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Healthy ageing is accompanied by cognitive decline that affects episodic memory processes in particular. Studies showed that anodal transcranial direct current stimulation (tDCS) to the left dorsolateral prefrontal cortex (DLPFC) may counteract this cognitive deterioration by increasing excitability and inducing neuroplasticity in the targeted cortical region. While stimulation gains are more consistent in initial low performers, relying solely on behavioural measures to predict treatment benefits does not suffice for a reliable implementation of this method as a therapeutic option. Hence, an exploration of the underlying neurophysiological mechanisms regarding the differential stimulation effect is warranted. Glutamatergic metabolites (Glx) and γ-aminobutyric acid (GABA) are involved in learning and memory processes and can be influenced with tDCS; wherefore, they present themselves as potential biomarkers for tDCS-induced behavioural gains, which are affiliated with neuroplasticity processes. In the present randomized, double-blind, sham-controlled, crossover study, 33 healthy young and 22 elderly participants received anodal tDCS to their left DLPFC during the encoding phase of a verbal episodic memory task. Using MEGA-PRESS edited magnetic resonance spectroscopy (MRS), Glx and GABA levels were measured in the left DLPFC before and after the stimulation period. Further, we tested whether baseline performance and neurotransmitter levels predicted subsequent gains. No beneficial group effects of tDCS emerged in either verbal retrieval performances or neurotransmitter concentrations. Moreover, baseline performance levels did not predict stimulation-induced cognitive gains, nor did Glx or GABA levels. Nevertheless, exploratory analyses suggested a predictive value of the Glx : GABA ratio, with lower ratios at baseline indicating greater tDCS-related gains in delayed recall performance. This highlights the importance of further studies investigating neurophysiological mechanisms underlying previously observed stimulation-induced cognitive benefits and their respective interindividual heterogeneity.

We assessed the structure–function relationship of the human cholinergic system and hypothesized that structural measures are associated with short-latency sensory afferent inhibition (SAI), an electrophysiological measure of central cholinergic signal transmission. Healthy volunteers (n = 36) and patients with mild cognitive impairment (MCI, n = 20) underwent median nerve SAI and 3T structural MRI to determine the volume of the basal forebrain and the thalamus. Patients with MCI had smaller basal forebrain (p p 10% SAI) had more basal forebrain volume than non-responders (p = 0.004) or patients with MCI (p r = 0.33, p

Background:Arousal and sleep represent basic domains of behavior, and alterations are of high clinical importance. Objective/hypothesis:The aim of this study was to further elucidate the neurobiology of insomnia disorder (ID) and the potential for new treatment developments, based on the modulation of cortical activity through the non-invasivebrain stimulationtechnique transcranial direct current stimulation (tDCS). Specifically, we tested the hypotheses that bi-frontal anodal tDCS shortens and cathodal tDCS prolongs total sleep time in patients with ID, compared to sham stimulation. Furthermore, we tested for differences in indices of arousal between ID patients and healthy controls and explored their potential impact on tDCS effects. Methods:Nineteen ID patients underwent a within-subject repeated-measures sleep laboratory study with adaptation, baseline and three experimental nights. Bifrontal anodal, cathodal and sham tDCS was delivered in a counterbalanced order immediately prior to sleep. WakeEEGwas recorded prior to and after tDCS as well as on the following morning. Subsequently, we compared patients with ID to a healthy control group from an earlier dataset. Results:Against our hypothesis, we did not observe any tDCS effects on sleep continuity or sleep architecture in patients with ID. Further analyses of nights without stimulation demonstrated significantly increased levels of arousal in ID patients compared to healthy controls, as indexed by subjective reports, reduced total sleep time, increased wake after sleep onset and increased high frequency EEG power during wakefulness andNREM sleep. Of note, indices of increased arousal predicted the lack of effect of tDCS in ID patients. Conclusions:Our study characterizes for the first time differential effects of tDCS on sleep in patients with ID and healthy controls, presumably related to persistent hyperarousal in ID. These findings suggest that adapted tDCS protocols need to be developed to modulate arousal and sleep dependent on baseline arousal levels.

Importance Previous trials on the effect of levothyroxine on depressive symptom scores in patients with subclinical hypothyroidism were limited by small sample sizes (N = 57 to 94) and potential biases. Objective To assess the effect of levothyroxine on the development of depressive symptoms in older adults with subclinical hypothyroidism in the largest trial on this subject and to update a previous meta-analysis including the results from this study. Design, Setting, and Participants This predefined ancillary study analyzed data from participants in the Thyroid Hormone Replacement for Untreated Older Adults with Subclinical Hypothyroidism (TRUST) trial, a double-blind, randomized, placebo-controlled, parallel-group clinical trial conducted from April 2013 to October 31, 2016. The TRUST trial included adults aged 65 years or older diagnosed with subclinical hypothyroidism, defined as the presence of persistently elevated thyroid-stimulating hormone (TSH) levels (4.6-19.9 mIU/L) with free thyroxine (T4) within the reference range. Participants were identified from clinical and general practitioner laboratory databases and recruited from the community in Switzerland, the Netherlands, Ireland, and the UK. This ancillary study included a subgroup of 472 participants from the Netherlands and Switzerland; after exclusions, a total of 427 participants (211 randomized to levothyroxine and 216 to placebo) were analyzed. This analysis was conducted from December 1, 2019, to September 1, 2020. Interventions Randomization to either levothyroxine or placebo. Main Outcomes and Measures Depressive symptom scores after 12 months measured with the Geriatric Depression Scale (GDS-15), with higher scores indicating more depressive symptoms (minimal clinically important difference = 2). Results A total of 427 participants with subclinical hypothyroidism (mean [SD] age, 74.52 [6.29] years; 239 women [56%]) were included in this analysis. The mean (SD) TSH level was 6.57 (2.22) mIU/L at baseline and decreased after 12 months to 3.83 (2.29) mIU/L in the levothyroxine group; in the placebo group, it decreased from 6.55 (2.04) mIU/L to 5.91 (2.66) mIU/L. At baseline, the mean (SD) GDS-15 score was 1.26 (1.85) in the levothyroxine group and 0.96 (1.58) in the placebo group. The mean (SD) GDS-15 score at 12 months was 1.39 (2.13) in the levothyroxine and 1.07 (1.67) in the placebo group with an adjusted between-group difference of 0.15 for levothyroxine vs placebo (95% CI, -0.15 to 0.46; P = .33). In a subgroup analysis including participants with a GDS-15 of at least 2, the adjusted between-group difference was 0.61 (95% CI, -0.32 to 1.53; P = .20). Results did not differ according to age, sex, or TSH levels. A previous meta-analysis (N = 278) on the association of levothyroxine with depressive symptoms was updated to include these findings, resulting in an overall standardized mean difference of 0.09 (95% CI, -0.05 to 0.22). Conclusions and Relevance This ancillary study of a randomized clinical trial found that depressive symptoms did not differ after levothyroxine therapy compared with placebo after 12 months; thus, these results do not provide evidence in favor of levothyroxine therapy in older persons with subclinical hypothyroidism to reduce the risk of developing depressive symptoms. Trial Registration ClinicalTrials.gov Identifier: NCT01853579.

