Nerve impulse propagation and wavelet theory
A luminous stimulus which penetrates in a retina is converted to a nerve message. Ganglion cells give a response that may be approximated by a wavelet. We determine a function PSI which is associated with the propagation of nerve impulses along an axon. Each kind of channel (inward and outward) may be open or closed, depending on the transmembrane potential. The transition between these states is a random event. Using quantum relations, we estimate the number of channels susceptible to switch between the closed and open states. Our quantum approach was first to calculate the energy level distribution in a channel. We obtain, for each kind of channel, the empty level density and the filled level density of the open and closed conformations. The joint density of levels provides the transition number between the closed and open conformations. The algebraic sum of inward and outward open channels is a function PSI of the normalized energy E. The function PSI verifies the major properties of a wavelet. We calculate the functional dependence of the axon membrane conductance with the transmembrane energy.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Sparse chaos in cortical circuits
Nerve impulses, the currency of information flow in the brain, are generated by an instability of the neuronal membrane potential dynamics. Neuronal circuits exhibit collective chaos that appears essential for learning, …
Impulse Noise Removal In Speech Using Wavelets
A new method for removing impulse noise from speech in the wavelet transform domain is proposed. The method utilizes the multiresolution property of the wavelet transform, which provides finer time resolution at the high…
Neuron segmentation using 3D wavelet integrated encoder-decoder network
Motivation: 3D neuron segmentation is a key step for the neuron digital reconstruction, which is essential for exploring brain circuits and understanding brain functions. However, the fine line-shaped nerve fibers of neu…
DecoderSegmentationTFDWT: Fast Discrete Wavelet Transform TensorFlow Layers
TFDWT is an open-source Python library that allows the construction of TensorFlow Layers for Fast Discrete Wavelet Transform (DWT) and Inverse Discrete Wavelet Transform (IDWT) in end-to-end backpropagation learning netw…
A Novel Wavelet-base Algorithm for Reconstruction of the Time-Domain Impulse Response from Band-limited Scattering Parameters with Applications
In this paper, we introduce a novel waveletbased algorithm for reconstructing time-domain impulse responses from band-limited scattering parameters (frequencydomain data) with a particular focus on ship hull applications…