Villa Alessandro E P
NeuroHeuristic Research Group, University of Lausanne, UNIL Chamberonne Internef 138.1, 1015 Lausanne, VD Switzerland.
Cogn Neurodyn. 2025 Dec;19(1):144. doi: 10.1007/s11571-025-10332-z. Epub 2025 Sep 5.
This paper introduces the concept of -a novel transdisciplinary paradigm designed to advance cognitive neurodynamics by integrating insights from molecular biology, computing, behavioral science, and clinical neuroscience. Contrasted with the traditional reductionist approach rooted in classical determinism, neuroheuristics emphasizes a flexible, problem-solving methodology for investigating brain function across multiple levels of complexity. The paper explores the epistemological interplay among genetic, epigenetic, and environmental factors in brain development and pathology. The neuroheuristic framework aims to elucidate complex cognitive phenomena-such as memory, decision-making, and creativity-by bridging bottom-up and top-down research strategies. By incorporating contemporary technologies and recognizing the brain's dynamic, nonlinear properties, neuroheuristics proposes a transformative shift in cognitive neurodynamics, enabling a deeper understanding of human cognition, disease mechanisms, and artificial intelligence. Its applicability is demonstrated through ongoing interdisciplinary research spanning neurophysiological disorders, computational modeling, and data-driven analytical techniques.
本文介绍了一种新型跨学科范式的概念，该范式旨在通过整合分子生物学、计算机科学、行为科学和临床神经科学的见解来推进认知神经动力学。与植根于经典决定论的传统还原论方法形成对比，神经启发式方法强调一种灵活的、解决问题的方法，用于在多个复杂层面研究大脑功能。本文探讨了大脑发育和病理学中遗传、表观遗传和环境因素之间的认识论相互作用。神经启发式框架旨在通过弥合自下而上和自上而下的研究策略来阐明复杂的认知现象，如记忆、决策和创造力。通过纳入当代技术并认识到大脑的动态、非线性特性，神经启发式方法在认知神经动力学方面提出了变革性转变，从而能够更深入地理解人类认知、疾病机制和人工智能。通过正在进行的跨学科研究，涵盖神经生理疾病、计算建模和数据驱动的分析技术，证明了其适用性。