The concepts of brain reserve and cognitive reserve were recently suggested as valuable predictors of stroke outcome. To test this hypothesis, we used age, years of education and lesion size as clinically feasible coarse proxies of brain reserve, cognitive reserve, and the extent of stroke pathology correspondingly. Linear and logistic regression models were used to predict cognitive outcome (Montreal Cognitive Assessment) and stroke-induced impairment and disability (NIH Stroke Scale; modified Rankin Score) in a sample of 104 chronic stroke patients carefully controlled for potential confounds. Results revealed 46% of explained variance for cognitive outcome (p

Background: Cognitive functions and activities of daily living (ADL) become increasingly impaired with progressing Alzheimer's disease. However, the temporal dynamics of this decline are inconsistent. Objective: To gain insight into the classical temporal cascade of specific cognitive and ADL changes, which may aid in improving detection of an impending clinical deterioration in patients, and to select ADL items and tests most sensitive to change in a specific disease stage. Methods: Patients with mild Alzheimer's dementia (AD; MMSE = 23.9±2.88) were followed at 12 and 24 months. Lead-lag analysis of changes in cognitive and functional outcome measures (CDR-SOB, 12 neuropsychological subtest scores from the CERAD + test battery, 25 Bayer-ADL items) was applied to rank the temporal sequence of changes on an ordinal scale. Results: Of 164 patients with mild AD, moderate disease progression was identified in 84 patients over 24 months (ΔMMSE 5.8±8.64; ΔCDR-SOB 4.32±4.03). Ten Bayer-ADL item measures were altered early in moderate progressors and included in a new ADL composite score. Accordingly, the new ADL score surpassed all neuropsychological measures in repeated lead-lag analysis. The Bayer-ADL total score, TMT-A, and MMSE were lagging variables in all lead-lag analyses. Conclusion: Short-term clinical deterioration in mild AD is initially preceded by changes (i.e., decline) in a well-defined set of ADL and not in classical cognitive measures. Keywords: Alzheimer’s disease; bayer activities of daily living scale; cognitive changes; disease progression; functional changes; lead and lag analysis.

Key Points Question Is bupropion an effective and safe treatment for apathy in nondepressed patients with dementia of Alzheimer type? Findings In this 12-week, multicenter, double-blind, placebo-controlled, randomized clinical trial, 54 patients received bupropion and 54 received placebo. The mean change in the Apathy Evaluation Scale–Clinician Version score was not statistically significant between the treatment groups. Meaning Bupropion did not improve apathy in patients with dementia of Alzheimer type without depressed mood., This randomized clinical trial examines the efficacy and safety of the dopamine and noradrenaline reuptake inhibitor bupropion in the treatment of apathy in patients with dementia of Alzheimer type., Importance Apathy is a frequent neuropsychiatric symptom in dementia of Alzheimer type and negatively affects the disease course and patients’ and caregivers’ quality of life. Effective treatment options are needed. Objective To examine the efficacy and safety of the dopamine and noradrenaline reuptake inhibitor bupropion in the treatment of apathy in patients with dementia of Alzheimer type. Design, Setting, and Participants This 12-week, multicenter, double-blind, placebo-controlled, randomized clinical trial was conducted in a psychiatric and neurological outpatient setting between July 2010 and July 2014 in Germany. Patients with mild-to-moderate dementia of Alzheimer type and clinically relevant apathy were included. Patients with additional clinically relevant depressed mood were excluded. Data analyses were performed between August 2018 and August 2019. Interventions Patients received either bupropion or placebo (150 mg for 4 weeks plus 300 mg for 8 weeks). In case of intolerability of 300 mg, patients continued to receive 150 mg throughout the study. Main Outcomes and Measures Change on the Apathy Evaluation Scale–Clinician Version (AES-C) (score range, 18-72 points) between baseline and week 12 was the primary outcome parameter. Secondary outcome parameters included measures of neuropsychiatric symptoms, cognition, activities of daily living, and quality of life. Outcome measures were assessed at baseline and at 4, 8, and 12 weeks. Results A total of 108 patients (mean [SD] age, 74.8 [5.9] years; 67 men [62%]) were included in the intention-to-treat analysis, with 54 randomized to receive bupropion and 54 randomized to receive placebo. The baseline AES-C score was comparable between the bupropion group and the placebo group (mean [SD], 52.2 [8.7] vs 50.4 [8.2]). After controlling for the baseline AES-C score, site, and comedication with donepezil or galantamine, the mean change in the AES-C score between the bupropion and placebo groups was not statistically significant (mean change, 2.22; 95% CI, –0.47 to 4.91; P = .11). Results on secondary outcomes showed statistically significant differences between bupropion and placebo in terms of total neuropsychiatric symptoms (mean change, 5.52; 95% CI, 2.00 to 9.04; P = .003) and health-related quality of life (uncorrected for multiple comparisons; mean change, –1.66; 95% CI, –3.01 to –0.31; P = .02) with greater improvement in the placebo group. No statistically significant changes between groups were found for activities of daily living (mean change, –2.92; 95% CI, –5.89 to 0.06; P = .05) and cognition (mean change, –0.27; 95% CI, –3.26 to 2.73; P = .86). The numbers of adverse events (bupropion group, 39 patients [72.2%]; placebo group, 33 patients [61.1%]) and serious adverse events (bupropion group, 5 patients [9.3%]; placebo group, 2 patients [3.7%]) were comparable between groups. Conclusions and Relevance Although it is safe, bupropion was not superior to placebo for the treatment of apathy in patients with dementia of Alzheimer type in the absence of clinically relevant depressed mood. Trial Registration EU Clinical Trials Register Identifier: 2007-005352-17

Background/objectives The diagnostic process in a university memory clinic is based largely on cognitive testing. However, input from informants, acquired through interview or questionnaires, may significantly impact diagnosis. We sought to evaluate whether informant questionnaires for basic and instrumental activities of daily living, or for identifying progressive cognitive decline would improve diagnostic predictability of neurodegenerative disorders compared with either the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological test battery or the Mini-Mental State Examination score alone. Design Retrospective data analysis using logit models. Setting University hospital outpatient memory clinic. Participants A total of 394 patients with dementia, mild cognitive impairment (MCI), depression, or subjective cognitive impairment were assessed. Measurements Bristol Activities of Daily Living Scale, Functional Activities Questionnaire, Informant Questionnaire on Cognitive Decline in the Elderly, and the Physical Self-Maintenance Scale questionnaires were obtained. Analyses through logit models were performed to predict outcome diagnoses, based on cognitive scores alone or in combination with one or more informant questionnaires. Results The four questionnaires were highly correlated (.31-.86). The addition of informant questionnaires improved diagnostic predictability between differential diagnoses of MCI and dementia, or dementia and depression. However, the misprediction rate was reduced by up to 6 percentage points only. Adding more than one questionnaire or all CERAD subtests instead of their sum score never improved prediction in regularized logit models to a clinically relevant extent. Conclusion Although questionnaires contribute to a statistically better prediction of the outcome diagnosis, for some sets of differential diagnoses, the benefit may not be clinically pertinent when routine semistructured informant interviews are used by trained personnel. However, standardized assessment, particularly when patients are seen longitudinally, should not be underestimated.

