ArticlePLoS computational biology2014
Intrinsic neuronal properties switch the mode of information transmission in networks.
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 16 papers.
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Who cites it
16 citing papers in PubMed.
- Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration.Cell reports · 2024Article
- Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration.bioRxiv : the preprint server for biology · 2024Article
- A reservoir of timescales emerges in recurrent circuits with heterogeneous neural assemblies.eLife · 2023Article
- EngineeringAPL bioengineering · 2021Article
- Article
- Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation.Nature communications · 2019Article
- Acetylcholine Mediates Dynamic Switching Between Information Coding Schemes in Neuronal Networks.Frontiers in systems neuroscience · 2019Article
- Theoretical Models of Neural Development.iScience · 2018Review
- From connectome to cognition: The search for mechanism in human functional brain networks.NeuroImage · 2017Review
- Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection.PLoS computational biology · 2017Article
- Synaptic and intrinsic homeostasis cooperate to optimize single neuron response properties and tune integrator circuits.Journal of neurophysiology · 2016Article
- Review
- Computational implications of biophysical diversity and multiple timescales in neurons and synapses for circuit performance.Current opinion in neurobiology · 2016Review
- Ion channel degeneracy enables robust and tunable neuronal firing rates.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Temporal dynamics in fMRI resting-state activity.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Subthreshold membrane currents confer distinct tuning properties that enable neurons to encode the integral or derivative of their input.Frontiers in cellular neuroscience · 2014Article
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Authors and funding
4 authors.
Funding
Abstract
Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission.
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