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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Simultaneous recordings from thousands of neurons allow studying functional cell assemblies.
  • Determining synaptic connectivity patterns underlying these assemblies is challenging.

Purpose of the Study:

  • To develop a simulation-based approach using a large-scale cortical network model to study functional cell assemblies.
  • To investigate how synaptic connectivity structure influences assembly composition and activation.

Main Methods:

  • Detected functional cell assemblies from stimulus-evoked spiking activity of 186,665 neurons using a detailed cortical network model.
  • Quantified the effects of thalamic innervation, recurrent connectivity, and dendritic synapse arrangement on assembly composition.

Main Results:

  • Synaptic connectivity features reduced uncertainty in neuron assembly membership by up to 30%.
  • Assemblies were activated in stimulus-specific sequences and grouped by temporal order.
  • Connectivity's predictive power increased with temporal alignment, population interconnectedness, and dendritic clustering.

Conclusions:

  • Synaptic connectivity patterns, not just amount but also local structure, are crucial for assembly emergence.
  • Reversed Hebb's postulate: cells wired together fire together, with connectivity shaping assembly dynamics.
  • Subcellular and network-level connectivity details influence functional cell assembly formation.