Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space
Johanna Senk, Espen Hagen, Sacha J. van Albada, Markus Diesmann

TL;DR
This study extends a local cortical network model to a larger area, demonstrating that it preserves key spiking and LFP features, including weak spike correlations and spatially coherent LFP signals, aligning with experimental data.
Contribution
The paper introduces a scalable 4x4 mm² cortical network model that maintains realistic spiking and LFP properties, bridging the gap between small-scale models and large-area neural recordings.
Findings
Upscaling preserves original spiking statistics.
Weak pairwise spike-train correlations match experimental data.
LFP signals show strong spatial coherence with distance.
Abstract
Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The interpretation of the recorded data calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Multi-layer spiking neuron network models of local cortical circuits covering about 1 mm have been developed, integrating experimentally obtained neuron-type-specific connectivity data and reproducing features of observed in-vivo spiking statistics. Local field potentials (LFPs) can be computed from the simulated spiking activity. We here extend a local network and LFP model to an area of 4x4 mm, preserving the neuron density and introducing distance-dependent connection probabilities and conduction delays. We find…
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Taxonomy
TopicsNeural dynamics and brain function · Neuroscience and Neural Engineering · stochastic dynamics and bifurcation
