-- Inviato da Libero Mail per Android -------- Messaggio inoltrato -------- Da: tozziart...@libero.it A: pcmarijuan.i...@aragon.es Data: mercoledì, 30 novembre 2016, 09:52AM +01:00 Oggetto: Response to Jerry LR Chandler
> >>Dear Pedro, >>here you are! >>I tried 4 times to submit this comment. >>Ciao, and thanks! >>> >>>> >>>>>Dear Jerry, >>>>>Thanks for the intriguing questions! >>>>>I thank our guest, Pedro Marijuan, for giving us the opportunity to talk with such high-ranked scientists. >>>>> >>>>> Let’s start! >>>>>The questions raised in this post are highly provocative. From the perspective of physical phenomenology, it is necessary to identify corresponding illations between the electric fields of brain dynamics (such as EEG patterns) and the mathematics of electric fields / electro-magnetism. It goes without saying that such correspondences must associate the measured quantities with the theoretical quantities. In other words, the units of measurements of “brain activity" should be associated with Maxwell’s equations. >>>>> >>>>>Are we really sure that this proposition is true? How does central nervous system process information? Current theories are based on two tenets: (a) information is transmitted by action potentials, the language by which neurons communicate with each other—and (b) homogeneous neuronal assemblies of cortical circuits operate on these neuronal messages where the operations are characterized by the intrinsic connectivity among neuronal populations. In this view, the size and time course of any spike is stereotypic and the information is restricted to the temporal sequence of the spikes; namely, the “neural code”. However, an increasing amount of novel data point towards an alternative hypothesis: (a) the role of neural code in information processing is overemphasized. Instead of simply passing messages, action potentials play a role in dynamic coordination at multiple spatial and temporal scales, establishing network interactions across several levels of a hierarchical modular architecture, modulating and regulating the propagation of neuronal messages. (b) Information is processed at all levels of neuronal infrastructure from macromolecules to population dynamics. For example, intra-neuronal (changes in protein conformation, concentration and synthesis) and extra-neuronal factors (extracellular proteolysis, substrate patterning, myelin plasticity, microbes, metabolic status) can have a profound effect on neuronal computations. This means molecular message passing may have cognitive connotations. This essay introduces the concept of “supramolecular chemistry”, involving the storage of information at the molecular level and its retrieval, transfer and processing at the supramolecular level, through transitory non-covalent molecular processes that are self-organized, self-assembled and dynamic. Finally, we note that the cortex comprises extremely heterogeneous cells, with distinct regional variations, macromolecular assembly, receptor repertoire and intrinsic microcircuitry. This suggests that every neuron (or group of neurons) embodies different molecular information that hands an operational effect on neuronal computation. >>>>>For further details, see: >>>>>http://link.springer.com/article/10.1007/s11571-015-9337-1 >>>>> >>>>> In the philosophy of science, this is the basic distinction between traditional mathematical narratives as pure abstractions and APPLIED mathematical theories of explanations of scientific facts. >>>>> >>>>>Pursuing Quine’s naturalized epistemology, we are aware that we need to make testable previsions, in order to “link” mathematical theories with explanations of scientific facts. This is exactly what we (try to) do. >>>>>The best example is the following, that shows how a novel approach might lead to unpredictable testable results: >>>>>Current advances in neurosciences deal with the functional architecture of the central nervous system, paving the way for general theories that improve our understanding of brain activity. From topology, a strong concept comes into play in understanding brain functions, namely, the 4D space of a “hypersphere’s torus”, undetectable by observers living in a 3D world. The torus may be compared with a video game with biplanes in aerial combat: when a biplane flies off one edge of gaming display, it does not crash but rather it comes back from the opposite edge of the screen. Our thoughts exhibit similar behaviour, i.e. the unique ability to connect past, present and future events in a single, coherent picture