This title appears in the Scientific Report :
2019
Please use the identifier:
http://hdl.handle.net/2128/24850 in citations.
Evaluating Signatures of Synfire Chains in Massively Parallel Spike Recordings with a Spatial Monte Carlo Simulation
Evaluating Signatures of Synfire Chains in Massively Parallel Spike Recordings with a Spatial Monte Carlo Simulation
To investigate cortical network interactions during a reach-to-grasp task [1], we analyzed spatio-temporalpatterns (STPs) in massively parallel spike data. Using the SPADE analysis [2,3], we found 50 to 150 significant STPs in about 150 simultaneously recorded neurons during the movement period of t...
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Personal Name(s): | Berling, David (Corresponding author) |
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Tetzlaff, Tom / Kleinjohann, Alexander / Stella, Alessandra / Diesmann, Markus / Grün, Sonja | |
Contributing Institute: |
Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Imprint: |
2019
|
Conference: | INM/ICS Retreat 2019, Jülich (Germany), 2019-06-25 - 2019-06-26 |
Document Type: |
Poster |
Research Program: |
Helmholtz Analytics Framework Human Brain Project Specific Grant Agreement 2 GRK 2416: MultiSenses-MultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration Theory, modelling and simulation Connectivity and Activity |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
To investigate cortical network interactions during a reach-to-grasp task [1], we analyzed spatio-temporalpatterns (STPs) in massively parallel spike data. Using the SPADE analysis [2,3], we found 50 to 150 significant STPs in about 150 simultaneously recorded neurons during the movement period of the task. Out of the 150 observed neurons, only a small fraction contributes to the observed patterns: all STPs are composed of different subsets of the same 6 neurons. Here, we investigate if the characteristics of STPs asfound in the data can be explained by a simple assembly network model, the synfire chain (SFC) model [4].In the SFC model, neurons form groups connected in a feedforward, highly convergent-divergent manner. Synchronous stimulation of neurons in the first group results in volleys of spikes reliably propagatingthrough the chain [5]. Spike recordings from a subset of cells in this model would reveal recurring STPssimilar to those observed in the data, provided the same SFCs are repeatedly stimulated.We investigate if the observed STP statistics is consistent with a network model where SFCs are spatiallydistributed in accordance with biologically realistic connection probabilities. In the context of this model,we evaluate the probability of observing multiple neurons involved in the same STP by means of a 10x10Utah electrode array spanning 4x4mm2 of cortical space. We explore how model parameters such as theneuron density, the distance dependence of lateral connections between cortical neurons and the spatialreach of extracellular electrodes constrain the spatial arrangement of SFCs (see figure) and the number ofobservable SFC neurons. In future work, we will further investigate the temporal characteristics of STPs bystudying the dynamics of the SFC network model proposed here. |