Increased Gray-Matter Volume in the Right Angular and Posterior Parahippocampal Gyri in Loving-Kindness Meditators

Laboratory of Neuropsychology, The University of Hong Kong, Room 610, Knowles Building, Pokfulam Road, Hong Kong, China. .
Social Cognitive and Affective Neuroscience (Impact Factor: 7.37). 07/2012; 8(1). DOI: 10.1093/scan/nss076
Source: PubMed


Previous voxel-based morphometry (VBM) studies have revealed that meditation is associated with structural brain changes in regions underlying cognitive processes that are required for attention or mindfulness during meditation. This VBM study examined brain changes related to the practice of an emotion-oriented meditation: loving-kindness meditation (LKM). A 3 T magnetic resonance imaging (MRI) scanner captured images of the brain structures of 25 men, 10 of whom had practiced LKM in the Theravada tradition for at least 5 years. Compared with novices, more gray matter volume was detected in the right angular and posterior parahippocampal gyri in LKM experts. The right angular gyrus has not been previously reported to have structural differences associated with meditation, and its specific role in mind and cognitive empathy theory suggests the uniqueness of this finding for LKM practice. These regions are important for affective regulation associated with empathic response, anxiety and mood. At the same time, gray matter volume in the left temporal lobe in the LKM experts appeared to be greater, an observation that has also been reported in previous MRI meditation studies on meditation styles other than LKM. Overall, the findings of our study suggest that experience in LKM may influence brain structures associated with affective regulation.

21 Reads
  • Source
    • "In a further quantitative meta-analysis, Spreng and colleagues demonstrated a strong overlap of the autobiographical brain network and the DMN, particularly in the PHG (Spreng et al., 2009). Interestingly, increased gray matter volume in the parahippocampal gyri was found in meditators (Leung et al., 2013), whereas the cortex was thinner in this area in late life depressive patients who did not respond to psychotherapy (Mackin et al., 2012). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. Compared to healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. © The Author (2015). Published by Oxford University Press. For Permissions, please email:
    Social Cognitive and Affective Neuroscience 01/2015; 10(8). DOI:10.1093/scan/nsu158 · 7.37 Impact Factor
  • Source
    • "Effects were considered to be significant when the volume of a cluster was greater than the minimum cluster size on whole brain GMV (determined using the Monte Carlo simulation; 1032 mm 3 ), in which case the probability of a type I error was less than 0.01. Generally, AlphaSim has been widely used in previous VBM studies (DeYoung et al., 2010; Fink et al., 2013; Kong et al., 2013; Leung et al., 2013; W. Li et al., 2014; Schwartz et al., 2010). Previous studies have shown that personality is an important predictor of social well-being (Hill et al., 2012; Joshanloo et al., 2012; Wilt et al., 2010). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Social well-being reflects the appraisal of one's circumstance and functioning in society, which is crucial for individuals’ mental and physical health. However, little is known about the neural processes associated with social well-being. In this study, we used voxel-based morphometry (VBM) to identify the brain regions underlying individual differences in social well-being, as measured by the Social Well-being Scale (SWBS), in a large sample of young healthy adults. We found that social well-being was negatively correlated with gray matter volume in left mid-dorsolateral prefrontal cortex (mid-DLPFC) that is implicated in executive functioning, emotional regulation and social reasoning. The results remained significant even after controlling for the effect of socioeconomic status. Furthermore, although basic personality factors such as neuroticism, extraversion, and conscientiousness (as measured by the NEO Personality Inventory) all contributed to social well-being, only extraversion acted as a mediational mechanism underlying the association between the left mid-DLPFC volume and social well-being. Together, our findings provide the first evidence for the structural basis of individual differences in social well-being, and suggest that the personality trait of extraversion might play an important role in the acquisition and process of social well-being.
    NeuroImage 11/2014; DOI:10.1016/j.neuroimage.2014.10.062 · 6.36 Impact Factor
  • Source
    • "That is, if the spontaneous neural activity in an individual's thalamus was weakly correlated with those of other DMN nodes, the individual was more mindful. Previous neuroimaging studies on mindfulness have identified multiple regions of the DMN, including the PCC, MPFC, LPC, LTC, PHG, and thalamus, that are involved in mindfulness (Holzel et al., 2008; Luders et al., 2009; Brewer et al., 2011; Dickenson et al., 2013; Leung et al., 2013; Shaurya Prakash et al., 2013). Our study extends these findings by providing the first empirical evidence of how these DMN regions work collaboratively at the network level where the thalamus is the relevant node for trait mindfulness. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Mindfulness is typically defined as nonjudgmental awareness of experiences in the present moment, which is beneficial for mental and physical well-being. Previous studies have identified multiple regions in the default mode network (DMN) that are involved in mindfulness, but little is known about how these regions work collaboratively as a network. Here, we used resting-state functional magnetic resonance imaging to investigate the role of the DMN in trait mindfulness by correlating spontaneous functional connectivity among DMN nodes with self-reported trait mindfulness in a large population of young adults. Among all pairs of the DMN nodes, we found that individuals with weaker functional connectivity between the thalamus and posterior cingulate cortex (PCC) were more mindful of the present. Post-hoc analyses of these two nodes further revealed that graph-based nodal properties of the thalamus, not the PCC, were negatively correlated with trait mindfulness, suggesting that a low involvement of the thalamus in the DMN is relevant for high trait mindfulness. Our findings not only suggest the thalamus as a switch between mind-wandering and mindfulness, but also invite future studies on mechanisms of how mindfulness produces beneficial effects by modulating the thalamus.
    Neuroscience 08/2014; 278(1). DOI:10.1016/j.neuroscience.2014.08.006 · 3.36 Impact Factor
Show more

Preview (2 Sources)

21 Reads
Available from