Abbott LF, Nelson SB. (2000). Synaptic plasticity: taming the beast. Nature neuroscience. 3 Suppl [PubMed]

Angulo SL et al. (2017). Tau and amyloid-related pathologies in the entorhinal cortex have divergent effects in the hippocampal circuit. Neurobiology of disease. 108 [PubMed]

Antunes G, Simoes-de-Souza FM. (2018). AMPA receptor trafficking and its role in heterosynaptic plasticity. Scientific reports. 8 [PubMed]

• AMPA receptor trafficking and its role in heterosynaptic plasticity (Antunes et al 2018) [Model]

Aumentado-Armstrong T, Metzen MG, Sproule MK, Chacron MJ. (2015). Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli. PLoS computational biology. 11 [PubMed]

• Midbrain torus semicircularis neuron model (Aumentado-Armstrong et al. 2015) [Model]

Bartolozzi C, Indiveri G. (2007). Synaptic dynamics in analog VLSI. Neural computation. 19 [PubMed]

Bednar JA, Kelkar A, Miikkulainen R. (2004). Scaling self-organizing maps to model large cortical networks. Neuroinformatics. 2 [PubMed]

• Scaling self-organizing maps to model large cortical networks (Bednar et al 2004) [Model]

Bhaumik B, Mathur M. (2003). A cooperation and competition based simple cell receptive field model and study of feed-forward linear and nonlinear contributions to orientation selectivity. Journal of computational neuroscience. 14 [PubMed]

Bono J, Clopath C. (2019). Synaptic plasticity onto inhibitory neurons as a mechanism for ocular dominance plasticity. PLoS computational biology. 15 [PubMed]

• Inhibitory neuron plasticity as a mechanism for ocular dominance plasticity (Bono & Clopath 2019) [Model]

Brette R. (2012). Computing with neural synchrony. PLoS computational biology. 8 [PubMed]

• Computing with neural synchrony (Brette 2012) [Model]

Burkitt AN, Meffin H, Grayden DB. (2004). Spike-timing-dependent plasticity: the relationship to rate-based learning for models with weight dynamics determined by a stable fixed point. Neural computation. 16 [PubMed]

Cook EP, Johnston D. (1999). Voltage-dependent properties of dendrites that eliminate location-dependent variability of synaptic input. Journal of neurophysiology. 81 [PubMed]

Costa RP, Froemke RC, Sjöström PJ, van Rossum MC. (2015). Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning. eLife. 4 [PubMed]

• Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015) [Model]

D'Albis T, Kempter R. (2017). A single-cell spiking model for the origin of grid-cell patterns. PLoS computational biology. 13 [PubMed]

• A single-cell spiking model for the origin of grid-cell patterns (D'Albis & Kempter 2017) [Model]

González-Rueda A, Pedrosa V, Feord RC, Clopath C, Paulsen O. (2018). Activity-Dependent Downscaling of Subthreshold Synaptic Inputs during Slow-Wave-Sleep-like Activity In Vivo. Neuron. 97 [PubMed]

• Feedforward network undergoing Up-state-mediated plasticity (Gonzalez-Rueda et al. 2018) [Model]

Gottschalk A, Haney P. (2003). Computational aspects of anesthetic action in simple neural models. Anesthesiology. 98 [PubMed]

Günay C, Prinz AA. (2010). Model calcium sensors for network homeostasis: sensor and readout parameter analysis from a database of model neuronal networks. The Journal of neuroscience : the official journal of the Society for Neuroscience. 30 [PubMed]

• Lobster STG pyloric network model with calcium sensor (Gunay & Prinz 2010) (Prinz et al. 2004) [Model]

Hazan L, Ziv NE. (2020). Activity dependent and independent determinants of synaptic size diversity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 40 [PubMed]

• Kesten and Langevin synaptic size fluctuation simulator (Hazan & Ziv 2020) [Model]
• Mesoscopic model of spontaneous synaptic size fluctuations (Hazan & Ziv 2020) [Model]

Häusser M, Spruston N, Stuart GJ. (2000). Diversity and dynamics of dendritic signaling. Science (New York, N.Y.). 290 [PubMed]

Izhikevich EM. (2006). Polychronization: computation with spikes. Neural computation. 18 [PubMed]

