Neural correlates of attentional expertise in long-term meditation practitioners

Abstract

Meditation refers to a family of mental training practices that are designed to familiarize the practitioner with specific types of mental processes. One of the most basic forms of meditation is concentration meditation, in which sustained attention is focused on an object such as a small visual stimulus or the breath. In age-matched participants, using functional MRI, we found that activation in a network of brain regions typically involved in sustained attention showed an inverted u-shaped curve in which expert meditators (EMs) with an average of 19,000 h of practice had more activation than novices, but EMs with an average of 44,000 h had less activation. In response to distracter sounds used to probe the meditation, EMs vs. novices had less brain activation in regions related to discursive thoughts and emotions and more activation in regions related to response inhibition and attention. Correlation with hours of practice suggests possible plasticity in these mechanisms.

Fig. 1.

Meditation block data. Activation in concentration meditation block (Med.) vs. resting state block (Rest) for 12 EMs (A), 12 age-matched NMs (B), and t test subtraction of EMs (C) (red hues reflect greater activation in EMs vs. NMs) vs. regular NMs (blue hues reflect greater activation in NMs vs. EMs). Alpha maps ranging from P < 0.001 (orange, positive activation; medium blue, negative activation) to P < 0.01 (orange/medium blue) to P < 0.05, corrected (red, positive activation; dark blue, negative activation) are overlaid on inflated population-average, landmark- and surface-based atlas cortical model brains and an axial slice at z = 11 to show midbrain regions. ‡, smaller than corrected for multiple comparisons. (D) Activation in attention-shifting metaanalysis ROIs. Color scale is the same for all panels (see key). (E) Response over time (seconds) for left DLPFC. Start of the meditation block is indicated by an orange line at 80 sec. Standard error bars are shown for every 10 sec. (F) Bar graphs for amplitude of activation in DLPFC in the “early” part of the meditation block (the first 10 sec, excluding the first 2 sec because of hemodynamic delay) and the “late” part of the meditation block (120 sec to 200 sec).

Fig. 2.

Expertise-related differences in response to distractor sounds. (A) State (all sounds in Med. vs. Rest) by group (EM vs. INM) ANOVA results (left) showing cluster in P. Cing that is more active for the INMs. (B) Voxel-wise regression of sounds in Med. with hours of practice in the EMs showing negative (blue) correlation and positive (orange) correlation (P < 0.02 uncorrected). (C) Example of negative correlation in right P. Cing. (D) State by group ANOVA for negative sounds showing small focus of greater activation in Amyg in INMs vs. EMs. (E) Voxel-wise regression of response to negative sounds in Med. with hours in EMs showing bilateral Amyg (P < 0.02 uncorrected). (F) Correlation within EMs in right Amyg ROI. One outlier (orange) was not included in correlation.