Spatial Richness of Neural Magnetic Fields: Computational Modeling Dataset

A 1.1 GB dataset from figshare supports research into brain implants that measure neural magnetic fields. Computational modeling illustrates how dense neuron networks are easier to distinguish via magnetic spike templates. The dataset, authored by Ziad Ali and last updated in April 2026, is shared under a CC-BY-4.0 license.

Use Cases

• Comparing informational content of neural magnetic fields and electrical potentials based on the described mathematical formalism.
• Developing spike-sorting algorithms for dense neuron networks based on magnetic spike templates.
• Approximating neuronal morphological reconstruction using sparse sensor arrays based on the solenoidal nature of magnetic fields.
• Modeling the distance-scaling characteristics of extracellular magnetic fields generated by spiking neurons.

Strengths

• Dataset size is explicitly 1.1 GB, indicating substantial content.
• License is clearly defined as CC-BY-4.0, permitting broad reuse with attribution.
• Last update date is provided as 2026-04-21, suggesting recent maintenance.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Likely generated through computational modeling as described in the summary.

Freshness

Last updated 2026-04-21 01:05:16; freshness should be verified.