Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement.

By Gina G. Turrigiano. 2011

685 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neuroscience

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

1. Wolfgang Maass
2. Gina G. Turrigiano
3. Yi Zhong
4. Stephen D. Van Hooser
5. Donald B. Katz
6. Keith B. Hengen
7. Mary E. Lambo
8. James B. Ackman

In Cognitive Neuroscience

1. Wolfgang Maass
2. German Ignacio Parisi
3. Michael Pfeiffer
4. Christopher Kanan
5. Wulfram Gerstner
6. Stefan Wermter
7. James B. Ackman
8. Michael C. Crair

In Neuroscience

1. Christopher Kanan
2. German Ignacio Parisi
3. James B. Ackman
4. Michael C. Crair
5. Michael Pfeiffer
6. Yi Zhong
7. Stefan Wermter
8. Stephen D. Van Hooser

Citations in the corpus

• Continual Lifelong Learning with Neural Networks: A Review (2018, background): “Homeostatic mechanisms of plasticity include synaptic scaling and meta-plasticity which directly affect synaptic strengths (Davis, 2006; Turrigiano, 2011).”
• Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents (2013, methodology): “…MD paradigm (lid suture) to perturb visual drive in juvenile rats during a developmental period (postnatal days 27–32 [P27–P32]), when this perturbation is known to induce both Hebbian and homeostatic forms of plasticity within V1 (Smith et al., 2009; Turrigiano, 2011; Levelt and Hübener, 2012).”
• Role of emergent neural activity in visual map development (2013, positive): “Some of the morphological and functional changes in neuronal properties brought about by obstructing activity during development can be considered homeostatic responses to the withdrawal of synaptic drive [59].”
• The Biology of Forgetting – A Perspective (2017, background): “Other homeostatic signaling mechanisms are known to counterbalance neural plasticity to stabilize neuronal function (Turrigiano, 2011; Davis, 2013).”
• Modeling the dynamic interaction of Hebbian and homeostatic plasticity. (2014, background): “…only TNFa-dependent homeostatic plasticity, which mediates scaling up of strengths in response to reduced activity, while ignoring separate mechanisms that scale synapses down in response to hyperactivity (Stellwagen and Malenka, 2006) and other forms of homeostatic plasticity (Turrigiano, 2011).”
• Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity (2013, background): “excitability through homeostatic mechanisms were observed in experiments [13,46].”