[Show abstract][Hide abstract] ABSTRACT: Mammalian sleep emerges from attenuated activity in the ascending reticular arousal system (ARAS), the main arousal network of the brain. This system originates in the brain stem and activates the thalamus and cortex during wakefulness via a well-characterized ‘bottom-up’ pathway. Recent studies propose that a less investigated cortico-thalamic ‘top-down’ pathway also regulates sleep. The present work integrates the current evidence on sleep regulation with a focus on the ‘top-down’ pathway and explores the potential to translate this information into clinically relevant interventions. Specifically, we elaborate the concept that arousal and sleep continuity in humans can be modulated by non-invasive brain stimulation (NIBS) techniques that increase or decrease cortical excitability. Based on preclinical studies, the modulatory effects of the stimulation are thought to extend to subcortical arousal networks. Further exploration of the ‘top-down’ regulation of sleep and its modulation through non-invasive brain stimulation techniques may contribute to the development of novel treatments for clinical conditions of disrupted arousal and sleep, which are among the major health problems worldwide.
Full-text · Article · Jan 2016 · Sleep Medicine Reviews
[Show abstract][Hide abstract] ABSTRACT: Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.
Full-text · Article · Nov 2015 · Frontiers in Human Neuroscience
[Show abstract][Hide abstract] ABSTRACT: Therapeutic sleep deprivation (SD) is a rapid acting treatment for major depressive disorder (MDD). Within hours, SD leads to a dramatic decrease in depressive symptoms in 50–60% of patients with MDD. Scientifically, therapeutic SD presents a unique paradigm to study the neurobiology of MDD. Yet, up to now, the neurobiological basis of the antidepressant effect, which is most likely different from today’s first-line treatments, is not sufficiently understood. This article puts the idea forward that sleep/wake-dependent shifts in synaptic plasticity, i.e. the neural basis of adaptive network function and behavior, represent a critical mechanism of therapeutic SD in MDD. Particularly, this article centers on two major hypotheses of MDD and sleep, the synaptic plasticity hypothesis of MDD and the synaptic homeostasis hypothesis of sleep-wake regulation, and on how they can be integrated into a novel synaptic plasticity model of therapeutic SD in MDD. As a major component, the model proposes that therapeutic SD, by homeostatically enhancing cortical synaptic strength, shifts the initially deficient inducibility of associative synaptic long-term potentiation (LTP) in patients with MDD in a more favorable window of associative plasticity. Research on the molecular effects of SD in animals and humans, including observations in the neurotrophic, adenosinergic, monoaminergic, and glutamatergic system, provides some support for the hypothesis of associative synaptic plasticity facilitation after therapeutic SD in MDD. The model proposes a novel framework for a mechanism of action of therapeutic SD that can be further tested in humans based on non-invasive indices and in animals based on direct studies of synaptic plasticity. Further determining the mechanisms of action of SD might contribute to the development of novel fast acting treatments for MDD, one of the major health problems worldwide.
Full-text · Article · Nov 2015 · Sleep Medicine Reviews
[Show abstract][Hide abstract] ABSTRACT: The psychosis high-risk state is accompanied by alterations in functional brain activity during working memory processing. We used binary automatic pattern-classification to discriminate between the at-risk mental state (ARMS), first episode psychosis (FEP) and healthy controls (HCs) based on n-back WM-induced brain activity. Linear support vector machines and leave-one-out-cross-validation were applied to fMRI data of matched ARMS, FEP and HC (19 subjects/group). The HC and ARMS were correctly classified, with an accuracy of 76.2% (sensitivity 89.5%, specificity 63.2%, p = 0.01) using a verbal working memory network mask. Only 50% and 47.4% of individuals were classified correctly for HC vs. FEP (p = 0.46) or ARMS vs. FEP (p = 0.62), respectively. Without mask, accuracy was 65.8% for HC vs. ARMS (p = 0.03) and 65.8% for HC vs. FEP (p = 0.0047), and 57.9% for ARMS vs. FEP (p = 0.18). Regions in the medial frontal, paracingulate, cingulate, inferior frontal and superior frontal gyri, inferior and superior parietal lobules, and precuneus were particularly important for group separation. These results suggest that FEP and HC or FEP and ARMS cannot be accurately separated in small samples under these conditions. However, ARMS can be identified with very high sensitivity in comparison to HC. This might aid classification and help to predict transition in the ARMS.