Purpose Previous studies showed voxel-based volumetry as a helpful tool in detecting pathologic brain atrophy. Aim of this study was to investigate whether the inclusion of CSF volume improves the imaging based diagnostic accuracy using combined automated voxel- and region-based volumetry. Methods In total, 120 individuals (30 healthy elderly, 30 frontotemporal dementia (FTD), 30 Alzheimer’s dementia (AD) and 30 Lewy body dementia (LBD) patients) were analyzed with voxel-based morphometry and compared to a reference group of 360 healthy elderly controls. Abnormal GM and CSF volumes were visualized via z-scores. Volumetric results were finally evaluated by ROC analyses. Results Based on the volume of abnormal GM and CSF voxels high accuracy was shown in separating dementia from normal ageing (AUC 0.93 and 0.91, respectively) within 5 different brain regions per hemisphere (frontal, medial temporal, temporal, parietal, occipital). Accuracy for separating FTD and AD was higher based on CSF volume (FTD: AUC 0.80 vs. 0.75 in frontal regions; AD: AUC 0.78 vs. 0.68 in parietal regions based on CSF and GM respectively). Conclusions Differentiation of dementia patients from normal ageing persons shows high accuracy when based on automatic volumetry alone. Evaluating volumes of abnormal CSF performed better than volumes of abnormal GM, especially in AD and FTD patients.

Sleep modulates motor learning, but its detailed impact on performance curves remains to be fully characterized. This study aimed to further determine the impact of brief daytime periods of NREM sleep on ‘offline’ (task discontinuation after initial training) and ‘on-task’ (performance within the test session) changes in motor skill performance (finger tapping task). In a mixed design (combined parallel group and repeated measures) sleep laboratory study (n = 17 ‘active’ wake vs. sleep, n = 19 ‘passive’ wake vs. sleep), performance curves were assessed prior to and after a 90 min period containing either sleep, active or passive wakefulness. We observed a highly significant, but state- (that is, sleep/wake)-independent early offline gain and improved on-task performance after sleep in comparison to wakefulness. Exploratory curve fitting suggested that the observed sleep effect most likely emerged from an interaction of training-induced improvement and detrimental ‘time-on-task’ processes, such as fatigue. Our results indicate that brief periods of NREM sleep do not promote early offline gains but subsequent on-task performance in motor skill learning.

The APOE ε4 allele increases the risk for sporadic Alzheimer's disease and modifies brain activation patterns of numerous cognitive domains. We assessed cognitively intact older adults with a letter n-back task to determine if previously observed increases in ε4 carriers' working-memory-related brain activation are compensatory such that they serve to maintain working memory function. Using multiple regression models, we identified interactions of APOE variant and age in bilateral hippocampus independently from task performance: ε4 carriers only showed a decrease in activation with increasing age, suggesting high sensitivity of fMRI data for detecting changes in Alzheimer's disease-relevant brain areas before cognitive decline. Moreover, we identified ε4 carriers to show higher activations in task-negative medial and task-positive inferior frontal areas along with better performance under high working memory load relative to non-ε4 carriers. The increased frontal recruitment is compatible with models of neuronal compensation, extends on existing evidence, and suggests that ε4 carriers require additional neuronal resources to successfully perform a demanding working memory task.

Objective:To distinguish white matter remodeling directly induced by stroke lesion from that evoked by remote network dysfunction, using spatial neglect as a model.Methods:We examined 24 visual neglect/extinction patients and 17 control patients combining comprehensive analyses of diffusion tensor metrics and global fiber tracking with neuropsychological testing in the acute (6.3 ± 0.5 days poststroke) and chronic (134 ± 7 days poststroke) stroke phases.Results:Compared to stroke controls, patients with spatial neglect/extinction displayed longitudinal white matter alterations with 2 defining signatures: (1) perilesional degenerative changes characterized by congruently reduced fractional anisotropy and increased radial diffusivity (RD), axial diffusivity, and mean diffusivity, all suggestive of direct axonal damage by lesion and therefore nonspecific for impaired attention network and (2) transneuronal changes characterized by an increased RD in contralesional frontoparietal and bilateral occipital connections, suggestive of primary periaxonal involvement; these changes were distinctly related to the degree of unrecovered neglect symptoms in chronic stroke, hence emerging as network-specific alterations.Conclusions:The present data show how stroke entails global alterations of lesion-spared network architecture over time. Sufficiently large lesions of widely interconnected association cortex induce distinct, large-scale structural reorganization in domain-specific network connections. Besides their relevance to unrecovered domain-specific symptoms, these effects might also explain mechanisms of domain-general deficits in stroke patients, pointing to potential targets for therapeutic intervention.

Affect can directly influence memory storage and retrieval, which offers the opportunity to improve memory performance by changing affective responses. A promising target is the left dorsolateral prefrontal cortex (dlPFC), as it is functionally involved in both affect and memory. This study explores whether anodal transcranial direct current stimulation (tDCS) to the left dlPFC improves memory retrieval through the reduction of negative affect and if this interacts with age. We randomly assigned 94 healthy individuals (n = 43 young, n = 51 elderly) to either sham or active tDCS during encoding of a verbal episodic memory task. Participants completed two questionnaires assessing affective states pre- and post-stimulation. They had to recall items unexpectedly 20 min after encoding and to name which feelings were associated with this free recall. We applied mediation models to explore the relation between tDCS, change in affect, and memory retrieval. In young participants, the reduction of negative affect via anodal tDCS fully mediated the increase in memory retrieval (R2 = 57%; p

