# brain: ubiquity of uncertainty in neuron systems.

AA << demonstrate that final-state uncertainty is ubiquitous in multistable systems of coupled neuronal maps, meaning that predicting whether one such system will eventually be chaotic or nonchaotic is often nearly impossible. (They) propose a "chance synchronization" mechanism that governs the emergence of unpredictability in neuron systems and support it by using basin classification, uncertainty exponent, and basin entropy techniques to analyze five simple discrete-time systems, each consisting of a different neuron model. >>

Their << ️results illustrate that uncertainty in neuron systems is not just a product of noise or high-dimensional complexity; it is also a fundamental property of low-dimensional, deterministic models, which has profound implications for understanding brain function, modeling cognition, and interpreting unpredictability in general multistable systems. >>

Brandon B. Le, Bennett Lamb, et al. Ubiquity of Uncertainty in Neuron Systems. arXiv: 2507.15702v1 [q-bio.NC]. Jul 21, 2025.

https://arxiv.org/abs/2507.15702

Also: brain, uncertainty, noise, in https://www.inkgmr.net/kwrds.html 

Keywords: brain, uncertainty, noise, coupled neuronal maps, chance synchronization.

# life: detecting hallucinations (in large language models) using semantic entropy.

<< Large language model (LLM) systems, such as ChatGPT or Gemini, can show impressive reasoning and question-answering capabilities but often ‘hallucinate’ false outputs and unsubstantiated answers. >>

<< Here (AA) develop new methods grounded in statistics, proposing entropy-based uncertainty estimators for LLMs to detect a subset of hallucinations— confabulations— which are arbitrary and incorrect generations. (Their) method addresses the fact that one idea can be expressed in many ways by computing uncertainty at the level of meaning rather than specific sequences of words. >>

Their method << works across datasets and tasks without a priori knowledge of the task, requires no task-specific data and robustly generalizes to new tasks not seen before. By detecting when a prompt is likely to produce a confabulation, helps users understand when they must take extra care with LLMs and opens up new possibilities for using LLMs that are otherwise prevented by their unreliability. >>️️

Sebastian Farquhar, Jannik Kossen, et al. Detecting hallucinations in large language models using semantic entropy. Nature 630, 625–630. Jun 19, 2024.

https://www.nature.com/articles/s41586-024-07421-0

Also: ai (artificial intell) (bot), entropy, in https://www.inkgmr.net/kwrds.html 

Keywords: life, artificial intelligence,  LLMs, confabulations, uncertainty, hallucinations, entropy, semantic entropy

# behav: the benefit of ignorance for traffic through a random congestible network.

<< When traffic is routed through a network that is susceptible to congestion, the self-interested decisions made by individual users do not, in general, produce the optimal flow. This discrepancy is quantified by the so-called "price of anarchy." >>

AA << consider whether the traffic produced by self-interested users is made better or worse when users have uncertain knowledge about the cost functions of the links in the network, and define a parallel concept that (They) call the "price of ignorance."  >>

AA << introduce a simple model in which fast, congestible links and slow, incongestible links are mixed randomly in a large network and users plan their routes with finite uncertainty about which of the two cost functions describes each link. >>

<< One of (Their) key findings is that a small level of user ignorance universally improves traffic, regardless of the network composition. Further, there is an optimal level of ignorance which, in (the) model, causes the self-interested user behavior to coincide with the optimum. Many features of (AA) model can be understood analytically, including the optimal level of user ignorance and the existence of critical scaling near the percolation threshold for fast links, where the potential benefit of user ignorance is greatest. >>️

Alican Saray, Calvin Pozderac, et al. The benefit of ignorance for traffic through a random congestible network. arXiv: 2503.09684v1 [cond-mat.dis-nn]. Mar 12, 2025.

https://arxiv.org/abs/2503.09684

Also:  network, behav, random, uncertainty, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, behavior,  randomness, uncertainty, price of anarchy, price of ignorance

# gst: apropos of viscoelastic flow instabilities, uncertainty in elastic turbulence.

<< Elastic turbulence can lead to increased flow resistance, mixing and heat transfer. Its control - either suppression or promotion - has significant potential, and there is a concerted ongoing effort by the community to improve our understanding. >>

AA << identify four regimes of uncertainty evolution, characterised by I) rapid transfer to large scales, with large scale growth rates of τ6 (where τ represents time), II) a dissipative reduction of uncertainty, III) exponential growth at all scales, and IV) saturation. These regimes are governed by the interplay between advective and polymeric contributions (which tend to amplify uncertainty), viscous, relaxation and dissipation effects (which reduce uncertainty), and inertial contributions. >>