as if we were allowed to watch the three screens of past-present-future “glued” together in a mental kaleidoscope. Here we hypothesize that brain functions are embedded in a imperceptible fourth spatial dimension and propose a method to empirically assess its presence. Neuroimaging fMRI series can be evaluated, looking for the topological hallmark of the presence of a fourth dimension. Indeed, there is a typical feature which reveal the existence of a functional hypersphere: the simultaneous activation of areas opposite each other on the 3D cortical surface. Our suggestion—substantiated by recent findings—that brain activity takes place on a closed, donut-like trajectory helps to solve long-standing mysteries concerning our psychological activities, such as mind-wandering, memory retrieval, consciousness and dreaming state. >>>>>For further details, see: >>>>>http://link.springer.com/article/10.1007%2Fs11571-016-9379-z >>>>> >>>>>We puzzled the neuroscientific community, giving rise to a hot debate: >>>>>http://blogs.discovermagazine.com/neuroskeptic/2016/06/11/the-four-dimensional-brain/#.WDvjihrhCUm >>>>> >>>>>Until we found the smoking gun: >>>>>We introduce a novel method for the measurement of information in fMRI neuroimages, i.e., nucleus clustering's Renyi entropy derived from strong proximities in feature-based Voronoi tessellations, e.g., maximal nucleus clustering (MNC). We show how MNC is a novel, fast and inexpensive image-analysis technique, independent from the standard blood-oxygen-level dependent signals, which facilitates the objective detection of hidden temporal patterns of entropy/information in zones of fMRI images generally not taken into account by the subjective standpoint of the observer. In order to evaluate the potential applications of MNC, we looked for the presence of a fourth dimension's distinctive hallmarks in a temporal sequence of 2D images taken during spontaneous brain activity. Indeed, recent findings suggest that several brain activities, such as mind-wandering and memory retrieval, might take place in the functional space of a four dimensional hypersphere, which is a double donut-like structure undetectable in the usual three dimensions. We found that the Renyi entropy is higher in MNC areas than in the surrounding ones, and that these temporal patterns closely resemble the trajectories predicted by the possible presence of a hypersphere in the brain. >>>>>For further details, see (this manuscript is not yet published, but it is in advanced review): >>>>>http://biorxiv.org/content/early/2016/08/30/072397 >>>>> >>>>> >>>>>Concernig your answers to our questions, I may summarize our response in this way: >>>>>A s we stated above, the bipolarity of electrical particles is just one one the countless functional phenomena occurring in the brain. See, for example, our still unpublished manuscript, where we assess cortical activity in terms of McKean-Vlasov equations, derived from the classical Vlasov equations for plasma : >>>>>http://vixra.org/abs/1610.0014 >>>>> >>>>>From a philosophical point of view, we pursue the William Bechtel’s approach of a mechanistic explanation in psychology, that goes from reduction back to higher levels. >>>>>http://www.tandfonline.com/doi/abs/10.1080/09515080903238948 >>>>>Becthel states that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. This means that, when looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. >>>>>But the main question here is: w hat does a topologic reformulation add >>>>>in the evaluation of the nervous processes? BUT and its extensions provide a methodological approach which makes it possible for us to study experience in terms of projections from real to abstract phase spaces. The importance of projections between environmental spaces, where objects lie, and brain phase spaces, where mental operations take place, is also suggested by a recent paper, which provides a rigorous way of measuring distance on concave neural manifolds ( http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002400 ). The real, measurable nervous activity can be described in terms of paths occurring on n-spheres. It leads to a consideration of affinities among nervous signals, characterized as antipodal points on multi-dimensional spheres embedded in abstract spaces. To provide an example, embedding brain activities in n-spheres allows the quantification of geometric parameters, such as angles, lengths, and so on, that could be useful in neuroimaging data optimization. BUT and its ingredients can be modified