Full-text · Article · Oct 2015 · Clinical neuroimaging
[Show abstract][Hide abstract] ABSTRACT: The synaptic plasticity hypothesis of major depressive disorder (MDD) posits that alterations of synaptic plasticity represent a final common pathway underlying the clinical symptoms of the disorder. This study tested the hypotheses that patients with MDD show an attenuation of cortical synaptic long-term potentiation (LTP) like plasticity in comparison to healthy controls, and that this attenuation recovers after remission. Cortical synaptic LTP-like plasticity was measured using a transcranial magnetic stimulation protocol, i.e. paired associative stimulation (PAS), in 27 inpatients with MDD according to ICD-10 criteria and 27 sex- and age-matched healthy controls. The amplitude of motor evoked potentials was measured before and after PAS. Patients were assessed during the acute episode and at follow-up to determine the state- or trait-character of LTP-like changes. LTP-like plasticity, the PAS-induced increase in motor evoked potential amplitudes was significantly attenuated in patients with an acute episode of MDD compared to healthy controls. Patients with remission showed a restoration of synaptic plasticity, whereas the deficits persisted in patients without remission, indicative for a state-character of impaired LTP-like plasticity. The results provide first evidence for a state-dependent partial occlusion of cortical LTP-like plasticity in MDD. This further identifies impaired LTP-like plasticity as a potential pathomechanism and treatment target of the disorder.Neuropsychopharmacology accepted article preview online, 07 October 2015. doi:10.1038/npp.2015.310.
Full-text · Article · Oct 2015 · Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology
[Show abstract][Hide abstract] ABSTRACT: LTP-like plasticity measured by visual evoked potentials (VEP) can be induced in the intact human brain by presenting checkerboard reversals. Also associated with LTP-like plasticity, around two third of participants respond to transcranial magnetic stimulation (TMS) with a paired-associate stimulation (PAS) protocol with a potentiation of their motor evoked potentials. LTP-like processes are also required for verbal and motor learning tasks. We compared effect sizes, responder rates and intercorrelations as well as the potential influence of attention between these four assessments in a group of 37 young and healthy volunteers. We observed a potentiation effect of the N75 and P100 VEP component which positively correlated with plasticity induced by PAS. Subjects with a better subjective alertness were more likely to show PAS and VEP potentiation. No correlation was found between the other assessments. Effect sizes and responder rates of VEP potentiation were higher compared to PAS. Our results indicate a high variability of LTP-like effects and no evidence for a system-specific nature. As a consequence, studies wishing to assess individual levels of LTP-like plasticity should employ a combination of multiple assessments.
Full-text · Article · Sep 2015 · Frontiers in Human Neuroscience
[Show abstract][Hide abstract] ABSTRACT: Background:
Hippocampal grey matter (GM) atrophy predicts conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Pilot data suggests that mean diffusivity (MD) in the hippocampus, as measured with diffusion tensor imaging (DTI), may be a more accurate predictor of conversion than hippocampus volume. In addition, previous studies suggest that volume of the cholinergic basal forebrain may reach a diagnostic accuracy superior to hippocampal volume in MCI.
The present study investigated whether increased MD and decreased volume of the hippocampus, the basal forebrain and other AD-typical regions predicted time to conversion from MCI to AD dementia.
79 MCI patients with DTI and T1-weighted magnetic resonance imaging (MRI) were retrospectively included from the European DTI Study in Dementia (EDSD) dataset. Of these participants, 35 converted to AD dementia after 6-46 months (mean: 21 months). We used Cox regression to estimate the relative conversion risk predicted by MD values and GM volumes, controlling for age, gender, education and center.
Decreased GM volume in all investigated regions predicted an increased risk for conversion. Additionally, increased MD in the right basal forebrain predicted increased conversion risk. Reduced volume of the right hippocampus was the only significant predictor in a stepwise model combining all predictor variables.
Volume reduction of the hippocampus, the basal forebrain and other AD-related regions was predictive of increased risk for conversion from MCI to AD. In this study, volume was superior to MD in predicting conversion.
