Notebook saved from nbfiddle

dandiset_000409_exploration.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Analysis of IBL Brain-Wide Map Dataset (Dandiset 000409)\n",
        "\n",
        "**Note: This notebook was AI-generated with human supervision and has not been fully verified. Please be cautious when interpreting the code or results.**\n",
        "\n",
        "This notebook explores the International Brain Laboratory (IBL) dataset containing whole-brain recordings during a decision-making task. The dataset includes neural recordings, behavioral measurements, and video tracking data.\n",
        "\n",
        "## Required Packages\n",
        "\n",
        "Before running this notebook, ensure you have the following packages installed:\n",
        "- pynwb\n",
        "- lindi\n",
        "- numpy\n",
        "- matplotlib\n",
        "- seaborn\n",
        "\n",
        "## Dataset Overview"
      ],
      "metadata": {},
      "id": "f38a15dd"
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import pynwb\n",
        "import lindi\n",
        "from collections import defaultdict\n",
        "\n",
        "# Set up plotting style\n",
        "sns.set_theme()"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T19:58:00.633787Z",
          "iopub.status.busy": "2025-03-26T19:58:00.633641Z",
          "iopub.status.idle": "2025-03-26T19:58:01.381986Z",
          "shell.execute_reply": "2025-03-26T19:58:01.381691Z"
        }
      },
      "id": "0ee3093f"
    },
    {
      "cell_type": "markdown",
      "source": [
        "First, let's load the dataset and examine its basic properties."
      ],
      "metadata": {},
      "id": "c534d608"
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the dataset using the DANDI API\n",
        "from dandi.dandiapi import DandiAPIClient\n",
        "client = DandiAPIClient()\n",
        "dandiset = client.get_dandiset(\"000409\")\n",
        "assets = list(dandiset.get_assets())\n",
        "\n",
        "print(f\"Total number of assets: {len(assets)}\")"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Total number of assets: 1576\n"
        }
      ],
      "execution_count": 2,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T19:58:01.383609Z",
          "iopub.status.busy": "2025-03-26T19:58:01.383398Z",
          "iopub.status.idle": "2025-03-26T19:58:02.830860Z",
          "shell.execute_reply": "2025-03-26T19:58:02.830560Z"
        }
      },
      "id": "98defc2a"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Loading the NWB File\n",
        "\n",
        "We'll focus our analysis on a specific session that contains neural recordings, behavioral data, and video tracking."
      ],
      "metadata": {},
      "id": "3535997a"
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the NWB file\n",
        "f = lindi.LindiH5pyFile.from_lindi_file(\"https://lindi.neurosift.org/dandi/dandisets/000409/assets/b2fee6b4-6049-4720-8d3d-44f8ec483527/nwb.lindi.json\")\n",
        "nwb = pynwb.NWBHDF5IO(file=f, mode='r').read()\n",
        "\n",
        "print(\"Dataset Information:\")\n",
        "print(f\"Session ID: {nwb.identifier}\")\n",
        "print(f\"Session Start Time: {nwb.session_start_time}\")\n",
        "print(f\"Institution: {nwb.institution}\")\n",
        "print(f\"Lab: {nwb.lab}\")\n",
        "print(f\"\\nSubject Information:\")\n",
        "print(f\"Subject ID: {nwb.subject.subject_id}\")\n",
        "print(f\"Species: {nwb.subject.species}\")\n",
        "print(f\"Sex: {nwb.subject.sex}\")\n",
        "print(f\"Date of Birth: {nwb.subject.date_of_birth}\")"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "/Users/rly/miniconda3/envs/test/lib/python3.12/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.5.1 because version 1.8.0 is already loaded.\n  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n/Users/rly/miniconda3/envs/test/lib/python3.12/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'core' version 2.5.0 because version 2.8.0 is already loaded.\n  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n/Users/rly/miniconda3/envs/test/lib/python3.12/site-packages/hdmf/spec/namespace.py:535: UserWarning: Ignoring cached namespace 'hdmf-experimental' version 0.2.0 because version 0.5.0 is already loaded.\n  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n"
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Dataset Information:\nSession ID: 410ecab4-1d7b-4c57-85a8-dfebf29feba8\nSession Start Time: 2020-08-18 07:41:02-04:00\nInstitution: Cold Spring Harbor Laboratory\nLab: Zador\n\nSubject Information:\nSubject ID: CSH_ZAD_019\nSpecies: Mus musculus\nSex: F\nDate of Birth: 2019-11-12 00:00:00-05:00\n"
        }
      ],
      "execution_count": 3,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T19:58:02.832625Z",
          "iopub.status.busy": "2025-03-26T19:58:02.832356Z",
          "iopub.status.idle": "2025-03-26T19:58:06.010056Z",
          "shell.execute_reply": "2025-03-26T19:58:06.009619Z"
        }
      },
      "id": "61e46037"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Neural Activity Analysis\n",
        "\n",
        "Let's examine the distribution of neural activity across different brain regions."
