JitCon: Just in time connectivity for large spiking networks (Lytton et al. 2008)

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Accession:106891
This simulation is primarily an illustration and is not well optimized for actually running large networks. jitcon.mod contains a large amount of C level code, understanding of which requires some knowledge of Neuron internals
Reference:
1 . Lytton WW, Omurtag A, Neymotin SA, Hines ML (2008) Just in time connectivity for large spiking networks Neural Comput 20(11):2745-56 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Epilepsy;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu];
Files displayed below are from the implementation

Lytton WW, Omurtag A, Neymotin SA, Hines ML (2008) Just in time connectivity for large spiking networks Neural Comput 20(11):2745-56[PubMed]

References and models cited by this paper

References and models that cite this paper

Chadderdon GL, Mohan A, Suter BA, Neymotin SA, Kerr CC, Francis JT, Shepherd GM, Lytton WW (2014) Motor cortex microcircuit simulation based on brain activity mapping. Neural Comput 26:1239-62 [Journal] [PubMed]

   Motor cortex microcircuit simulation based on brain activity mapping (Chadderdon et al. 2014) [Model]

Chadderdon GL, Neymotin SA, Kerr CC, Lytton WW (2012) Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex PLoS ONE 2012 7(10):e47251 [Journal]

   Reinforcement learning of targeted movement (Chadderdon et al. 2012) [Model]

Djurfeldt M (2012) The Connection-set Algebra-A Novel Formalism for the Representation of Connectivity Structure in Neuronal Network Models Neuroinformatics 10(3):287-304 [Journal] [PubMed]

   Connection-set Algebra (CSA) for the representation of connectivity in NN models (Djurfeldt 2012) [Model]

Dura-Bernal S, Li K, Neymotin SA, Francis JT, Principe JC, Lytton WW (2016) Restoring behavior via inverse neurocontroller in a lesioned cortical spiking model driving a virtual arm. Front. Neurosci. Neuroprosthetics 10:28 [Journal]

   Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015) [Model]

Dura-Bernal S, Zhou X, Neymotin SA, Przekwas A, Francis JT, Lytton WW (2015) Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm. Front Neurorobot 9:13 [Journal] [PubMed]

   Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015) [Model]

Kerr CC, Neymotin SA, Chadderdon GL, Fietkiewicz CT, Francis JT, Lytton WW (2012) Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex IEEE Transactions on Neural Systems & Rehabilitation Engineering 20(2):153-60 [Journal] [PubMed]

   Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012) [Model]

Kerr CC, Van Albada SJ, Neymotin SA, Chadderdon GL, Robinson PA, Lytton WW (2013) Cortical information flow in Parkinson's disease: a composite network-field model. Front Comput Neurosci 7:39:1-14 [Journal] [PubMed]

   Composite spiking network/neural field model of Parkinsons (Kerr et al 2013) [Model]

Lytton WW, Neymotin SA, Hines ML (2008) The virtual slice setup. J Neurosci Methods 171:309-15 [Journal] [PubMed]

   The virtual slice setup (Lytton et al. 2008) [Model]

Neymotin SA, Chadderdon GL, Kerr CC, Francis JT, Lytton WW (2013) Reinforcement learning of 2-joint virtual arm reaching in a computer model of sensorimotor cortex Neural Computation 25(12):3263-93 [Journal] [PubMed]

   Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013) [Model]

Neymotin SA, Lee H, Park E, Fenton AA, Lytton WW (2011) Emergence of physiological oscillation frequencies in a computer model of neocortex. Front Comput Neurosci 5:19-75 [Journal] [PubMed]

   Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011) [Model]

Rowan MS, Neymotin SA, Lytton WW (2014) Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci 8:39 [Journal] [PubMed]

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

Rowan MS,Neymotin SA (2013) Synaptic Scaling Balances Learning in a Spiking Model of Neocortex Adaptive and Natural Computing Algorithms, Tomassini M, Antonioni A, Daolio F, Buesser P, ed. pp.20 [Journal]

   Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013) [Model]

(12 refs)