Oculomotor Indexes for Perturbation and Occlusion Windows

Sergio Delle Monache published oculomotor indexes for perturbation and occlusion windows on figshare in June 2026. The dataset likely contains tabular data from Pictorial and Neutral Scenario blocks, denoted by PS and NS columns. It includes metrics such as post saccadic error (PSE), saccadic τ (SACCTAU), SPEM τ (SPEMTAU), and SPEM gain (SPEMGAIN).

Use Cases

• Analyzing post-saccadic error (PSE) to quantify oculomotor accuracy.
• Comparing saccadic τ (SACCTAU) and SPEM τ (SPEMTAU) between Pictorial and Neutral Scenario blocks.
• Investigating SPEM gain (SPEMGAIN) as a measure of smooth pursuit performance.
• Studying differences between Oculomotor Task and Oculo-Manual Task conditions.
• Evaluating oculomotor responses to perturbation and occlusion windows.

Strengths

• Data is clearly structured with columns denoting Pictorial (PS) and Neutral Scenario (NS) blocks.
• Task column uses defined values (0 and 1) for Oculomotor Task and Oculo-Manual Task.
• Key oculomotor metrics (PSE, SACCTAU, SPEMTAU, SPEMGAIN) are explicitly named.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (97.2 KB), indicating a limited scope.

Provenance

Source

figshare

Freshness

Last updated 2026-06-03 18:00:03; freshness should be verified.