Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients
Study Design & Technical Specifications
Sample Size / Cohort
34 Patients
Subject / Study Model
CNS Experimental / Clinical Model
Analytical Modalities
Primary Abstract & Repository Description
Source: DANDI ArchiveEditorial Critique, Methodological Value & Reusability Guide
1. Scientific Context & Translational Bottlenecks
This resource from DANDI Archive ("Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients") addresses critical scientific questions within Parkinson's Disease (PD). Research in this domain currently faces major translational bottlenecks, including quantifying prodromal alpha-synuclein pathology, dopaminergic nigrostriatal circuit vulnerability, and non-motor progression heterogeneity. By focusing on key thematic elements (DBS, Local Field Potential, Beta Oscillations, Subthalamic Nucleus, NWB), this work contributes empirical evidence toward understanding how molecular, cellular, or systems-level alterations relate to core disease pathways such as α-synuclein seed amplification assays (SAA), LRRK2/GBA1 variants, DAT-SPECT, and digital motor kinematics. Integrating these findings into the broader open science ecosystem helps reduce fragmentation across independent laboratories and accelerates hypothesis verification.
日本語解説を表示 (Japanese)
DANDI Archiveより公開された本リソース（「Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients」）は、パーキンソン病（PD）領域における重要な学術的・臨床的課題に焦点を当てています。現在のパーキンソン病（PD）研究では、前駆期におけるα-シヌクレイン病理の定量化、黒質線条体ドパミン神経回路の選択的脆弱性、および非運動症状を含む進行速度の多様性解明といったトランスレーショナルリサーチ上のボトルネックが存在します。本リソースは関連キーワード（DBS, Local Field Potential, Beta Oscillations, Subthalamic Nucleus, NWB）を軸として、α-シヌクレイン凝集増幅法（SAA）、LRRK2/GBA1遺伝子変異、DAT-SPECT画像、およびデジタル運動計測指標などの主要経路や病態メカニズムの理解に資する知見・データを提供しており、研究室や機関ごとに分散しがちな知見をオープンサイエンス基盤上で統合・検証する上で重要な位置づけを持ちます。
2. Methodology & Data Architecture Value
Structured as an open scientific dataset, this repository leverages Electrophysiology (LFP), Kinematics across CNS Experimental / Clinical Model (34 Patients). Its primary architectural value lies in providing standardized, machine-readable primary records via DANDI Archive under CC-BY 4.0. Unlike isolated summary tables in static publications, access to underlying Electrophysiology (LFP), Kinematics distributions enables independent inspection of signal-to-noise ratios, preprocessing parameter sensitivity, and cross-modality feature extraction.
日本語解説を表示 (Japanese)
本リソースは公開科学データセットとして、神経科学実験・臨床モデル（サンプル規模: 34 Patients）における「Electrophysiology (LFP), Kinematics」データを収録しています。DANDI Archiveを通じてライセンス（CC-BY 4.0）のもとで構造化データが提供されている点が最大の強みです。論文内の静的な要約統計量のみならず、生データや処理済み特徴量の分布に直接アクセスできるため、信号雑音比（S/N比）の検証、前処理パイプラインの感度分析、およびマルチモーダル特徴量抽出において高い学術的価値を発揮します。
3. Secondary Analysis & Reusability Scenarios
Researchers and computational neuroscientists can reuse this resource across multiple secondary workflows: (1) Cross-Cohort Harmonization & Meta-Analysis — combining these Electrophysiology (LFP), Kinematics records with complementary repositories (such as OpenNeuro, DANDI, Agora, or Europe PMC) to increase statistical power; (2) Computational Benchmarking & Machine Learning — utilizing the documented features (DBS, Local Field Potential, Beta Oscillations, Subthalamic Nucleus, NWB) as training, validation, or out-of-distribution test sets for predictive biomarker discovery in Parkinson's Disease (PD); and (3) Experimental Protocol Alignment — referencing the study design (CNS Experimental / Clinical Model, 34 Patients) to calibrate sample size calculations (power analysis) and endpoint selection for upcoming preclinical or clinical studies.
日本語解説を表示 (Japanese)
本リソースは以下のような二次解析・再利用シナリオに幅広く活用可能です。(1) コホート横断的ハーモナイゼー��ョンとメタ解析：本リソースの「Electrophysiology (LFP), Kinematics」データを他の公開リポジトリ（OpenNeuro、DANDI、Agora、ADNI等）の同種データと統合し、統計的検出力（Statistical Power）を高めた統合解析を実施する。(2) 機械学習・バイオマーカー予測モデルの検証：抽出された特徴量や関連因子（DBS, Local Field Potential, Beta Oscillations, Subthalamic Nucleus, NWB）を、パーキンソン病（PD）の進行予測・サブタイプ分類モデルの外部検証（External Validation）や転移学習データとして利用する。(3) 後続研究のプロトコル設計：対象モデル（神経科学実験・臨床モデル）およびサンプル規模（34 Patients）の設計仕様を参照し、新規の非臨床試験や臨床研究におけるサンプルサイズ設計（検出力計算）や主要評価項目の妥当性検討に役立てる。
4. Methodological Limitations & Caveats
While curated from an authoritative scientific source, secondary analysts should account for potential cohort selection biases and site-specific batch effects. Specifically, when interpreting Electrophysiology (LFP), Kinematics results in Parkinson's Disease (PD), researchers must control for confounding variables (such as age, sex, post-mortem interval, scanner/instrument drift, or medication state) and verify compliance with open-access attribution requirements (CC-BY 4.0).
