Interparticipant consistency of languageprocessing networks during abstract thoughts Abstract   Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we expand this assumption by showing that an extremely openended, highlevel cognitive task of thinking about an abstract content, loosely defined as xe2x80x9cabstract thinkingxe2x80x9d  leads to highly consistent activation maps. Specifically, we show that activation maps generated during such cognitive process were precisely located relative to borders of wellknown networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at u003e95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found remarkably consistent activation maps across individuals engaged in abstract thinking. This activation bordered, but strictly avoided visual and motor networks. On the other hand, it overlapped with left lateralized language networks. Activation of the default mode network (DMN) during abstract thought was similar to DMN activation during rest. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature  abstract thinking activates surprisingly precise and consistent networks in participantsu0027 brains.

Metacontrol of human creativity: The neurocognitive mechanisms of convergent and divergent thinking Abstract   Creativity is a complex construct that would benefit from a more comprehensive mechanistic approach. Two processes have been defined to be central to creative cognition: divergent and convergent thinking. These two processes are most often studied using the Alternate Uses Test (heavily relying on divergent thinking), and the Remote Associates Test (heavily relying on convergent thinking, at least with analytical solutions). Although creative acts should be regarded compound processes, most behavioral and neuroimaging studies ignore the composition of basic operations relevant for the task they investigate. In order to provide leverage for a more mechanistic, and eventually even comprehensive computational, approach to creative cognition, we compare findings from divergent and convergent thinking studies and review the similarities and differences between the two underlying types of processes, from a neurocognitive perspective with a strong focus on cortical structures. In this narrative review, we discuss a broad scope of neural correlates of divergent and convergent thinking. We provide a first step towards theoretical integration, by suggesting that creative cognition in divergent and convergentthinking heavy tasks is modulated by metacontrol states, where divergent thinking and insight solutions in convergentthinking tasks seem to benefit from metacontrol biases towards flexibility, whereas convergent, analytical thinking seems to benefit from metacontrol biases towards persistence. These particular biases seem to be reflected by specific cortical brainactivation patterns, involving left frontal and right temporalparietal networks. Our tentative framework could serve as a first proxy to guide neuroscientific creativity research into assessing more mechanistic details of human creative cognition.