Possible Roles of Neural Electron Spin Networks in Memory and Consciousness

Spin is the origin of quantum effects in both Bohm and Hestenes quantum formulism and a fundamental quantum process associated with the structure of space-time. Thus, we have recently theorized that spin is the mind-pixel and developed a qualitative model of consciousness based on nuclear spins inside neural membranes and proteins. In this paper, we explore the possibility of unpaired electron spins being the mind-pixels. Besides free O2 and NO, the main sources of unpaired electron spins in neural membranes and proteins are transition metal ions and O2 and NO bound/absorbed to large molecules, free radicals produced through biochemical reactions and excited molecular triplet states induced by fluctuating internal magnetic fields. We show that unpaired electron spin networks inside neural membranes and proteins are modulated by action potentials through exchange and dipolar coupling tensors and spin-orbital coupling and g-factor tensors and perturbed by microscopically strong and fluctuating internal magnetic fields produced largely by diffusing O2. We argue that these spin networks could be involved in brain functions since said modulation inputs information carried by the neural spike trains into them, said perturbation activates various dynamics within them and the combination of the two likely produce stochastic resonance thus synchronizing said dynamics to the neural firings. Although quantum coherence is desirable, it is not required for these spin networks to serve as the microscopic components for the classical neural networks. On the quantum aspect, we speculate that human brain works as follows with unpaired electron spins being the mind-pixels: Through action potential modulated electron spin interactions and fluctuating internal magnetic field driven activations, the neural electron spin networks inside neural membranes and proteins form various entangled quantum states some of which survive decoherence through quantum Zeno effects or in decoherence-free subspaces and then collapse contextually via irreversible and non-computable means producing consciousness and, in turn, the collective spin dynamics associated with said collapses have effects through spin chemistry on classical neural activities thus influencing the neural networks of the brain. Thus, according to this alternative model, the unpaired electron spin networks are the “mind-screen,” the neural membranes and proteins are the mind-screen and memory matrices, and diffusing O2 and NO are pixel-activating agents. Together, they form the neural substrates of consciousness

Dewey, Enactivism and Greek Thought

In this chapter, I examine how Dewey circumnavigated debates between empiricists and a priorists by showing that active bodies can perform integrative operations traditionally attributed to “inner” mechanisms, and how he thereby realized developments at which the artificial intelligence, robotics and cognitive science communities only later arrived. Some of his ideas about experience being constituted through skills actively deployed in cultural settings were inspired by ancient Greek sources. Thus in some of his more radical moments, Dewey refined rather than invented the wheel, and I suggest that prominent embodiment figures have done the same, Dewey having anticipated them, particularly Noë and his version of enactivism. I urge that cognitive science may progress into relatively unexplored territory by traveling Dewey’s historically sensitive path

Instrumentation and Evaluation of Distributed Computations

Distributed computations are a very important aspect of modern computing, especially given the rise of distributed systems used for applications such as web search, massively multiplayer online games, financial trading, and cloud computing. When running these computations across several physical machines it becomes much more difficult to determine exactly what is occurring on each system at a specific point in time. This is due to each server having an independent clock, thus making event timestamps inherently inaccurate across machine boundaries. Another difficulty with evaluating distributed experiments is the coordination required to launch daemons, executables, and logging across all machines, followed by the necessary gathering of all related output data. The goal of this research is to overcome these obstacles and construct a single, global timeline of events from all servers. We employ high-resolution clock synchronization to bring all servers within microseconds as measured by a modified version of the Network Time Protocol implementation. Kernel and user-level events with wall-clock timestamps are then logged during basic network socket experiments. These data are then collected from each server and merged into a single dataset, sorted by timestamp, and plotted on a timeline. The entire experiment, from setup to teardown to data collection, is coordinated from a single server. The timeline visualizations provide a narrative of not only how packets flow between servers, but also how kernel interrupt handlers and other events shape an experiment's execution

