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@INPROCEEDINGS{Stella:894205,
      author       = {Stella, Alessandra and Bouss, Peter and Palm, Günther and
                      Grün, Sonja},
      title        = {{B}ehaviorally {R}elevant {S}patio-{T}emporal {S}pike
                      {P}atterns in {P}arallel {S}pike {T}rains},
      reportid     = {FZJ-2021-03096},
      year         = {2021},
      abstract     = {The Hebbian hypothesis [1] states that neurons organize in
                      assemblies of co-active neuronsacting as information
                      processing units. We hypothesize that assembly activity is
                      expressedby the occurrence of precise spatio-temporal
                      patterns (STPs) of spikes - with precisetemporal delays
                      between the spikes - emitted by neurons that presumably are
                      members ofan assembly.We developed a method, called SPADE
                      [2,3,4], that detects significant STPs in massivelyparallel
                      spike trains. SPADE involves three steps: it first
                      identifies repeatingSTPs using Frequent Itemset Mining [5];
                      second, it evaluates the detected patterns forsignificance
                      through surrogates (trial-shifting); third, it removes the
                      false positive patternsthat are a by-product of true
                      patterns and the background activity.Here, we aim to
                      evaluate if cell assemblies are active in relation to motor
                      behavior [2].Therefore, we analyzed N=20 experimental
                      sessions consisting of about 100 parallel spiketrains
                      recorded by a 100-electrode Utah array in the pre-/motor
                      cortex of two macaquemonkeys performing a reach-to-grasp
                      task [6,7]. In this task, the monkey, after an
                      instructedpreparatory period, had to pull and hold an object
                      by using either a side or a precision grip,and using either
                      high or low force (four behavioral conditions). We segmented
                      trials into 500ms periods and concatenated them to analyze
                      separately for the occurrence of STPs. Eachsignificant STP
                      is identified by its neuron composition, its number and
                      times of occurrencesand the delays between spikes of the
                      pattern. The temporal resolution of the detectedpatterns is
                      fixed to 5ms.We find that STPs occur in all phases of the
                      behavior. In particular, we find about 6 patternsper
                      session, where only 3 to 13 individual neurons are involved
                      in STPs. Pattern can repeatfrom 280 to 10 times, depending
                      on the size, which varies from 2 to 6 neurons. Within
                      asession, patterns strongly depend on the behavioral
                      context, and we do not find identicalpatterns in the
                      different epochs. Thus, patterns are specific to a
                      behavioral condition,suggesting that different assemblies
                      are activated for each specific behavioral context.Patterns
                      that occur in a single session typically overlap in the
                      participating neurons, and afew individual neurons appear as
                      hubs, i.e. are involved in several patterns. We also
                      findthat pattern neurons are not located within a small
                      region, but distributed across the entirecortical surface
                      covered by the Utah array.Our results are consistent with
                      the model of the synfire chain (SFC) [8]. A theoretical
                      studyshowed [9] that patterns emerging from SFC activity can
                      be found in parallel spike train datarecorded with a
                      100-electrode Utah array, i.e. despite the strong
                      subsampling.References[1] Hebb, D. O. (1949). John Wiley
                      $\&$ Sons.[2] Torre et al (2016) J Neurosci. DOI:
                      10.1523/JNEUROSCI.4375-15.2016.[3] Quaglio et al. (2017).
                      Front Comp Neurosci,. DOI: 10.3389/fncom.2017.00041.[4]
                      Stella et al. (2019). Biosystems.
                      DOI:10.1016/j.biosystems.2019.104022.[5] Pormann et al.
                      (2021). Submitted.[6] Brochier et al. (2018). Scientific
                      data. DOI: 10.1038/sdata.2018.55.[7] Riehle et al. (2013).
                      Front. Neural Circuits. DOI: 10.3389/fncir.2013.00048.[8]
                      Abeles (1991) Cambridge University Press.[9] Berling, David
                      (2020). Master thesis in physics, RWTH Aachen Univ.,
                      Germany.},
      month         = {Jul},
      date          = {2021-07-03},
      organization  = {Computational Neuroscience Conference,
                       Online (USA), 3 Jul 2021 - 7 Jul 2021},
      subtyp        = {After Call},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {571 - Connectivity and Activity (POF3-571) / 5231 -
                      Neuroscientific Foundations (POF4-523) / HAF - Helmholtz
                      Analytics Framework (ZT-I-0003) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907) / HBP SGA3 -
                      Human Brain Project Specific Grant Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF3-571 / G:(DE-HGF)POF4-5231 /
                      G:(DE-HGF)ZT-I-0003 / G:(EU-Grant)785907 /
                      G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/894205},
}