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

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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];
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lsnm_in_python-master
visual_model
subject_6
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
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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
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iv1hev1h.w
iv1vev1v.w
iv4cev4c.w
iv4hev4h.w
iv4vev4v.w
lgnsev1h.w
lgnsev1v.w
weightslist.txt
                            
% Fri Aug 21 04:52:55 2015

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

Connect(efd1, inss)  {
  From:  (1, 1)  {
    ([ 1, 1]  0.029725) 
  }
  From:  (1, 2)  {
    ([ 1, 2]  0.029770) 
  }
  From:  (1, 3)  {
    ([ 1, 3]  0.030880) 
  }
  From:  (1, 4)  {
    ([ 1, 4]  0.030507) 
  }
  From:  (1, 5)  {
    ([ 1, 5]  0.030737) 
  }
  From:  (1, 6)  {
    ([ 1, 6]  0.029866) 
  }
  From:  (1, 7)  {
    ([ 1, 7]  0.030615) 
  }
  From:  (1, 8)  {
    ([ 1, 8]  0.030007) 
  }
  From:  (1, 9)  {
    ([ 1, 9]  0.029411) 
  }
  From:  (2, 1)  {
    ([ 2, 1]  0.030912) 
  }
  From:  (2, 2)  {
    ([ 2, 2]  0.029602) 
  }
  From:  (2, 3)  {
    ([ 2, 3]  0.030135) 
  }
  From:  (2, 4)  {
    ([ 2, 4]  0.029381) 
  }
  From:  (2, 5)  {
    ([ 2, 5]  0.030970) 
  }
  From:  (2, 6)  {
    ([ 2, 6]  0.030620) 
  }
  From:  (2, 7)  {
    ([ 2, 7]  0.030037) 
  }
  From:  (2, 8)  {
    ([ 2, 8]  0.029982) 
  }
  From:  (2, 9)  {
    ([ 2, 9]  0.029833) 
  }
  From:  (3, 1)  {
    ([ 3, 1]  0.029022) 
  }
  From:  (3, 2)  {
    ([ 3, 2]  0.029197) 
  }
  From:  (3, 3)  {
    ([ 3, 3]  0.029958) 
  }
  From:  (3, 4)  {
    ([ 3, 4]  0.030526) 
  }
  From:  (3, 5)  {
    ([ 3, 5]  0.030127) 
  }
  From:  (3, 6)  {
    ([ 3, 6]  0.030093) 
  }
  From:  (3, 7)  {
    ([ 3, 7]  0.029874) 
  }
  From:  (3, 8)  {
    ([ 3, 8]  0.029650) 
  }
  From:  (3, 9)  {
    ([ 3, 9]  0.030703) 
  }
  From:  (4, 1)  {
    ([ 4, 1]  0.030831) 
  }
  From:  (4, 2)  {
    ([ 4, 2]  0.029182) 
  }
  From:  (4, 3)  {
    ([ 4, 3]  0.030444) 
  }
  From:  (4, 4)  {
    ([ 4, 4]  0.029983) 
  }
  From:  (4, 5)  {
    ([ 4, 5]  0.029830) 
  }
  From:  (4, 6)  {
    ([ 4, 6]  0.029334) 
  }
  From:  (4, 7)  {
    ([ 4, 7]  0.029885) 
  }
  From:  (4, 8)  {
    ([ 4, 8]  0.030227) 
  }
  From:  (4, 9)  {
    ([ 4, 9]  0.030358) 
  }
  From:  (5, 1)  {
    ([ 5, 1]  0.030383) 
  }
  From:  (5, 2)  {
    ([ 5, 2]  0.029621) 
  }
  From:  (5, 3)  {
    ([ 5, 3]  0.030829) 
  }
  From:  (5, 4)  {
    ([ 5, 4]  0.030501) 
  }
  From:  (5, 5)  {
    ([ 5, 5]  0.029103) 
  }
  From:  (5, 6)  {
    ([ 5, 6]  0.030091) 
  }
  From:  (5, 7)  {
    ([ 5, 7]  0.029677) 
  }
  From:  (5, 8)  {
    ([ 5, 8]  0.029930) 
  }
  From:  (5, 9)  {
    ([ 5, 9]  0.029824) 
  }
  From:  (6, 1)  {
    ([ 6, 1]  0.029780) 
  }
  From:  (6, 2)  {
    ([ 6, 2]  0.030588) 
  }
  From:  (6, 3)  {
    ([ 6, 3]  0.030791) 
  }
  From:  (6, 4)  {
    ([ 6, 4]  0.030885) 
  }
  From:  (6, 5)  {
    ([ 6, 5]  0.029252) 
  }
  From:  (6, 6)  {
    ([ 6, 6]  0.030444) 
  }
  From:  (6, 7)  {
    ([ 6, 7]  0.029928) 
  }
  From:  (6, 8)  {
    ([ 6, 8]  0.029906) 
  }
  From:  (6, 9)  {
    ([ 6, 9]  0.030328) 
  }
  From:  (7, 1)  {
    ([ 7, 1]  0.029946) 
  }
  From:  (7, 2)  {
    ([ 7, 2]  0.029721) 
  }
  From:  (7, 3)  {
    ([ 7, 3]  0.029920) 
  }
  From:  (7, 4)  {
    ([ 7, 4]  0.030570) 
  }
  From:  (7, 5)  {
    ([ 7, 5]  0.029791) 
  }
  From:  (7, 6)  {
    ([ 7, 6]  0.030873) 
  }
  From:  (7, 7)  {
    ([ 7, 7]  0.029812) 
  }
  From:  (7, 8)  {
    ([ 7, 8]  0.030114) 
  }
  From:  (7, 9)  {
    ([ 7, 9]  0.029498) 
  }
  From:  (8, 1)  {
    ([ 8, 1]  0.030627) 
  }
  From:  (8, 2)  {
    ([ 8, 2]  0.030482) 
  }
  From:  (8, 3)  {
    ([ 8, 3]  0.029791) 
  }
  From:  (8, 4)  {
    ([ 8, 4]  0.029137) 
  }
  From:  (8, 5)  {
    ([ 8, 5]  0.030106) 
  }
  From:  (8, 6)  {
    ([ 8, 6]  0.030690) 
  }
  From:  (8, 7)  {
    ([ 8, 7]  0.030484) 
  }
  From:  (8, 8)  {
    ([ 8, 8]  0.030762) 
  }
  From:  (8, 9)  {
    ([ 8, 9]  0.030729) 
  }
  From:  (9, 1)  {
    ([ 9, 1]  0.029627) 
  }
  From:  (9, 2)  {
    ([ 9, 2]  0.029703) 
  }
  From:  (9, 3)  {
    ([ 9, 3]  0.030479) 
  }
  From:  (9, 4)  {
    ([ 9, 4]  0.029991) 
  }
  From:  (9, 5)  {
    ([ 9, 5]  0.030921) 
  }
  From:  (9, 6)  {
    ([ 9, 6]  0.030492) 
  }
  From:  (9, 7)  {
    ([ 9, 7]  0.029767) 
  }
  From:  (9, 8)  {
    ([ 9, 8]  0.029287) 
  }
  From:  (9, 9)  {
    ([ 9, 9]  0.029005) 
  }
}

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