Although post-stroke cognitive deficit can significantly limit patient independence and social re-integration, clinical routine predictors for this condition are lacking. ‘Cognitive reserve’ limits the detrimental effects of slowly developing neurodegeneration. We aimed to determine whether comparable effects also exist in acute stroke. Using 'years of education' as a proxy, we investigated whether cognitive reserve beneficially influences cognitive performance and disability after stroke, whilst controlling for age and lesion size as measure of stroke pathology. Within the first week of ischemic right hemisphere stroke, 36 patients were assessed for alertness, working memory, executive functions, spatial neglect, global cognition and motor deficit at 4.9 ± 2.1 days post-stroke, in addition to routine clinical tests (NIH Stroke Scale, modified Rankin Scale on admission

Animals and humans spend on average one third of their lives in sleep, but its functions remain to be specified. Distinct lines of research propose that sleep promotes local strengthening of information-bearing synapses (plasticity) and global downscaling of synaptic strength (stability) in neural networks-prerequisites for adaptive behavior in a changing environment. However, the potential orchestration of these processes, particularly in humans, needs to be further characterized. Here, we use electrophysiological, behavioral, and molecular indices to noninvasively study cortical plasticity and network stability in humans. We observe indices of local strengthening of prior induced long-term potentiation-like plasticity (paired associative stimulation induced change in motor-evoked potential) and global network stabilization (homeostatic regulation of wake EEG theta activity) after brief periods of nonrapid eye movement sleep compared with wakefulness. The interplay of local sleep slow oscillations and spindle activity, previously related to synaptic refinements during sleep, is identified as a potential mechanism. Our findings are consistent with the notion that sleep-specific brain activity patterns reduce the plasticity-stability dilemma by orchestrating local plasticity and global stability of neural assemblies in the human cortex. Future studies are needed to further decipher the neural mechanisms underlying our indirect observations.

BACKGROUND: Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). OBJECTIVES: To determine whether pattern classification using SVMs facilitates predicting conversion to clinically definite multiple sclerosis (CDMS) from clinically isolated syndrome (CIS). METHODS: We used baseline MRI data from 364 patients with CIS, randomised to interferon beta-1b or placebo. Non-linear SVMs and 10-fold cross-validation were applied to predict converters/non-converters (175/189) at two years follow-up based on clinical and demographic data, lesion-specific quantitative geometric features and grey-matter-to-whole-brain volume ratios. We applied linear SVM analysis and leave-one-out cross-validation to subgroups of converters (n=25) and non-converters (n=44) based on cortical grey matter segmentations. RESULTS: Highest prediction accuracies of 70.4% (p=8e-5) were reached with a combination of lesion-specific geometric (image-based) and demographic/clinical features. Cortical grey matter was informative for the placebo group (acc.: 64.6%, p=0.002) but not for the interferon group. Classification based on demographic/clinical covariates only resulted in an accuracy of 56% (p=0.05). Overall, lesion geometry was more informative in the interferon group, EDSS and sex were more important for the placebo cohort. CONCLUSIONS: Alongside standard demographic and clinical measures, both lesion geometry and grey matter based information can aid prediction of conversion to CDMS.

A substantial proportion of cognitively healthy elders (HC) show abnormally high amyloid-β (Aβ) deposition, a major pathology of Alzheimer's disease (AD). These subjects are at increased risk of Alzheimer's disease (AD) dementia, and biomarkers are needed to predict their cognitive deterioration. Here we used relevance vector regression (RVR), a pattern-recognition method, to predict concurrent cognitive decline on the basis of longitudinal gray matter (GM) changes, within two a priori, meta-analytically defined functional networks subserving episodic memory and executive function. Ninety-six HC subjects were assessed annually for three years with structural MRI and cognitive tests within the Alzheimer's Disease Neuroimaging Initiative. Presence of abnormal biomarker values of Aβ (Aβ+) were determined with cerebrospinal fluid and amyloid-PET (HC-Aβ+, n=30; with n=66 for normal HC-Aβ-). Using leave-one-out cross-validation, we found that in HC-Aβ+ patterns of GM changes within both networks predicted decline in episodic memory (r=0.61, p

Acetylcholine is critically involved in modulating learning and memory function, which both decline in neurodegeneration. It remains unclear to what extent structural and functional changes in the cholinergic system contribute to episodic memory dysfunction in mild cognitive impairment (MCI), in addition to hippocampal degeneration. A better understanding is critical, given that the cholinergic system is the main target of current symptomatic treatment in mild to moderate Alzheimer's disease. We simultaneously assessed the structural and functional integrity of the cholinergic system in 20 patients with MCI and 20 matched healthy controls and examined their effect on verbal episodic memory via multivariate regression analyses. Mediating effects of either cholinergic function or hippocampal volume on the relationship between cholinergic structure and episodic memory were computed. In MCI, a less intact structure and function of the cholinergic system was found. A smaller cholinergic structure was significantly correlated with a functionally more active cholinergic system in patients, but not in controls. This association was not modulated by age or disease severity, arguing against compensational processes. Further analyses indicated that neither functional nor structural changes in the cholinergic system influence verbal episodic memory at the MCI stage. In fact, those associations were fully mediated by hippocampal volume. Although the cholinergic system is structurally and functionally altered in MCI, episodic memory dysfunction results primarily from hippocampal neurodegeneration, which may explain the inefficiency of cholinergic treatment at this disease stage.

Sleep is ubiquitous in animals and humans, but its function remains to be further determined. The synaptic homeostasis hypothesis of sleep–wake regulation proposes a homeostatic increase in net synaptic strength and cortical excitability along with decreased inducibility of associative synaptic long-term potentiation (LTP) due to saturation after sleep deprivation. Here we use electrophysiological, behavioural and molecular indices to non-invasively study net synaptic strength and LTP-like plasticity in humans after sleep and sleep deprivation. We demonstrate indices of increased net synaptic strength (TMS intensity to elicit a predefined amplitude of motor-evoked potential and EEG theta activity) and decreased LTP-like plasticity (paired associative stimulation induced change in motor-evoked potential and memory formation) after sleep deprivation. Changes in plasma BDNF are identified as a potential mechanism. Our study indicates that sleep recalibrates homeostatic and associative synaptic plasticity, believed to be the neural basis for adaptive behaviour, in humans., Sleep deprivation is believed to lead to homeostatic increases in synaptic strength and reduced inducibility of associative LTP, based mainly on findings from animal studies. Here, Kuhn et al. demonstrate similar sleep-dependent synaptic plasticity changes in humans along with altered plasma BDNF levels.

