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@ARTICLE{Pastorelli:1022258,
      author       = {Pastorelli, Elena and Yegenoglu, Alper and Kolodziej,
                      Nicole and Wybo, Willem and Simula, Francesco and Diaz,
                      Sandra and Storm, Johan Frederik and Paolucci, Pier
                      Stanislao},
      title        = {{T}wo-compartment neuronal spiking model expressing
                      brain-state specific apical-amplification, -isolation and
                      -drive regimes},
      journal      = {arXiv},
      publisher    = {arXiv},
      reportid     = {FZJ-2024-01376},
      year         = {2023},
      abstract     = {There is mounting experimental evidence that brain-state
                      specific neural mechanisms supported by connectomic
                      architectures serve to combine past and contextual knowledge
                      with current, incoming flow of evidence (e.g. from sensory
                      systems). Such mechanisms are distributed across multiple
                      spatial and temporal scales and require dedicated support at
                      the levels of individual neurons and synapses. A prominent
                      feature in the neocortex is the structure of large, deep
                      pyramidal neurons which show a peculiar separation between
                      an apical dendritic compartment and a basal
                      dentritic/peri-somatic compartment, with distinctive
                      patterns of incoming connections and brain-state specific
                      activation mechanisms, namely apical-amplification,
                      -isolation and -drive associated to the wakefulness, deeper
                      NREM sleep stages and REM sleep. The cognitive roles of
                      apical mechanisms have been demonstrated in behaving
                      animals. In contrast, classical models of learning spiking
                      networks are based on single compartment neurons that miss
                      the description of mechanisms to combine apical and
                      basal/somatic information. This work aims to provide the
                      computational community with a two-compartment spiking
                      neuron model which includes features that are essential for
                      supporting brain-state specific learning and with a
                      piece-wise linear transfer function (ThetaPlanes) at highest
                      abstraction level to be used in large scale bio-inspired
                      artificial intelligence systems. A machine learning
                      algorithm, constrained by a set of fitness functions,
                      selected the parameters defining neurons expressing the
                      desired apical mechanisms.},
      keywords     = {Neurons and Cognition (q-bio.NC) (Other) / Neural and
                      Evolutionary Computing (cs.NE) (Other) / FOS: Biological
                      sciences (Other) / FOS: Computer and information sciences
                      (Other)},
      cin          = {INM-6 / IAS-6 / JSC / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)INM-10-20170113},
      pnm          = {5234 - Emerging NC Architectures (POF4-523) / 5231 -
                      Neuroscientific Foundations (POF4-523) / 5232 -
                      Computational Principles (POF4-523) / HBP SGA3 - Human Brain
                      Project Specific Grant Agreement 3 (945539) / ICEI -
                      Interactive Computing E-Infrastructure for the Human Brain
                      Project (800858)},
      pid          = {G:(DE-HGF)POF4-5234 / G:(DE-HGF)POF4-5231 /
                      G:(DE-HGF)POF4-5232 / G:(EU-Grant)945539 /
                      G:(EU-Grant)800858},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/arXiv.2311.06074},
      url          = {https://juser.fz-juelich.de/record/1022258},
}