The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.
Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
Open accessAbstract
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, so far, not been able to account for learning complex tasks that demand credit assignment in hierarchical networks. Here we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then pyramidal neurons higher in a hierarchical circuit can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits. The authors propose a synaptic plasticity rule for pyramidal neurons based on postsynaptic bursting that captures experimental data and solves the credit assignment problem for deep networks.
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Deep reinforcement learning and its neuroscientific implications
Botvinick, M., Wang, J. X., Dabney, W., Miller, K. J., & Kurth-Nelson, Z. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.014 · Cited by 269
Perirhinal input to neocortical layer 1 controls learning
Doron, G., Shin, J. N., Takahashi, N., Drüke, M., Bocklisch, C., Skenderi, S., de Mont, L., Toumazou, M., Ledderose, J., Brecht, M., et al. (2020) · Science · doi:10.1126/science.aaz3136 · Cited by 160
Self-citationBidirectional synaptic plasticity rapidly modifies hippocampal representations
Milstein, A. D., Li, Y., Bittner, K. C., Grienberger, C., Soltesz, I., Magee, J. C., & Romani, S. (2021) · eLife · doi:10.7554/elife.73046 · Cited by 151
Inferring neural activity before plasticity as a foundation for learning beyond backpropagation
Song, Y., Millidge, B., Salvatori, T., Lukasiewicz, T., Xu, Z., & Bogacz, R. (2024) · Nature Neuroscience · doi:10.1038/s41593-023-01514-1 · Cited by 85
Mental navigation and the neural mechanisms of insight
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Metadata
- Authors
- Payeur, A., Guerguiev, J., Zenke, F., Richards, B. A., & Naud, R.
- Venue
- Nature Neuroscience
- Published
- 2021-05-13
- Volume
- 24
- Issue
- 7
- Pages
- 1010-1019
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W3162006056
- Cited by
- 292
- References
- 126
- FWCI
- 22.81
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
