This Research Topic is part of the Methods in Frontiers in Human Neuroscience series.
This series aims to highlight the latest experimental techniques and methods used to investigate fundamental questions in Cognitive Neuroscience research, from methods in attentional research to Memory processes. Review articles or opinions on methodologies or applications including the advantages and limitations of each are welcome. This Topic includes technologies and up-to-date methods which help advance science.
The contributions to this collection will undergo peer review. Novelty may vary, but the utility of a method or protocol must be evident. We welcome contributions covering all aspects of the research methods used for the investigation of the Cognitive Neuroscience of dance and complex movement, but of particular interest are neuroaesthetics and the social, affective, and cognitive neuroscience aspects of this. Submissions will be handled by the team of Topic Editors in the respective sections.
This Research Topic welcomes:
• Empirical works: Empirical studies using new or existing methods. These manuscripts may include primary (original) data. We encourage qualitative as well as quantitative studies and investigations using ecologically valid designs.
• Methods and Protocols: Detailed descriptions of new methods and/or protocols or existing methods that are significantly improved or adapted for specific purposes. These papers should include pitfalls and troubleshooting to benefit those who may evaluate or employ these techniques. Protocols should be supported by sufficient evidence and can include primary (original) data.
• Perspective or General Commentaries on methods and protocols relevant to dance or movement research. We especially encourage multidisciplinary approaches to study dance and movement and how dance and movement can better help us understand the human mind and cognition.
• Reviews and mini reviews of topical methods and protocols highlighting the important future directions of the field.
#CollectionSeries
This Research Topic is part of the Methods in Frontiers in Human Neuroscience series.
This series aims to highlight the latest experimental techniques and methods used to investigate fundamental questions in Cognitive Neuroscience research, from methods in attentional research to Memory processes. Review articles or opinions on methodologies or applications including the advantages and limitations of each are welcome. This Topic includes technologies and up-to-date methods which help advance science.
The contributions to this collection will undergo peer review. Novelty may vary, but the utility of a method or protocol must be evident. We welcome contributions covering all aspects of the research methods used for the investigation of the Cognitive Neuroscience of dance and complex movement, but of particular interest are neuroaesthetics and the social, affective, and cognitive neuroscience aspects of this. Submissions will be handled by the team of Topic Editors in the respective sections.
This Research Topic welcomes:
• Empirical works: Empirical studies using new or existing methods. These manuscripts may include primary (original) data. We encourage qualitative as well as quantitative studies and investigations using ecologically valid designs.
• Methods and Protocols: Detailed descriptions of new methods and/or protocols or existing methods that are significantly improved or adapted for specific purposes. These papers should include pitfalls and troubleshooting to benefit those who may evaluate or employ these techniques. Protocols should be supported by sufficient evidence and can include primary (original) data.
• Perspective or General Commentaries on methods and protocols relevant to dance or movement research. We especially encourage multidisciplinary approaches to study dance and movement and how dance and movement can better help us understand the human mind and cognition.
• Reviews and mini reviews of topical methods and protocols highlighting the important future directions of the field.
#CollectionSeries
