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_3
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
                            
% Wed Aug 19 14:47:03 2015

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

Connect(efd2, exss)  {
  From:  (1, 1)  {
    ([ 1, 1]  0.009484) 
  }
  From:  (1, 2)  {
    ([ 1, 2]  0.009102) 
  }
  From:  (1, 3)  {
    ([ 1, 3]  0.010178) 
  }
  From:  (1, 4)  {
    ([ 1, 4]  0.011080) 
  }
  From:  (1, 5)  {
    ([ 1, 5]  0.011958) 
  }
  From:  (1, 6)  {
    ([ 1, 6]  0.010143) 
  }
  From:  (1, 7)  {
    ([ 1, 7]  0.008860) 
  }
  From:  (1, 8)  {
    ([ 1, 8]  0.010893) 
  }
  From:  (1, 9)  {
    ([ 1, 9]  0.008860) 
  }
  From:  (2, 1)  {
    ([ 2, 1]  0.008018) 
  }
  From:  (2, 2)  {
    ([ 2, 2]  0.009442) 
  }
  From:  (2, 3)  {
    ([ 2, 3]  0.011852) 
  }
  From:  (2, 4)  {
    ([ 2, 4]  0.010429) 
  }
  From:  (2, 5)  {
    ([ 2, 5]  0.011778) 
  }
  From:  (2, 6)  {
    ([ 2, 6]  0.011483) 
  }
  From:  (2, 7)  {
    ([ 2, 7]  0.011455) 
  }
  From:  (2, 8)  {
    ([ 2, 8]  0.008871) 
  }
  From:  (2, 9)  {
    ([ 2, 9]  0.010992) 
  }
  From:  (3, 1)  {
    ([ 3, 1]  0.011251) 
  }
  From:  (3, 2)  {
    ([ 3, 2]  0.009934) 
  }
  From:  (3, 3)  {
    ([ 3, 3]  0.011766) 
  }
  From:  (3, 4)  {
    ([ 3, 4]  0.008761) 
  }
  From:  (3, 5)  {
    ([ 3, 5]  0.010516) 
  }
  From:  (3, 6)  {
    ([ 3, 6]  0.009579) 
  }
  From:  (3, 7)  {
    ([ 3, 7]  0.008905) 
  }
  From:  (3, 8)  {
    ([ 3, 8]  0.008398) 
  }
  From:  (3, 9)  {
    ([ 3, 9]  0.009499) 
  }
  From:  (4, 1)  {
    ([ 4, 1]  0.009993) 
  }
  From:  (4, 2)  {
    ([ 4, 2]  0.008410) 
  }
  From:  (4, 3)  {
    ([ 4, 3]  0.009555) 
  }
  From:  (4, 4)  {
    ([ 4, 4]  0.010923) 
  }
  From:  (4, 5)  {
    ([ 4, 5]  0.011468) 
  }
  From:  (4, 6)  {
    ([ 4, 6]  0.008971) 
  }
  From:  (4, 7)  {
    ([ 4, 7]  0.008421) 
  }
  From:  (4, 8)  {
    ([ 4, 8]  0.011116) 
  }
  From:  (4, 9)  {
    ([ 4, 9]  0.010061) 
  }
  From:  (5, 1)  {
    ([ 5, 1]  0.011037) 
  }
  From:  (5, 2)  {
    ([ 5, 2]  0.009593) 
  }
  From:  (5, 3)  {
    ([ 5, 3]  0.010248) 
  }
  From:  (5, 4)  {
    ([ 5, 4]  0.011519) 
  }
  From:  (5, 5)  {
    ([ 5, 5]  0.011068) 
  }
  From:  (5, 6)  {
    ([ 5, 6]  0.008310) 
  }
  From:  (5, 7)  {
    ([ 5, 7]  0.009033) 
  }
  From:  (5, 8)  {
    ([ 5, 8]  0.010831) 
  }
  From:  (5, 9)  {
    ([ 5, 9]  0.009192) 
  }
  From:  (6, 1)  {
    ([ 6, 1]  0.010964) 
  }
  From:  (6, 2)  {
    ([ 6, 2]  0.009605) 
  }
  From:  (6, 3)  {
    ([ 6, 3]  0.011992) 
  }
  From:  (6, 4)  {
    ([ 6, 4]  0.008119) 
  }
  From:  (6, 5)  {
    ([ 6, 5]  0.009170) 
  }
  From:  (6, 6)  {
    ([ 6, 6]  0.011795) 
  }
  From:  (6, 7)  {
    ([ 6, 7]  0.010458) 
  }
  From:  (6, 8)  {
    ([ 6, 8]  0.009686) 
  }
  From:  (6, 9)  {
    ([ 6, 9]  0.008119) 
  }
  From:  (7, 1)  {
    ([ 7, 1]  0.008633) 
  }
  From:  (7, 2)  {
    ([ 7, 2]  0.008819) 
  }
  From:  (7, 3)  {
    ([ 7, 3]  0.009119) 
  }
  From:  (7, 4)  {
    ([ 7, 4]  0.009547) 
  }
  From:  (7, 5)  {
    ([ 7, 5]  0.008699) 
  }
  From:  (7, 6)  {
    ([ 7, 6]  0.008374) 
  }
  From:  (7, 7)  {
    ([ 7, 7]  0.009906) 
  }
  From:  (7, 8)  {
    ([ 7, 8]  0.011400) 
  }
  From:  (7, 9)  {
    ([ 7, 9]  0.011783) 
  }
  From:  (8, 1)  {
    ([ 8, 1]  0.011563) 
  }
  From:  (8, 2)  {
    ([ 8, 2]  0.010132) 
  }
  From:  (8, 3)  {
    ([ 8, 3]  0.010077) 
  }
  From:  (8, 4)  {
    ([ 8, 4]  0.010341) 
  }
  From:  (8, 5)  {
    ([ 8, 5]  0.010650) 
  }
  From:  (8, 6)  {
    ([ 8, 6]  0.008162) 
  }
  From:  (8, 7)  {
    ([ 8, 7]  0.009138) 
  }
  From:  (8, 8)  {
    ([ 8, 8]  0.010360) 
  }
  From:  (8, 9)  {
    ([ 8, 9]  0.010554) 
  }
  From:  (9, 1)  {
    ([ 9, 1]  0.009787) 
  }
  From:  (9, 2)  {
    ([ 9, 2]  0.010471) 
  }
  From:  (9, 3)  {
    ([ 9, 3]  0.009489) 
  }
  From:  (9, 4)  {
    ([ 9, 4]  0.010408) 
  }
  From:  (9, 5)  {
    ([ 9, 5]  0.010233) 
  }
  From:  (9, 6)  {
    ([ 9, 6]  0.010082) 
  }
  From:  (9, 7)  {
    ([ 9, 7]  0.009687) 
  }
  From:  (9, 8)  {
    ([ 9, 8]  0.009204) 
  }
  From:  (9, 9)  {
    ([ 9, 9]  0.008898) 
  }
}

Loading data, please wait...