Menno M. Schoonheim

Sleep benefits subsequent hippocampal functioning

Sleep before learning benefits memory encoding through unknown mechanisms. We found that even a mild sleep disruption that suppressed slow-wave activity and induced shallow sleep, but did not reduce total sleep time, was sufficient to affect subsequent successful encoding-related hippocampal activation and memory performance in healthy human subjects. Implicit learning was not affected. Our results suggest that the hippocampus is particularly sensitive to shallow, but intact, sleep.

Subcortical atrophy and cognition Sex effects in multiple sclerosis

Objectives: Gray matter (GM) atrophy is common in multiple sclerosis (MS), as is cognitive dysfunction. Understanding the exact relationship between atrophy and cognition requires further investigation. The aim of this study was to investigate the relationship between subcortical GM atrophy and cognition in early relapsing onset MS. Methods: Structural MRI and neuropsychological evaluations were performed in 120 patients (80 women) and 50 controls (30 women), part of an early inception cohort, 6 years postdiagnosis. Deep GM volumes were segmented automatically. Cognition was assessed in 7 domains. Stepwise linear regression was used to predict average cognition in the patient group. Results: Most deep GM volumes were reduced in patients, with larger effects on average in men (−11%) than in women (−6.3%). Only the bilateral hippocampus, amygdala, and right nucleus accumbens in men, and right hippocampus and nucleus accumbens, bilateral amygdala, and putamen in women, showed no atrophy compared to controls. All cognitive domains except visuospatial memory were affected in men; none were significantly affected in women. In the MS group, average cognition was best predicted by thalamic volume, sex, and education (adjusted R2 = 0.31), while lesion volume was not a significant predictor in the model. Conclusions: Six years postdiagnosis, almost all subcortical structures were affected by MS, especially in men. Cognition was most severely affected in male patients. Thalamic volume, sex, and education best predicted average cognition. These results underline the relevance of specific subcortical structures to cognition, as well as the relevance of (sex-specific) atrophy in MS.

Resting-State Brain Networks in Type 1 Diabetic Patients With and Without Microangiopathy and Their Relation to Cognitive Functions and Disease Variables

Cognitive functioning depends on intact brain networks that can be assessed with functional magnetic resonance imaging (fMRI) techniques. We hypothesized that cognitive decrements in type 1 diabetes mellitus (T1DM) are associated with alterations in resting-state neural connectivity and that these changes vary according to the degree of microangiopathy. T1DM patients with (MA+: n = 49) and without (MA−: n = 52) microangiopathy were compared with 48 healthy control subjects. All completed a neuropsychological assessment and resting-state fMRI. Networks were identified using multisubject independent component analysis; specific group differences within each network were analyzed using the dual-regression method, corrected for confounding factors and multiple comparisons. Relative to control subjects, MA− patients showed increased connectivity in networks involved in motor and visual processes, whereas MA+ patients showed decreased connectivity in networks involving attention, working memory, auditory and language processing, and motor and visual processes. Better information-processing speed and general cognitive ability were related to increased degree of connectivity. T1DM is associated with a functional reorganization of neural networks that varies, dependent on the presence or absence of microangiopathy.

The limits of functional reorganization in multiple sclerosis

Investigating the brain at rest using functional MRI is a popular new method to investigate brain function in physiologic and pathologic conditions. Avoiding traditional task-based restrictions, it enables the researcher to investigate the entire brain with minimal burden and has therefore flourished recently, leading to the discovery of several consistent networks1 that are active in the healthy brain performing no task (i.e., at rest). One of these is the so-called default-mode network (DMN), which encompasses the medial prefrontal, anterior cingulate, posterior cingulate/precuneus, and lateral parietal cortices. The DMN was initially identified since it is frequently deactivated when performing active cognitive tasks, leading to the hypothesis that this network is involved in cognitive postprocessing at rest; supporting this idea is the finding that it is completely quiet in coma.2 Most current resting state studies focus on this network and have yielded a plethora of studies in a wide spectrum of neurologic diseases, like Alzheimer disease (AD), whereas multiple sclerosis (MS) has been notably absent until now. Resting state studies alone cannot answer all questions regarding task-based functions. Combining resting state with task-based paradigms therefore allows for an optimal assessment of function in several disease states. Normal deactivation of regions of the DMN during tasks is, for example, present3 in early mild cognitive impairment (MCI) stages, combined with …

Diffusion tensor imaging in type 1 diabetes: decreased white matter integrity relates to cognitive functions

To the Editor: Type 1 diabetes, particularly in the presence of microangiopathy, is associated with cognitive dysfunction, mainly observed in domains involving processing speed, suggesting white matter involvement [1]. White matter hyperintensities, a commonly used marker for white matter damage on MRI, however, do not occur more prevalently in type 1 diabetes compared with controls [2]. Therefore, we assessed white matter tract integrity using MRI-diffusion tensor imaging (DTI) and cognitive functions in type 1 diabetic patients with and without microangiopathy and in controls. We hypothesised that type 1 diabetic patients with microangiopathy would show the most pronounced reductions in white matter tract integrity compared with the other groups, and that these differences would be associated with cognitive differences.

