Publication
Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation
Related publications (33)
Taming neuronal noise with large networks
How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...
EPFL2022Towards the Validation of Noise Experiments in the CROCUS Reactor Using the TRIPOLI-4 Monte Carlo Code in Analog Mode
Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari
Intrinsic neutron noise experiments offer a non-invasive manner to measure the prompt decay constant or reactivity of fissile systems. Using the fluctuations in the density of fission chains, one can infer the kinetics parameters via correlation analysis s ...
2021How single neuron properties shape chaotic dynamics and signal transmission in random neural networks
Wulfram Gerstner, Tilo Schwalger, Samuel Pavio Muscinelli
While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...
2019Inferring and validating mechanistic models of neural microcircuits based on spike-train data
The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic m ...
2019Robust image alignment for cryogenic transmission electron microscopy
Cryo-electron microscopy recently experienced great improvements in structure resolution due to direct electron detectors with improved contrast and fast read-out leading to single electron counting. High frames rates enabled dose fractionation, where a lo ...
Elsevier BV2017Statistical structure of neural spiking under non-Poissonian or other non-white stimulation
Nerve cells in the brain generate sequences of action potentials with a complex statistics. Theoretical attempts to understand this statistics were largely limited to the case of a temporally uncorrelated input (Poissonian shot noise) from the neurons in t ...
Springer2015Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition
The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then stagge ...
Oxford Univ Press Inc2015Slow fluctuations in recurrent networks of spiking neurons
Networks of fast nonlinear elements may display slowfluctuations if interactions are strong. We find a transition in the long-term variability of a sparse recurrent network of perfect integrate-and-fire neurons at which the Fano factor switches from zero t ...
Amer Physical Soc2015Connection-type-specific biases make uniform random network models consistent with cortical recordings
Wulfram Gerstner, Carl Petersen, Tim Vogels, Michael Avermann, Christian Tomm
Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the implicit hypothesis that they are a good representation of real neuronal networks has been met with skepticism. Here we used two experimental data sets, a stu ...
American Physiological Society2014Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses
Random networks of integrate-and-fire neurons with strong current-based synapse scan, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze ...
Frontiers Research Foundation2014