人間の脳皮質のマルチモダル分割
Matthew F Glasser1, Timothy S Coalson1, Emma C Robinson2,3
1Department of Neuroscience, Washington University Medical School, Saint Louis, Missouri 63110, USA.
Nature
|July 21, 2016
まとめ
研究者は高度な神経画像を用いて 半球ごとに180の異なる皮質領域を特定することで 人間の脳皮質をマッピングしました 新しい機械学習ツールは これらの領域を正確に特定し 将来の脳研究を支援します
科学分野:
- 神経科学
- 神経解剖学
- 脳のマッピング
背景:
- 人間の脳皮質を 異なる領域に分割することは 脳の機能を理解するために 極めて重要です
- 脳皮質領域の定義は 神経科学の長年の課題でした
研究 の 目的:
- 詳細で客観的な脳皮質の地図を作る
- これらの領域の自動識別のための機械学習分類器を開発する.
主な方法:
- ヒューマン・コネクトーム・プロジェクト (HCP) の マルチモダル磁気共鳴画像データを活用した.
- 半球ごとに180の皮質の領域を定義する 客観的,半自動的な神経解剖学的アプローチを採用した.
- 地域特有の"指紋"を認識するために,マルチモダルのデータで機械学習分類器を訓練しました.
主要な成果:
- 210人の健康な成人のグループ平均で 半球あたり180の皮質領域を成功裏に描いた.
- 97の新しい地域が特定され,以前報告された83の地域が確認されました.
- 機械学習による分類は 96.6%の精度で 新しい被験者の皮質領域を検出し グループ分割を複製しました
結論:
- 開発されたパーセラーションと分類器は,人間の脳皮質を研究するための神経解剖学的精度を高めています.
- これらのツールは 脳の組織,個々の変異,発達,老化,病気に関する研究を容易にするでしょう
- 自由に利用できるリソースは ニューロサイエンスの科学的な応用と進歩を可能にします
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