Large-scale neural model of visual short-term memory (Ulloa, Horwitz 2016; Horwitz, et al. 2005,...)

 Download zip file 
Help downloading and running models
Accession:206337
Large-scale neural model of visual short term memory embedded into a 998-node connectome. The model simulates electrical activity across neuronal populations of a number of brain regions and converts that activity into fMRI and MEG time-series. The model uses a neural simulator developed at the Brain Imaging and Modeling Section of the National Institutes of Health.
References:
1 . Tagamets MA, Horwitz B (1998) Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cereb Cortex 8:310-20 [PubMed]
2 . Ulloa A, Horwitz B (2016) Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex. Front Neuroinform 10:32 [PubMed]
3 . Horwitz B, Warner B, Fitzer J, Tagamets MA, Husain FT, Long TW (2005) Investigating the neural basis for functional and effective connectivity. Application to fMRI. Philos Trans R Soc Lond B Biol Sci 360:1093-108 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Prefrontal cortex (PFC);
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Python;
Model Concept(s): Working memory;
Implementer(s): Ulloa, Antonio [antonio.ulloa at alum.bu.edu];
/
lsnm_in_python-master
visual_model
subject_15
attsefd2.w
attvatts.w
efd1efd1.w
efd1efd2.w
efd1exfr.w
efd1ifd1.w
efd1infs.w
efd1inss.w
efd2efd1.w
efd2efd2.w
efd2ev4c.w
efd2ev4h.w
efd2ev4v.w
efd2exss.w
efd2ifd2.w
ev1hev1h.w
ev1hev4c.w
ev1hev4h.w
ev1hiv1h.w
ev1vev1v.w
ev1vev4c.w
ev1vev4v.w
ev1viv1v.w
ev4c.wt *
ev4cev4c.w
ev4civ4c.w
ev4h.wt *
ev4hev1h.w
ev4hev4h.w
ev4hiv4h.w
ev4v.wt *
ev4vev1v.w
ev4vev4v.w
ev4viv4v.w
exfrexfr.w
exfrifd1.w
exfrifd2.w
exfrinfr.w
exfsefd2.w
exfsexfr.w
exfsexfs.w
exfsifd1.w
exfsinfs.w
exssev4c.w
exssev4h.w
exssev4v.w
exssexfs.w
exssexss.w
exssinss.w
ifd1efd1.w
ifd2efd2.w
infrexfr.w
infsexfs.w
inssexss.w
iv1hev1h.w
iv1vev1v.w
iv4cev4c.w
iv4hev4h.w
iv4vev4v.w
lgnsev1h.w
lgnsev1v.w
weightslist.txt *
                            
% Thu Nov 19 22:10:16 2015

% Input layer: (9, 9)
% Output layer: (9, 9)
% Fanout size: (1, 1)
% Fanout spacing: (1, 1)
% Specified fanout weights

