Meditation is a family of mental practices that encompasses a wide array of techniques employing distinctive mental strategies. We systematically reviewed 78 functional neuroimaging (fMRI and PET) studies of meditation, and used activation likelihood estimation to meta-analyze 257 peak foci from 31 experiments involving 527 participants. We found reliably dissociable patterns of brain activation and deactivation for four common styles of meditation (focused attention, mantra recitation, open monitoring, and compassion/loving-kindness), and suggestive differences for three others (visualization, sense-withdrawal, and non-dual awareness practices). Overall, dissociable activation patterns are congruent with the psychological and behavioral aims of each practice. Some brain areas are recruited consistently across multiple techniques-including insula, pre/supplementary motor cortices, dorsal anterior cingulate cortex, and frontopolar cortex-but convergence is the exception rather than the rule. A preliminary effect-size meta-analysis found medium effects for both activations (d=0.59) and deactivations (d=-0.74), suggesting potential practical significance. Our meta-analysis supports the neurophysiological dissociability of meditation practices, but also raises many methodological concerns and suggests avenues for future research.
Neurofeedback relying on functional magnetic resonance imaging (fMRI-nf) heralds new prospects for self-regulating brain and behavior. Here we provide the first comprehensive review of the fMRI-nf literature and the first systematic database of fMRI-nf findings. We synthesize information from 99 fMRI-nf experiments-the bulk of currently available data. The vast majority of fMRI-nf findings suggest that self-regulation of specific brain signatures seems viable; however, replication of concomitant behavioral outcomes remains sparse. To disentangle placebo influences and establish the specific effects of neurofeedback, we highlight the need for double-blind placebo-controlled studies alongside rigorous and standardized statistical analyses. Before fMRI-nf can join the clinical armamentarium, research must first confirm the sustainability, transferability, and feasibility of fMRI-nf in patients as well as in healthy individuals. Whereas modulating specific brain activity promises to mold cognition, emotion, thought, and action, reducing complex mental health issues to circumscribed brain regions may represent a tenuous goal. We can certainly change brain activity with fMRI-nf. However, it remains unclear whether such changes translate into meaningful behavioral improvements in the clinical domain.
Neurofeedback, one of the primary examples of self-regulation, designates a collection of techniques that train the brain and help to improve its function. Since coming on the scene in the 1960s, electroencephalography-neurofeedback has become a treatment vehicle for a host of mental disorders; however, its clinical effectiveness remains controversial. Modern imaging technologies of the living human brain (e.g., real-time functional magnetic resonance imaging) and increasingly rigorous research protocols that utilize such methodologies begin to shed light on the underlying mechanisms that may facilitate more effective clinical applications. In this paper we focus on recent technological advances in the field of human brain imaging and discuss how these modern methods may influence the field of neurofeedback. Toward this end, we outline the state of the evidence and sketch out future directions to further explore the potential merits of this contentious therapeutic prospect.
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