Chorusing, synchrony, and the evolutionary functions of rhythm

A central goal of biomusicology is to understand the biological basis of human musicality. One approach to this problem has been to compare core components of human musicality (relative pitch perception, entrainment, etc.) with similar capacities in other animal species. Here we extend and clarify this comparative approach with respect to rhythm. First, whereas most comparisons between human music and animal acoustic behavior have focused on spectral properties (melody and harmony), we argue for the central importance of temporal properties, and propose that this domain is ripe for further comparative research. Second, whereas most rhythm research in non-human animals has examined animal timing in isolation, we consider how chorusing dynamics can shape individual timing, as in human music and dance, arguing that group behavior is key to understanding the adaptive functions of rhythm. To illustrate the interdependence between individual and chorusing dynamics, we present a computational model of chorusing agents relating individual call timing with synchronous group behavior. Third, we distinguish and clarify mechanistic and functional explanations of rhythmic phenomena, often conflated in the literature, arguing that this distinction is key for understanding the evolution of musicality. Fourth, we expand biomusicological discussions beyond the species typically considered, providing an overview of chorusing and rhythmic behavior across a broad range of taxa (orthopterans, fireflies, frogs, birds, and primates). Finally, we propose an “Evolving Signal Timing” hypothesis, suggesting that similarities between timing abilities in biological species will be based on comparable chorusing behaviors. We conclude that the comparative study of chorusing species can provide important insights into the adaptive function(s) of rhythmic behavior in our “proto-musical” primate ancestors, and thus inform our understanding of the biology and evolution of rhythm in human music and language

Scheduling Heterogeneous HPC Applications in Next-Generation Exascale Systems

Next generation HPC applications will increasingly time-share system resources with emerging workloads such as in-situ analytics, resilience tasks, runtime adaptation services and power management activities. HPC systems must carefully schedule these co-located codes in order to reduce their impact on application performance. Among the techniques traditionally used to mitigate the performance effects of time- share systems is gang scheduling. This approach, however, leverages global synchronization and time agreement mechanisms that will become hard to support as systems increase in size. Alternative performance interference mitigation approaches must be explored for future HPC systems. This dissertation evaluates the impacts of workload concurrency in future HPC systems. It uses simulation and modeling techniques to study the performance impacts of existing and emerging interference sources on a selection of HPC benchmarks, mini-applications, and applications. It also quantifies the cost and benefits of different approaches to scheduling co-located workloads, studies performance interference mitigation solutions based on gang scheduling, and examines their synchronization requirements. To do so, this dissertation presents and leverages a new Extreme Value Theory- based model to characterize interference sources, and investigate their impact on Bulk Synchronous Parallel (BSP) applications. It demonstrates how this model can be used to analyze the interference attenuation effects of alternative fine-grained OS scheduling approaches based on periodic real time schedulers. This analysis can, in turn, guide the design of those mitigation techniques by providing tools to understand the tradeoffs of selecting scheduling parameters

Making Applications Faster by Asynchronous Execution: Slowing Down Processes or Relaxing MPI Collectives

Comprehending the performance bottlenecks at the core of the intricate hardware-software interactions exhibited by highly parallel programs on HPC clusters is crucial. This paper sheds light on the issue of automatically asynchronous MPI communication in memory-bound parallel programs on multicore clusters and how it can be facilitated. For instance, slowing down MPI processes by deliberate injection of delays can improve performance if certain conditions are met. This leads to the counter-intuitive conclusion that noise, independent of its source, is not always detrimental but can be leveraged for performance improvements. We employ phase-space graphs as a new tool to visualize parallel program dynamics. They are useful in spotting certain patterns in parallel execution that will easily go unnoticed with traditional tracing tools. We investigate five different microbenchmarks and applications on different supercomputer platforms: an MPI-augmented STREAM Triad, two implementations of Lattice-Boltzmann fluid solvers, and the LULESH and HPCG proxy applications.Comment: 18 pages, 14 figures, 7 tables. Corrected Fig. 4 layou