Decoding Temporal Features of Birdsong Through Neural Activity Analysis

Version 1.1
Ahmadi, Amirmasoud; Robotka, Hermina; Gahr, Manfred; Theunissen, Frederic, 2025, "Decoding Temporal Features of Birdsong Through Neural Activity Analysis", https://doi.org/10.17617/3.AUMDAU, Edmond, V1
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Description

Overview

This repository contains every dataset, analysis output and visualisation that support the manuscript “Decoding Temporal Features of Birdsong Through Neural Activity Analysis” by Amirmasoud Ahmadi, Hermina Robotka, Manfred Gahr and Frederic Theunissen (2025). Neural activity was recorded in the auditory pallium of adult zebra finches while they listened to unfamiliar conspecific songs. All archives are provided as .mat, .csv or .avi files to maximise cross-platform usability.

1 · Decoding Results

  • LFP_Decoding_Results.zip: predictions of Events, Envelopes and Landmarks from local-field potentials.
  • MUAe_Decoding_Results.zip: identical analyses on multi-unit activity envelopes.
  • LFP + MUAe_Decoding_Results.zip: performance obtained when LFP and MUAe feature vectors are concatenated.

2 · Single-Unit Responses

Single_Unit_Response_To_Song_Playback.zip supplies spike trains and peri-stimulus time histograms for 423 well-isolated neurons, enabling cell-by-cell comparisons with the population-based decoders.

3 · SUMMARY TABLES (KEY DATASET)

Summary_Results_Table.zip compiles the headline decoding statistics in three clearly labelled folders:

  • LFP/
    • LFP_EventDetection.csv
    • LFP_Env.csv
    • LFP_EnvelopeLandmarks.csv
  • MUAe/
    • MUAe_EventDetection.csv
    • MUAe_Env.csv
    • MUAe_EnvelopeLandmarks.csv
  • Fusion (LFP_MUAe)/
    • Fusion_EventDetection.csv
    • Fusion_Env.csv
    • Fusion_EnvelopeLandmarks.csv

Each file reports overall accuracy, Cohen kappa, syllable-level and silent-period accuracies, together with full metadata (Birds_Name, Sex_Birds, Song_Number, Depth_Record, etc.). These metrics reproduce the numbers in Table 1 of the manuscript.

4 · Figure Source Data

Six archives (Figure2_Data.zip, Figure3_Data.zip, Figure4_Data.zip, Figure5_Data.zip, Figure6_Data.zip, Figure7_Data.zip) recreate every panel of the main figures. SupFig_Data.zip holds all supplementary figure data. Each archive contains MATLAB matrices and comma-separated tables.

5 · Supplementary Video

Figure4_3D_Video.zip contains an .avi file showing a rotating three-dimensional map of decoding accuracy across recording sites, corresponding to Figure 4 of the paper. Additional demonstration videos related to the study can be found on YouTube at www.youtube.com/@Amir_Channel_Sci.

6 · Code Availability

All scripts that generate the manuscript figures and the core routines used for neural-signal processing are openly available at https://github.com/amirmasoud92/ZF_Neural_Decoding.

Please cite both the manuscript and this dataset if you reuse any of these files.

Subject Biology; Physics; Mathematics; Computer Science, Systems and Electrical Engineering
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Figure2_Data.zip
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Figure3_Data.zip
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Figure4_Data.zip
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Figure_4_A_B_Video.zip
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Figure 4_Video Spatial Map of Decoding Results
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LFP + MUAe_Decoding_Results.zip
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Decoding Results based on LFP+MUAe Signals
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LFP_Decoding_Results.zip
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Decoding Results based on LFP Signals
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MUAe_Decoding_Results.zip
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Decoding Results based on MUAe Signals
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