---
res:
  bibo_abstract:
  - 'Thin pancake-like neuronal networks cultured on top of a planar microelectrode
    array have been extensively tried out in neuroengineering, as a substrate for
    the mobile robot’s control unit, i.e., as a cyborg’s brain. Most of these attempts
    failed due to intricate self-organizing dynamics in the neuronal systems. In particular,
    the networks may exhibit an emergent spatial map of steady nucleation sites (“n-sites”)
    of spontaneous population spikes. Being unpredictable and independent of the surface
    electrode locations, the n-sites drastically change local ability of the network
    to generate spikes. Here, using a spiking neuronal network model with generative
    spatially-embedded connectome, we systematically show in simulations that the
    number, location, and relative activity of spontaneously formed n-sites (“the
    vitals”) crucially depend on the samplings of three distributions: (1) the network
    distribution of neuronal excitability, (2) the distribution of connections between
    neurons of the network, and (3) the distribution of maximal amplitudes of a single
    synaptic current pulse. Moreover, blocking the dynamics of a small fraction (about
    4%) of non-pacemaker neurons having the highest excitability was enough to completely
    suppress the occurrence of population spikes and their n-sites. This key result
    is explained theoretically. Remarkably, the n-sites occur taking into account
    only short-term synaptic plasticity, i.e., without a Hebbian-type plasticity.
    As the spiking network model used in this study is strictly deterministic, all
    simulation results can be accurately reproduced. The model, which has already
    demonstrated a very high richness-to-complexity ratio, can also be directly extended
    into the three-dimensional case, e.g., for targeting peculiarities of spiking
    dynamics in cerebral (or brain) organoids. We recommend the model as an excellent
    illustrative tool for teaching network-level computational neuroscience, complementing
    a few benchmark models.@eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Dmitrii
      foaf_name: Zendrikov, Dmitrii
      foaf_surname: Zendrikov
  - foaf_Person:
      foaf_givenName: Alexander
      foaf_name: Paraskevov, Alexander
      foaf_surname: Paraskevov
      foaf_workInfoHomepage: http://www.librecat.org/personId=d05e3c56-9262-11ed-9231-be692464e5ac
  bibo_doi: 10.1016/j.neunet.2024.106589
  bibo_volume: 180
  dct_date: 2024^xs_gYear
  dct_identifier:
  - UT:001316474600001
  dct_isPartOf:
  - http://id.crossref.org/issn/0893-6080
  - http://id.crossref.org/issn/1879-2782
  dct_language: eng
  dct_publisher: Elsevier@
  dct_title: The vitals for steady nucleation maps of spontaneous spiking coherence
    in autonomous two-dimensional neuronal networks@
  fabio_hasPubmedId: '39217864'
...