Wang Y et al. (2006). Heterogeneity in the pyramidal network of the medial prefrontal cortex. Nature neuroscience. 9 [PubMed]

See more from authors: Wang Y · Markram H · Goodman PH · Berger TK · Ma J · Goldman-Rakic PS

References and models cited by this paper
References and models that cite this paper

Barak O, Tsodyks M. (2007). Persistent activity in neural networks with dynamic synapses. PLoS computational biology. 3 [PubMed]

Barros-Zulaica N et al. (2019). Estimating the Readily-Releasable Vesicle Pool Size at Synaptic Connections in the Neocortex Frontiers in Synaptic Neuroscience. 11

Brette R et al. (2007). Simulation of networks of spiking neurons: a review of tools and strategies. Journal of computational neuroscience. 23 [PubMed]

Chadderdon GL et al. (2014). Motor cortex microcircuit simulation based on brain activity mapping. Neural computation. 26 [PubMed]

Costa RP, Sjöström PJ, van Rossum MC. (2013). Probabilistic inference of short-term synaptic plasticity in neocortical microcircuits. Frontiers in computational neuroscience. 7 [PubMed]

Esposito U, Giugliano M, Vasilaki E. (2014). Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity. Frontiers in computational neuroscience. 8 [PubMed]

Esposito U, Giugliano M, van Rossum M, Vasilaki E. (2014). Measuring symmetry, asymmetry and randomness in neural network connectivity. PloS one. 9 [PubMed]

Hass J, Hertäg L, Durstewitz D. (2016). A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity. PLoS computational biology. 12 [PubMed]

Hayut I, Fanselow EE, Connors BW, Golomb D. (2011). LTS and FS inhibitory interneurons, short-term synaptic plasticity, and cortical circuit dynamics. PLoS computational biology. 7 [PubMed]

Ibañez S, Luebke JI, Chang W, Draguljić D, Weaver CM. (2019). Network Models Predict That Pyramidal Neuron Hyperexcitability and Synapse Loss in the dlPFC Lead to Age-Related Spatial Working Memory Impairment in Rhesus Monkeys. Frontiers in computational neuroscience. 13 [PubMed]

Ibañez S, Sengupta N, Luebke JI, Wimmer K, Weaver CM. (2024). Myelin dystrophy impairs signal transmission and working memory in a multiscale model of the aging prefrontal cortex. eLife. 12 [PubMed]

Konstantoudaki X, Papoutsi A, Chalkiadaki K, Poirazi P, Sidiropoulou K. (2014). Modulatory effects of inhibition on persistent activity in a cortical microcircuit model. Frontiers in neural circuits. 8 [PubMed]

Lim S, Goldman MS. (2013). Balanced cortical microcircuitry for maintaining information in working memory. Nature neuroscience. 16 [PubMed]

Lim S, Goldman MS. (2014). Balanced cortical microcircuitry for spatial working memory based on corrective feedback control. The Journal of neuroscience : the official journal of the Society for Neuroscience. 34 [PubMed]

Markram H et al. (2015). Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 163 [PubMed]

Nichols EJ, Hutt A. (2015). Neural field simulator: two-dimensional spatio-temporal dynamics involving finite transmission speed. Frontiers in neuroinformatics. 9 [PubMed]

Papoutsi A, Kastellakis G, Poirazi P. (2017). Basal tree complexity shapes functional pathways in the prefrontal cortex. Journal of neurophysiology. 118 [PubMed]

Papoutsi A, Sidiropoulou K, Cutsuridis V, Poirazi P. (2013). Induction and modulation of persistent activity in a layer V PFC microcircuit model. Frontiers in neural circuits. 7 [PubMed]

Papoutsi A, Sidiropoulou K, Poirazi P. (2014). Dendritic nonlinearities reduce network size requirements and mediate ON and OFF states of persistent activity in a PFC microcircuit model. PLoS computational biology. 10 [PubMed]

Potjans TC, Diesmann M. (2014). The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. Cerebral cortex (New York, N.Y. : 1991). 24 [PubMed]

Ramaswamy S et al. (2015). The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex. Frontiers in neural circuits. 9 [PubMed]

Sussillo D, Toyoizumi T, Maass W. (2007). Self-tuning of neural circuits through short-term synaptic plasticity. Journal of neurophysiology. 97 [PubMed]

Testa-Silva G et al. (2012). Hyperconnectivity and slow synapses during early development of medial prefrontal cortex in a mouse model for mental retardation and autism. Cerebral cortex (New York, N.Y. : 1991). 22 [PubMed]

Torres JJ, Cortes JM, Marro J, Kappen HJ. (2007). Competition between synaptic depression and facilitation in attractor neural networks. Neural computation. 19 [PubMed]

Vasilaki E, Giugliano M. (2014). Emergence of connectivity motifs in networks of model neurons with short- and long-term plastic synapses. PloS one. 9 [PubMed]

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