Predicting brain activation maps for arbitrary tasks with cognitive encoding models.
Predicting brain activation maps for arbitrary tasks with cognitive encoding models.
复制标题
DOI：
10.1016/j.neuroimage.2022.119610
复制
发表时间：
2022-11
期刊：
影响因子：
5.7
通讯作者：
Poldrack, Russell A.
中科院分区：
文献类型：
--
作者：
Walters, Jonathon;King, Maedbh;Bissett, Patrick G.;Ivry, Richard B.;Diedrichsen, Jorn;Poldrack, Russell A.
对心理功能的神经结构有了深入的了解，就可以准确地预测任何心理任务的特定大脑活动模式，而这仅仅是基于已知的与该任务有关的认知功能。编码模型（EM），其从已知特征（例如，刺激特性），已经在限定的域（例如，视觉神经科学），但是实现预测任意任务的全脑活动的领域通用EM主要受到以下数据集的可用性的限制：1）充分跨越心理功能的大空间，以及2）用这样的功能充分注释以允许鲁棒的EM规范。我们研究使用EM的基础上正式规范的心理功能，预测皮质激活模式在广泛的任务。我们使用了多领域任务组合，这是一个数据集，其中24名受试者完成了32次10分钟的功能磁共振成像扫描，每35秒切换一次任务，并参与了44种不同心理操作的总条件。条件由一组专家使用认知图谱本体进行注释，以确定pupelis参与的功能，并针对个体受试者，对新皮层反应进行区域认知EM（CEMs）拟合。我们发现，CEMs预测皮质激活地图的高准确性，优于基于置换的空模型，同时接近数据的噪声上限，而不是仅仅由认知或感知运动功能驱动。CEM概括错误的相似性结构的层次聚类揭示了心理功能之间的关系。特征重要性的空间分布系统地与大规模的静息态功能网络（RSN）重叠，支持RSN内功能专业化的假设，同时以可解释的数据驱动的方式将其功能接地。我们的实施和验证的CEMS提供了一个证明的原则，在认知神经科学中的正式本体的效用，并激励使用CEMS在认知理论的进一步测试。
A deep understanding of the neural architecture of mental function should enable the accurate prediction of a specific pattern of brain activity for any psychological task, based only on the cognitive functions known to be engaged by that task. Encoding models (EMs), which predict neural responses from known features (e.g., stimulus properties), have succeeded in circumscribed domains (e.g., visual neuroscience), but implementing domain-general EMs that predict brain-wide activity for arbitrary tasks has been limited mainly by availability of datasets that 1) sufficiently span a large space of psychological functions, and 2) are sufficiently annotated with such functions to allow robust EM specification. We examine the use of EMs based on a formal specification of psychological function, to predict cortical activation patterns across a broad range of tasks. We utilized the Multi-Domain Task Battery, a dataset in which 24 subjects completed 32 ten-minute fMRI scans, switching tasks every 35 s and engaging in 44 total conditions of diverse psychological manipulations. Conditions were annotated by a group of experts using the Cognitive Atlas ontology to identify putatively engaged functions, and region-wise cognitive EMs (CEMs) were fit, for individual subjects, on neocortical responses. We found that CEMs predicted cortical activation maps of held-out tasks with high accuracy, outperforming a permutation-based null model while approaching the noise ceiling of the data, without being driven solely by either cognitive or perceptual-motor features. Hierarchical clustering on the similarity structure of CEM generalization errors revealed relationships amongst psychological functions. Spatial distributions of feature importances systematically overlapped with large-scale resting-state functional networks (RSNs), supporting the hypothesis of functional specialization within RSNs while grounding their function in an interpretable data-driven manner. Our implementation and validation of CEMs provides a proof of principle for the utility of formal ontologies in cognitive neuroscience and motivates the use of CEMs in the further testing of cognitive theories.
登录
查看更多内容
影响因子：
5.7
作者：
Jenkinson, M;Bannister, P;Smith, S
通讯作者：
Smith, S
影响因子：
3.5
作者：
Gorgolewski K;Burns CD;Madison C;Clark D;Halchenko YO;Waskom ML;Ghosh SS
通讯作者：
Ghosh SS
影响因子：
25
作者：
King M;Hernandez-Castillo CR;Poldrack RA;Ivry RB;Diedrichsen J
通讯作者：
Diedrichsen J
影响因子：
3.5
作者：
Abraham A;Pedregosa F;Eickenberg M;Gervais P;Mueller A;Kossaifi J;Gramfort A;Thirion B;Varoquaux G
通讯作者：
Varoquaux G
影响因子：
16.6
作者：
Eisenberg, Ian W.;Bissett, Patrick G.;Poldrack, Russell A.
通讯作者：
Poldrack, Russell A.