日本語解説を表示 (Japanese)
信頼性の高い学術情報源から収録されていますが、二次解析や他研究との比較を行う際には、コホート選択バイアスや測定施設間差（バッチエフェクト）に留意する必要があります。特にパーキンソン病（PD）における「Electrophysiology (LFP), Kinematics」データの解釈では、年齢・性別・罹病期間・測定機器のキャリブレーション差・併用薬などの交絡因子を適切に補正することが推奨されます。また、データや図表の二次利用時は提供元（DANDI Archive）の利用条件（CC-BY 4.0）および適切な引用表記を遵守してください。
Data Access, Reproducibility & Analysis Starter Guide
NWB (Neurodata Without Borders) v2.x
Quick Data Access & Structured Export
Open the primary repository directly or download structured metadata (JSON / CSV) in one click.
This cellular neurophysiology resource utilizes the Neurodata Without Borders (NWB) standard, encapsulating intracellular/extracellular voltage traces, spike times, stimulus waveforms, and optical imaging ROI fluorescence inside self-describing HDF5/Zarr containers.
Programmatic Data Retrieval (Python Starter Code & Recommended SDKs)
Python Quickstart: Stream & Analyze NWB Electrophysiology Data
# 1. Install DANDI & PyNWB toolkit
# pip install dandi pynwb remfile h5py
from dandi.dandiapi import DandiAPIClient
import pynwb
import remfile
import h5py
# Connect to DANDI Archive and locate Dandiset 000026
with DandiAPIClient() as client:
dandiset = client.get_dandiset("000026", "draft")
assets = list(dandiset.get_assets())
nwb_asset = next(a for a in assets if a.path.endswith(".nwb"))
s3_url = nwb_asset.get_content_url(follow_redirects=1, strip_query=True)
# Stream NWB metadata & spike/voltage series directly over HTTP
byte_stream = remfile.File(s3_url)
with h5py.File(byte_stream, "r") as h5_file:
with pynwb.NWBHDF5IO(file=h5_file, load_namespaces=True) as io:
nwbfile = io.read()
print("Session Description:", nwbfile.session_description)
print("Acquisition Series:", list(nwbfile.acquisition.keys()))Recommended Open-Source Software & SDKs
Standardized 4-Step Workflow & Governance Checklist
Standardized Acquisition & Preprocessing Workflow
1. Stream or Download Dandiset via DANDI CLI / fsspec
Inspect NWB file hierarchies remotely via HTTP range requests (remfile/fsspec) before downloading multi-gigabyte recordings.
2. Extract Acquisition & Stimulus TimeSeries via PyNWB
Load ElectricalSeries or PatchClampSeries objects and align timestamps against behavioral or optogenetic stimulus epochs.
3. Electrophysiological Feature Quantification (IPFX / SpikeInterface)
Compute resting membrane potential, input resistance, action potential half-width, and firing rate adaptation.
4. Cross-Modal Transcriptomic / Morphological Alignment
For Patch-seq or multimodal dandi sets, link cell specimen IDs with transcriptomic cell-type taxonomies.
Reproducibility & Governance Checklist
- Cite both the DANDI Archive Dandiset DOI and original study authors in secondary publications.
- Verify sampling rate (Hz) and conversion/gain factors on ElectricalSeries before spectral analysis.
- Pin pynwb and hdmf package versions to guarantee deterministic HDF5 schema deserialization.
Tags & Modalities
Bibliometrics, Peer-Review Status & Citation Export
Cross-referenced via Semantic Scholar, Europe PMC & bioRxiv
1. Citation Metrics & Context Breakdown
Citation Context Breakdown
2. Peer-Review Validation & Revision History
Verified Publication / Open Dataset Record
Metadata and license integrity verified against primary repository records.
3. Standardized Academic Citation & BibTeX Export
Starr PA et al. (2026). Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients. DANDI Archive. https://doi.org/10.48324/dandi.000026/0.201021.1832
@misc{pa2026dand,
title = {Dandiset 000026: Subthalamic Nucleus Local Field Potentials (LFP) and Beta-Band Dynamics in Parkinson’s Patients},
author = {Starr PA and de Hemptinne C and Movement Disorders Neuroengineering Lab},
year = {2026},
journal = {DANDI Archive},
howpublished = {\url{https://doi.org/10.48324/dandi.000026/0.201021.1832}},
doi = {10.48324/dandi.000026/0.201021.1832},
note = {CNS Open Data: parkinson}
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Academic Research & Medical Information Disclaimer
This page provides structured scientific metadata, methodological critiques, and open-data reusability guidelines intended strictly for neuroscience researchers and data scientists. It does not constitute medical advice, clinical diagnosis, or treatment recommendations.
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