in different guises, in order to assess a wide range of nervous functions. Although this field is nearly novel and still in progress, with several unpublished findings, we may provide some examples . Such a methodological approach has been proved useful in the evaluation of brain symmetries, which allow us to perform coarse- or fine-grained evaluation of fMRI images and to assess the relationships, affinities, shape-deformations and closeness among BOLD activated areas ( http://onlinelibrary.wiley.com/doi/10.1002/jnr.23720/abstract ). >>>>>Further, BUT has been proved useful in the evaluation of cortical histological images previoulsy treated with Voronoi tessellation ( http://www.sciencedirect.com/science/article/pii/S0304394016301999 ). >>>>>A wide range of brain dynamics, ranging from neuronal membrane activity to spikes, from seizures to spreading depression, lie along a continuum of the repertoire of the neuronal nonlinear activities which may be of substantial importance in enabling our understanding of central nervous system function and in the control of pathological neurological states. Nonlinear dynamics are frequently studied through logistic maps equipped with Hopf bifurcations, where intervals are dictated by Feigenbaum constants. Tozzi and Peters (2016, quoted above) introduced an approach that offers an explanation of nervous nonlinearity and Hopf bifurcations in terms of algebraic topology. Hopf bifurcation transformations (the antipodal points) can be described as paths or trajectories on abstract spheres embedded in n-spheres where n stands for the Feigenbaum constant’s irrational number . Although the paper takes into account just Hopf bifurcations among the brain nonlinear dynamics, this is however a starting point towards the “linearization” of other nonlinear dynamics in the brain. In sum, BUT makes it possible for us to evaluate nonlinear brain dynamics, which occur during knowledge acquisition and processing, through much simpler linear techniques. >>>>> >>>>>BUT and its variants are not just a methodological approach, but also >>>>>display a physical , quantifiable counterpart. To make an example, although anatomical and functional relationships among cortical structures are fruitfully studied, e.g. , in terms of dynamic causal modelling, pairwise entropies and temporal-matching oscillations, nevertheless proximity among brain signals adds information that has the potential to be operationalized. For example, based on the ubiquitous presence of antipodal cortical zones with co-occuring BOLD activation, it has been recently suggested that spontaneous brain activity might display donut-like trajectories (Tozzi and Peters 2016, see above). >>>>>BUT allows the evaluation of energetic nervous requirements too. There exists a physical link between the two spheres S n and S n-1 and their energetic features. When two antipodal functions a n-sphere S n , standing for symmetries, project to a n -Euclidean manifold (where S n-1 lies), a single function is achieved and a symmetry break occurs (Tozzi and Peters 2016, see above). It is known that a decrease in symmetry goes together with a decrease in entropy. It means that the single mapping function on S n-1 displays energy parameters lower than the sum of two corresponding antipodal functions on S n . Therefore, in the system S n and S n-1 , a decrease in dimensions gives rise to a decrease in energy. We achieve a system in which the energetic changes do not depend anymore on thermodynamic parameters, but rather on affine connections, homotopies and continuous functions. A preliminary example is provided by a recent paper, where BUT allows the detection of Bayesian Kullback-Leibler divergence during unsure perception (Tozzi and Peters, 2016, see above) . Therefore, paraphrasing what you stated, t he meaning specified by the mathematical symbol IS the meaning specified by a physical symbol, at least in our BUT case. >>>>> >>>>> >>>>>Concerning the a priori Kantian notions (not just of space and time!), the most successful current neuroscientific approaches are framed exactly on… Kantian a priori! See: >>>>>http://journal.frontiersin.org/article/10.3389/fnsys.2016.00079/full >>>>>The paper says: “ Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. ” >>>>> >>>>>In such a context, a phrase of yours is very important: “ Perhaps this >>>>>premise rests on the a priori Kantian notions of space and time rather than the systematic categories of Aristotelian causality”. Therefore, your premise (e.g., the systematic categories of