Abstract
The human lateral prefrontal cortex (LPFC) enables flexible goal-directed behavior. Yet, its organizing principles remain actively debated despite decades of research. Meta-analysis efforts to map the LPFC have either been restricted in scope or suffered from limited expressivity in meta-analysis tools. The latter short-coming hinders the complexity of questions that can be expressed in a meta-analysis and hence limits the specificity of structure-function associations. Here, we adopt NeuroLang, a novel approach to meta-analysis based on first-order probabilistic logic programming, to infer the organizing principles of the LPFC with greater specificity from 14,371 neuroimaging publications. Our results reveal a rostrocaudal and a dorsoventral gradient, respectively explaining the most and second-most variance in whole-brain meta-analytic connectivity in the LPFC. Moreover, we find a cross-study agreement on a spectrum of increasing abstraction from caudal to rostral LPFC both in specific network connectivity and structure-function associations that supports a domain-general role for the mid-LPFC. Furthermore, meta-analyzing inter-hemispheric asymmetries along the rostrocaudal gradient reveals specific associations with topics of language, memory, response inhibition, and error processing. Overall, we provide a comprehensive mapping of the organizing principles of task-dependent activity in the LPFC, grounding future hypothesis generation on a quantitative overview of past findings.
Competing Interest Statement
The authors have declared no competing interest.
