Biology subjects

Sanjuan, A.

Publications and source records attributed to Sanjuan, A..

4 recordsLinked to original sources

bioRxiv2023

The meditative brain: State and trait changes in harmonic complexity for long-term mindfulness meditators

Meditation is an ancient practice that is shown to yield benefits for cognition, emotion regulation and human flourishing. In the last two decades, there has been a surge of interest in extracting the neural correlates of meditation, in particular of mindfulness meditation. Yet, these efforts have been mostly limited to the analysis of certain regions or networks of interest and a clear understanding of meditation-induced changes in the whole-brain dynamics has been lacking. Here, we investigate meditation-induced changes in brain dynamics using a novel connectome-specific harmonic decomposition method. Specifically, utilising the connectome harmonics as brain states - elementary building blocks of complex brain dynamics - we study the immediate (state) and long-term (trait) effects of mindfulness meditation in terms of the energy, power and complexity of the repertoire of these harmonic brain states. Our results reveal increased power, energy and complexity of the connectome harmonic repertoire and demonstrate that meditation alters brain dynamics in a frequency selective manner. Remarkably, the frequency-specific alterations observed in meditation are reversed in resting state in group-wise comparison revealing for the first time the long-term (trait) changes induced by meditation. These findings also provide evidence for the entropic brain hypothesis in meditation and provide a novel understanding of state and trait changes in brain dynamics induced by mindfulness meditation revealing the unique connectome harmonic signatures of the meditative brain.

neuroscience↗

bioRxiv2021

Increased sensitivity to strong perturbations in a whole-brain model of LSD

Lysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brains global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders. HighlightsO_LINovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD) C_LIO_LIShift of brains global working point to more complex dynamics after LSD intake C_LIO_LIConsistently longer recovery time after model perturbation under LSD influence C_LIO_LIStrongest effects in resting state networks relevant for psychedelic experience C_LIO_LIHigher response diversity across brain regions under LSD influence after an external in silico perturbation C_LI

neuroscience↗

bioRxiv2019

Characterizing the dynamical complexity underlying meditation

Over the past 2,500 years, contemplative traditions have explored the nature of the mind using meditation. More recently, neuroimaging research on meditation has revealed differences in brain function and structure in meditators. Nevertheless, the underlying neural mechanisms are still unclear. In order to understand how meditation shapes global activity through the brain, we investigated the spatiotemporal dynamics across the whole-brain functional network using the Intrinsic Ignition Framework. Recent neuroimaging studies have demonstrated that different states of consciousness differ in their underlying dynamical complexity, i.e., how the broadness of communication is elicited and distributed through the brain over time and space. In this work, controls and experienced meditators were scanned using functional magnetic resonance imaging (fMRI) during resting-state and meditation (focused attention on breathing). Our results evidenced that the dynamical complexity underlying meditation shows less complexity than during resting-state in the meditator group but not in the control group. Furthermore, we report that during resting-state, the brain activity of experienced meditators showed higher metastability (i.e., a wider dynamical regime over time) than the one observed in the control group. Overall, these results indicate that the meditation state operates in a different dynamical regime than the resting-state.

neuroscience↗

bioRxiv2017

Subject- and behavior-specific signatures extracted from fMRI data using whole-brain effective connectivity

The study of brain communication based on fMRI data is often limited because such measurements are a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications, in particular when only a few recording sessions are available. The present study aims to define a reliable standard for the extraction of multiple signatures from fMRI data, while verifying that they do not mix information about the different modalities. In particular, condition-specific signature should not be contaminated by subject-related information. Practically, signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key for robust prediction is using effective connectivity instead of functional connectivity. Our method demonstrates excellent generalization capabilities for subject identification in two datasets, using only a few sessions per subject as reference. Using another dataset with resting state and movie viewing, we show that the two signatures related to subjects and tasks correspond to distinct subnetworks, which are thus topologically orthogonal. Our results set solid foundations for applications tailored to individual subjects, such as clinical diagnostic.

neuroscience↗