Connect(exss, exfs)  {
  From:  (1, 1)  {
    ([ 1, 1]  0.210123) 
  }
  From:  (1, 2)  {
    ([ 1, 2]  0.200200) 
  }
  From:  (1, 3)  {
    ([ 1, 3]  0.217620) 
  }
  From:  (1, 4)  {
    ([ 1, 4]  0.214980) 
  }
  From:  (1, 5)  {
    ([ 1, 5]  0.188379) 
  }
  From:  (1, 6)  {
    ([ 1, 6]  0.190173) 
  }
  From:  (1, 7)  {
    ([ 1, 7]  0.201921) 
  }
  From:  (1, 8)  {
    ([ 1, 8]  0.185750) 
  }
  From:  (1, 9)  {
    ([ 1, 9]  0.191446) 
  }
  From:  (2, 1)  {
    ([ 2, 1]  0.204334) 
  }
  From:  (2, 2)  {
    ([ 2, 2]  0.199649) 
  }
  From:  (2, 3)  {
    ([ 2, 3]  0.181118) 
  }
  From:  (2, 4)  {
    ([ 2, 4]  0.186020) 
  }
  From:  (2, 5)  {
    ([ 2, 5]  0.217219) 
  }
  From:  (2, 6)  {
    ([ 2, 6]  0.202203) 
  }
  From:  (2, 7)  {
    ([ 2, 7]  0.198997) 
  }
  From:  (2, 8)  {
    ([ 2, 8]  0.184036) 
  }
  From:  (2, 9)  {
    ([ 2, 9]  0.197007) 
  }
  From:  (3, 1)  {
    ([ 3, 1]  0.180033) 
  }
  From:  (3, 2)  {
    ([ 3, 2]  0.185706) 
  }
  From:  (3, 3)  {
    ([ 3, 3]  0.212042) 
  }
  From:  (3, 4)  {
    ([ 3, 4]  0.183446) 
  }
  From:  (3, 5)  {
    ([ 3, 5]  0.210885) 
  }
  From:  (3, 6)  {
    ([ 3, 6]  0.182063) 
  }
  From:  (3, 7)  {
    ([ 3, 7]  0.184858) 
  }
  From:  (3, 8)  {
    ([ 3, 8]  0.192479) 
  }
  From:  (3, 9)  {
    ([ 3, 9]  0.219596) 
  }
  From:  (4, 1)  {
    ([ 4, 1]  0.198770) 
  }
  From:  (4, 2)  {
    ([ 4, 2]  0.202147) 
  }
  From:  (4, 3)  {
    ([ 4, 3]  0.185325) 
  }
  From:  (4, 4)  {
    ([ 4, 4]  0.198926) 
  }
  From:  (4, 5)  {
    ([ 4, 5]  0.182932) 
  }
  From:  (4, 6)  {
    ([ 4, 6]  0.216007) 
  }
  From:  (4, 7)  {
    ([ 4, 7]  0.208284) 
  }
  From:  (4, 8)  {
    ([ 4, 8]  0.190901) 
  }
  From:  (4, 9)  {
    ([ 4, 9]  0.191678) 
  }
  From:  (5, 1)  {
    ([ 5, 1]  0.218296) 
  }
  From:  (5, 2)  {
    ([ 5, 2]  0.219231) 
  }
  From:  (5, 3)  {
    ([ 5, 3]  0.189499) 
  }
  From:  (5, 4)  {
    ([ 5, 4]  0.204191) 
  }
  From:  (5, 5)  {
    ([ 5, 5]  0.188370) 
  }
  From:  (5, 6)  {
    ([ 5, 6]  0.187768) 
  }
  From:  (5, 7)  {
    ([ 5, 7]  0.197963) 
  }
  From:  (5, 8)  {
    ([ 5, 8]  0.200060) 
  }
  From:  (5, 9)  {
    ([ 5, 9]  0.185039) 
  }
  From:  (6, 1)  {
    ([ 6, 1]  0.188194) 
  }
  From:  (6, 2)  {
    ([ 6, 2]  0.217905) 
  }
  From:  (6, 3)  {
    ([ 6, 3]  0.209715) 
  }
  From:  (6, 4)  {
    ([ 6, 4]  0.200982) 
  }
  From:  (6, 5)  {
    ([ 6, 5]  0.197972) 
  }
  From:  (6, 6)  {
    ([ 6, 6]  0.202332) 
  }
  From:  (6, 7)  {
    ([ 6, 7]  0.201803) 
  }
  From:  (6, 8)  {
    ([ 6, 8]  0.203510) 
  }
  From:  (6, 9)  {
    ([ 6, 9]  0.209065) 
  }
  From:  (7, 1)  {
    ([ 7, 1]  0.211055) 
  }
  From:  (7, 2)  {
    ([ 7, 2]  0.192743) 
  }
  From:  (7, 3)  {
    ([ 7, 3]  0.202501) 
  }
  From:  (7, 4)  {
    ([ 7, 4]  0.215500) 
  }
  From:  (7, 5)  {
    ([ 7, 5]  0.204462) 
  }
  From:  (7, 6)  {
    ([ 7, 6]  0.205247) 
  }
  From:  (7, 7)  {
    ([ 7, 7]  0.214477) 
  }
  From:  (7, 8)  {
    ([ 7, 8]  0.217757) 
  }
  From:  (7, 9)  {
    ([ 7, 9]  0.180439) 
  }
  From:  (8, 1)  {
    ([ 8, 1]  0.185501) 
  }
  From:  (8, 2)  {
    ([ 8, 2]  0.191201) 
  }
  From:  (8, 3)  {
    ([ 8, 3]  0.183036) 
  }
  From:  (8, 4)  {
    ([ 8, 4]  0.219247) 
  }
  From:  (8, 5)  {
    ([ 8, 5]  0.192766) 
  }
  From:  (8, 6)  {
    ([ 8, 6]  0.191877) 
  }
  From:  (8, 7)  {
    ([ 8, 7]  0.200200) 
  }
  From:  (8, 8)  {
    ([ 8, 8]  0.212469) 
  }
  From:  (8, 9)  {
    ([ 8, 9]  0.180521) 
  }
  From:  (9, 1)  {
    ([ 9, 1]  0.219885) 
  }
  From:  (9, 2)  {
    ([ 9, 2]  0.189160) 
  }
  From:  (9, 3)  {
    ([ 9, 3]  0.214656) 
  }
  From:  (9, 4)  {
    ([ 9, 4]  0.214876) 
  }
  From:  (9, 5)  {
    ([ 9, 5]  0.218217) 
  }
  From:  (9, 6)  {
    ([ 9, 6]  0.186687) 
  }
  From:  (9, 7)  {
    ([ 9, 7]  0.190125) 
  }
  From:  (9, 8)  {
    ([ 9, 8]  0.183826) 
  }
  From:  (9, 9)  {
    ([ 9, 9]  0.202132) 
  }
}

Loading data, please wait...