10,279 research outputs found
The arrow of time and the nature of spacetime
This paper extends the work of a previous paper [arXiv:1208.2611] on the flow
of time, to consider the origin of the arrow of time. It proposes that a `past
condition' cascades down from cosmological to micro scales, being realized in
many microstructures and setting the arrow of time at the quantum level by
top-down causation. This physics arrow of time then propagates up, through
underlying emergence of higher level structures, to geology, astronomy,
engineering, and biology. The appropriate space-time picture to view all this
is an emergent block universe (`EBU'), that recognizes the way the present is
different from both the past and the future. This essential difference is the
ultimate reason the arrow of time has to be the way it is.Comment: 56 pages, 7 figure
Nonlinear brain dynamics and many-body field dynamics
We report measurements of the brain activity of subjects engaged in
behavioral exchanges with their environments. We observe brain states which are
characterized by coordinated oscillation of populations of neurons that are
changing rapidly with the evolution of the meaningful relationship between the
subject and its environment, established and maintained by active perception.
Sequential spatial patterns of neural activity with high information content
found in sensory cortices of trained animals between onsets of conditioned
stimuli and conditioned responses resemble cinematographic frames. They are not
readily amenable to description either with classical integrodifferential
equations or with the matrix algebras of neural networks. Their modeling is
provided by field theory from condensed matter physics.Comment: 8 pages, Invited talk presented at Fr\"ohlich Centenary International
Symposium "Coherence and Electromagnetic Fields in Biological Systems", July
1-4, 2005, Prague, Czech Republi
Nonlinear brain dynamics as macroscopic manifestation of underlying many-body field dynamics
Neural activity patterns related to behavior occur at many scales in time and
space from the atomic and molecular to the whole brain. Here we explore the
feasibility of interpreting neurophysiological data in the context of many-body
physics by using tools that physicists have devised to analyze comparable
hierarchies in other fields of science. We focus on a mesoscopic level that
offers a multi-step pathway between the microscopic functions of neurons and
the macroscopic functions of brain systems revealed by hemodynamic imaging. We
use electroencephalographic (EEG) records collected from high-density electrode
arrays fixed on the epidural surfaces of primary sensory and limbic areas in
rabbits and cats trained to discriminate conditioned stimuli (CS) in the
various modalities. High temporal resolution of EEG signals with the Hilbert
transform gives evidence for diverse intermittent spatial patterns of amplitude
(AM) and phase modulations (PM) of carrier waves that repeatedly re-synchronize
in the beta and gamma ranges at near zero time lags over long distances. The
dominant mechanism for neural interactions by axodendritic synaptic
transmission should impose distance-dependent delays on the EEG oscillations
owing to finite propagation velocities. It does not. EEGs instead show evidence
for anomalous dispersion: the existence in neural populations of a low velocity
range of information and energy transfers, and a high velocity range of the
spread of phase transitions. This distinction labels the phenomenon but does
not explain it. In this report we explore the analysis of these phenomena using
concepts of energy dissipation, the maintenance by cortex of multiple ground
states corresponding to AM patterns, and the exclusive selection by spontaneous
breakdown of symmetry (SBS) of single states in sequences.Comment: 31 page
Flow structure and optical beam propagation in high-Reynolds-number gas-phase shear layers and jets
We report on the structure of the scalar index-of-refraction field generated by turbulent, gas-phase, incompressible and compressible shear layers and incompressible jets, and on associated beam-propagation aero-optical phenomena. Using simultaneous imaging of the optical-beam distortion and the turbulent-flow index-of-refraction field, wavefront-phase functions were computed for optical beams emerging from the turbulent region in these free-shear flows, in an aero-optical regime producing weak wavefront distortions. Spatial wavefront-phase behaviour is found to be dominated by the large-scale structure of these flows. A simple level-set representation of the index-of-refraction field in high-Reynolds-number, incompressible shear layers is found to provide a good representation of observed wavefront-phase behaviour, indicating that the structure of the unsteady outer boundaries of the turbulent region provides the dominant contributions
Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience
This essay is presented with two principal objectives in mind: first, to
document the prevalence of fractals at all levels of the nervous system, giving
credence to the notion of their functional relevance; and second, to draw
attention to the as yet still unresolved issues of the detailed relationships
among power law scaling, self-similarity, and self-organized criticality. As
regards criticality, I will document that it has become a pivotal reference
point in Neurodynamics. Furthermore, I will emphasize the not yet fully
appreciated significance of allometric control processes. For dynamic fractals,
I will assemble reasons for attributing to them the capacity to adapt task
execution to contextual changes across a range of scales. The final Section
consists of general reflections on the implications of the reviewed data, and
identifies what appear to be issues of fundamental importance for future
research in the rapidly evolving topic of this review
Statistical Mechanics and Visual Signal Processing
The nervous system solves a wide variety of problems in signal processing. In
many cases the performance of the nervous system is so good that it apporaches
fundamental physical limits, such as the limits imposed by diffraction and
photon shot noise in vision. In this paper we show how to use the language of
statistical field theory to address and solve problems in signal processing,
that is problems in which one must estimate some aspect of the environment from
the data in an array of sensors. In the field theory formulation the optimal
estimator can be written as an expectation value in an ensemble where the input
data act as external field. Problems at low signal-to-noise ratio can be solved
in perturbation theory, while high signal-to-noise ratios are treated with a
saddle-point approximation. These ideas are illustrated in detail by an example
of visual motion estimation which is chosen to model a problem solved by the
fly's brain. In this problem the optimal estimator has a rich structure,
adapting to various parameters of the environment such as the mean-square
contrast and the correlation time of contrast fluctuations. This structure is
in qualitative accord with existing measurements on motion sensitive neurons in
the fly's brain, and we argue that the adaptive properties of the optimal
estimator may help resolve conlficts among different interpretations of these
data. Finally we propose some crucial direct tests of the adaptive behavior.Comment: 34pp, LaTeX, PUPT-143
Electroencephalographic field influence on calcium momentum waves
Macroscopic EEG fields can be an explicit top-down neocortical mechanism that
directly drives bottom-up processes that describe memory, attention, and other
neuronal processes. The top-down mechanism considered are macrocolumnar EEG
firings in neocortex, as described by a statistical mechanics of neocortical
interactions (SMNI), developed as a magnetic vector potential . The
bottom-up process considered are waves prominent in synaptic
and extracellular processes that are considered to greatly influence neuronal
firings. Here, the complimentary effects are considered, i.e., the influence of
on momentum, . The canonical
momentum of a charged particle in an electromagnetic field, (SI units), is calculated, where the charge of
is , is the magnitude of the charge of an
electron. Calculations demonstrate that macroscopic EEG can be
quite influential on the momentum of ions, in
both classical and quantum mechanics. Molecular scales of
wave dynamics are coupled with fields developed at macroscopic
regional scales measured by coherent neuronal firing activity measured by scalp
EEG. The project has three main aspects: fitting models to EEG
data as reported here, building tripartite models to develop
models, and studying long coherence times of waves in the
presence of due to coherent neuronal firings measured by scalp
EEG. The SMNI model supports a mechanism wherein the interaction at tripartite synapses, via a dynamic centering
mechanism (DCM) to control background synaptic activity, acts to maintain
short-term memory (STM) during states of selective attention.Comment: Final draft. http://ingber.com/smni14_eeg_ca.pdf may be updated more
frequentl
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