ArticlePLoS computational biology2014
Poisson-like spiking in circuits with probabilistic synapses.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Computing the effects of excitatory-inhibitory balance on neuronal input-output properties.PLoS computational biology · 2026Article
- Hippocampal and medial prefrontal ensemble spiking represents episodes and rules in similar task spaces.Cell reports · 2023Article
- Synaptic mechanisms for motor variability in a feedforward network.Science advances · 2020Article
- Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences.Scientific reports · 2020Article
- Cortical reliability amid noise and chaos.Nature communications · 2019Article
- Redundancy in synaptic connections enables neurons to learn optimally.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits.Journal of computational neuroscience · 2018Article
- Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms.Journal of neural engineering · 2018Article
- The Dynamics of Balanced Spiking Neuronal Networks Under Poisson Drive Is Not Chaotic.Frontiers in computational neuroscience · 2018Article
- Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning.Frontiers in neuroscience · 2018Article
- Editorial: Metastable Dynamics of Neural Ensembles.Frontiers in systems neuroscience · 2017Article
- Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines.Frontiers in neuroscience · 2016Article
- Stimuli Reduce the Dimensionality of Cortical Activity.Frontiers in systems neuroscience · 2016Article
- Causal Inference and Explaining Away in a Spiking Network.Scientific reports · 2015Article
- Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.PloS one · 2015Article
- A pre-docking source for the power-law behavior of spontaneous quantal release: application to the analysis of LTP.Frontiers in cellular neuroscience · 2015Article
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Abstract
Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex.
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