ABSTRACT

In the 2010s, significant progress has been made in several key areas of laterality research, including neuroimaging, genetics and comparative research. In the present article, we discuss which trends are likely to shape laterality research in the 2020s. These include, but are not limited to: (1) Finding laterality-specific solutions to the replication crisis. (2) Integrating non-W.E.I.R.D. (Western, Educated, Industrialized, Rich, and Democratic) samples into laterality research to a larger extent. (3). Combining meta-analysis and large-scale databank studies to come to unbiased conclusions about true effects. (4) Understanding altered laterality in different psychiatric and neurodevelopmental disorders. (5) Exploring the relevance of laterality research for the treatment of psychiatric and neurodevelopmental disorders. (6) Investigating the molecular correlates of environmental factors that affect laterality. (7) Bridging the gap between laterality research in human subjects and non-human model species. (8) Utilizing “next-generation” neuroimaging in laterality research. (9) Integrating graph-theory and machine learning into laterality research. (10) Enhancing ecological validity in laterality research using mobile EEG and smartphone-based data collection. These trends will likely shape the next decade of laterality research by opening the way for novel questions, enhancing collaborations and boosting the reliability and validity of research findings in our field.

摘要

2010 年代，偏侧性研究的几个关键领域取得了重大进展，包括神经影像学、遗传学和比较研究。在本文中，我们将讨论哪些趋势可能会影响 2020 年代的偏侧性研究。这些包括但不限于： (1) 寻找针对复制危机的特定侧向性解决方案。(2) 将非WEIRD（西方的、受过教育的、工业化的、富有的、民主的）样本更大程度地整合到偏侧性研究中。(3). 结合荟萃分析和大规模数据库研究，得出关于真实效果的公正结论。(4) 了解不同精神和神经发育障碍的偏侧性改变。(5) 探索偏侧性研究与治疗精神和神经发育障碍的相关性。(6) 调查影响偏侧性的环境因素的分子相关性。(7) 弥合人类受试者和非人类模型物种的偏侧性研究之间的差距。(8) 在偏侧研究中利用“下一代”神经影像学。(9) 将图论和机器学习整合到偏侧性研究中。(10) 使用移动脑电图和基于智能手机的数据收集提高侧向研究的生态有效性。这些趋势可能会通过为新问题开辟道路、加强合作和提高我们领域研究结果的可靠性和有效性来塑造未来十年的侧向性研究。(8) 在偏侧性研究中利用“下一代”神经影像学。(9) 将图论和机器学习整合到偏侧性研究中。(10) 使用移动脑电图和基于智能手机的数据收集提高侧向研究的生态有效性。这些趋势可能会通过为新问题开辟道路、加强合作和提高我们领域研究结果的可靠性和有效性来塑造未来十年的侧向性研究。(8) 在偏侧研究中利用“下一代”神经影像学。(9) 将图论和机器学习整合到偏侧性研究中。(10) 使用移动脑电图和基于智能手机的数据收集提高侧向研究的生态有效性。这些趋势可能会通过为新问题开辟道路、加强合作和提高我们领域研究结果的可靠性和有效性来塑造未来十年的侧向性研究。