Noise is an inherent part of neuronal dynamics, and thus of the brain. It can be observed in neuronal activity at different spatiotemporal scales, including in neuronal membrane potentials, local field potentials, electroencephalography, and magnetoencephalography. A central research topic in contemporary neuroscience is to elucidate the functional role of noise in neuronal information processing. Experimental studies have shown that a suitable level of noise may enhance the detection of weak neuronal signals by means of stochastic resonance. In response, theoretical research, based on the theory of stochastic processes, nonlinear dynamics, and statistical physics, has made great strides in elucidating the mechanism and the many benefits of...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...
Noise has already been shown to play a constructive role in neuronal processing and reliability, acc...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...
Information processing in nonlinear systems can sometimes be enhanced by the presence of stochastic ...
Information processing in nonlinear systems can sometimes be enhanced by the presence of stochastic ...
The brain is an intrinsically noisy environment. Neurons and networks are able to detect and classif...
Abstract:- Biological noise has already been shown to play a constructive role in neuronal processin...
Stochastic resonance is a nonlinear phenomenon in which the activity of a dynamical system becomes m...
We show that the conventional stochastic resonance (SR) effect for aperiodic signals in a model neur...
Neuronal encoding of an electromagnetic (EM) signal is investigated in the presence of biological no...
Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system en...
Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system en...
Aperiodic stochastic resonance (ASR) is a phenomenon in which the response of a nonlinear system to ...
We rst demonstrate how to quantify the information conveyed in temporal ring patterns of neurons. We...
Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectu...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...
Noise has already been shown to play a constructive role in neuronal processing and reliability, acc...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...
Information processing in nonlinear systems can sometimes be enhanced by the presence of stochastic ...
Information processing in nonlinear systems can sometimes be enhanced by the presence of stochastic ...
The brain is an intrinsically noisy environment. Neurons and networks are able to detect and classif...
Abstract:- Biological noise has already been shown to play a constructive role in neuronal processin...
Stochastic resonance is a nonlinear phenomenon in which the activity of a dynamical system becomes m...
We show that the conventional stochastic resonance (SR) effect for aperiodic signals in a model neur...
Neuronal encoding of an electromagnetic (EM) signal is investigated in the presence of biological no...
Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system en...
Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system en...
Aperiodic stochastic resonance (ASR) is a phenomenon in which the response of a nonlinear system to ...
We rst demonstrate how to quantify the information conveyed in temporal ring patterns of neurons. We...
Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectu...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...
Noise has already been shown to play a constructive role in neuronal processing and reliability, acc...
Input noise, defined as the root mean square of the fluctuations in the input, typically limits the ...