Properties and temporal dynamics of choice- and action-predictive signals during item recognition decisions

Long-Term and Meditation-Specific Modulations of Brain Connectivity Revealed Through Multivariate Pattern Analysis

Neuroimaging studies have provided evidence that extensive meditation practice modifies the functional and structural properties of the human brain, such as large-scale brain region interplay. However, it remains unclear how different meditation styles are involved in the modulation of these large-scale brain networks. Here, using machine learning and fMRI functional connectivity, we investigated how focused attention and open monitoring meditation styles impact large-scale brain networks. Specifically, we trained a classifier to predict the meditation style in two groups of subjects: expert Theravada Buddhist monks and novice meditators. We showed that the classifier was able to discriminate the meditation style only in the expert group. Additionally, by inspecting the trained classifier, we observed that the Anterior Salience and the Default Mode networks were relevant for the classification, in line with their theorized involvement in emotion and self-related regulation in meditation. Interestingly, results also highlighted the role of specific couplings between areas crucial for regulating attention and self-awareness as well as areas related to processing and integrating somatosensory information. Finally, we observed a larger involvement of left inter-hemispheric connections in the classification. In conclusion, our work supports the evidence that extensive meditation practice modulates large-scale brain networks, and that the different meditation styles differentially affect connections that subserve style-specific functions.

Alpha rhythm modulations in the intraparietal sulcus reflect decision signals during item recognition

Theoretical work and empirical observations suggest a contribution of regions along the intraparietal sulcus to the process of evidence accumulation during episodic memory retrieval. In the present study, we recorded magnetoencephalographic signals in a group of healthy human participants to test whether the pattern of oscillatory modulations in the lateral parietal lobe is consistent with the mnemonic accumulator hypothesis. To this aim, the dynamic properties and the spatial distribution of MEG oscillatory power modulations were investigated during an item recognition task in which the amount of evidence for old vs. new memory decisions was manipulated across three levels. A data-driven approach was employed to identify brain nodes where oscillatory activity was sensitive to both retrieval success and the amount of evidence for old decisions. The analysis identified three nodes in the left lateral parietal lobe where the event-related desynchronization (ERD) in the alpha frequency band showed both effects. Further analyses revealed that the alpha ERD in the intraparietal sulcus, but not in other parietal nodes: i. showed modulation of duration in response to the amount of evidence for both old and new decisions, ii. was behaviorally significant, and iii. more accurately tracked the subjective memory judgment rather than the objective memory status. The present findings provide support for a recent anatomical-functional model of the parietal involvement in episodic memory retrieval and suggest that the alpha ERD in the intraparietal sulcus might represent a neural signature of the evidence accumulation process during simple memory-based decisions.

Neuroplasticity within and between Functional Brain Networks in Mental Training Based on Long-Term Meditation

(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators. (3) The results show that fMRI connectivity patterns in multiple key brain networks can differentially predict the meditation expertise and age of long-term meditators. Expertise-predictive patterns are differently affected by FA and OM, while age-predictive patterns are not influenced by the meditation form. The FA meditation connectivity pattern modulated by expertise included nodes and connections implicated in focusing, sustaining and monitoring attention, while OM patterns included nodes associated with cognitive control and emotion regulation. (4) The study highlights a long-term effect of meditation practice on multivariate patterns of functional brain connectivity and suggests that meditation expertise is associated with specific neuroplastic changes in connectivity patterns within and between multiple brain networks.