Detecting delirium in elderly emergency patients is critical to their outcome. The Nursing Delirium Screening Scale (Nu-DESC) is a short, feasible instrument that allows nurses to systematically screen for delirium. This is the first study to validate the Nu-DESC in a German emergency department (ED). The Nu-DESC was implemented in a high-volume, interdisciplinary German ED. A consecutively recruited sample of medical patients aged ≥ 70 years was screened by assigned nurses who performed the Nu-DESC as part of their daily work routine. The results were compared to a criterion standard diagnosis of delirium. According to the criterion standard diagnosis, delirium was present in 47 (14.9%) out of the 315 patients enrolled. The Nu-DESC shows a good specificity level of 91.0% (95% CI 87.0-94.2), but a moderate sensitivity level of 66.0% (95% CI 50.7-79.1). Positive and negative likelihood ratios are 7.37 (95% CI 4.77-11.36) and 0.37 (95% CI 0.25-0.56), respectively. In an exploratory analysis, we find that operationalizing the Nu-DESC item "disorientation" by specifically asking patients to state the day of the week and the name of the hospital unit would raise Nu-DESC sensitivity to 77.8%, with a specificity of 84.6% (positive and negative likelihood ratio of 5.05 and 0.26, respectively). The Nu-DESC shows good specificity but moderate sensitivity when performed by nurses during their daily work in a German ED. We have developed a modified Nu-DESC version, resulting in markedly enhanced sensitivity while maintaining a satisfactory level of specificity.

The identification of pathological atrophy in MRI scans requires specialized training, which is scarce outside dedicated centers. We sought to investigate the clinical usefulness of computer-generated representations of local grey matter (GM) loss or increased volume of cerebral fluids (CSF) as normalized deviations (z-scores) from healthy aging to either aid human visual readings or directly detect pathological atrophy. Two experienced neuroradiologists rated atrophy in 30 patients with Alzheimer's disease (AD), 30 patients with frontotemporal dementia (FTD), 30 with dementia due to Lewy-body disease (LBD) and 30 healthy controls (HC) on a three-point scale in 10 anatomical regions as reference gold standard. Seven raters, varying in their experience with MRI diagnostics rated all cases on the same scale once with and once without computer-generated volume deviation maps that were overlaid on anatomical slices. In addition, we investigated the predictive value of the computer generated deviation maps on their own for the detection of atrophy as identified by the gold standard raters. Inter and intra-rater agreements of the two gold standard raters were substantial (Cohen's kappa κ > 0.62). The intra-rater agreement of the other raters ranged from fair (κ = 0.37) to substantial (κ = 0.72) and improved on average by 0.13 (0.57, Highlights • The visual identification of atrophy is most accurate in the temporal lobe. • Voxel-wise deviations of tissue volume from normal aging is easy to implement. • Displaying voxel-wise deviations subjectively but not objectively aids readers. • Voxel-wise deviations themselves show high agreement with expert readings. • Information on tissue deviations should be provided with cerebral MRI scans.

In mild cognitive impairment (MCI), small benefits from cognitive training were observed for memory functions but there appears to be great variability in the response to treatment. Our study aimed to improve the characterization and selection of those participants who will benefit from cognitive intervention. We evaluated the predictive value of disease-specific biological factors for the outcome after cognitive training in MCI (n = 25) and also considered motivation of the participants. We compared the results of the cognitive intervention group with two independent control groups of MCI patients (local memory clinic, n = 20; ADNI cohort, n = 302). The primary outcome measure was episodic memory as measured by verbal delayed recall of a 10-word list. Episodic memory remained stable after treatment and slightly increased 6 months after the intervention. In contrast, in MCI patients who did not receive an intervention, episodic memory significantly decreased during the same time interval. A larger left entorhinal cortex predicted more improvement in episodic memory after treatment and so did higher levels of motivation. Adding disease-specific biological factors significantly improved the prediction of training-related change compared to a model based simply on age and baseline performance. Bootstrapping with resampling (n = 1000) verified the stability of our finding. Cognitive training might be particularly helpful in individuals with a bigger left entorhinal cortex as individuals who did not benefit from intervention showed 17% less volume in this area. When extended to alternative treatment options, stratification based on disease-specific biological factors is a useful step towards individualized medicine.

Older patients with depression or Alzheimer's disease (AD) at the stage of early dementia or mild cognitive impairment may present with objective cognitive impairment, although the pathology and thus therapy and prognosis differ substantially. In this study, we assessed the potential of an automated algorithm to categorize a test set of 65 T1-weighted structural magnetic resonance images (MRI). A convenience sample of elderly individuals fulfilling clinical criteria of either AD (n = 28) or moderate and severe depression (n = 37) was recruited from different settings to assess the potential of the pattern recognition method to assist in the differential diagnosis of AD versus depression. We found that our algorithm learned discriminative patterns in the subject's grey matter distribution reflected by an area under the receiver operator characteristics curve of up to 0.83 (confidence interval ranged from 0.67 to 0.92) and a balanced accuracy of 0.79 for the separation of depression from AD, evaluated by leave-one-out cross validation. The algorithm also identified consistent structural differences in a clinically more relevant scenario where the data used during training were independent from the data used for evaluation and, critically, which included five possible diagnoses (specifically AD, frontotemporal dementia, Lewy body dementia, depression, and healthy aging). While the output was insufficiently accurate to use it directly as a means for classification when multiple classes are possible, the continuous output computed by the machine learning algorithm differed between the two groups that were investigated. The automated analysis thus could complement, but not replace clinical assessments.

Background: The use of imaging markers for the diagnosis of predementia and early dementia stages of Alzheimer's disease (AD) has widely been explored in research settings and specialized care. The use of these markers in primary care has yet to be established. Objective: Summarize current evidence for the usefulness of imaging markers for AD in primary compared to specialized care settings. Method: Selective overview of the literature, and pilot data on the use of MRI-based hippocampus and basal forebrain volumetry for the discrimination of AD dementia and mild cognitive impairment (MCI) cases from healthy controls in 58 cases from a primary care cohort and 58 matched cases from a memory clinic's sample. Results: Molecular imaging marker of amyloid pathology, and volumetric markers of regional and whole brain atrophy support the diagnosis of AD dementia and MCI due to AD, and contribute to confidence in the differential diagnosis of AD and non-AD related dementias in specialized care. Limited evidence from the literature and our primary care cohort suggests that the diagnostic accuracy of volumetric imaging markers may be similar in the dementia stage of AD, but may be inferior for cases with MCI in primary compared with specialized care. Conclusion: Evidence is still widely lacking on the use of imaging markers for early and differential diagnosis of AD dementia, and detection of prodromal AD in primary care. Further progress to fill this gap will depend on the availability of international multimodal data from well-defined primary care cohorts.

