Morphology controls how hippocampal CA1 pyramidal neuron responds to uniform electric fields: a biophysical modeling study.

Responses of different neurons to electric field (EF) are highly variable, which depends on intrinsic properties of cell type. Here we use multi-compartmental biophysical models to investigate how morphologic features affect EF-induced responses in hippocampal CA1 pyramidal neurons. We find that the basic morphologies of neuronal elements, including diameter, length, bend, branch, and axon terminals, are all correlated with somatic depolarization through altering the current sources or sinks created by applied field.

Complexity of resting-state EEG activity in the patients with early-stage Parkinson's disease.

To investigate the abnormal brain activities in the early stage of Parkinson's disease (PD), the electroencephalogram (EEG) signals were recorded with 20 channels from non-dementia PD patients (18 patients, 8 females) and age matched healthy controls (18 subjects, 8 females) during the resting state. Two methods based on the ordinal patterns of the recorded series, i.e.

Metabolic Energy of Action Potentials Modulated by Spike Frequency Adaptation.

Spike frequency adaptation (SFA) exists in many types of neurons, which has been demonstrated to improve their abilities to process incoming information by synapses. The major carrier used by a neuron to convey synaptic signals is the sequences of action potentials (APs), which have to consume substantial metabolic energies to initiate and propagate. Here we use conductance-based models to investigate how SFA modulates the AP-related energy of neurons.

Biophysical Insights into How Spike Threshold Depends on the Rate of Membrane Potential Depolarization in Type I and Type II Neurons.

Dynamic spike threshold plays a critical role in neuronal input-output relations. In many neurons, the threshold potential depends on the rate of membrane potential depolarization (dV/dt) preceding a spike. There are two basic classes of neural excitability, i.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input.

Neuronal spike initiation modulated by extracellular electric fields.

Based on a reduced two-compartment model, the dynamical and biophysical mechanism underlying the spike initiation of the neuron to extracellular electric fields is investigated in this paper. With stability and phase plane analysis, we first investigate in detail the dynamical properties of neuronal spike initiation induced by geometric parameter and internal coupling conductance. The geometric parameter is the ratio between soma area and total membrane area, which describes the proportion of area occupied by somatic chamber.

Exploring how extracellular electric field modulates neuron activity through dynamical analysis of a two-compartment neuron model.

To investigate how extracellular electric field modulates neuron activity, a reduced two-compartment neuron model in the presence of electric field is introduced in this study. Depending on neuronal geometric and internal coupling parameters, the behaviors of the model have been studied extensively. The neuron model can exist in quiescent state or repetitive spiking state in response to electric field stimulus.

Closed-loop control of the thalamocortical relay neuron's Parkinsonian state based on slow variable.

A novel closed-loop control strategy is proposed to control Parkinsonian state based on a computational model. By modeling thalamocortical relay neurons under external electric field, a slow variable feedback control is applied to restore its relay functionality. Qualitative and quantitative analysis demonstrates the performance of feedback controller based on slow variable is more efficient compared with traditional feedback control based on fast variable.

Characterizing electrical signals evoked by acupuncture through complex network mapping: a new perspective on acupuncture.

The electrical signals are obtained in spinal dorsal root after different manipulations of acupuncture (MA) being taken at the 'Zusanli' point of the experiment rats. After combining the analysis of the data generated from neuronal network model and that evoked by acupuncture, it is found that features of neuronal chaotic rate time series induced by periodic stimuli can be characterized by complex network approach. The features of signals evoked by MA 'nb' 'nx' (twisting) and MA 'tb' 'tx' (lifting and thrusting) are shown to be different according to the topologies of the mapped networks.

[Influence of acupuncture of Zusanli (ST 36) on connectivity of brain functional network in healthy subjects].

Objective: To observe the effect of acupuncture of Zusanli (ST 36) on electroencephalogram (EEG) so as to probe into its law in regulating the interconnectivity of brain functional network.

Methods: A total of 9 healthy young volunteer students (6 male, 3 female) participated in the present study. They were asked to take a dorsal position on a test-bed.

Vibrational resonance in feedforward network.

This paper investigates vibrational resonance in multi-layer feedforward network (FFN) based on FitzHugh-Nagumo (FHN) neuron model. High-frequency stimuli can improve the input-output linearity of firing rates, especially for the inputs with low firing rate. For FFN network, it is found that high-frequency disturbances play important roles in enhancing the propagation of weak signal through layers.

Bifurcations in Morris-Lecar model exposed to DC electric field.

As an important neuron model, the Morris-Lecar (ML) equations can exhibit classes I and II excitabilities with appropriate system parameters. In this paper, the effects of external DC electric field on the neuro-computational properties of ML model are investigated using bifurcation analysis. We obtain the bifurcation diagram in two dimensional parameter space of externally applied DC current and trans-membrane potential induced by external DC electric field.