[Show abstract][Hide abstract] ABSTRACT: Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significantly differ from that seen in a dementia clinic. At a single dementia clinic, we evaluated the ability of a linear support vector machine trained with completely unrelated data to differentiate between Alzheimer’s disease (AD), frontotemporal dementia (FTD), Lewy body dementia, and healthy aging based on 3D-T1 weighted MRI data sets. Furthermore, we predicted progression to AD in subjects with mild cognitive impairment (MCI) at baseline and automatically quantified white matter hyperintensities from FLAIR-images. Separating additionally recruited healthy elderly from those with dementia was accurate with an area under the curve (AUC) of 0.98. Multi-class separation of 138 patients with either AD or FTD from other included groups was good on the training set (AUC >0.9) but substantially less accurate (AUC = 0.76 for AD and 0.78 for FTD) on data from the local clinic. Longitudinal data from 28 cases with MCI at baseline and appropriate follow-up data were available. The computer tool discriminated progressive from stable MCI with AUC = 0.73, compared to AUC = 0.80 for the training set. A relatively low accuracy by clinicians (AUC = 0.81) illustrates the difficulties of predicting conversion in this heterogeneous cohort. This first application of a MRI-based pattern recognition method to a routine sample demonstrates feasibility, but also illustrates that automated multi-class differential diagnoses have to be the focus of future methodological developments and application studies.
Full-text · Article · Aug 2015 · Journal of Alzheimer's disease: JAD
[Show abstract][Hide abstract] ABSTRACT: Background
Cognitive and motor task performance in premanifest Huntington's disease (HD) gene-carriers is often within normal ranges prior to clinical diagnosis, despite loss of brain volume in regions involved in these tasks. This indicates ongoing compensation, with the brain maintaining function in the presence of neuronal loss. However, thus far, compensatory processes in HD have not been modeled explicitly. Using a new model, which incorporates individual variability related to structural change and behavior, we sought to identify functional correlates of compensation in premanifest-HD gene-carriers.
We investigated the modulatory effects of regional brain atrophy, indexed by structural measures of disease load, on the relationship between performance and brain activity (or connectivity) using task-based and resting-state functional MRI.
Consistent with compensation, as atrophy increased performance-related activity increased in the right parietal cortex during a working memory task. Similarly, increased functional coupling between the right dorsolateral prefrontal cortex and a left hemisphere network in the resting-state predicted better cognitive performance as atrophy increased. Such patterns were not detectable for the left hemisphere or for motor tasks.
Our findings provide evidence for active compensatory processes in premanifest-HD for cognitive demands and suggest a higher vulnerability of the left hemisphere to the effects of regional atrophy.
[Show abstract][Hide abstract] ABSTRACT: Objective:
Paired associative stimulation (PAS) is a widely used transcranial magnetic stimulation (TMS) paradigm to induce synaptic long-term potentiation (LTP)-like plasticity in the intact human brain. The PAS effect is reduced in Alzheimer's dementia (AD) but has not yet been assessed in patients with mild cognitive impairment (MCI).
PAS was assessed in a group of 24 MCI patients and 24 elderly controls. MCI patients were further stratified by their cognitive profile as well as hippocampal atrophy and Apolipoprotein E (ApoE) genotype.
There was no difference in PAS effects between MCI patients and healthy controls. MCI patients tended to show a higher response rate and an average PAS effect. PAS effects were not correlated with markers of disease severity or ApoE genotype but were more pronounced in individuals with shorter sleep duration and in MCI subjects with higher ratings of subjective alertness.
Contrary to our initial hypothesis, there was no clear difference in PAS between MCI patients and healthy controls.
Our results argue against a continuous reduction of LTP-like plasticity along the spectrum of clinical MCI when stratified by MCI-subtype, APOE genotype or hippocampus atrophy.
No preview · Article · Aug 2015 · Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology
[Show abstract][Hide abstract] ABSTRACT: Objectives:
The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI).
Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects.
Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics.
Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.
Full-text · Article · Jun 2015 · Clinical neuroimaging
[Show abstract][Hide abstract] ABSTRACT: We present in this paper a method to perform a length parameterization of cortical sulcus meshes. Such parameterization allows morphological features to be localized in a normalized way along the length of the sulcus and can be used to perform population studies and group comparisons. Our method uses the second eigenfunction of the Laplace-Beltrami operator, and the resulting parameterization is quasi-isometric. The process is validated on the central sulci of a set of subjects and its efficiency is demonstrated by quantifying morphological differences between left and right-handed subjects.
[Show abstract][Hide abstract] ABSTRACT: Alzheimer’s disease (AD), the predominant cause of dementia, is characterized by progressive loss of memory and other cognitive functions with advancing age, and both genetic and non-genetic factors modifying disease risk. This chapter provides a summary of the underlying neuropathology, epidemiology, and clinical characteristics of AD. Additionally, recently developed methods of automated diagnosing, novel therapeutic strategies, and possible preventing variables are briefly described.