Recent advances in brain imaging have improved the measure of neural processes related to perceptual, cognitive and affective functions, yet the relation between brain activity and subjective experience remains poorly characterized. In part, it is a challenge to obtain reliable accounts of participant’s experience in such studies. Here we addressed this limitation by utilizing experienced meditators who are expert in introspection. We tested a novel method to link objective and subjective data, using real-time fMRI (rt-fMRI) to provide participants with feedback of their own brain activity during an ongoing task. We provided real-time feedback during a focused attention task from the posterior cingulate cortex, a hub of the default mode network shown to be activated during mind-wandering and deactivated during meditation. In a first experiment, both meditators and non-meditators reported significant correspondence between the feedback graph and their subjective experience of focused attention and mind-wandering. When instructed to volitionally decrease the feedback graph, meditators, but not non-meditators, showed significant deactivation of the posterior cingulate cortex. We were able to replicate these results in a separate group of meditators using a novel step-wise rt-fMRI discovery protocol in which participants were not provided with prior knowledge of the expected relationship between their experience and the feedback graph (i.e., focused attention versus mind-wandering). These findings support the feasibility of using rt-fMRI to link objective measures of brain activity with reports of ongoing subjective experience in cognitive neuroscience research, and demonstrate the generalization of expertise in introspective awareness to novel contexts.

Key words: Real-time neurofeedback, Real-time fMRI, Focused attention, Posterior cingulate cortex, Default mode network, Meditation

In this paper we describe the development of a flexible and interactive learning environment for studying the Java programming language. The system has been written using Java and has been designed around an extended version of the CORE [1] design methodology. Earlier work using CORE resulted in hypertext based learning environments such as CLEM (CORE Learning Environment for Modula-2) [2]. The current work seeks to enhance and augment the features provided in the early work by offering additional representations of the topics under study, incorporating audio and video resources, and improving the flexibility of the possible learning paths through the learning materials.