Philipp G. Sämann

Development of the Brain's Default Mode Network from Wakefulness to Slow Wave Sleep

Falling asleep is paralleled by a loss of conscious awareness and reduced capacity to process external stimuli. Little is known on sleep-associated changes of spontaneously synchronized anatomical networks as detected by resting-state functional magnetic resonance imaging (rs-fMRI). We employed functional connectivity analysis of rs-fMRI series obtained from 25 healthy participants, covering all non-rapid eye movement (NREM) sleep stages. We focused on the default mode network (DMN) and its anticorrelated network (ACN) that are involved in internal and external awareness during wakefulness. Using independent component analysis, cross-correlation analysis (CCA), and intraindividual dynamic network tracking, we found significant changes in DMN/ACN integrity throughout the NREM sleep. With increasing sleep depth, contributions of the posterior cingulate cortex (PCC)/retrosplenial cortex (RspC), parahippocampal gyrus, and medial prefrontal cortex to the DMN decreased. CCA revealed a breakdown of corticocortical functional connectivity, particularly between the posterior and anterior midline node of the DMN and the DMN and the ACN. Dynamic tracking of the DMN from wakefulness into slow wave sleep in a single subject added insights into intraindividual network fluctuations. Results resonate with a role of the PCC/RspC for the regulation of consciousness. We further submit that preserved corticocortical synchronization could represent a prerequisite for maintaining internal and external awareness.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Development of a Large-Scale Functional Brain Network during Human Non-Rapid Eye Movement Sleep

Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization of slow-frequency blood oxygen level-dependent (BOLD) signal fluctuations during wakeful resting. In this study, we used graph theoretical measures to explore how physiological changes during sleep are reflected in functional connectivity and small-world network properties of a large-scale, low-frequency functional brain network. Twenty-five young and healthy participants fell asleep during a 26.7 min fMRI scan with simultaneous polysomnography. A maximum overlap discrete wavelet transformation was applied to fMRI time series extracted from 90 cortical and subcortical regions in normalized space after residualization of the raw signal against unspecific sources of signal fluctuations; functional connectivity analysis focused on the slow-frequency BOLD signal fluctuations between 0.03 and 0.06 Hz. We observed that in the transition from wakefulness to light sleep, thalamocortical connectivity was sharply reduced, whereas corticocortical connectivity increased; corticocortical connectivity subsequently broke down in slow-wave sleep. Local clustering values were closest to random values in light sleep, whereas slow-wave sleep was characterized by the highest clustering ratio (gamma). Our findings support the hypothesis that changes in consciousness in the descent to sleep are subserved by reduced thalamocortical connectivity at sleep onset and a breakdown of general connectivity in slow-wave sleep, with both processes limiting the capacity of the brain to integrate information across functional modules.

Diffusion Magnetic Resonance Histograms as a Surrogate Marker and Predictor of Disease Progression in CADASIL A Two-Year Follow-Up Study

Background and Purpose— Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a cerebral small vessel disease caused by mutations in the NOTCH3 gene. MRI is sensitive in detecting preclinical involvement and changes over time. However, little is known about correlations between MRI metrics and clinical measures on a longitudinal scale. In this study, we assessed the role of quantitative MRI (T2-lesion volume and diffusion tensor imaging [DTI]–derived metrics) in monitoring and predicting disease progression. Methods— Sixty-two CADASIL subjects were followed prospectively over a period of 26.3±1.2 months. Dual-echo scans, DTI scans, and clinical scales were obtained at baseline and at follow-up. T2-lesion volumes were determined quantitatively, and histograms of mean diffusivity (MD) were produced. Results— At follow-up, T2-lesion volumes and MD histogram metrics had changed significantly (all P<0.01). Lesion volumes and average MD correlated with clinical scores at baseline. Changes of average MD correlated with changes of the Rankin score, the National Institutes of Health Stroke Scale score, and the structured interview for the diagnosis of Alzheimer dementia and multiinfarct dementia score (all P<0.01). On multivariate analysis, average MD and systolic blood pressure at baseline were predictors of changes of average MD during follow-up. Moreover, average MD was the main predictor of clinical progression. Sample size estimates showed that the number of individuals required to detect a treatment effect in an interventional trial may be reduced when using MD histograms as an end point. Conclusions— This study establishes correlations between changes of DTI histogram metrics and clinical measures over time. DTI histograms may be used as an adjunct outcome measure in future therapeutic trials. Moreover, DTI histogram metrics predict disease progression in CADASIL.

