic representation and discuss possible selective pressures toward it. Finally, we consider knowledgeable implications of these trends, within limits. (Abstract)

Our central hypothesis is that the representation we are converging toward is a statistical model of an underlying reality that generates our observations. Consistent with the multitask scaling hypothesis, such an appreciation would naturally be useful toward many tasks. Additionally, this worldview might be relatively simple, assuming that scientists are correct in suggesting that the fundamental laws of nature are indeed simple functions (Gell-Mann, 1995), in line with the simplicity bias hypothesis. (7)

Phillip Isola is an assistant professor and a principal investigator in MIT’s Computer Science and Artificial Intelligence Laboratory. His work focuses on why we represent the world the way we do, and how we can replicate these abilities in digital forms. Before coming to MIT, he was a visiting research scientist at OpenAI. He earned a PhD in brain and cognitive sciences at MIT and spent two years as a postdoc at the University of California, Berkeley.

Strachan, James, et al. Testing theory of mind in large language models and humans. Nature Human Behaviour. May, 2024. Into 2024, twelve computational neuroscientists posted in Germany, Italy, the UK and USA can begin to notice basic affinities between our own cerebral cognition and perceptive capabilities in these nascent cyberspace faculties. See also The Platonic Representation Hypothesis by Minyoung Huh, et al. arXiv:2405.07987 and Predicting the next sentence (not word) in large language models by Shaoyun Yu, et al in Science Advancesfor May 2024. Altogether a viable sense of a global brain as it envelopes the biosphere becomes evident. As these many articles contend, for better or worse depending on how well we might understand and moderate.

At the core of what defines us as humans is the concept of theory of mind: the ability to be aware of other people’s mental states. The development of large language models (LLMs) such as ChatGPT has led to the possibility that they exhibit behaviour similar to our theory of mind tasks. Here we compare human and LLM performance from understanding false beliefs to interpreting indirect requests and recognizing irony. We found that GPT-4 models performed at human levels for indirect requests, false beliefs and misdirection, but struggled with faux pas. These findings show that LLMs are consistent with mentalistic inference in humans and highlight the need for testing to ensure valid comparisons between human and artificial intelligences. (Abstract)

As artificial intelligence (AI) continues to evolve, it also becomes increasingly important to heed calls for open science to these models. Direct access to the parameters, data and documentation used to construct models can allow for targeted probing and experimentation into the key parameters affecting social reasoning, informed by and building on comparisons with human data. As such, open models can not only serve to accelerate the development of future AI technologies but also serve as models of human cognition. (7)

Tosato, Tommaso, et al. Lost in Translation: The Algorithmic Gap Between LMs and the Brain\. . . University of Montreal and Strungmann Institute for Neuroscience, Frankfurt researchers propose a series of parsed programs to better cross-align computational text with our intricate vernaculars. See also Building Artificial Intelligence with Creative Agency by Liane Gabora and Joscha Bach at 2407.10978 for a similar endeavor by way of autocatalic networks.

Language Models (LMs) have achieved impressive performance on linguistic tasks, but their relation to human processing remains unclear. This paper examines pros and con between LMs and the brain at different levels to compare their internal efficacy. We discuss how insights from neuroscience such as sparsity, modularity, internal states, and interactive learning can inform the development of more biologically plausible language models. The role of scaling laws is seen as an analogous way to bridge these loquacious systems. By developing LMs that more closely align with brain function, we aim to advance both artificial intelligence and our understanding of human cognition. (Abstract)

Rabb, Nathaniel and Steven Sloman. Radical Collective Intelligence and the Reimagining of Cognitive Science.. Topics in Cognitive Science.. 16/2, 2024. As the quote says, MIT and Brown University introduce a special issue along with a novel perspective for the endeavor. Among the papers we note What Makes Us Smart? by Joseph Henrich and Michael Muthukrishna (see below) and The Wisdom of the Crowd is not a Forgone Conclusion. Effects of Self-Selection on (Collaborative) Knowledge Construction by Marie-Christin Krebs, et al.

Our special issue How Minds Work: The Collective in the Individual proposes a “radical CI” as a new paradigm for for this emergent collaborative facility. Radical CI posits that the representations and processes necessary to perform the cognitive functions that humans perform are collective entities, not encapsulated by any individual. This concept clarifies how the volume's contributions either rethink long-studied cognitive processes (memory, metacognition, reasoning) or contemplate how radical CI can arise.

