Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA 02130, United States; Boston Attention & Learning Laboratory, VA Boston Healthcare System, Boston, MA 02130, United States; Geriatric Research, Education, & Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, United States; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, United States.
Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA 02130, United States; Boston Attention & Learning Laboratory, VA Boston Healthcare System, Boston, MA 02130, United States; Geriatric Research, Education, & Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, United States; Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, United States.
Neuroimage. 2018 May 1;171:148-164. doi: 10.1016/j.neuroimage.2018.01.002. Epub 2018 Jan 4.
Novel paradigms have allowed for more precise measurements of sustained attention ability and fluctuations in sustained attention over time, as well as the neural basis of fluctuations and lapses in performance. However, in recent years, concerns have arisen over the replicability of neuroimaging studies and psychology more broadly, particularly given the typically small sample sizes. One recently developed paradigm, the gradual-onset continuous performance task (gradCPT) has been validated behaviorally in large samples of participants. Yet neuroimaging studies investigating the neural basis of performance on this task have only been collected in small samples. The present study completed both a robust replication of the original neuroimaging findings and extended previous results from the gradCPT task using a large sample of 140 Veteran participants. Results replicate findings that fluctuations in attentional stability are tracked over time by BOLD activity in task positive (e.g., dorsal and ventral attention networks) and task negative (e.g., default network) regions. Extending prior results, we relate this coupling between attentional stability and on-going brain activity to overall sustained attention ability and demonstrate that this coupling strength, along with across-network coupling, could be used to predict individual differences in performance. Additionally, the results extend previous findings by demonstrating that temporal dynamics across the default and dorsal attention networks are associated with lapse-likelihood on subsequent trials. This study demonstrates the reliability of the gradCPT, and underscores the utility of this paradigm in understanding attentional fluctuations, as well as individual variation and deficits in sustained attention.
新的范式使得对持续注意力能力的更精确测量以及随着时间的推移注意力的波动,以及性能波动和失误的神经基础成为可能。然而,近年来,人们对神经影像学研究乃至更广泛的心理学的可重复性产生了担忧,特别是考虑到通常的小样本量。最近开发的一种范式,即渐增式连续绩效任务(gradCPT)已经在大量参与者中得到了行为验证。然而,关于该任务表现的神经基础的神经影像学研究仅在小样本中进行了收集。本研究使用 140 名退伍军人的大样本完成了对原始神经影像学发现的稳健复制,并扩展了 gradCPT 任务的先前结果。研究结果复制了以下发现:随着时间的推移,任务正性(例如,背侧和腹侧注意网络)和任务负性(例如,默认网络)区域的 BOLD 活动跟踪注意力稳定性的波动。扩展先前的结果,我们将注意力稳定性和正在进行的大脑活动之间的这种耦合与整体持续注意力能力联系起来,并证明这种耦合强度以及跨网络的耦合可以用于预测表现的个体差异。此外,结果通过证明默认网络和背侧注意网络之间的时间动态与后续试验中的失误可能性相关,扩展了先前的发现。本研究证明了 gradCPT 的可靠性,并强调了该范式在理解注意力波动以及个体差异和持续注意力缺陷方面的效用。