A 4-day Study of Neurofeedback Training of Cognitive Control in Healthy Adults
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 40
- 主要终点
- Neurofeedback learning
研究概览
简要总结
This project will examine whether individuals can be trained, using real-time feedback about brain function during neuroimaging, to effectively remove thoughts from mind by providing them with a sense of what it feels like to successfully remove a thought.
详细描述
On the first day, an anatomical MRI scan will be followed by a 12-min resting state scan, a 30-min item localizer task in which participants view a set of 80 scene stimuli 3 times each, and a 10-min memory test outside the scanner. The brain data from the localizer will be used to identify baseline measures of item-specific brain activity patterns. On 3 subsequent days (within the next 2 weeks), participants will receive neurofeedback training. In each 1-hr session, an anatomical scan will be followed by 8 runs (5 min each) of 20 trials, half with each operation, randomly ordered, and a 10-min behavioral memory test. In the scanner, participants will perform a working memory task in which they encode a scene image and then are instructed to either maintain that image in mind for a few seconds or to suppress that image from mind. At the end of each trial, neurofeedback will be provided to the participant visually to denote their "level of engagement" in the instructed operation on that trial. The neurofeedback is derived from the MRI classifier fit for the instructed operation (maintain or suppress) from a working memory operation classifier that is pre-trained on prior data. Participants (N=40) will be randomly assigned to either the positive or negative valence condition. They will encounter stimuli from their assigned valence only during the neuroimaging task, but from both valences during the behavioral tests, so that the investigators can evaluate whether any learning generalizes across emotional valence.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 40 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Right-handed
- •Speak English fluently
- •Minimum 8th grade education
- •Good hearing
- •Good vision or minimal correction with contacts or eyeglasses
排除标准
- •History of significant illnesses (including cardiovascular disease, cancer, immunodeficiency disorders (including HIV infection)
- •Unstable endocrine disorders
- •Neurological disorders
- •Neuromuscular disorders
- •Blood dyscrasias
- •History of major psychiatric disorders (including schizophrenia, bipolar disorder, and dementia)
- •Substance dependence
- •History of head trauma with loss of consciousness
- •Cerebrovascular accident
- •Neurosurgical intervention
- •Metal implants in the body (including pacemakers, neurostimulators, or other metal objects)
- •Metal piercings that cannot be removed for the scan
- •Women who are pregnant or who think they may be pregnant
结局指标
主要结局
Neurofeedback learning
时间窗: Within 2 weeks after the first day of the experiment, 3 neurofeedback training sessions lasting about 1 hour will occur at least 24 hours apart. The outcome measure will be computed at the end of all 3 sessions.
Visual fMRI neurofeedback (e.g., the diameter of a circle) will be provided to the participant at the end of each trial denoting the "level of engagement" in the instructed operation on that trial. The neurofeedback score is derived from the fMRI pattern classifier using regularized logistic regression for the instructed operation from a pre-trained working memory operation classifier. Scores range from 0 to 1, with higher scores indicating better fits to the target pattern of activity. The investigators will quantify neurofeedback learning by computing changes in feedback scores within each session and across the sessions.
Neural consequences of control
时间窗: Within 2 weeks after the first day of the experiment, 3 neurofeedback training sessions lasting about 1 hour will occur at least 24 hours apart. The outcome measure will be computed across all trials in each run, and for each of the 3 sessions.
Proactive interference for the encoding of trial N, separately following maintain trials and suppress trials, will be assessed using within-subject item-specific activity pattern matching between the localizer data and the main task data. Proactive interference would be reflected in a reduced correspondence (lower scores) between the localizer representation for an item and the representation of that item when it is encoded on trial N. Higher scores would reflect a release from proactive interference.
Behavioral consequences of control
时间窗: This outcome measure will be collected at the end of the first day of the experiment and at the end of each of the 3 subsequent neurofeedback sessions occurring at least 24 hours apart within the next 2 weeks.
After each session, participants will be evaluated with behavioral memory tests on both positive and negative information. Two pictures (of the same valence) are presented for memorization on each trial, an instruction is given to manipulate the memory of one of those images, then a probe image appears and participants are to respond, as quickly and accurately as then can, YES if that probe image was one of the images presented at the beginning of the trial (even if the participant was asked to suppress that image) or NO otherwise. Half the probes contain new images. The accuracies and response times for this memory test will be statistically analyzed. The investigators will compare differences in these measures across condition (maintain vs. suppress) and cue type (manipulated vs. non-manipulated item). For the 3 neurofeedback sessions, the investigators will also relate a participant's neurofeedback scores with their behavioral performance on this memory test.
次要结局
- Training transfer across valence(Within 2 weeks after the first day of the experiment, 3 neurofeedback training sessions lasting about 1 hour will occur at least 24 hours apart. This outcome measure will be collected at the end of each of the 3 sessions.)
研究者
Jarrod Lewis-Peacock
Associate Professor
University of Texas at Austin