Data Sheet 1: Pulvinar Pathways as Skip Connections in Vision Models

A PDF data sheet describes a computational neuroscience study investigating pulvinar-inspired long-range skip connections in convolutional vision models. The author is Narmin Zarinabadi, and the file was last updated on May 14, 2026. The dataset is 539.6 KB in size and is licensed under CC-BY-4.0.

Use Cases

• Benchmarking biologically inspired skip connections based on the described pulvinar-like pathway.
• Studying gain control mechanisms in neural networks based on the described gating mechanism.
• Analyzing model decision criteria under uncertainty based on the near-threshold detection task results.
• Investigating the relationship between representational geometry and task performance based on the matched representational regimes experiment.

Strengths

• The description provides a detailed account of the experimental methodology and results.
• The dataset is openly licensed under CC-BY-4.0 for reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is a 539.6 KB PDF, which is a very small and limited data artifact.

Provenance

Source

figshare

Collection Method

The data sheet describes a computational experiment evaluating a pulvinar-inspired architecture.

Freshness

Last updated 2026-05-14 04:25:06; freshness should be verified.