Mouse Neural and Behavioral Data for Value-Dependent Memory Consolidation, 2026

1.9 GB of processed neural and behavioral data from head-fixed mice navigating virtual environments. The dataset, authored by Geonung Youn in 2026, was used to examine how learned reward probability modulates ripple-associated reactivation across hippocampal and prefrontal circuits. It includes spike timing, ripple events, licking, and spatial position variables recorded with Neuropixels probes.

Use Cases

• Analyzing value-dependent reactivation patterns based on ripple event timestamps and reward probabilities.
• Modeling the relationship between spatial navigation and neural population activity based on spike timing and position data.
• Investigating hippocampal-prefrontal circuit coordination during memory consolidation based on simultaneous mPFC and iCA1 recordings.
• Correlating behavioral variables like licking events with neural metrics for reactivation analyses.

Strengths

• Data size is 1.9 GB, indicating a substantial volume of processed neural recordings.
• Includes simultaneous recordings from two brain regions (medial prefrontal cortex and intermediate CA1) using Neuropixels probes.
• Covers three distinct reward probability conditions (0.2, 0.4, and 0.8) for behavioral analysis.
• Released under a permissive CC-BY-4.0 license for broad reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

Geonung Youn and Min Whan Jung, via figshare.

Collection Method

Recorded from head-fixed mice navigating linear virtual environments using Neuropixels probes (versions 1.0 or 2.0).

Time Range

2026

Freshness

Last updated 2026-05-08 14:09:07; freshness should be verified.

Geography

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