Objective Executive deficits are frequent sequelae of neurological and psychiatric disorders, but their adequate neuropsychological assessment is still a matter of contention, given that executive tasks draw on a multitude of cognitive processes that are often not sufficiently specified. In line with this, results on psychometric properties of the Tower of London, a task measuring planning ability as a prototypical executive function, are equivocal and furthermore lacking completely for adult clinical populations. Methods We used a structurally balanced item set implemented in the Tower of London (Freiburg version, TOL-F) that accounts for major determinants of problem difficulty beyond the commonly used minimum number of moves to solution. Split-half reliability, internal consistency, and criterion-related concurrent validity of TOL-F accuracy were assessed in patients with stroke ( N =60), Parkinson syndrome ( N =51), and mild cognitive impairment ( N =29), and healthy adults ( N =155). Results Across samples, mean split-half and lower-bound indices of reliability of accuracy scores were adequate ( r ≥.7) or higher. Compared to a subset of healthy controls matched for age, sex, and education levels, deficits in planning accuracy emerged for all three clinical samples. Conclusions Based on consistently adequate reliability and a good criterion-related validity of accuracy scores, the TOL-F demonstrates its utility for testing planning ability in clinical samples and healthy adults. Using item sets systematically accounting for several determinants of task difficulty can thus significantly enhance the contended reliability of executive tasks and provide an opportunity to resolve the underspecification of cognitive processes contributing to executive functioning in health and disease.

Spatial disorientation is a frequent symptom in Alzheimer's disease and in mild cognitive impairment (MCI). In the clinical routine, spatial orientation is less often tested with real-world navigation but rather with 2D visuoconstructive tasks. However, reports about the association between the two types of tasks are sparse. Additionally, spatial disorientation has been linked to volume of the right hippocampus but it remains unclear whether right hippocampal subregions have differential involvement in real-world navigation. Yet, this would help uncover different functional roles of the subregions, which would have important implications for understanding the neuronal underpinnings of navigation skills. We compared patients with amnestic MCI (aMCI; n = 25) and healthy elderly controls (HC; n = 25) in a real-world navigation task that engaged different spatial processes. The association between real-world navigation and different visuoconstructive tasks was tested (i.e., figures from the Consortium to Establish a Registry for Alzheimer's Disease; CERAD, the Rey-Osterrieth Complex Figure task; and clock drawing). Furthermore, the relation between spatial navigation and volume of right hippocampal subregions was examined. Linear regression and relative weight analysis were applied for statistical analyses. Patients with aMCI were significantly less able to correctly navigate through a route compared to HC but had comparable map drawing and landmark recognition skills. The association between visuoconstructive tasks and real-world navigation was only significant when using the visuospatial memory component of the Rey figure. In aMCI, more volume of the right hippocampal tail was significantly associated with better navigation skills, while volume of the right CA2/3 region was a significant predictor in HC. Standard visuoconstructive tasks (e.g., the CERAD figures or clock drawing) are not sufficient to detect real-world spatial disabilities in aMCI. Consequently, more complex visuoconstructive tasks (i.e., the Rey figure) should be routinely included in the assessment of cognitive functions in the context of AD. Moreover, in those elderly individuals with impaired complex visuospatial memory, route finding behaviour should be evaluated in detail. Regarding the contribution of hippocampal subregions to spatial navigation, the right hippocampal tail seems to be particularly important for patients with aMCI, while the CA2/3 region appears to be more relevant in HC.

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be genetically confirmed with certainty decades before clinical onset. This allows the investigation of functional and structural changes in HD many years prior to disease onset, which may reveal important mechanistic insights into brain function, structure and organization in general. While regional atrophy is present at early stages of HD, it is still unclear if both hemispheres are equally affected by neurodegeneration and how the extent of asymmetry affects domain-specific functional decline. Here, we used whole-brain voxel-based analysis to investigate cross-sectional and longitudinal hemispheric asymmetries in grey matter (GM) volume in 56 manifest HD (mHD), 83 pre-manifest HD (preHD), and 80 healthy controls (HC). Furthermore, a regression analysis was used to assess the relationship between neuroanatomical asymmetries and decline in motor and cognitive measures across the disease spectrum. The cross-sectional analysis showed striatal leftward-biased GM atrophy in mHD, but not in preHD, relative to HC. Longitudinally, no net 36-month change in GM asymmetries was found in any of the groups. In the regression analysis, HD-related decline in quantitative-motor (Q-Motor) performance was linked to lower GM volume in the left superior parietal cortex. These findings suggest a stronger disease effect targeting the left hemisphere, especially in those with declining motor performance. This effect did not change over a period of three years and may indicate a compensatory role of the right hemisphere in line with recent functional imaging studies., Highlights • Reduced grey matter volume in left striatum was found in manifest HD at first visit. • 36-month data did not provide evidence for a shift in GM lateralization in HD. • Decline in motor performance in HD was linked to increased left parietal GM loss.

Background Errorless learning (EL) is a method for optimizing learning, which uses feed-forward instructions in order to prevent people from making mistakes during the learning process. The majority of previous studies on EL taught patients with dementia artificial tasks of little or no relevance for their daily lives. Furthermore, only a few controlled studies on EL have so far been performed and just a handful of studies have examined the long-term effects of EL. Tasks were not always trained in the patients’ natural or home environment, limiting the external validity of these studies. This multicenter parallel randomized controlled trial examines the effects of EL compared with trial and error learning (TEL) on the performance of activities of daily living in persons with Alzheimer’s or mixed-type dementia living at home. Methods Patients received nine 1-hour task training sessions over eight weeks using EL or TEL. Task performance was measured using video observations at week 16. Secondary outcome measures were task performance measured at week 26, satisfaction with treatment, need for assistance, challenging behavior, adverse events, resource utilization and treatment costs. Results A total of 161 participants were randomized, of whom 71 completed the EL and 74 the TEL arm at week 11. Sixty-nine EL patients and 71 TEL patients were assessed at the 16-week follow-up (the primary measurement endpoint). Intention-to-treat analysis showed a significantly improved task performance in both groups. No significant differences between the treatment groups were found for primary or secondary outcomes. Conclusions Structured relearning improved the performance of activities of daily living. Improvements were maintained for 6 months. EL had no additional effect over TEL. Trial registration German Register of Clinical Trials DRKS00003117. Registered 31 May 2011. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0247-9) contains supplementary material, which is available to authorized users.

Although episodic memory impairment is usually the earliest sign of Alzheimer's disease (AD), there are up to 15% of patients presenting with early impairment in non-memory cognitive functions (i.e., atypical AD). Stratifying patients with AD may aid clinical trials. Previous studies divided patients by cognitive profile, focusing on cross-sectional analyses without testing stability of clusters over time. We used principal component analysis followed by cluster analyses in 127 patients with AD based on 24 cognitive scores at 0, 6, 12, and 24 months follow-up. We investigated the definition of clusters and their stability over time as well as interactions of cluster assignment and disease severity. At each time point, six distinct factors and four distinct clusters were extracted that did not differ substantially between time points. Clusters were defined by cognitive profile rather than disease severity. 85% of patients fell into the same cluster twice, 42% three times, and 17% four times. Subjects with focal semantic impairment progressed significantly faster than the other cluster. Longitudinally, focal deficits increased relatively rather than tending toward average disease severity. The observed similar cluster definitions at each time point indicate the validity of the approach. Cluster-specific longitudinal increases of focal impairments and significant between-cluster differences in disease progression make this approach useful for stratified inclusion into clinical trials.

