Emergence of Resonances in Neural Systems: The Interplay between Adaptive Threshold and Short-Term Synaptic Plasticity

In this work we study the detection of weak stimuli by spiking (integrate-and-fire) neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between adaptive neuron threshold and activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our main results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic stochastic synaptic models and realistic signals such as poissonian spike trains

Irregular Dynamics in Up and Down Cortical States

Complex coherent dynamics is present in a wide variety of neural systems. A typical example is the voltage transitions between up and down states observed in cortical areas in the brain. In this work, we study this phenomenon via a biologically motivated stochastic model of up and down transitions. The model is constituted by a simple bistable rate dynamics, where the synaptic current is modulated by short-term synaptic processes which introduce stochasticity and temporal correlations. A complete analysis of our model, both with mean-field approaches and numerical simulations, shows the appearance of complex transitions between high (up) and low (down) neural activity states, driven by the synaptic noise, with permanence times in the up state distributed according to a power-law. We show that the experimentally observed large fluctuation in up and down permanence times can be explained as the result of sufficiently noisy dynamical synapses with sufficiently large recovery times. Static synapses cannot account for this behavior, nor can dynamical synapses in the absence of noise

Cellular and Humoral Mechanisms Involved in the Control of Tuberculosis

Mycobacterium tuberculosis (Mtb) infection is a major international public health problem. One-third of the world's population is thought to have latent tuberculosis, a condition where individuals are infected by the intracellular bacteria without active disease but are at risk for reactivation, if their immune system fails. Here, we discuss the role of nonspecific inflammatory responses mediated by cytokines and chemokines induced by interaction of innate receptors expressed in macrophages and dendritic cells (DCs). We also review current information regarding the importance of several cytokines including IL-17/IL-23 in the development of protective cellular and antibody-mediated protective responses against Mtb and their influence in containment of the infection. Finally, in this paper, emphasis is placed on the mechanisms of failure of Mtb control, including the immune dysregulation induced by the treatment with biological drugs in different autoimmune diseases. Further functional studies, focused on the mechanisms involved in the early host-Mtb interactions and the interplay between host innate and acquired immunity against Mtb, may be helpful to improve the understanding of protective responses in the lung and in the development of novel therapeutic and prophylactic tools in TB