AI Medical Compendium Journal:
Journal of biological physics

Showing 1 to 7 of 7 articles

Synchronization in STDP-driven memristive neural networks with time-varying topology.

Journal of biological physics
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by s...

Identifying key factors in cell fate decisions by machine learning interpretable strategies.

Journal of biological physics
Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it is important to identify the decision-making mechanisms and important individual molecules behind the fate decision processes. In this paper, we propo...

The effects of temperature on the dynamics of the biological neural network.

Journal of biological physics
The nerve cells are responsible for transmitting messages through the action potential, which generates electrical stimulation. One of the methods and tools of electrical stimulation is infrared neural stimulation (INS). Since the mechanism of INS is...

Learning the local landscape of protein structures with convolutional neural networks.

Journal of biological physics
One fundamental problem of protein biochemistry is to predict protein structure from amino acid sequence. The inverse problem, predicting either entire sequences or individual mutations that are consistent with a given protein structure, has received...

Unwrapping the phase portrait features of adventitious crackle for auscultation and classification: a machine learning approach.

Journal of biological physics
The paper delves into the plausibility of applying fractal, spectral, and nonlinear time series analyses for lung auscultation. The thirty-five sound signals of bronchial (BB) and pulmonary crackle (PC) analysed by fast Fourier transform and wavelet ...

Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics.

Journal of biological physics
In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural systems in the basic kinematic case of clusters of neuron-like units. Here we extend this approach to networks and begin developing a dynamical theory for ...

Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

Journal of biological physics
We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time-de...