Phase-locking patterns in a resonate and fire neural model with periodic drive.

In this paper we studied a resonate and fire relaxation oscillator subject to time dependent modulation to investigate phase-locking phenomena occurring in neurophysiological systems. The neural model (denoted LFHN) was obtained by linearization of the FitzHugh-Nagumo neural model near an hyperbolic fixed point and then by introducing an integrate-and-fire mechanism for spike generation. By employing specific tools to study circle maps, we showed that this system exhibits several phase-locking patterns in the presence of periodic perturbations. Moreover, both the amplitude and frequency of the modulation strongly impact its phase-locking properties. In addition, general conditions for the generation of firing activity were also obtained. In addition, it was shown that for moderate noise levels the phase-locking patterns of the LFHN persist. Moreover, in the presence of noise, the rotation number changes smoothly as the stimulation current increases. Then, the statistical properties of the firing map were investigated too. Lastly, the results obtained with the forced LFHN suggest that such neural model could be used to fit specific experimental data on the firing times of neurons.

Dynamical properties of LFPs from mice with unilateral injection of TeNT.

Local field potential (LFP) recordings were performed from the visual cortex (V1) of a focal epilepsy mouse model. Epilepsy was induced by a unilateral injection of the synaptic blocker tetanus neurotoxin (TeNT). LFP signals were simultaneously recorded from V1 of both hemispheres of each animal under acute and chronic conditions (i.e. during and after the period of TeNT action). All data were analysed by using nonlinear time series methods. Suitable values of the lag time and embedding dimension for phase space reconstruction were estimated by employing well-known methods. The results showed that lag times are sensitive to the presence of TeNT. Interestingly, TeNT promoted an increase in the level of linear and nonlinear correlation of LFP signals. The values of the embedding dimension failed to show any dependence on the presence of the neurotoxin. However, a local nonlinear prediction method showed that the presence of TeNT increases the predictability, quantified by the normalized prediction error, of the neural recordings. From a neurophysiological point of view, the above results suggest that TeNT injected in one hemisphere strongly impacts the local electrical activity of the neural populations in the opposite hemisphere. We hypothesize that this could arise from a qualitative and quantitative alteration of the transmission properties of the callosal fibers.

Environmental enrichment modulates cortico-cortical interactions in the mouse.

Environmental enrichment (EE) is an experimental protocol based on a complex sensorimotor stimulation that dramatically affects brain development. While it is widely believed that the effects of EE result from the unique combination of different sensory and motor stimuli, it is not known whether and how cortico-cortical interactions are shaped by EE. Since the primary visual cortex (V1) is one of the best characterized targets of EE, we looked for direct cortico-cortical projections impinging on V1, and we identified a direct monosynaptic connection between motor cortex and V1 in the mouse brain. To measure the interactions between these areas under standard and EE rearing conditions, we used simultaneous recordings of local field potentials (LFPs) in awake, freely moving animals. LFP signals were analyzed by using different methods of linear and nonlinear analysis of time series (cross-correlation, mutual information, phase synchronization). We found that EE decreases the level of coupling between the electrical activities of the two cortical regions with respect to the control group. From a functional point of view, our results indicate, for the first time, that an enhanced sensorimotor experience impacts on the brain by affecting the functional crosstalk between different cortical areas.

The synchronization properties of a network of inhibitory interneurons depend on the biophysical model.

The synchronization properties of a pair of coupled fast spiking interneurons are studied by using the theory of weakly coupled oscillators. Four different biophysical models of the single fast spiking interneuron are used and the corresponding results are compared. It is shown that for a pair of identical coupled cells, the synchronization properties are model-dependent. In particular, the firing coherence of the network is strongly affected by the reversal potential, the kinetics of the inhibitory postsynaptic current and the electrical coupling; the activation properties of the sodium and potassium currents play a significant role too.

Calcium signalling in astrocytes and modulation of neural activity.

Starting from the experimental data on ATP evoked calcium responses in astrocytes, a biophysical model describing these phenomena was built. The simulations showed, in agreement with the experimental findings, that the intracellular calcium fluxes mediated by the P2X and P2Y purinoreceptors are responsible for the biphasic ATP evoked calcium response in astrocytes. Then, the modulation effects on the neural dynamics arising from the release of glutamate from astrocyte are also investigated. By using a minimal network model describing a neuron coupled to the astrocyte, we demonstrated that the calcium extrusion rate through the astrocyte membrane is critically involved in the generation of different firing patterns of the neuron.

Signal processing properties of fast spiking interneurons.

Fast spiking interneurons receive excitatory synaptic inputs from pyramidal cells and a relevant problem is to understand how these cells readout this information. Here this topic is investigated theoretically by using a biophysical modeling of a pair of coupled fast spiking interneuron models. The model predicts, in agreement with the experimental findings, that these cells are capable of transmitting pre-synaptic signals with high temporal precision and transferring high frequency inputs while preserving their relative timing. Moreover, it is shown that a pair of fast spiking interneurons, coupled through both inhibitory and electrical synapses, behaves as a coincidence detector. Lastly, to understand the mechanisms underlying these phenomena, a theoretical analysis is carried out by using a simpler modeling approach.

Stochastic resonance in a sinusoidally forced LIF model with noisy threshold.

In this report, the LIF neural model driven by underthreshold sinusoidal signals but with a gaussian-distributed noise on the threshold, is approximated by suitably defining an instantaneous firing (or escape) rate, which depends only on the momentary value of the voltage variable. This allows us to obtain, by analytically solving the relevant equations, the main statistical functions describing the "firing activity"; namely, the probability density function of firing phases and that of interspike intervals. From these functions two quantities can be derived, whose dependence on the noise intensity allows the Stochastic Resonance (SR) to be demonstrated. Besides the "regular" SR, the analysed system was found to produce, either for low frequencies and large amplitudes of modulation or for high modulation frequencies, resonance curves displaying two peaks. This bimodal feature of the resonance curves is accounted for on the basis of phase locked firing patterns.

Synchronization in a network of fast-spiking interneurons.

Experimental results revealed that in neocortex inhibitory fast-spiking (FS) interneurons interact also by electrical synapses (gap-junctions). They receive sensory information from thalamus and transfer it to principal cells by feedforward inhibition. Moreover, their synchronous discharge enhances their inhibitory control of pyramidal neurons. By using a biophysical model of FS interneurons the synchronization properties of a network of two synaptically coupled units are investigated. In the case they interact only by inhibitory synapses, well defined regions exist in the parameters space described by the strength and duration of the synaptic current, where synchronous regimes occur. Then an empirical protocol is proposed to determine approximately the borders of the synchronization manifold (SM). When electrical synapses are included, the region of synchronous discharge of the two interneurons becomes larger. In both cases, the coherent states are characterized by discharge frequencies in the gamma range. Lastly, the effects of heterogeneity, either obtained by using different stimulation currents or unidirectional inhibitory coupling, are studied.