14,710 research outputs found
Cortical Synchronization and Perceptual Framing
How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. Perceptual framing is a process that resynchronizes cortical activities corresponding to the same retinal object. A neural network model is presented that is able to rapidly resynchronize clesynchronized neural activities. The model provides a link between perceptual and brain data. Model properties quantitatively simulate perceptual framing data, including psychophysical data about temporal order judgments and the reduction of threshold contrast as a function of stimulus length. Such a model has earlier been used to explain data about illusory contour formation, texture segregation, shape-from-shading, 3-D vision, and cortical receptive fields. The model hereby shows how many data may be understood as manifestations of a cortical grouping process that can rapidly resynchronize image parts which belong together in visual object representations. The model exhibits better synchronization in the presence of noise than without noise, a type of stochastic resonance, and synchronizes robustly when cells that represent different stimulus orientations compete. These properties arise when fast long-range cooperation and slow short-range competition interact via nonlinear feedback interactions with cells that obey shunting equations.Office of Naval Research (N00014-92-J-1309, N00014-95-I-0409, N00014-95-I-0657, N00014-92-J-4015); Air Force Office of Scientific Research (F49620-92-J-0334, F49620-92-J-0225)
Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions
Cell movement and intercellular signaling occur simultaneously during the
development of tissues, but little is known about how movement affects
signaling. Previous theoretical studies have shown that faster moving cells
favor synchronization across a population of locally coupled genetic
oscillators. An important assumption in these studies is that cells can
immediately interact with their new neighbors after arriving at a new location.
However, intercellular interactions in cellular systems may need some time to
become fully established. How movement affects synchronization in this
situation has not been examined. Here we develop a coupled phase oscillator
model in which we consider cell movement and the gradual recovery of
intercellular coupling experienced by a cell after movement, characterized by a
moving rate and a coupling recovery rate respectively. We find (1) an optimal
moving rate for synchronization, and (2) a critical moving rate above which
achieving synchronization is not possible. These results indicate that the
extent to which movement enhances synchrony is limited by a gradual recovery of
coupling. These findings suggest that the ratio of time scales of movement and
signaling recovery is critical for information transfer between moving cells.Comment: 18 single column pages + 1 table + 5 figures + Supporting Informatio
Synchronized Oscillations During Cooperative Feature Linking in a Cortical Model of Visual Perception
A neural network model of synchronized oscillator activity in visual cortex is presented in order to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these recent experiments, it was reported that synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained not only for single bar stimuli but also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli. For the double bar case, synchronous oscillations are induced in the region between the bars, but no oscillations are induced in the regions beyond the stimuli. These results were achieved with cellular units that exhibit limit cycle oscillations for a robust range of input values, but which approach an equilibrium state when undriven. Single and double bar synchronization of these oscillators was achieved by different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models. In preattentive visual segmentation, synchronous oscillations may reflect the binding of local feature detectors into a globally coherent grouping. In object recognition, synchronous oscillations may occur during an attentive resonant state that triggers new learning. These modelling results support earlier theoretical predictions of synchronous visual cortical oscillations and demonstrate the robustness of the mechanisms capable of generating synchrony.Air Force Office of Scientific Research (90-0175); Army Research Office (DAAL-03-88-K0088); Defense Advanced Research Projects Agency (90-0083); National Aeronautics and Space Administration (NGT-50497
Synchronization in dynamical networks of locally coupled self-propelled oscillators
Systems of mobile physical entities exchanging information with their
neighborhood can be found in many different situations. The understanding of
their emergent cooperative behaviour has become an important issue across
disciplines, requiring a general conceptual framework in order to harvest the
potential of these systems. We study the synchronization of coupled oscillators
in time-evolving networks defined by the positions of self-propelled agents
interacting in real space. In order to understand the impact of mobility in the
synchronization process on general grounds, we introduce a simple model of
self-propelled hard disks performing persistent random walks in 2 space and
carrying an internal Kuramoto phase oscillator. For non-interacting particles,
self-propulsion accelerates synchronization. The competition between agent
mobility and excluded volume interactions gives rise to a richer scenario,
leading to an optimal self-propulsion speed. We identify two extreme dynamic
regimes where synchronization can be understood from theoretical
considerations. A systematic analysis of our model quantifies the departure
from the latter ideal situations and characterizes the different mechanisms
leading the evolution of the system. We show that the synchronization of
locally coupled mobile oscillators generically proceeds through coarsening
verifying dynamic scaling and sharing strong similarities with the phase
ordering dynamics of the 2 XY model following a quench. Our results shed
light into the generic mechanisms leading the synchronization of mobile agents,
providing a efficient way to understand more complex or specific situations
involving time-dependent networks where synchronization, mobility and excluded
volume are at play
Synchronization of moving integrate and fire oscillators
We present a model of integrate and fire oscillators that move on a plane.
The phase of the oscillators evolves linearly in time and when it reaches a
threshold value they fire choosing their neighbors according to a certain
interaction range. Depending on the velocity of the ballistic motion and the
average number of neighbors each oscillator fires to, we identify different
regimes shown in a phase diagram. We characterize these regimes by means of
novel parameters as the accumulated number of contacted neighbors.Comment: 9 pages, 5 figure
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