<< In elastic turbulence, reducing Reynolds number increases uncertainty at short times, but does not significantly influence the growth of uncertainty at later times. At late times, the growth of uncertainty increases with Weissenberg number, with decreasing polymeric diffusivity, and with the logarithm of the maximum length scale, as large flow features adjust the balance of advective and relaxation effects. >>

Jack R. C. King, Robert J. Poole, et al. Uncertainty in Elastic Turbulence. arXiv: 2501.09421v1 [physics.flu-dyn]. Jan 16, 2025. 

https://arxiv.org/abs/2501.09421

Also: uncertainty, elastic, turbulence, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, uncertainty, elastic, elasticity, turbulence 

# gst: trade-off between coherence and dissipation for excitable phase oscillators.

<< Thermodynamic uncertainty relation (TUR) bounds coherence in stochastic oscillatory systems. In this paper, (AA) show that both dynamical and thermodynamic bounds play important roles for the excitable oscillators, e.g. neurons. >>

<< Excitable systems such as neurons have distinctive coherence features compared with other oscillators having no excitability. >>️

AA << combined the well-established results, i.e. the fluctuation of the ISI (inter-spike-interval) limited by 1/3 and the coherence resonance phenomenon, together with the TUR developed in recent years to investigate the coherence in the excitable phase oscillators. (AA) find quite different trade-off relation in the subthreshold (excitable) region and superthreshold (oscillatory) region, separated by the SNIC (saddle-node on an invariant circle) bound but meanwhile lower bounded by the TUR. Furthermore, (They) found that there is an optimal entropy production corresponding to the maximum coherence, which could serve as an alternative interpretation of the coherence resonance. It implies that more entropy production does not necessarily result in higher accuracy of currents. >>️

Chunming Zheng. Trade-off between coherence and dissipation for excitable phase oscillators. arXiv: 2412.16603v1 [cond-mat.stat-mech]. Dec 21, 2024.

https://arxiv.org/abs/2412.16603

Also: brain, entropy, dissipation, uncertainty, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, brain, neurons, entropy, oscillators, excitable phase oscillators, coherence, dissipation, uncertainty

# gst: taming uncertainty, a tutorial by NaN et Al.

<< All models are wrong, but some are useful. >>. George Box. ️

Nan Chen, Stephen Wiggins, Marios Andreou. Taming Uncertainty in a Complex World: The Rise of Uncertainty Quantification - A Tutorial for Beginners. arXiv: 2408.01823v1 [math.DS]. Aug 3, 2024. 

https://arxiv.org/abs/2408.01823

Also: NaN 'Not a Number'. In: Onda pneica. Apr 10, 2005 (quasi-stochastic poetry) https://inkpi.blogspot.com/2005/04/1694b-onda-pneica.html ;  nan(). In: Linux manual. https://www.man7.org/linux/man-pages/man3/nanf.3.html

Also: << Amico, qualunque  cosa suonerai . . . >>. Jelly Roll Morton. In: Soniche a ramulo. Jan 28, 2007 (quasi-stochastic poetry). https://inkpi.blogspot.com/2007/01/2113-soniche-ramulo.html  

Also: uncertainty, Mr. Jelly Roll Morton, jazz, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, uncertainty, Jelly Roll, jazz

# gst: approaching uncertainty among many-body real-time dynamics

<< Analog quantum simulation is emerging as a powerful tool for uncovering classically unreachable physics such as many-body real-time dynamics. >>️

AA << examines the interplay of errors arising from simulation of approximate time evolution with those due to practical, real-world device constraints. >>️

Nikita A. Zemlevskiy, Henry F. Froland, Stephan Caspar. Optimization of algorithmic errors in analog quantum simulations. Phys. Rev. A 109, 052425. May 15, 2024. 

https://journals.aps.org/pra/abstract/10.1103/PhysRevA.109.052425

<< The new technique focuses on two sources of error that arise from the approximations used to map the quantum system of interest to the analog quantum simulator. In a real-world simulator, these error sources are linked in a complex way, and individually minimizing each error can increase the overall uncertainty of a simulation. (AA) tackled this problem by first isolating the two error sources and then carefully studying their interplay. This analysis enabled the researchers to finely tune a simulation’s parameters to minimize its overall uncertainty and to maximize its precision. >>️

Ryan Wilkinson. Quantifying Uncertainties in Quantum Simulations. 

