ArticlePLoS computational biology2011
Quantifying the relative contributions of divisive and subtractive feedback to rhythm generation.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Slow negative feedback enhances robustness of square-wave bursting.Journal of computational neuroscience · 2023Article
- Quantitative roles of ion channel dynamics on ventricular action potential.Channels (Austin, Tex.) · 2021Article
- Divisive gain modulation enables flexible and rapid entrainment in a neocortical microcircuit model.Journal of neurophysiology · 2020Article
- Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.Journal of computational neuroscience · 2019Article
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- Phasic Firing and Coincidence Detection by Subthreshold Negative Feedback: Divisive or Subtractive or, Better, Both.Frontiers in computational neuroscience · 2017Article
- Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model.Physical review. E, Statistical, nonlinear, and soft matter physics · 2015Article
- Determining the contributions of divisive and subtractive feedback in the Hodgkin-Huxley model.Journal of computational neuroscience · 2014Article
- Entrainment to periodic initiation and transition rates in a computational model for gene translation.PloS one · 2014Article
- Nonlinear Dynamics of Neuronal Excitability, Oscillations, and Coincidence Detection.Communications on pure and applied mathematics · 2013Article
- Sub- and suprathreshold adaptation currents have opposite effects on frequency tuning.The Journal of physiology · 2012Article
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3 authors.
Funding
Abstract
Biological systems are characterized by a high number of interacting components. Determining the role of each component is difficult, addressed here in the context of biological oscillations. Rhythmic behavior can result from the interplay of positive feedback that promotes bistability between high and low activity, and slow negative feedback that switches the system between the high and low activity states. Many biological oscillators include two types of negative feedback processes: divisive (decreases the gain of the positive feedback loop) and subtractive (increases the input threshold) that both contribute to slowly move the system between the high- and low-activity states. Can we determine the relative contribution of each type of negative feedback process to the rhythmic activity? Does one dominate? Do they control the active and silent phase equally? To answer these questions we use a neural network model with excitatory coupling, regulated by synaptic depression (divisive) and cellular adaptation (subtractive feedback). We first attempt to apply standard experimental methodologies: either passive observation to correlate the variations of a variable of interest to system behavior, or deletion of a component to establish whether a component is critical for the system. We find that these two strategies can lead to contradictory conclusions, and at best their interpretive power is limited. We instead develop a computational measure of the contribution of a process, by evaluating the sensitivity of the active (high activity) and silent (low activity) phase durations to the time constant of the process. The measure shows that both processes control the active phase, in proportion to their speed and relative weight. However, only the subtractive process plays a major role in setting the duration of the silent phase. This computational method can be used to analyze the role of negative feedback processes in a wide range of biological rhythms.
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Registered trials
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