Analyze_RAThc3

This repository analyzes rat hippocampal recordings from the HC-3 dataset (Buzsáki lab), focusing on identifying place cells and quantifying spatial tuning during linear track navigation. It includes preprocessing, multiple statistical methods for place cell detection, and group-level analyses across four rats.

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Dataset Overview

• Source: Buzsáki lab – CRCNS HC-3 open dataset

• Subjects: ec012, ec013, ec014, ec016

• Experiment Type: Linear track recordings

• Modalities:

  • Spike times: .res.N
  • Waveforms: .spk.N
  • Position tracking: .whl

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Core Analysis Notebooks

• 00-PlaceCells.ipynb — Identify place cells using spatial information and ANOVA
• 01-Estimated__Method.ipynb — Evaluate detection method performance and thresholds
• 02-ExampleNeurons.ipynb — Visualize and summarize example neuron responses
• PREPROCESS_POSITION.ipynb — Preprocess behavioral position data from .whl files
• REPORT_SESSION.ipynb — Generate session-level summaries
• REPORT_UNIT.ipynb — Analyze and visualize unit-level spatial tuning

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Place Cell Detection Methods Compared

We implemented and compared the following detection strategies:

• Spatial Information (SI) Thresholding
• Spatial Information Permutation Test
• ANOVA Permutation Test

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Group-Level & Statistical Figure Notebooks

• Figure_RAT_GROUP.ipynb — Group-level summary statistics across rats
• Figure_RAT_PCA.ipynb — Principal component analysis of unit tuning features
• Figure_RAT_STATS_DISTRIBUTION.ipynb — Visualize distributions of key statistical metrics (SI, F-values, etc.)