Histopathological studies in Alzheimer's disease (AD) suggest severe and region-specific neurodegeneration of the basal forebrain cholinergic system (BFCS). Here, we studied the between-center reliability and diagnostic accuracy of MRI-based BFCS volumetry in a large multicenter data set, including participants with prodromal (n = 41) or clinically manifest AD (n = 134) and 148 cognitively healthy controls. Atrophy was determined using voxel-based and region-of-interest based analyses of high-dimensionally normalized MRI scans using a newly created map of the BFCS based on postmortem in cranio MRI and histology. The AD group showed significant volume reductions of all subregions of the BFCS, which were most pronounced in the posterior nucleus basalis Meynert (NbM). The mild cognitive impairment-AD group showed pronounced volume reductions in the posterior NbM, but preserved volumes of anterior-medial regions. Diagnostic accuracy of posterior NbM volume was superior to hippocampus volume in both groups, despite higher multicenter variability of the BFCS measurements. The data of our study suggest that BFCS morphometry may provide an emerging biomarker in AD.

The early, preferably pre-clinical, identification of neurodegenerative diseases is important as treatment will be most successful before substantial neuronal loss. Here, we reasoned that functional brain changes as measured using functional magnetic resonance imaging (fMRI) will precede neurodegeneration. Three independent cohorts of patients with the genetic mutation leading to Huntington's Disease (HD) but without any clinical symptoms and matched controls performed three different fMRI tasks: Sequential finger tapping engaged the motor system, which is primarily affected by HD, whereas a working-memory task and a task aiming to induce irritation represented the range of low- and high-level cognitive functions also affected by HD. Each diagnostic group of every cohort included 11-16 subjects. After segmentation into 76 cortical and 14 subcortical regions, we extracted functional connectivity patterns through pairwise correlation between the signals in the regions. The resulting coefficients were directly embedded as input to a pattern classifier aiming to separate controls from gene mutation carriers. Alternatively, graph-theory measures such as degree and clustering coefficient were used as features for the discrimination. Classification accuracy never outperformed the accuracy of a grouping based on parameter estimates from a general-linear model approach or a grouping based on features extracted from anatomical images as reported in a previous analysis. Despite good within-subject stability between two runs of the same task, a high between-subject variability led to chance-level accuracy. These results indicate that standard graph-metrics are insufficient to detect subtle disease related changes when within-group variability is high. Developing methods that reduce variability related to noise should be the focus of future studies.

Background Individuals with subjective memory impairment (SMI) report worsening of memory without impairment in cognitive tests. Despite normal cognitive performance, they may be at higher risk of cognitive decline compared with individuals without SMI. Methods We used a discriminative function (a support vector machine) trained on an independent data set of 226 healthy control subjects and 191 patients with probable Alzheimer's disease (AD) dementia to characterize the baseline gray matter patterns of 24 individuals with SMI and 53 control subjects. We tested for associations of these gray matter patterns with SMI presence, cognitive performance at baseline, and cognitive decline at follow-up. Results Individuals with SMI showed greater similarity to an AD gray matter pattern compared with control subjects without SMI. In addition, episodic memory decline was associated with an AD gray matter pattern in the SMI group. Conclusions Our results indicate a link between the gray matter atrophy pattern of patients with AD and the presence of SMI. Furthermore, multivariate pattern recognition approaches seem to be a sensitive method for identifying subtle brain changes that correspond to future memory decline in SMI.

The availability of an accurate genetic test to identify Huntington's Disease (HD) in the pre-symptomatic stage makes HD an important model to develop biomarkers for other neurodegenerative diseases, such as pre-clinical Alzheimer's Disease. We reasoned that functional changes, measured by functional MRI (fMRI), would precede gray matter changes and that performing a task specifically affected by the disease would carry the clearest signature. Separate cohorts of HD gene mutations carriers and controls performed four different fMRI tasks, probing functions either primarly affected by the disease (i.e. motor control), higher cognitive functions (i.e. working memory and irritability), or basic sensory functions (i.e. auditory system). With the aim to compare fMRI and structural MRI biomarkers, all subjects underwent an additional high-resolution T1-weighted MRI. Best classification performance was achived from fMRI-based activations with motor sequence tapping and task-induced irritation. Classification performance based on gray matter probability maps was also significantly above chance and similar to that of fMRI. Both were sufficiently informative to separate gene mutation carriers that were on average 17 years before predicted disease onset from controls with up to 80% accuracy. Further analyses showed that classification accuracy was best in regions of interest with low within-group heterogeneity in relation to disease specific changes. Our study indicates that structural and some functional markers can accurately detect pre-clinical neurodegeneration. However, the lower variability and easier processing of the strucutral MRI data make latter the more useful tool for disease detection in a clinical setting.

Background: Based on animal research several authors have warned that the application of methylphenidate, the first-line drug for the treatment of attention-deficit/hyperactivity disorder (ADHD), might have neurotoxic effects potentially harming the brain. We investigated whether methylphenidate application, over a 1-year period, results in cerebral volume decrease. Methods: We acquired structural MRIs in a double-blind study comparing methylphenidate to placebo. Global and regional brain volumes were analyzed at baseline, after 3 months and after 12 months using diffeomorphic anatomic registration through exponentiated lie algebra. Results: We included 131 adult patients with ADHD into the baseline sample, 98 into the 3-month sample (54 in the methylphenidate cohort and 44 in the placebo cohort) and 76 into the 1-year sample (37 in the methylphenidate cohort and 29 in the placebo cohort). Methylphenidate intake compared with placebo did not lead to any detectable cerebral volume loss; there was a trend toward bilateral cerebellar grey matter increase. Limitations: Detecting possible neurotoxic effects of methylphenidate might require a longer observation period. Conclusion: There is no evidence of grey matter volume loss after 1 year of methylphenidate treatment in adult patients with ADHD.

