脳の処理メカニズムから性格特性を導出するボトムアップフレームワークの提案：半球側性化・前頭前皮質—辺縁系グラデーションの二次元モデルと処理フェーズ階層

茶谷, 萌香

doi:10.51094/jxiv.3368

##article.authors##

茶谷, 萌香独立研究者 https://orcid.org/0009-0005-5423-9441

DOI:

https://doi.org/10.51094/jxiv.3368

キーワード:

半球側性化、前頭前皮質、辺縁系、デフォルトモードネットワーク、実行制御ネットワーク、処理フェーズ、モダリティ階層、個人差、性格神経科学、皮質階層、ボトムアップフレームワーク

抄録

個人の性格特性と脳構造の関連を探る既存の神経科学的アプローチは、再現可能な結果を示せていない。本稿はその根本原因を「脳領域と性格の対応表探索」というアプローチ自体にあると論じ、脳の処理メカニズムから性格特性を導出するボトムアップフレームワークを提案する。フレームワークは二つの個人差次元から構成される。第一に高次連合野における半球側性化（左右軸）：樹状突起長の非対称性に基づくAsymmetric Sampling in Time仮説。第二に前頭前皮質と辺縁系の前後グラデーション（前後軸）：Layer IVの顆粒性/無顆粒性の構造差。これら二軸の個人差はDMN（生成フェーズ）とECN（評価フェーズ）という普遍的な処理シーケンスの中で発現し、入出力モダリティが下層として側性化パターンを規定する。両軸は利き手性に類比的な発達的に安定したトレイトであり、本フレームワークは既存研究のメタ分析に向けた研究選別基準の提供を目的とする。

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