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3D olfactory bulb: operators (Migliore et al, 2015)

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"... Using a 3D model of mitral and granule cell interactions supported by experimental findings, combined with a matrix-based representation of glomerular operations, we identify the mechanisms for forming one or more glomerular units in response to a given odor, how and to what extent the glomerular units interfere or interact with each other during learning, their computational role within the olfactory bulb microcircuit, and how their actions can be formalized into a theoretical framework in which the olfactory bulb can be considered to contain "odor operators" unique to each individual. ..."
1 . Migliore M, Cavarretta F, Marasco A, Tulumello E, Hines ML, Shepherd GM (2015) Synaptic clusters function as odor operators in the olfactory bulb. Proc Natl Acad Sci U S A 112:8499-504 [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): Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Activity Patterns; Dendritic Action Potentials; Active Dendrites; Synaptic Plasticity; Action Potentials; Synaptic Integration; Unsupervised Learning; Sensory processing; Olfaction;
Implementer(s): Migliore, Michele [Michele.Migliore at]; Cavarretta, Francesco [francescocavarretta at];
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell; AMPA; NMDA; Gaba; I Na,t; I A; I K; Gaba; Glutamate;
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from util import *
from lpt import lpt, statistics
from all2all import all2all

def load_bal(cx, npart):
  ''' cx is list of (complexity, gid) pairs on this process
      return: an LPT balanced list of gids that should belong to this process
  elapse = h.startsw()
  #send to rank 0
  r = all2all({0:cx})
  # make a list of all the (cx, gid)
  s = {}
  if rank == 0:
    c = []
    for i in r.values():
      c += i
    del r
    #distribute by LPT
    parts = lpt(c, npart)
    print statistics(parts)
    for i,p in enumerate(parts):
      s.update({i : p[1]})
    del r
  #send each partition to the proper rank
  local = all2all(s)
  del s
  if rank == 0:
    print "load_bal time %g" % (h.startsw()-elapse)
  return local[0]

if __name__ == '__main__':
  from util import serialize, finish
  if True:
    cx = [(10*rank+i, 10*rank+i) for i in range(1,5)]
    print cx
    cx = load_bal(cx, nhost)
    for r in serialize():
      print 'rank %d '%rank, cx
  if nhost > 0:

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