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• Three kinds of functional neurons are presented. • Magnetic field coupling is the main bridge for different functional neurons. • Electric synapse coupling and electric field coupling corrupt synchronization stability between different neurons. Specific biophysical neurons are presented to detect different stimuli, and these external exciting signals are encoded to trigger appropriate firing modes and action potentials for signal propagation between neurons in the network. A thermosensitive neuron can estimate the effect of temperature changes on the excitability and firing modes in nervous system, a photocurrent-dependent neuron can be sensitive to the changes of external illumination or light, and an auditory neuron can perceive acoustic wave when the vibration energy is absorbed and converted into field energy in the loop of neural circuits. From biophysical viewpoint, some specific electric components such as thermistor, phototube, and piezoelectric ceramics can be incorporated into neural circuits for activating specific functions, and thus the external stimuli such as heat, light and vibration can be detected because these energy injections can be converted to intrinsic field energy in the neural circuits. In this paper, three kinds of different neural circuits are coupled in a close loop, energy pumping and the stability of phase synchronization are investigated by regulating the properties of coupling channels, furthermore, the noise effect is also estimated. When induction coil is used to couple the neural circuits, phase stability is controlled under magnetic field coupling, and the activation of noise can change the stability of phase synchronization. The intrinsic field energy in the light-dependent neuron is increased with the increase of coupling intensity when voltage coupling via resistor and magnetic field coupling via induction coil are switched on. In case of electric field coupling via capacitor, the energy in the light-dependent neural circuit keeps oscillatory with small amplitude. These results indicate that magnetic field can be the most suitable way for realizing synchronous information encoding between different functional neurons than the electric synapse coupling because continuous pumping of ions can induce magnetic field in the cell, and all the neurons are controlled completely by effective pumping in field energy. [ABSTRACT FROM AUTHOR]

Both electrical and chemical synapses play important role in receiving and propagating signals between biological neurons. The activation of electrical synapse coupling is generated via gap junction connection while chemical synapse coupling depends on the release of neurotransmitter for triggering stable propagation of ions. In a practical way, voltage coupling via resistor connection between artificial neural circuits is often used to describe the gap junction coupling via electrical synapse between neurons. Magnetic field coupling via induction coil between neural circuits can be effective to estimate the chemical synapse coupling when ions are propagated and released in the cell. In this paper, the physical properties of magnetic field coupling between neural circuits are discussed. For simplicity, two Hindmarsh–Rose neurons are connected to trigger magnetic field coupling and the coupling channel is tamed to detect possible occurrence of synchronization. Two neurons are stimulated with different stimuli, and it is confirmed that the synchronous firing mode is decided by the neuron with higher forcing amplitude. Furthermore, the collective behaviors of HR neuron in the small-world network and scale free network are investigated by changing the coupling intensity and diversity in external stimulus, respectively. Statistical synchronization factor is calculated to estimate the dependence of synchronization on coupling gain and the number of bursting neurons in the network. In case of small-world connection, synchronization approach becomes difficult. However, complete synchronization can be stabilized on the scale free network under magnetic field coupling. [ABSTRACT FROM AUTHOR]

Some nonlinear circuits can present similar dynamical properties in the outputs as biological neurons by taming the external stimulus and bifurcation parameter, and they can be used for further investigation on neural activities. In this work, a photoelectric converter such as phototube is incorporated into the Fitzhugh-Nagumo neural circuit and a light-sensitive neuron is obtained to describe the nonlinear response in visual neuron. Furthermore, an additive induction coil is also connected to the phototube in this branch circuit of this neural circuit for detecting the disturbance from external magnetic field, and this functional neuron can perceive external illumination and changes of external magnetic field synchronously. Scale transformation is applied for the circuit equation and equivalent photoelectric neuron model is obtained. The intrinsic field energy of the neural circuit is described by equivalent Hamilton energy and the dependence firing modes on energy is clarified. When neurons are clustered closely, energy diversity can trigger field coupling and the synaptic connection will be regulated in the coupling intensity adaptively. An artificial hybrid is developed by combining capacitor and inductor in the coupling channel, and synchronization approach and energy balance is controlled completely. These results provide potential explanation for knowing the growth mechanism for synapse connection and external energy injection can be effective to control the collective behaviors of neurons. • A functional neural circuit is designed to detect external illumination and magnetic field. • Hamilton energy for biological neuron is obtained. • Stochastic resonance is induced in the biophysical neuron under noisy magnetic field. • Hybrid synapse is controllable under energy flow. • Biophysical mechanism for synapse controllability is explained. [ABSTRACT FROM AUTHOR]