Predicting Future Errors During Skill Performance
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 40
- 试验地点
- 1
- 主要终点
- To detect future skill errors up to approximately 1 s before they occur
研究概览
简要总结
Background:
Many tasks people do every day require a series of individual movements. Control over these movements is called motor skills. But even highly skilled people can make mistakes. Researchers have found that they can predict when a person will make a mistake 0.1 second before it happens. Now, they want to find out if they can increase that time up to 1 second-long enough to warn the person and prevent the mistake.
Objective:
To see if motor skill errors can be detected up to 1 second before they occur.
Eligibility:
Right-handed healthy adults aged 18 to 35.
Design:
Participants will have 2 to 5 study visits. Each visit will be 1 to 2 hours.
They will have a physical and neurological exam.
They will have 1 or 2 magnetic resonance imaging (MRI) scans. They will lie on a table that slides into a large cylinder. The MRI uses strong magnets to capture images of the inside of the body, including the brain.
They will have another scan, called magnetoencephalography (MEG). Small metal disks attached to wires will be taped to their head. Participants will sit in a padded chair with their head inside of a helmet. The helmet will not cover their eyes or face. Participants will perform a series of typing tasks on a keyboard. They will have short breaks between each round. Their head movements will be tracked, and their eye and finger movements will be videotaped.
详细描述
Study Description:
Human motor skills are composed of sequences of individual actions performed with utmost precision. However, even highly skilled human behavior is susceptible to errors. When these errors occur, they may have serious consequences, for example, when pilots are manually landing a plane or when surgeons control robotic devices during surgery. In such cases, the ability to predict and prevent these upcoming errors from occurring would clearly be advantageous. We recently utilized a withinindividual machine learning strategy to characterize brain activity predictive of future motor skill performance errors, in a manner consistent with accepted practices in the field. Implementation of this novel approach combining brain oscillatory activity (particularly in the low frequency delta range) and behavior (keypress transition times, KTT) in our previous work showed that we can predict up to 70% of single future erroneous keypress actions within 0.1s before they occur. One limitation of this work is that 0.1s preceding errors does not give enough time for subjects to stop an upcoming erroneous action. This protocol aims to characterize using this within-individual machine learning approach, already demonstrated to be effective in our own lab, to predict future erroneous actions up to approximately 1s before they occur. We intend to eventually develop a warning signal that allows subjects to stop upcoming skill errors. This development would allow communication to rapidly inform subjects to stop potential future errors. To this effect, we will record neural magnetoencephalography (MEG) activity while human participants perform sequences of motor actions.
Objectives:
The primary objective is to detect future skill errors up to approximately 1s before they occur. To predict these future errors, we will evaluate how brain activity and behavioral features preceding an error differ from those preceding correct sequence keypresses. We will also explore the feasibility of providing a feedback signal to participants when brain activity encodes future errors in real-time. Secondarily, we will evaluate spatial and temporal features of neural representations and replay and their relationship with erroneous and correct sequences.
Endpoints:
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 35 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •INCLUSION CRITERIA:
- •In order to be eligible to participate in this study, an individual must meet all of the following criteria:
- •Stated willingness to comply with all study procedures and availability for the duration of the study
- •Male or female, aged 18-35
- •In good general health as evidenced by medical history and normal neurological examination as determined by the screening clinician
- •English speaking
- •Right-handedness as reported by participant
- •Ability of subject to understand and the willingness to sign a written informed consent document
排除标准
- •An individual who meets any of the following criteria will be excluded from participation in this study:
- •HCPS-affiliated NIH staff (i.e. - staff from our section)
- •Current pregnancy
- •Contraindications for MRI, or MEG
- •Severe or progressive neurological, psychological or medical condition as determined by the medical history review or physical and neurological exam.
研究组 & 干预措施
Healthy
Healthy young volunteers
结局指标
主要结局
To detect future skill errors up to approximately 1 s before they occur
时间窗: 60 months
We measure prediction performance by contrasting predicted probability of future errors against their behavioral performance. To predict future errors, we will evaluate how brain activity preceding an error differs from the preceding correct sequence keypresses. We will also explore the feasibility of providing feedback signal to the participant when brain activity encodes future errors in real-time.
次要结局
- We will evaluate preparatory neural activity features for upcoming skill actions, correct and erroneous keypresses, during skill learning as well as neural replay associated with both correct and erroneous keypresses and skill performance.(60 months)