Human creativity does not solely rely on our individual cognitive abilities, but instead emerges from the recombination of ideas, practices, and approaches that result from social interactions and idea exchanges in large, diverse populations. These population-level processes, which operate over generations, influence not only on our tools, technologies, and languages, but also key aspects of our culturally-evolved cognition, such as our epistemologies and ontologies. (JH & MM)

Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

Coleman, Gavin and William DeRocco. Predicting the Galactic population of free-floating planets from realistic initial conditions. arXiv:2407.05992. We cite this entry by Queen Mary University of London and UC, Santa Cruz exophysicists for its content as it gathers and conveys an early quantified observance of an interstellar spacescape populated with diverse planetary entities. See also Resonant and Ultra-short-period Planet Systems are at Opposite Ends of the Exoplanet Age Distribution at arXiv:2407.04765 for another view.

But then in regard, we wonder if this milieu might be imagined as some manner of amniotic ocean suffused with potential ovular or seed-like objects. Indeed a prior article entitled An Amniotic Universe by Carl Sagan in the Atlantic Monthly (April 1979) does evoke a fluid cosmic fertility. Anyway, these musings are the sort of total reconception, decades later, that our revolutionary worldwise science invites.

We present the first prediction for the mass distribution function of Galactic free-floating planets (FFPs) that aims to include multiple formation pathways and stellar populations. We derive our results from simulations of planet birth, growth, migration, circumbinary systems and from wide binary systems. We find that interactions with circumbinary systems are the main progenitor for FFPs more massive than Earth, leading to a power-law that agrees well with the observations. In contrast, we find -planet scatterings likely produce planets at Mars mass and below, with a shallower power-law. The features we predict in the mass distribution of FFPs will be detectable by upcoming space-based microlensing surveys. (Excerpt)

D'Eugenio, Francesco, et al. JADES: Carbon enrichment 350 Myr after the Big Bang in a gas-rich galaxy.. arXiv:2311.09908.. As the awesome Webb telescope continues to send a stream of fantastic images from the outmost reaches, UK, USA, Australia, France, Italy, Germany, Japan, Spain report an even deeper probe into the onset appearance of metallic elements and compounds which can then engender a prebiotic milieu. Into 2024, might we be reaching a critical moment of actually confirming an inherent organic, fertile milieu?

Finding the first generation of metals in the early Universe and identifying their origin is an important goal of modern astrophysics. In regard, we report deep JWST/NIRSpec spectroscopy of a GS-z12 galaxy as the most distant detection of a metal transition and redshift via emission lines. We derive a super-solar carbon-to-oxygen ratio higher than the C/O measured in galaxies discovered by JWST, and higher than Type-II supernovae enrichment. Such a high C/O in a galaxy observed 350 Myr after the Big Bang may be explained by the yields of metal poor stars, and may even be the heritage of the first generation of supernovae from Population III progenitors. (Excerpt)

The appearance of the first galaxies marks a key phase transition of the Universe with the start of stellar nucleosynthesis and the diffusion of metals. Extensive theoretical work has been devoted to predicting the properties of the first generation of stars and their supernova yield. The launch of JWST enabled, for the first time, the measurement of the physical properties of galaxies. These are generally understood in terms of decreasing gas metallicity and increasing density, ionisation parameter, temperature and stochasticity of their star-formation histories. (1)

Campaio;i, Francesco, et al. Quantum Master Equations: Quantum Optics, Quantum Computing, and Beyond. PRX Quantum. 5/020202, 2024. An entry by RMIT University, Melbourne and University of Padua physicists to exemplify how this once arcane, prohibitive domain has now attained a current facile vernacular which is taught in high schools. See also Hyperdimensional Quantum Factorization by Prathyush Poduval, et al at arXiv:2406.11889 for another instance.

Quantum master equations are an invaluable tool to model the dynamics of a plethora of microscopic systems, ranging from quantum optics and quantum information processing to energy and charge transport, electronic and nuclear spin resonance, photochemistry, and more. This tutorial offers a concise and pedagogical introduction to quantum master equations, accessible to a broad, cross-disciplinary audience. The reader is guided through the basics of quantum dynamics with hands-on examples that increase in complexity. These methods are illustrated with code snippets in python and other languages as a starting point for more sophisticated implementations.

1 | 2 | 3 | 4 | 5 | 6 | 7  Next