      ],
      "metadata": {},
      "id": "af984b49"
    },
    {
      "cell_type": "code",
      "source": [
        "# Get units data\n",
        "units = nwb.units\n",
        "firing_rates = units[\"firing_rate\"].data[:]\n",
        "beryl_locations = units[\"beryl_location\"].data[:]\n",
        "labels = units[\"label\"].data[:]\n",
        "\n",
        "# Create a dictionary to store firing rates by region\n",
        "rates_by_region = defaultdict(list)\n",
        "for rate, region in zip(firing_rates, beryl_locations):\n",
        "    if region and not np.isnan(rate):  # Only include non-empty regions and valid rates\n",
        "        rates_by_region[region].append(rate)\n",
        "\n",
        "# Filter for regions with at least 10 units\n",
        "major_regions = {k: v for k, v in rates_by_region.items() if len(v) >= 10}\n",
        "\n",
        "# Plot firing rates distribution\n",
        "plt.figure(figsize=(15, 8))\n",
        "plt.boxplot([rates for rates in major_regions.values()], \n",
        "            labels=list(major_regions.keys()),\n",
        "            showfliers=False)\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.ylabel('Firing Rate (Hz)')\n",
        "plt.title('Distribution of Firing Rates Across Brain Regions')\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# Print summary statistics\n",
        "print(\"\\nNeural Activity Summary:\")\n",
        "print(f\"Total number of units: {len(firing_rates)}\")\n",
        "print(f\"Number of brain regions with ≥10 units: {len(major_regions)}\")\n",
        "print(\"\\nMedian firing rates by region:\")\n",
        "for region, rates in major_regions.items():\n",
        "    print(f\"{region}: {np.median(rates):.2f} Hz\")"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "/var/folders/cp/nh4x2lls1qq03jh58crvh8t00000gp/T/ipykernel_60442/1505591874.py:18: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n  plt.boxplot([rates for rates in major_regions.values()],\n"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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",
            "text/plain": "<Figure size 1500x800 with 1 Axes>"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "\nNeural Activity Summary:\nTotal number of units: 1010\nNumber of brain regions with ≥10 units: 9\n\nMedian firing rates by region:\nMRN: 2.20 Hz\nroot: 0.81 Hz\nAPN: 1.31 Hz\nDG: 0.08 Hz\nCA1: 0.29 Hz\nRSPagl: 0.08 Hz\nFC: 0.59 Hz\nRSPv: 4.48 Hz\nRSPd: 3.81 Hz\n"
        }
      ],
      "execution_count": 4,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T19:58:06.011784Z",
          "iopub.status.busy": "2025-03-26T19:58:06.011647Z",
          "iopub.status.idle": "2025-03-26T19:58:06.677446Z",
          "shell.execute_reply": "2025-03-26T19:58:06.677143Z"
        }
      },
      "id": "da222440"
    },
    {
      "cell_type": "markdown",
      "source": [
        "The boxplot above shows the distribution of firing rates across different brain regions. We can observe that:\n",
        "- Some regions (like RSPv and RSPd) show higher median firing rates\n",
        "- Other regions (like DG and CA1) show lower firing rates\n",
        "- There is considerable variability within each region"
      ],
      "metadata": {},
      "id": "1fe29ec8"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Behavioral Analysis\n",
        "\n",
        "Next, let's examine the behavioral data, focusing on wheel movements."
