Santi Chillemi

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.

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.

Nonlinearity Tests Using the Extrema of a Time Series

The analytical properties of the solution of a system of ODEs in the complex time plane influence its dynamical behavior on the real time axis. In particular, the extrema of the real time solution can be associated to the singularities of the complex solution falling close to the real time axis. Moreover for a twice differentiable stochastic process, the expected value of the number of extrema for unit time can be determined. These two results are used here as the starting point to introduce two new algorithms to test for time series nonlinearity. They do not require the phase space reconstruction protocol and seem to work well also for short data sets.

The leaky integrate-and-fire with noise: a useful tool to investigate SR

Abstract The behaviour of a relaxation-like neural model, driven by noise and underthreshold sinusoidal signal, is analysed by computer simulation. The histograms of interspike intervals and the cycle histograms (CHs) are computed as well as the power spectral densities (PSDs) of the point process generated. The system is shown to exhibit bona fide stochastic resonance (SR).

DYNAMICAL BEHAVIOR OF THE LINEARIZED VERSION OF THE FITZHUGH NAGUMO NEURAL MODEL

For a linearized version of the FitzHugh–Nagumo model, firing and resetting conditions are defined by analogy with the Integrate and Fire model. The dynamical behavior of the model, subject to periodic synaptic inputs, is investigated both theoretically and numerically, with particular emphasis on the synchronization properties. The study is then extended to a network of two synaptically coupled units.

Rescaling prescriptions: On the conflict between Hurst's analysis and the second moment prediction

Abstract The numerical treatment of anomalous diffusion shows that in some cases Hursts analysis and the second moment technique express the long-range properties by means of distinctly different rescaling coefficients. With theoretical arguments we show this effect to be determined by the finite speed of the propagation front.

A Minimal Model for the Respiratory Sinus Arrhythmia

The cardiac and respiratory rhythms in humans are known to be coupled by several mechanisms. In particular, the first rhythm is deeply modulated by the second. In this report we propose a simple operational model for heart rate variability which, taking such modulation into account, reproduces the main features of some experimental sequences of RR intervals recorded from healthy subjects in the resting condition. Also, peer analysis of the model performance allows us to answer the question whether the observed behaviour should be ascribed to phase synchronisation of the heart beating to the respiratory rhythm. Lastly, the changes of the model activity brought about by changing its relevant parameters are analysed and discussed

Phase locking states between fast-spiking interneurons coupled by electrical and chemical synapses

Abstract The phase locking states in a pair of Fast Spiking interneurons coupled by electrical and inhibitory synapses are investigated by using the theory of weakly coupled oscillators. It is shown that increasing either the decay time constant of the inhibitory current or the firing frequency of the cells favours the emergence of synchronous discharges. We also found that adding the electrical coupling promotes synchronous regimes.

Short- and Long-Term Statistical Properties of Heartbeat Time-Series in Healthy and Pathological Subjects

We analize heartbeat time-series corresponding to several groups of individuals (healthy, heart transplanted, with congestive heart failure (CHF), after myocardial infarction (MI), hypertensive), looking for short- and long-time statistical behaviors. In particular we study the persistency patterns of interbeat times and interbeat-time variations. Long-range correlations are revealed using an information-based technique which makes a wise use of the available statistics. The presence of strong long-range time correlations seems to be a general feature for all subjects, with the exception of some CHF individuals. We also show that short time-properties detected in healthy subjects, and seen also in hypertensive and MI patients, and completely absent in the trasplanted, are characterized by a general behavior when we apply a proper coarse-graining procedure for time series analysis.