Sleep Spindles and Hippocampal Functional Connectivity in Human NREM Sleep

We investigated human hippocampal functional connectivity in wakefulness and throughout non-rapid eye movement sleep. Young healthy subjects underwent simultaneous EEG and functional magnetic resonance imaging (fMRI) measurements at 1.5 T under resting conditions in the descent to deep sleep. Continuous 5 min epochs representing a unique sleep stage (i.e., wakefulness, sleep stages 1 and 2, or slow-wave sleep) were extracted. fMRI time series of subregions of the hippocampal formation (HF) (cornu ammonis, dentate gyrus, and subiculum) were extracted based on cytoarchitectonical probability maps. We observed sleep stage-dependent changes in HF functional coupling. The HF was integrated to variable strength in the default mode network (DMN) in wakefulness and light sleep stages but not in slow-wave sleep. The strongest functional connectivity between the HF and neocortex was observed in sleep stage 2 (compared with both slow-wave sleep and wakefulness). We observed a strong interaction of sleep spindle occurrence and HF functional connectivity in sleep stage 2, with increased HF/neocortical connectivity during spindles. Moreover, the cornu ammonis exhibited strongest functional connectivity with the DMN during wakefulness, while the subiculum dominated hippocampal functional connectivity to frontal brain regions during sleep stage 2. Increased connectivity between HF and neocortical regions in sleep stage 2 suggests an increased capacity for possible global information transfer, while connectivity in slow-wave sleep is reflecting a functional system optimal for segregated information reprocessing. Our data may be relevant to differentiating sleep stage-specific contributions to neural plasticity as proposed in sleep-dependent memory consolidation.

Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen’s d effect sizes: −0.10 to −0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: −0.26 to −0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

Neural Correlates of Dream Lucidity Obtained from Contrasting Lucid versus Non-Lucid REM Sleep: A Combined EEG/fMRI Case Study

STUDY OBJECTIVES To investigate the neural correlates of lucid dreaming. DESIGN Parallel EEG/fMRI recordings of night sleep. SETTING Sleep laboratory and fMRI facilities. PARTICIPANTS Four experienced lucid dreamers. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Out of 4 participants, one subject had 2 episodes of verified lucid REM sleep of sufficient length to be analyzed by fMRI. During lucid dreaming the bilateral precuneus, cuneus, parietal lobules, and prefrontal and occipito-temporal cortices activated strongly as compared with non-lucid REM sleep. CONCLUSIONS In line with recent EEG data, lucid dreaming was associated with a reactivation of areas which are normally deactivated during REM sleep. This pattern of activity can explain the recovery of reflective cognitive capabilities that are the hallmark of lucid dreaming.

Increased sleep pressure reduces resting state functional connectivity

ObjectIn humans, even a single night of partial sleep deprivation (PSD) can have a negative impact on cognition and affective processing, suggesting that sleep pressure represents a basic physiological constraint of brain function. Among the spontaneously fluctuating resting state networks, the default mode network (DMN) and its anticorrelated network (ACN) hold key functions in segregating internally and externally directed awareness. Task fMRI after sleep deprivation has revealed altered activation patterns in both networks. We hypothesized that effects of PSD in these intrinsically coupled networks can be detected by resting state fMRI.MethodsWe obtained 6-minute echoplanar imaging time series (1.5 Tesla) during eyes-closed, wakeful-resting experiments from 16 healthy volunteers after normal sleep and after PSD. We used independent component and cross-correlation analysis to study functional connectivity (fc), focusing on the DMN and ACN.ResultsAfter PSD, focal reductions of auto-correlation strength were detected in the posterior and anterior midline node of the DMN and in the lateral parietal and insular nodes of the ACN. Cross-correlation analysis confirmed reduced cortico-cortical connectivity within and between the DMN and ACN.ConclusionsIncreased sleep pressure is reflected in reduced fc of main DMN and ACN nodes during rest. Results have implications for understanding perceptual and cognitive changes after sleep deprivation and are relevant to clinical studies on conditions in which increased sleep propensity is present.