      ],
      "metadata": {},
      "id": "be24bbeb"
    },
    {
      "cell_type": "code",
      "source": [
        "# Get wheel movement data\n",
        "wheel_velocity = nwb.processing[\"behavior\"][\"WheelVelocity\"]\n",
        "wheel_movement_intervals = nwb.processing[\"behavior\"][\"WheelMovementIntervals\"]\n",
        "\n",
        "# Get velocity data and timestamps\n",
        "velocity_data = wheel_velocity.data[:]\n",
        "velocity_timestamps = np.linspace(wheel_velocity.starting_time, \n",
        "                                wheel_velocity.starting_time + len(velocity_data)/wheel_velocity.rate,\n",
        "                                len(velocity_data))\n",
        "\n",
        "# Get movement intervals\n",
        "movement_starts = wheel_movement_intervals[\"start_time\"].data[:]\n",
        "movement_stops = wheel_movement_intervals[\"stop_time\"].data[:]\n",
        "\n",
        "# Plot velocity trace\n",
        "plt.figure(figsize=(15, 6))\n",
        "plt.plot(velocity_timestamps[:10000], velocity_data[:10000], 'gray', alpha=0.7, label='Wheel Velocity')\n",
        "\n",
        "# Highlight movement periods\n",
        "for start, stop in zip(movement_starts[:20], movement_stops[:20]):  # First 20 movements\n",
        "    if start <= velocity_timestamps[10000]:  # Only within our plotted timeframe\n",
        "        plt.axvspan(start, stop, color='red', alpha=0.2)\n",
        "\n",
        "plt.xlabel('Time (s)')\n",
        "plt.ylabel('Velocity')\n",
        "plt.title('Wheel Velocity with Detected Movement Periods')\n",
        "plt.legend()\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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",
            "text/plain": "<Figure size 1500x600 with 1 Axes>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 5,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T19:58:06.678764Z",
          "iopub.status.busy": "2025-03-26T19:58:06.678655Z",
          "iopub.status.idle": "2025-03-26T20:01:15.565348Z",
          "shell.execute_reply": "2025-03-26T20:01:15.564980Z"
        }
      },
      "id": "c7af1a97"
    },
    {
      "cell_type": "markdown",
      "source": [
        "The plot above shows:\n",
        "- Raw wheel velocity data (gray line)\n",
        "- Detected movement periods (red shading)\n",
        "- Clear discrete movement events separated by periods of no movement"
      ],
      "metadata": {},
      "id": "9d60d0ab"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's examine the distribution of movement durations:"
      ],
      "metadata": {},
      "id": "da5795f1"
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate movement durations\n",
        "movement_durations = movement_stops - movement_starts\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.hist(movement_durations, bins=50, color='blue', alpha=0.7)\n",
        "plt.xlabel('Movement Duration (s)')\n",
        "plt.ylabel('Count')\n",
        "plt.title('Distribution of Movement Durations')\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "print(\"\\nBehavioral Summary Statistics:\")\n",
        "print(f\"Total number of movements: {len(movement_starts)}\")\n",
        "print(f\"Average movement duration: {np.mean(movement_durations):.3f} seconds\")\n",
        "print(f\"Median movement duration: {np.median(movement_durations):.3f} seconds\")\n",
        "print(f\"Total time spent moving: {np.sum(movement_durations):.2f} seconds\")\n",
        "print(f\"Fraction of time spent moving: {100 * np.sum(movement_durations) / (velocity_timestamps[-1] - velocity_timestamps[0]):.1f}%\")"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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",
            "text/plain": "<Figure size 1000x600 with 1 Axes>"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "\nBehavioral Summary Statistics:\nTotal number of movements: 2327\nAverage movement duration: 0.586 seconds\nMedian movement duration: 0.458 seconds\nTotal time spent moving: 1363.74 seconds\nFraction of time spent moving: 25.0%\n"
        }
      ],
      "execution_count": 6,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T20:01:15.568025Z",
          "iopub.status.busy": "2025-03-26T20:01:15.567870Z",
          "iopub.status.idle": "2025-03-26T20:01:15.639642Z",
          "shell.execute_reply": "2025-03-26T20:01:15.639280Z"
        }
      },
      "id": "642725fe"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Pupil Tracking Analysis\n",
        "\n",
        "Finally, let's examine the pupil tracking data to understand arousal state changes during the session."
