The microstructure of REM sleep: Why phasic and tonic?

Rapid eye movement (REM) sleep is a peculiar neural state that occupies 20-25% of nighttime sleep in healthy human adults and seems to play critical roles in a variety of functions spanning from basic physiological mechanisms to complex cognitive processes. REM sleep exhibits a plethora of transient neurophysiological features, such as eye movements, muscle twitches, and changes in autonomic activity, however, despite its heterogeneous nature, it is usually conceptualized as a homogeneous sleep state. We propose here that differentiating and exploring the fine microstructure of REM sleep, especially its phasic and tonic constituents would provide a novel framework to examine the mechanisms and putative functions of REM sleep. In this review, we show that phasic and tonic REM periods are remarkably different neural states with respect to environmental alertness, spontaneous and evoked cortical activity, information processing, and seem to contribute differently to the dysfunctions of REM sleep in several neurological and psychiatric disorders. We highlight that a distinctive view on phasic and tonic REM microstates would facilitate the understanding of the mechanisms and functions of REM sleep in healthy and pathological conditions.info:eu-repo/semantics/publishe

The modulatory effect of adaptive task-switching training on resting-state neural network dynamics in younger and older adults

With increasing life expectancy and active aging, it becomes crucial to investigate methods which could compensate for generally detected cognitive aging processes. A promising candidate is adaptive cognitive training, during which task difficulty is adjusted to the participants’ performance level to enhance the training and potential transfer effects. Measuring intrinsic brain activity is suitable for detecting possible distributed training-effects since resting-state dynamics are linked to the brain’s functional flexibility and the effectiveness of different cognitive processes. Therefore, we investigated if adaptive task-switching training could modulate resting-state neural dynamics in younger (18–25 years) and older (60–75 years) adults (79 people altogether). We examined spectral power density on resting-state EEG data for measuring oscillatory activity, and multiscale entropy for detecting intrinsic neural complexity. Decreased coarse timescale entropy and lower frequency band power as well as increased fine timescale entropy and higher frequency band power revealed a shift from more global to local information processing with aging before training. However, cognitive training modulated these age-group differences, as coarse timescale entropy and lower frequency band power increased from pre- to post-training in the old-training group. Overall, our results suggest that cognitive training can modulate neural dynamics even when measured outside of the trained task

Considering Individual Variation in the Search for Neuroimaging Features of Response to Pharmacotherapy for Major Depression

Many studies investigate the potential of neuroimaging features to predict treatment success for patients with major depression (MD), as this could improve outcomes in clinical practice. However, variable findings and methodological issues limit the generalizability of such research. In addition, we know little about the applicability of features identified in neuroimaging studies at an individual level, which is essential for translation to clinical practice. In this thesis, I examined these issues to advance our understanding of the opportunities and challenges that this field can leverage to get closer to personalized care. First, I investigated the robustness of fMRI functional connectivity features in three important brain networks related to MD and successful treatment using a large, multi-site dataset. I identified stable differences between participants before treatment based on if and how quickly their symptoms decreased during treatment, indicating their potential to predict outcomes. Second, I explored the relative magnitude of individual variation and group differences such as those identified in project 1. Specifically, the similarity in whole-brain fMRI connectivity across everyone, groups (patients vs controls, responders vs non-responders, female vs male participants), sessions (baseline, week 2 and 8) and individuals was quantified to estimate the relative amount of variance explained by each of these sources. Individual-specific connectivity, together with common connectivity across participants and sessions, explained most of the variance in the data, while group differences contributed only a small amount. Third, I examined the group-to-individual generalizability of brain features using EEG. After identifying differences between groups of patients whose symptoms did or did not decrease substantially with treatment, this study explored whether such group features could be identified in individual patients. The results revealed that individual brain features often deviated from group features. Overall, these findings indicate that, though robust features of antidepressant treatment success may be identified at the group level using large samples and thorough standardizing procedures, individual variation likely needs to be considered for these findings to be applicable to individual patients. Future research should examine if individual brain features can accurately inform clinical practice

Sharpening the paradox of REM sleep: cortical oscillations, synchronization and topographical aspects during phasic and tonic REM microstates

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The paradox of rapid eye movement sleep in the light of oscillatory activity and cortical synchronization during phasic and tonic microstates

Rapid Eye Movement (REM) sleep is a peculiar neural state showing a combination of muscle atonia and intense cortical activity. REM sleep is usually considered as a unitary state in neuroscientific research; however, it is composed of two different microstates: phasic and tonic REM. These differ in awakening thresholds, sensory processing, and cortical oscillations. Nevertheless, studies examining cortical oscillations during REM microstates are scarce, and used low spatial sampling. Here, we analyzed the data of 18 healthy individuals assessed by highdensity sleep EEG recordings. We systematically contrasted phasic and tonic REM periods in terms of topographical distribution, source localization, as well as local, global and long-range synchronization of frequencyspecific cortical activity. Tonic periods showed relatively increased high alpha and beta power over frontocentral derivations. In addition, higher frequency components of beta power exhibited increased global synchronization during tonic compared to phasic states. In contrast, in phasic periods we found increased power and synchronization of low frequency oscillations coexisting with increased and synchronized gamma activity. Source localization revealed several multimodal, higher-order associative, as well as sensorimotor areas as potential sources of increased high alpha/beta power during tonic compared to phasic REM. Increased gamma power in phasic REM was attributed to medial prefrontal and right lateralized temporal areas associated with emotional processing. Our findings emphasize the heterogeneous nature of REM sleep, expressed in two microstates with remarkably different neural activity. Considering the microarchitecture of REM sleep may provide new insights into the mechanisms of REM sleep in health and disease

PTSD-like symptoms, morning affect and intrusive memories in nightmare disorder

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High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways

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