Network-timing-dependent plasticity
By Vincent Delattre, D. Keller, M. Perich, Henry Markram, Eilif B. Muller. 2015
17 citations recorded by the source corpus.
Bursts of activity in networks of neurons are thought to convey salient information and drive synaptic plasticity. Here we report that network bursts also exert a profound effect on Spike-Timing-Dependent Plasticity (STDP). In acute slices of juvenile rat somatosensory cortex we paired a network burst, which alone induced long-term depression (LTD), with STDP-induced long-term potentiation (LTP) and LTD. We observed that STDP-induced LTP was either unaffected, blocked or flipped into LTD by the network burst, and that STDP-induced LTD was either saturated or flipped into LTP, depending on the relative timing of the network burst with respect to spike coincidences of the STDP event. We hypothesized that network bursts flip STDP-induced LTP to LTD by depleting resources needed for LTP and therefore developed a resource-dependent STDP learning rule. In a model neural network under the influence of the proposed resource-dependent STDP rule, we found that excitatory synaptic coupling was homeostatically regulated to produce power law distributed burst amplitudes reflecting self-organized criticality, a state that ensures optimal information coding.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Friedemann Zenke
- Surya Ganguli
- Wulfram Gerstner
- Henry Markram
- Idan Segev
- Felix Schürmann
- Sean L. Hill
- Etay Hay
In Cognitive Neuroscience
- Friedemann Zenke
- Surya Ganguli
- Wulfram Gerstner
- Henry Markram
- Idan Segev
- Felix Schürmann
- Sean L. Hill
- Etay Hay
In Electrical and Electronic Engineering
- Friedemann Zenke
- Surya Ganguli
- Wulfram Gerstner
- Henry Markram
- Shaul Druckmann
- Christian A. Rössert
- Eilif B. Muller
- Pierre Yger
Citations in the corpus
- The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “cuit without any additional control mechanisms, they can succumb to runaway neural activity as experience dependent neural correlations emerge in the recurrent circuit [73, 76, 77].”
- Reconstruction and Simulation of Neocortical Microcircuitry. (2015, methodology): “A recent study has experimentally characterized the plasticity mechanisms for maintaining the network close to this transition (Delattre et al., 2015).”