Topic: leaky integrate-and-fire neurons

The critical brain hypothesis states that the brain can benefit from operating close to a second-order phase transition. While it has been shown that several computational aspects of sensory information processing (e.g., sensitivity to input) are optimal in this regime, it is still unclear whether these computational benefits of criticality can be leveraged by neural systems performing behaviorally relevant computations. To address this question, we investigate signatures of criticality in networks optimized to perform efficient encoding. We consider a network of leaky integrate-and-fire neuro

The effects of a global inhibition are studied on different models of neural networks, from the Wilson-Cowan model to networks of leaky integrate-and-fire neurons. These systems typically display a region of parameter space where two different states are possible, one of low and another of high activity with a phenomenology typical of first order phase transitions, with e.g. hysteresis in correspondence of a sweep of a control parameter. The introduction of a global inhibition, given by the presence of inhibitory interneurons with very large in-degree and out-degree, leads to a smoothing of t

Interactions between spiking units grouped in distinct excitatory (E) and inhibitory (I) populations can result in a complex dynamical landscape. Part of this complexity, namely dynamics that depend on undelayed connectivities and external inputs, is retained by a simplified model, the threshold-linear network (TLN), which allows to derive fully analytical conditions for the emergence of multistability [1], paradoxical perturbation effects [2,3], and some oscillations [4,5]. These results, however, have only been applied to specific architectures, such as canonical circuits or all-inhibitory n

It is appealing to disclose the state of an animal as well as the functional connectivity of its neuronal circuit by calculating pairwise and higher-order interactions (HOI) among neuronal activity. Here, we present a systematic approach to achieve these goals by analysing the spiking activity of simultaneously recorded neurons. To this end, we first developed a method to extract significant pairwise and triple-wise interactions among neurons. Using statistically significant data, we then analysed pairwise and HOI from large-scale spiking activities in visual areas of mice during natural movie