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Laguerre-volterra identification of spike-timing-dependent plasticity from spiking activity: A simulation study.

, , and . EMBC, page 5578-5581. IEEE, (2013)

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The contribution of relative activation levels between populations of cells to network activity in a large-scale biologically realistic model of the hippocampus., , , , and . EMBC, page 5962-5965. IEEE, (2013)Generalized volterra kernel model identification of spike-timing-dependent plasticity from simulated spiking activity., , and . EMBC, page 6585-6588. IEEE, (2014)The role of topography in the transformation of spatiotemporal patterns by a large-scale, biologically realistic model of the rat dentate gyrus., , , , and . EMBC, page 5950-5953. IEEE, (2013)A sparse null code emerges in deep neural networks., , , and . UniReps, volume 243 of Proceedings of Machine Learning Research, page 302-314. PMLR, (2023)Monte Carlo validation of spike-timing-dependent plasticity identification from spiking activity., , and . EMBC, page 1624-1627. IEEE, (2016)Decoding memory features from hippocampal spiking activities using sparse classification models., , , , , and . EMBC, page 1620-1623. IEEE, (2016)Implementation of activity-dependent synaptic plasticity rules for a large-scale biologically realistic model of the hippocampus., , , , and . EMBC, page 1366-1369. IEEE, (2012)Towards a large-scale biologically realistic model of the hippocampus., , , , and . EMBC, page 4595-4598. IEEE, (2012)Phase component of frequency-domain functional near-infrared imaging improves decoding of motor-evoked neural activity., , , , , , and . NER, page 365-369. IEEE, (2021)A spiking network model for semantic representation and replay-based association acquisition., , , , , , and . ICONS, page 25:1-25:8. ACM, (2021)