Functional segmentation of the hippocampus in the healthy human brain and in Alzheimer's disease

In this study we segment the hippocampus according to functional connectivity assessed from resting state functional magnetic resonance images in healthy subjects and in patients with Alzheimers disease (AD). We recorded the resting FMRI signal from 16 patients and 22 controls. We used seed-based functional correlation analyses to calculate partial correlations of all voxels in the hippocampus relative to characteristic regional signal changes in the thalamus, the prefrontal cortex (PFC) and the posterior cingulate cortex (PCC), while controlling for ventricular CSF and white matter signals. Group comparisons were carried out controlling for age, gender, hippocampal volume and brain volume. The strength of functional connectivity in each region also was correlated with neuropsychological measures. We found that the hippocampus can be segmented into three distinct functional subregions (head, body, and tail), according to the relative connectivity with PFC, PCC and thalamus, respectively. The AD group showed stronger hippocampus-PFC and weaker hippocampus-PCC functional connectivity, the magnitudes of which correlated with MMSE in both cases. The results are consistent with an adaptive role of the PFC in the context of progression of dysfunction in PCC during earlier stages of AD. Extension of our approach could integrate regional volume measures for the hippocampus with their functional connectivity patterns in ways that should increase sensitivity for assessment of AD onset and progression.

Multi-parametric structural magnetic resonance imaging in relation to cognitive dysfunction in long-standing multiple sclerosis

Background: Cognitive deficits are common in multiple sclerosis. Most previous studies investigating the imaging substrate of cognitive deficits in multiple sclerosis included patients with relatively short disease durations and were limited to one modality/brain region. Objective: To identify the strongest neuroimaging predictors for cognitive dysfunction in a large cohort of patients with long-standing multiple sclerosis. Methods: Extensive neuropsychological testing and multimodal 3.0T MRI was performed in 202 patients with multiple sclerosis and 52 controls. Cognitive scores were compared between groups using Z-scores. Whole-brain, white matter, grey matter, deep grey matter and lesion volumes; cortical thickness, (juxta)cortical and cerebellar lesions; and extent and severity of diffuse white matter damage were measured. Stepwise linear regression was used to identify the strongest predictors for cognitive dysfunction. Results: All cognitive domains were affected in patients. Patients showed extensive atrophy, focal pathology and damage in up to 75% of the investigated white matter. Associations between imaging markers and average cognition were two times stronger in cognitively impaired patients than in cognitively preserved patients. The final model for average cognition consisted of deep grey matter DGMV volume and fractional anisotropy severity (adjusted R²=0.490; p<0.001). Conclusion: From all imaging markers, deep grey matter atrophy and diffuse white matter damage emerged as the strongest predictors for cognitive dysfunction in long-standing multiple sclerosis.

Structural MRI substrates of cognitive impairment in neuromyelitis optica

Objective: To identify the clinical and structural MRI markers for predicting cognitive impairment (CI) in patients with neuromyelitis optica (NMO). Methods: Fifty-four patients with NMO and 27 healthy controls underwent extensive neuropsychological testing and multimodal 3.0T MRI. The patient group was classified as CI or cognitively preserved (CP), using a criterion of ≤1.5 SD on at least 2 cognitive domains. MRI measurements included white matter (WM) lesion volume, gray matter (GM), WM, and deep GM (DGM) volume, cortical thickness, and the severity and extent of WM tract diffusion metric alterations based on fractional anisotropy and mean, axial, and radial diffusivity. Groups were compared using a multivariate general linear model, and clinical and MRI measurements were related to average cognition z scores by partial correlations and a stepwise linear regression model. Results: Twenty-six patients with NMO (48.2%) were classified as CI and showed WM tract diffusion abnormalities, particularly increased radial diffusivity, and GM especially DGM atrophy compared with healthy controls. Patients classified as CP also showed alterations of WM tract diffusion but without significant GM atrophy. Compared with the CP group, patients with CI demonstrated a lower level of education and decreased hippocampal volume. In the whole patient group, average cognition z scores were best predicted by the level of education and hippocampal volume (R2 = 0.46, p < 0.001). Conclusion: In patients with NMO, WM tract integrity disruption was identified in both CP and CI groups. GM atrophy, particularly in the DGM, was only found in the CI group. Hippocampal volume is the main MRI predictor of cognition in NMO.

Functional plasticity in MS Friend or foe

MRI is an irreplaceable tool for diagnosing and monitoring multiple sclerosis (MS). Indeed, conventional MRI is very sensitive in detecting focal, macroscopic white matter lesions of the CNS. This has led to the formulation of diagnostic criteria, which rely not only on the neurologic assessment, but also on MRI markers. Similarly, conventional MRI is also used worldwide to monitor natural MS evolution, or to monitor specific treatment strategies. Recently, research has tried to broaden the horizon of MRI applications in MS beyond lesion detection.1 In this context, diffusion tensor imaging studies have shown that patients with MS experience microstructural tissue abnormalities that …

Disrupted topological organization of structural and functional brain connectomes in clinically isolated syndrome and multiple sclerosis

The brain connectome of multiple sclerosis (MS) has been investigated by several previous studies; however, it is still unknown how the network changes in clinically isolated syndrome (CIS), the earliest stage of MS, and how network alterations on a functional level relate to the structural level in MS disease. Here, we investigated the topological alterations of both the structural and functional connectomes in 41 CIS and 32 MS patients, compared to 35 healthy controls, by combining diffusion tensor imaging and resting-state functional MRI with graph analysis approaches. We found that the structural connectome showed a deviation from the optimal pattern as early as the CIS stage, while the functional connectome only showed local changes in MS patients, not in CIS. When comparing two patient groups, the changes appear more severe in MS. Importantly, the disruptions of structural and functional connectomes in patients occurred in the same direction and locally correlated in sensorimotor component. Finally, the extent of structural network changes was correlated with several clinical variables in MS patients. Together, the results suggested early disruption of the structural brain connectome in CIS patients and provided a new perspective for investigating the relationship of the structural and functional alterations in MS.