Effects of rapid eye movement sleep deprivation on fear extinction recall and prediction error signaling

In a temporal difference learning approach of classical conditioning, a theoretical error signal shifts from outcome deliverance to the onset of the conditioned stimulus. Omission of an expected outcome results in a negative prediction error signal, which is the initial step towards successful extinction and may therefore be relevant for fear extinction recall. As studies in rodents have observed a bidirectional relationship between fear extinction and rapid eye movement (REM) sleep, we aimed to test the hypothesis that REM sleep deprivation impairs recall of fear extinction through prediction error signaling in humans. In a three‐day design with polysomnographically controlled REM sleep deprivation, 18 young, healthy subjects performed a fear conditioning, extinction and recall of extinction task with visual stimuli, and mild electrical shocks during combined functional magnetic resonance imaging (fMRI) and skin conductance response (SCR) measurements. Compared to the control group, the REM sleep deprivation group had increased SCR scores to a previously extinguished stimulus at early recall of extinction trials, which was associated with an altered fMRI time‐course in the left middle temporal gyrus. Post‐hoc contrasts corrected for measures of NREM sleep variability also revealed between‐group differences primarily in the temporal lobe. Our results demonstrate altered prediction error signaling during recall of fear extinction after REM sleep deprivation, which may further our understanding of anxiety disorders in which disturbed sleep and impaired fear extinction learning coincide. Moreover, our findings are indicative of REM sleep related plasticity in regions that also show an increase in activity during REM sleep. Hum Brain Mapp 33:2362–2376, 2012.

Brain volume changes in CADASIL A serial MRI study in pure subcortical ischemic vascular disease

Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited small vessel disease causing stroke and subcortical vascular dementia. Recent studies in sporadic subcortical ischemic vascular disease have drawn attention to brain atrophy as a clinically important marker of disease progression. However, little is known about the role of brain atrophy and its clinical correlates in CADASIL. Method: The authors determined the normalized brain volume (NBV) and percent brain volume change (PBVC) over 2 years in 76 CADASIL subjects (45.1 ± 9.7 years) using the SIENA (structural image evaluation using normalization of atrophy) software and its adaptation for cross-sectional measurements (SIENAX). Baseline assessments included systolic blood pressure (SBP), homocysteine levels, BMI, and APOE genotyping. T2-lesion volumes and clinical scales were assessed at both time points. Results: The NBV significantly correlated with all clinical scores (Rankin, NIH Stroke Scale, Barthel, structured interview for the diagnosis of Alzheimer dementia and multi-infarct dementia, Mattis dementia rating scale) at both time points independently of age and sex. PBVC correlated with changes of all clinical scores (all p < 0.01) except for the Mattis dementia rating scale (p = 0.10). In a linear regression model, age (p < 0.001), male sex (p < 0.01), and SBP (p = 0.07) were the main risk factors for a lower NBV at baseline. Age (p < 0.001) and SBP (p = 0.01) were risk factors for brain volume loss during follow-up. Sample size estimates showed that the number of individuals needed to demonstrate a treatment effect in a trial can be reduced when PBVC is used as an endpoint. Conclusions: This study identifies brain atrophy as an important aspect of the disease process in CADASIL and establishes significant correlations with multiple clinical aspects including cognition. Age and systolic blood pressure are risk factors for brain volume loss during follow-up. Percent brain volume change seems promising as an adjunct outcome measure in future interventional trials.