Physics 17, s51. May 15, 2024. 

https://physics.aps.org/articles/v17/s51

Also: uncertainty, error, noise in https://www.inkgmr.net/kwrds.html 

Keywords: gst, uncertainty, error, noise

# gst: apropos of uncertainty, notes on uncertainty, information, and classical dynamics.

<< Survival in this world is an adventure because we are so ignorant and everything around us seems so uncertain. In fact, it is hard to think of any realistic phenomenon that is completely free from one of the three kinds of uncertainty—deterministic (chaotic), stochastic, and quantum; more often than not, all of the three are present in various degrees. Thus, in order to gain any knowledge about any realistic system, one must understand how to characterize, quantify, and interpret these uncertainties. >>️

Sagar Chakraborty. Eclectic Notes on Uncertainty, Information, and Classical Dynamics. arXiv: 2404.13511v1 [physics.class-ph]. Apr 21, 2024.

https://arxiv.org/abs/2404.13511

Also: uncertainty, noise, error, in  https://www.inkgmr.net/kwrds.html 

Keywords: gst, information, uncertainty, ambiguity, noise, error 

# behav: unfrequent events under radical uncertainty; rats tend to avoid black swan situations.

AA << present a novel experimental design that aims at measuring the extent to which animal subjects are sensitive to rare and extreme events and, in addition, how rats respond to those very unfrequent events under radical uncertainty. (..) the novelty of (AA) design is that it provides two direct measures that help interpreting (..) behavioral data: Total Sensitivity to Rare and Extreme Events, and One-sided Sensitivity to Rare and Extreme Events with Black-Swan Avoidance/Jackpot-Seeking behaviors as limiting cases. >>️

<< First, most rats (..) can be grouped into a moderate to high Total Sensitivity group. This means that most rats diversify their choices across options in such a way that they more often rely on convex ones than on concave ones overall. Therefore, they tend to seek extreme gains/Jackpots and to avoid extreme losses/ Black Swans. In addition, most rats (..) tend to exhibit Black Swan Avoidance, which indicates that, given Total Sensitivity, they tend to try more often to avoid Black Swans than to seek Jackpots. (AA) interpret such a behavior as significant aversion towards uncertainty about rare and extreme losses.  >>️

<< all rats diversify their choices across a set of options, which is reminiscent of observed behaviors such as, for example, bet-hedging in animals and financial portfolio strategies used by humans >>

️

<< results from similar experiments among different species might be of interest for the analysis of neurobiological substrates involved in decision-making and its evolutionary traits in the context of rare and extreme events. >>️

Mickael Degoulet, Louis-Matis Willem, et al. Decision-Making in Rats is Sensitive to Rare and Extreme Events: the Black Swan Avoidance. bioRxiv 10.1101/2021.11.01.466806v1. Nov 04, 2021. 

https://www.biorxiv.org/content/10.1101/2021.11.01.466806v1

 Keywords: behav, game, decision-making, bet-hedging, trading, uncertainty, gain, loss, black swan 

# behav: apropos of the uncertainty about the 'Zona Incerta', a thresholding mechanism involved in curiosity and novelty-seeking behavior

<< Motivational drives are internal states that can be different even in similar interactions with external stimuli. Curiosity as the motivational drive for novelty-seeking and investigating the surrounding environment is for survival as essential and intrinsic as hunger. Curiosity, hunger, and appetitive aggression drive three different goal-directed behaviors—novelty seeking, food eating, and hunting >>️

<< Optogenetic activation of inhibitory neurons in medial ZI (ZIm) [medial Zona Incerta in mouse, freedom to choose what it wants], ZImGAD2 neurons, showed a dramatic increase in positive arousal level, depth of investigation, and duration of interaction with conspecifics and novel objects compared with familiar objects, crickets, and food. Optogenetic or chemogenetic deactivation of these neurons decreased depth and duration of investigation. Moreover, [AA] found that ZImGAD2 neurons are more active during deep investigation as compared with during shallow investigation. >>

<< [They] found that activation of prelimbic cortex (PL) axons into ZIm increases arousal level, and chemogenetic deactivation of these axons decreases the duration and depth of investigation. >>

<< Optogenetic activation of ZImGAD2 axons into lateral periaqueductal gray (lPAG) increases the arousal level, whereas chemogenetic deactivation of these axons decreases duration and depth of investigation. Calcium fiber photometry of these axons showed high activity during deep investigation and no significant activity during shallow investigation, suggesting a thresholding mechanism. >>️

<< Last, [AA] found a new subpopulation of inhibitory neurons in ZIm expressing tachykinin 1 (TAC1) that monosynaptically receive PL inputs and project to lPAG. Optogenetic activation and deactivation of these neurons, respectively, increased and decreased depth and duration of investigation. >>️️

Ahmadlou, Janou H. W. Houba, et al. A cell type–specific cortico-subcortical brain circuit for investigatory and novelty-seeking behavior. Science . Vol. 372, Issue 6543, eabe9681. doi: 10.1126/ science.abe9681. May 14, 2021. 

https://science.sciencemag.org/content/372/6543/eabe9681   

Brain mechanism of curiosity unraveled. Netherlands Institute for Neuroscience - KNAW.  May 13, 2021. 

https://www.sciencedaily.com/releases/2021/05/210513142430.htm