• Polychronization: Computation With Spikes (Izhikevich 2005) [Model]

Lindsay GW, Rigotti M, Warden MR, Miller EK, Fusi S. (2017). Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 37 [PubMed]

• Hebbian learning in a random network for PFC modeling (Lindsay, et al. 2017) [Model]

Liu Z, Golowasch J, Marder E, Abbott LF. (1998). A model neuron with activity-dependent conductances regulated by multiple calcium sensors. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]

• Activity dependent conductances in a neuron model (Liu et al. 1998) [Model]

Maex R, De Schutter E. (1998). Synchronization of golgi and granule cell firing in a detailed network model of the cerebellar granule cell layer. Journal of neurophysiology. 80 [PubMed]

• Network model of the granular layer of the cerebellar cortex (Maex, De Schutter 1998) [Model]
• Cerebellar granular layer (Maex and De Schutter 1998) [Model]

Mo CH, Gu M, Koch C. (2004). A learning rule for local synaptic interactions between excitation and shunting inhibition. Neural computation. 16 [PubMed]

Morrison A, Aertsen A, Diesmann M. (2007). Spike-timing-dependent plasticity in balanced random networks. Neural computation. 19 [PubMed]

Persi E, Horn D, Volman V, Segev R, Ben-Jacob E. (2004). Modeling of synchronized bursting events: the importance on inhomogeneity. Neural computation. 16 [PubMed]

Rabinowitch I, Segev I. (2006). The interplay between homeostatic synaptic plasticity and functional dendritic compartments. Journal of neurophysiology. 96 [PubMed]

• Homeostatic synaptic plasticity (Rabinowitch and Segev 2006a,b) [Model]

Rabinowitch I, Segev I. (2006). The endurance and selectivity of spatial patterns of long-term potentiation/depression in dendrites under homeostatic synaptic plasticity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]

• Homeostatic synaptic plasticity (Rabinowitch and Segev 2006a,b) [Model]

Renart A, Moreno-Bote R, Wang XJ, Parga N. (2007). Mean-driven and fluctuation-driven persistent activity in recurrent networks. Neural computation. 19 [PubMed]

Renart A, Song P, Wang XJ. (2003). Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks. Neuron. 38 [PubMed]

Rowan MS, Neymotin SA, Lytton WW. (2014). Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Frontiers in computational neuroscience. 8 [PubMed]

• Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014) [Model]

Segev I, London M. (2000). Untangling dendrites with quantitative models. Science (New York, N.Y.). 290 [PubMed]

Sollini J, Chapuis GA, Clopath C, Chadderton P. (2018). ON-OFF receptive fields in auditory cortex diverge during development and contribute to directional sweep selectivity. Nature communications. 9 [PubMed]

• Plasticity forms non-overlapping adjacent ON and OFF RFs in cortical neurons (Sollini et al 2018) [Model]

Sterratt DC, Willshaw D. (2008). Inhomogeneities in heteroassociative memories with linear learning rules. Neural computation. 20 [PubMed]

Toyoizumi T, Kaneko M, Stryker MP, Miller KD. (2014). Modeling the dynamic interaction of Hebbian and homeostatic plasticity. Neuron. 84 [PubMed]

• Modeling hebbian and homeostatic plasticity (Toyoizumi et al. 2014) [Model]

Triesch J. (2007). Synergies between intrinsic and synaptic plasticity mechanisms. Neural computation. 19 [PubMed]

Troyer TW, Doupe AJ. (2000). An associational model of birdsong sensorimotor learning I. Efference copy and the learning of song syllables. Journal of neurophysiology. 84 [PubMed]

Troyer TW, Doupe AJ. (2000). An associational model of birdsong sensorimotor learning II. Temporal hierarchies and the learning of song sequence. Journal of neurophysiology. 84 [PubMed]

Watt AJ, Sjöström PJ, Häusser M, Nelson SB, Turrigiano GG. (2004). A proportional but slower NMDA potentiation follows AMPA potentiation in LTP. Nature neuroscience. 7 [PubMed]

Wenning G, Obermayer K. (2003). Activity driven adaptive stochastic resonance. Physical review letters. 90 [PubMed]