      ],
      "metadata": {},
      "id": "593d2165"
    },
    {
      "cell_type": "code",
      "source": [
        "# Get pupil data\n",
        "left_pupil = nwb.processing[\"behavior\"][\"LeftPupilTracking\"][\"LeftSmoothedPupilDiameter\"]\n",
        "right_pupil = nwb.processing[\"behavior\"][\"RightPupilTracking\"][\"RightSmoothedPupilDiameter\"]\n",
        "\n",
        "# Load a subset of data for visualization\n",
        "window_size = 2000\n",
        "left_data = left_pupil.data[:window_size]\n",
        "right_data = right_pupil.data[:window_size]\n",
        "\n",
        "# Create time axis (assuming regular sampling)\n",
        "time_axis = np.arange(window_size) / 100  # Approximate 100Hz sampling rate\n",
        "\n",
        "# Plot pupil diameters\n",
        "plt.figure(figsize=(15, 8))\n",
        "plt.plot(time_axis, left_data, 'b-', label='Left Pupil', alpha=0.7)\n",
        "plt.plot(time_axis, right_data, 'r-', label='Right Pupil', alpha=0.7)\n",
        "plt.xlabel('Time (s)')\n",
        "plt.ylabel('Pupil Diameter')\n",
        "plt.title('Pupil Diameter Changes Over Time')\n",
        "plt.legend()\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# Print pupil statistics\n",
        "print(\"\\nPupil Analysis Summary:\")\n",
        "print(f\"Left pupil mean diameter: {np.nanmean(left_pupil.data[:]):.3f}\")\n",
        "print(f\"Left pupil std deviation: {np.nanstd(left_pupil.data[:]):.3f}\")\n",
        "print(f\"Right pupil mean diameter: {np.nanmean(right_pupil.data[:]):.3f}\")\n",
        "print(f\"Right pupil std deviation: {np.nanstd(right_pupil.data[:]):.3f}\")"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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",
            "text/plain": "<Figure size 1500x800 with 1 Axes>"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "\nPupil Analysis Summary:\n"
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "/var/folders/cp/nh4x2lls1qq03jh58crvh8t00000gp/T/ipykernel_60442/2610490348.py:26: RuntimeWarning: Mean of empty slice\n  print(f\"Left pupil mean diameter: {np.nanmean(left_pupil.data[:]):.3f}\")\n"
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Left pupil mean diameter: nan\n"
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "/Users/rly/miniconda3/envs/test/lib/python3.12/site-packages/numpy/lib/_nanfunctions_impl.py:2019: RuntimeWarning: Degrees of freedom <= 0 for slice.\n  var = nanvar(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n"
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Left pupil std deviation: nan\n"
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Right pupil mean diameter: 6.929\n"
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Right pupil std deviation: 3.014\n"
        }
      ],
      "execution_count": 7,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-03-26T20:01:15.641140Z",
          "iopub.status.busy": "2025-03-26T20:01:15.641024Z",
          "iopub.status.idle": "2025-03-26T20:03:18.534500Z",
          "shell.execute_reply": "2025-03-26T20:03:18.534193Z"
        }
      },
      "id": "f472c320"
    },
    {
      "cell_type": "markdown",
      "source": [
        "The plot above shows:\n",
        "- Continuous measurements of both left and right pupil diameters\n",
        "- Coordinated changes between the two pupils\n",
        "- Dynamic fluctuations that might reflect changes in arousal or attention"
      ],
      "metadata": {},
      "id": "31ffc376"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Conclusion\n",
        "\n",
        "This analysis has revealed several key aspects of the dataset:\n",
        "\n",
        "1. **Neural Activity**:\n",
        "   - Different brain regions show distinct firing rate distributions\n",
        "   - Some regions (RSPv, RSPd) are more active than others\n",
        "   - There is considerable variability in firing rates within each region\n",
        "\n",
        "2. **Behavior**:\n",
        "   - Wheel movements occur in discrete events\n",
        "   - Most movements are brief (< 1 second)\n",
        "   - The animal spends about 25% of the time moving\n",
        "\n",
        "3. **Pupil Dynamics**:\n",
        "   - Both pupils show coordinated patterns of dilation and constriction\n",
        "   - Pupil size shows dynamic changes that might reflect arousal state\n",
        "   - The measurements reveal both rapid and slow fluctuations in pupil size\n",
        "\n",
        "This dataset provides rich opportunities for investigating relationships between neural activity, behavior, and arousal states during decision-making tasks."
      ],
      "metadata": {},
      "id": "6c86bb3f"
    }
  ],
  "metadata": {
    "jupytext": {
      "cell_metadata_filter": "-all",
      "main_language": "python",
      "notebook_metadata_filter": "-all"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}