Aristotelian causality) is as questionable as a Kantian approach, or every other… All of us are just playing Wittgenstein’s linguistic jokes. >>>>> >>>>>Another example: “Given the theory of quantum mechanics and the critical role that angular momenta play in the organization of brain dynamics, I would conjecture that it is conceivable that electro-dynamic equations akin to Feynman diagrams are needed to quantify brain phenomenon”. >>>>> >>>>>This is another linguistic joke. Nobody ever demonstrated that the brain works with quantum mechanics and that angular momenta play a role in the organization of brain dynamics! To be honest, we published on BUT and quantum mechanics ( http://link.springer.com/article/10.1007/s10773-016-2998-7 ), therefore we were tempted to use such kind approaches for our brain models. However, in this case, a quantistic brain it is not a falsifiable theory at all. And despite Lakatos’ disruption of Popper’s falsifiability, I still think, in another linguistic joke, that a theory needs to be falsifiable… >>>>> >>>>> >>>>>Thanks a lot! >>>>>Ciao! >>>>> >>>>>Arturo Tozzi >>>>>AA Professor Physics, University North Texas >>>>>Pediatrician ASL Na2Nord, Italy >>>>>Comput Intell Lab, University Manitoba >>>>>http://arturotozzi.webnode.it/ >>>>> >>>>> >>>>>>----Messaggio originale---- >>>>>>Da: "Jerry LR Chandler" < jerry_lr_chand...@mac.com > >>>>>>Data: 28/11/2016 5.35 >>>>>>A: "FIS Webinar"< fis@listas.unizar.es > >>>>>>Cc: < tozziart...@libero.it > >>>>>>Ogg: Physical Phenomenology and Forms of Information Re: [Fis] NEW >>>>>>DISCUSSION SESSION--TOPOLOGICAL BRAIN. >>>>>> >>>>>>FIS Colleagues: >>>>>> >>>>>>The questions raised in this post are highly provocative. From the >>>>>>perspective of physical phenomenology, it is necessary to identify >>>>>>corresponding illations between the electric fields of brain dynamics >>>>>>(such as EEG patterns) and the mathematics of electric fields / >>>>>>electro-magnetism. It goes without saying that such correspondences must >>>>>>associate the measured quantities with the theoretical quantities. In >>>>>>other words, the units of measurements of “brain activity" should be >>>>>>associated with Maxwell’s equations. In the philosophy of science, this >>>>>>is the basic distinction between traditional mathematical narratives as >>>>>>pure abstractions and APPLIED mathematical theories of explanations of >>>>>>scientific facts. >>>>>> >>>>>>My responds to these questions are based on the propositional functions >>>>>>and the formation operators of applied (organic) mathematics. >>>>>>>>>> >>>>>>>>>>TOPOLOGY AND BRAIN FUNCTION >>>>>>>>>> >>>>>>>>>>Arturo Tozzi >>>>>>>>>>Center for Nonlinear Science, University of North Texas >>>>>>>>>>1155 Union Circle, #311427 >>>>>>>>>>Denton, TX 76203-5017, USA, and >>>>>>>>>>tozziart...@libero.it >>>>>>>>>>James F. Peters >>>>>>>>>>Department of Electrical and Computer Engineering, University of >>>>>>>>>>Manitoba >>>>>>>>>>75A Chancellor ’ s Circle, Winnipeg, MB R3T 5V6 >>>>>>>>>>james.pete...@umanitoba.ca >>>>>>>>>> >>>>>>>>>>Questions. >>>>>>>>>>1) Could we use projections and mappings, in order to >>>>>>>>>>describe brain activity? >>>>>>>>>> >>>>>>JLRC A propositional function is needed to associate the logic >>>>>>of the theorem with the physical phenomenology of brain activity. The >>>>>>bi-polarity of electrical particles that generate brain function make >>>>>>this task extra-ordinarily unlikely. >>>>>> >>>>>>>>>>What >>>>>>>>>>2) Is such a topological approach linked with previous >>>>>>>>>>claims of old “epistemologists” of recent “neuro-philosophers”? >>>>>>>>>> >>>>>>JLRC This question is not scientifically meaningful to me. But, >>>>>>see my comment on physical Kantianism below. >>>>>> >>>>>>>>>>3) Is such a topological approach linked with current >>>>>>>>>>neuroscientific models? >>>>>>>>>> >>>>>>JLRC No. present-day neuroscientific models are all based on electrical >>>>>>particles and organized collections of electrical particles. >>>>>> >>>>>>>>>>4) The BUT and its variants display four ingredients, e.g., >>>>>>>>>>a continuous function, antipodal points, changes of dimensions and >>>>>>>>>>the possibility of types of dimensions other than the spatial ones. >>>>>>>>>>Is it feasible to assess brain function in terms of BUT and its >>>>>>>>>>variants? >>>>>>JLRC I do not find a propositional function in this interrogative, so I >>>>>>respond in the negative. Physical phenomenology associated with brain >>>>>>dynamics are discrete physical events, such as ion transport and neuronal >>>>>>firings. But, of course, if anyone can find a way to associate >>>>>>continuous topological spaces with quantum electro-dynamics of angular >>>>>>momentum necessary for brain activity, then I would retract my opinion. >>>>>> >>>>>>>>>>5) How to operationalize the procedures? >>>>>>>>>> >>>>>>JLRC: Current theories of neuronal activity consists of several logical >>>>>>forms of physical sublations from the electrical particles to the >>>>>>mereological propositional functions of the whole. Which physical >>>>>>phenomena is the theory seeking to “operationalize”? >>>>>> >>>>>>>>>>6) Is it possible to build a general topological theory of >>>>>>>>>>the brain? >>>>>>>>>> >>>>>>JLRC Of course it is. It is just mathematics. One such general >>>>>>mathematical model was published and it appears to be mathematically >>>>>>sound. The [FIS] informational challenge is find correspondence >>>>>>relations between mathematical symbols and physical symbols such that the >>>>>>mathematical theory can be tested. The scientific challenge is to find >>>>>>causal pathways for physical phenomena, whatever the mathematical >>>>>>structure of the theory is. >>>>>>>>>>7) Our “from afar” approach takes into account the dictates >>>>>>>>>>of far-flung branches, from mathematics to physics, from algebraic >>>>>>>>>>topology, to neuroscience. Do you think that such broad >>>>>>>>>>multidisciplinary tactics could be the key able to unlock the >>>>>>>>>>mysteries of the brain, or do you think that more specific and “on >>>>>>>>>>focus” approaches could give us more chances? >>>>>>>>>> >>>>>>JLRC: Perhaps the term “consciousness” should be substituted for the >>>>>>word “brain”? Extensive biological knowledge of information processing >>>>>>in brains from organisms with only a few neurons to very large organisms >>>>>>with upward of ten to the ninth neurons exists. This information is >>>>>>generated from physical measurements. This information on the physical >>>>>>phenomenology associated with the physical methodology for measuring >>>>>>brain function (activity) is published in the open literature and >>>>>>available to any scientist who is interested in analysis of physical >>>>>>phenomenology. >>>>>> >>>>>>From my perspective, the deep premise underlying the hypothesis presented >>>>>>here is inadequate to describe the physical phenomenology of brain >>>>>>activity. Perhaps this premise rests on the a priori Kantian notions of >>>>>>space and time rather than the systematic categories of Aristotelian >>>>>>causality. >>>>>> >>>>>>At it’s root, my view is simple. Any abstract mathematical theorem has >>>>>>meaning only within the mathematical symbol system. Any model of >>>>>>physical phenomenology requires symbolic quantities of physical units of >>>>>>measure be associated with the symbolic mathematics. The meaning >>>>>>specified by the mathematical symbol is not the meaning specified by a >>>>>>physical symbol. >>>>>> >>>>>>Given the theory of quantum mechanics and the critical role that angular >>>>>>momenta play in the organization of brain dynamics, I would conjecture >>>>>>that it is conceivable that electro-dynamic equations akin to Feynman >>>>>>diagrams are needed to quantify brain phenomenon. Conceptually, one can >>>>>>speculate that such a hypothetical diagram for changes in angular >>>>>>momentum might take a conceptual form such as: >>>>>> >>>>>>A + B —> [ACB —> A’CB’] —> A’ + B’. >>>>>> >>>>>>where the alphabet symbols represent different collections of electrical >>>>>>particles. >>>>>> >>>>>>Cheers >>>>>> >>>>>>Jerry >>>>>> >>>>>>Jerry LR Chandler >>>>>>Research Professor >>>>>>George Mason University >>>>>>Krasnow Institute for Advanced Study >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>>>>>>NOTE: A simple explanation of BUT and its novel variants >>>>>>>>>> (with the proper bibliography) can be found in this short movie on >>>>>>>>>>Youtube: >>>>>>>>>>https://www.youtube.com/watch?v=oxfqraR1bIg >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>Best wishes >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>Arturo Tozzi >>>>>>>>>>AA Professor Physics, University North Texas >>>>>>>>>>Pediatrician ASL Na2Nord, Italy >>>>>>>>>>Comput Intell Lab, University Manitoba >>>>>>>>>>http://arturotozzi.webnode.it/ >>>>>>>>>> >>>>>>>> >>>>>>>_______________________________________________ >>>>>>>Fis mailing list >>>>>>>Fis@listas.unizar.es >>>>>>>http://listas.unizar.es/cgi-bin/mailman/listinfo/fis >>>>>> >>>>> >>>> >>> >>> >> >> >
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