Recent experimental results on spike avalanches measured in the urethane-anesthetized rat cortex have revealed scaling relations that indicate a phase transition at specific level of cortical firing rate variability. The point to critical exponents whose values differ from those branching process, which has been canonical model employed understand brain criticality. This suggested different model, with transition, might be required explain data. Here we show this is not necessarily case. By...

Asynchronous irregular (AI) and critical states are two competing frameworks proposed to explain spontaneous neuronal activity. Here, we propose a mean-field model with simple stochastic neurons that generalizes the integrate-and-fire network of Brunel (2000). We show point balanced inhibitory/excitatory synaptic weight ratio $g_c \approx 4$ corresponds second order absorbing phase transition usual in self-organized (SOC) models. At balance $g_c$, exhibits power-law avalanches exponents,...

Abstract Objective Although temporal lobe epilepsy (TLE) is recognized as a system‐level disorder, little work has investigated pathoconnectomics from dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested hypothesis network communication abnormal in this condition, studied interplay between hippocampal‐ and network‐level disease effects, assessed associations with cognition. Methods We simulated signal...

Slow–fast dynamics are intrinsically related to complex phenomena and responsible for many of the homeostatic that keep biological systems healthy functioning. We study a discrete-time membrane potential model can generate diverse set spiking behavior depending on choice slow–fast time scales, from fast bursting, or plateau action potentials—also known as cardiac spikes since they characteristic in heart myocytes. The lose stability, generating early delayed afterdepolarizations (EADs DADs,...

Abstract Activity in the brain propagates as waves of firing neurons, namely avalanches. These waves’ size and duration distributions have been experimentally shown to display a stable power-law profile, long-range correlations 1/ f b power spectrum vivo vitro . We study an avalanching biologically motivated model mammals visual cortex find extended critical-like region – Griffiths phase characterized by divergent susceptibility zero order parameter. This lies close expected experimental...

Abstract A homeostatic mechanism that keeps the brain highly susceptible to stimuli and optimizes many of its functions—although this is a compelling theoretical argument in favor criticality hypothesis , experimental evidence accumulated during last two decades still not entirely convincing, causing idea be seemingly unknown more clinically-oriented neuroscience community. In perspective review, we will briefly review framework underlying such bold hypothesis, point where theory experiments...

Many different kinds of noise are experimentally observed in the brain. Among them, we study a model noisy chemical synapse and obtain critical avalanches for spatiotemporal activity neural network. Neurons synapses modeled by dynamical maps. We discuss relevant neuronal synaptic properties to achieve state. verify that networks functionally excitable neurons with fast present power-law avalanches, due rebound spiking dynamics. also measuring subsampling our data, shedding light on...

We introduce a new map-based neuron model derived from the dynamical perceptron family that has best compromise between computational efficiency, analytical tractability, reduced parameter space and many behaviors. calculate bifurcation phase diagrams analytically computationally underpins rich repertoire of autonomous excitable report existence regime cardiac spikes corresponding to nonchaotic aperiodic behavior. compare features our standard models currently available in literature.

Transient or partial synchronization can be used to do computations, although a fully synchronized network is sometimes related the onset of epileptic seizures. Here, we propose homeostatic mechanism that capable maintaining neuronal at edge transition, thereby avoiding harmful consequences network. We model neurons by maps since they are dynamically richer than integrate-and-fire models and more computationally efficient conductance-based approaches. first describe phase transition dense...

Neuronal avalanches and asynchronous irregular (AI) firing patterns have been thought to represent distinct frameworks understand the brain spontaneous activity. The former is typically present in systems where there a balance between slow accumulation of tension its fast dissipation, whereas latter accompanied by synaptic excitation inhibition (E/I). Here, we develop new theory E/I that relies on two homeostatic adaptation mechanisms: short-term depression spike-dependent threshold...

Power-law-shaped avalanche-size distributions are widely used to probe for critical behavior in many different systems, particularly neural networks. The definition of avalanche is ambiguous. Usually, theoretical avalanches defined as the activity between a stimulus and relaxation an inactive absorbing state. On other hand, experimental neuronal by consecutive silent states. We claim that latter may be extended some models characterize their power-law behavior. study system which separation...

Physicists are starting to work in areas where noisy signal analysis is required. In these fields, such as Economics, Neuroscience, and Physics, the notion of causality should be interpreted a statistical measure. We introduce lay reader Granger between two time series illustrate ways calculating it: $X$ ``Granger-causes'' $Y$ if observation past increases predictability future when compared same prediction done with alone. other words, for quantities it suffices that information extracted...

We study a new biologically motivated model for the Macaque monkey primary visual cortex which presents power-law avalanches after stimulus. The signal propagates through all layers of via that depend on network structure and synaptic parameter. identify four different avalanche profiles as function excitatory postsynaptic potential. follow size-duration scaling relation present critical exponents match experiments. gives rise to regime two characteristic spatial scales, one vanishes in...

Animals navigate by learning the spatial layout of their environment. We investigated mice in an open maze where food was hidden one a hundred holes. Mice leaving from stable entrance learned to efficiently without need for landmarks. developed quantitative framework reveal how estimate location based on analyses trajectories and active hole checks. After learning, computed ‘target estimation vector’ (TEV) closely approximated mice’s route its check distribution. The TEV required both...

Animals navigate by learning the spatial layout of their environment. We investigated mice in an open maze where food was hidden one a hundred holes. Mice leaving from stable entrance learned to efficiently without need for landmarks. developed quantitative framework reveal how estimate location based on analyses trajectories and active hole checks. After learning, computed ‘target estimation vector’ (TEV) closely approximated mice’s route its check distribution. The TEV required both...

Hilar mossy cells (hMCs) in the dentate gyrus (DG) receive inputs from DG granule (GCs), CA3 pyramidal and inhibitory interneurons, provide feedback input to GCs. Behavioural vivo recording experiments implicate hMCs pattern separation, navigation spatial learning. Our link hMC intrinsic excitability their synaptically evoked spiking outputs. We performed electrophysiological recordings neurons found that displayed an adaptative spike threshold increased both proportion intensity of injected...

Transient or partial synchronization can be used to do computations, although a fully synchronized network is frequently related epileptic seizures. Here, we propose homeostatic mechanism that capable of maintaining neuronal at the edge transition, thereby avoiding harmful consequences network. We model neurons by maps since they are dynamically richer than integrate-and-fire models and more computationally efficient conductance-based approaches. first describe phase transition dense with...