Using skew Gabor filter in source signal separation and local spectral orientation analysis

Yu, Weichuan; Sommer, Gerald; Daniilidis, Kostas; Duncan, James S.

doi:10.1016/j.imavis.2004.09.006

Cited by 6 publications

(3 citation statements)

References 31 publications

(33 reference statements)

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“…A Gabor wavelet transform has been chosen for use in this work, because the responses of Gabor wavelets have optimal properties with respect to the time-frequency uncertainty principle [41]. The Gabor wavelet used had a centre frequency of 0.6 Hz and was applied with a continuous wavelet transform using scales from 1 to 100 in increments of 0.1, and a delta of 0.001.…”

Section: Methodsmentioning

confidence: 99%

“…The blurring from a Gabor wavelet is in the form of a Gaussian [41], as illustrated by a time slice at time point 1460 ms shown in figure 2c taken from the scalogram in figure 2a. Further techniques have to be applied to the transformed data in order to extract the instantaneous frequency information.…”

Section: Methodsmentioning

confidence: 99%

“…As can be seen by the scalogram in figure 2a the data in the work presented here is of this type. Drawing upon the Gaussian nature of the impulse response from the Gabor wavelet, we apply a technique of fitting a sum-of-Gaussians model to the transformed data at each point in time [41]. Figure 2c shows such a fitting.…”

Section: Methodsmentioning

confidence: 99%

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Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

Bhowmik

Shanahan

2013

PLoS ONE

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Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%