Arousal and sleep are fundamental physiological processes, and their modulation is of high clinical significance. This study tested the hypothesis that total sleep time in humans can be modulated by the non-invasive brain stimulation technique transcranial direct current stimulation (tDCS) targeting a 'top-down' cortico-thalamic pathway of sleep-wake regulation. Nineteen healthy participants underwent a within-subject, repeated-measures protocol across five nights in the sleep laboratory with polysomnographic monitoring (adaptation, baseline, three experimental nights). tDCS was delivered via bi-frontal target electrodes and bi-parietal return electrodes prior to sleep (anodal 'activation', cathodal 'deactivation' and sham stimulation). Bi-frontal anodal stimulation significantly decreased total sleep time, compared to cathodal and sham stimulation. This effect was location specific. Bi-frontal cathodal stimulation did not significantly increase total sleep time, potentially due to ceiling effects in good sleepers. Exploratory resting-state EEG analyses prior to and after the tDCS protocols were consistent with the notion of increased cortical arousal after anodal stimulation and decreased cortical arousal after cathodal stimulation. The study provides proof-of-concept that total sleep time can be decreased by non-invasive bi-frontal anodal tDCS in healthy humans. Further elucidating the 'top-down' pathway of sleep-wake regulation is expected to increase knowledge on the fundamentals of sleep-wake regulation and to contribute to the development of novel treatments for clinical conditions of disturbed arousal and sleep.Neuropsychopharmacology accepted article preview online, 04 May 2016. doi:10.1038/npp.2016.65.

The exploration and retrieval of words during category fluency involves different strategies to improve or maintain performance. Deficits in that task, which are common in patients with amnestic mild cognitive impairment (aMCI), mirror either impaired semantic memory or dysfunctional executive control mechanisms. Relating category fluency to tasks that place greater demands on either semantic knowledge or executive functions might help to determine the underlying cognitive process. The aims of this study were to compare performance and strategy use of 20 patients with aMCI to 30 healthy elderly controls (HC) and to identify the dominant component (either executive or semantic) for better task performance in category fluency. Thus, the relationship between category fluency, design fluency and naming was examined. As fluency tasks have been associated with the superior frontal gyrus (SFG), the inferior frontal gyrus (IFG), and the temporal pole, we further explored the relationship between gray matter volume in these areas and both performance and strategy use. Patients with aMCI showed significantly lower performance and significantly less strategy use during fluency tasks compared to HC. However, both groups equally improved their performance when repeatedly confronted with the same task. In aMCI, performance during category fluency was significantly predicted by design fluency performance, while in HC, it was significantly predicted by naming performance. In HC, volume of the SFG significantly predicted both category and design fluency performance, and strategy use during design fluency. In aMCI, the SFG and the IFG predicted performance during both category and design fluency. The IFG significantly predicted strategy use during category fluency in both groups. The reduced category fluency performance in aMCI seems to be primarily due to dysfunctional executive control mechanisms rather than impaired semantic knowledge. This finding is directly relevant to patients in the different stages of Alzheimer's disease as it links the known semantic fluency deficit in this population to executive functions. Although patients with aMCI are impaired in both performance and strategy use compared to HC, they are able to increase performance over time. However, only HC were able to significantly improve the utilization of fluency strategies in both category and design fluency over time. HC seem to rely more heavily on the SFG during fluency tasks, while in patients with aMCI additional frontal brain areas are involved, possibly reflecting compensational processes.

Visual neglect after left-hemispheric lesion is thought to be less frequent, less severe, and shorter lived than visuospatial attention deficits resulting from right-hemispheric lesions. However, reports exist opposing this assumption, and it is unclear how these findings fit into the current theories of visuospatial processing. Furthermore, only little is known about the exact structure-function relationship between visuospatial attention deficits and left-hemispheric stroke. We investigated neglect in 121 patients with acute left-hemispheric ischemic stroke by following clinical development from within the first 24 h of stroke onset until hospital discharge. Visuospatial attention deficits occurred in 17.4 % (n = 21). Voxel-based lesion-symptom mapping associated visual neglect to the right with lesion in the left superior and middle temporal gyrus, temporal pole, frontal operculum, and insula. Neglect severity, captured by the Center of Cancellation Score of the Bells test, was associated with lesion in the left anterior temporal lobe and the left frontal operculum. The left-hemispheric lesion pattern of neglect thus involves areas of the ventral attention system and partly mirrors the critical regions of the right hemisphere known to be associated with neglect. Based on our prospective analysis on a large cohort of patients with left-hemispheric stroke, this study shows that in a remarkable number of patients, the left hemisphere essentially contributes to an intact representation of space and clarifies the impact of the distinct left-hemispheric structures involved in visuospatial processing.

Diffusion tensor imaging (DTI) detects microstructural changes of the cerebral white matter in Alzheimer's disease (AD). The use of DTI for the diagnosis of AD in a multicenter setting has not yet been investigated. We used voxel-based analysis of fractional anisotropy, mean diffusivity, and grey matter volumes from multimodal magnetic resonance imaging data of 137 AD patients and 143 healthy elderly controls collected across 9 different scanners. We compared different univariate analysis approaches to model the effect of scanner, including a linear model across all scans with a scanner covariate, a random effects model with scanner as a random variable as well as a voxel-based meta-analysis. We found significant reduction of fractional anisotropy and significant increase of mean diffusivity in core areas of AD pathology including corpus callosum, medial and lateral temporal lobes, as well as fornix, cingulate gyrus, precuneus, and prefrontal lobe white matter. Grey matter atrophy was most pronounced in medial and lateral temporal lobe as well as parietal and prefrontal association cortex. The effects of group were spatially more restricted with random effects modeling of scanner effects compared to simple pooled analysis. All three analysis approaches yielded similar accuracy of group separation in block-wise cross-validated logistic regression. Our results suggest similar effects of center on group separation based on different analysis approaches and confirm a typical pattern of cortical and subcortical microstructural changes in AD using a large multimodal multicenter data set.

Attention-Deficit/Hyperactivity Disorder (ADHD) is marked by inhibitory and attentional deficits which can persist into adulthood. Those deficits have been associated with dysfunctional fronto-striatal and fronto-parietal circuits. The present study sought to delineate neural correlates of component specific inhibitory deficits in adult ADHD using functional magnetic resonance imaging (fMRI). 20 adult ADHD patients and 24 matched healthy controls were included. Brain activation was assessed during three stages of behavioral inhibition, i.e. interference inhibition (Simon task), action withholding (Go/no-go task) and action cancelation (Stop-signal task). Behaviorally, ADHD patients were affected in all tasks. Impaired interference inhibition was associated with hypoactivation in parietal and medial frontal regions. During action withholding and cancelation ADHD patients displayed hypoactivation in a fronto-striatal network. These findings support the notion of at least two disturbed neural circuits in ADHD differentially associated with deficits in separate inhibitory subcomponents. Thereby, deficits in inhibitory subcomponents which are closely connected to response interference were related to hypofunction in more attention related circuits, while stopping related deficits were rather associated with hypofunction in inhibitory circuits.

Univariate analyses have identified gray matter (GM) alterations in different groups of MS patients. While these methods detect differences on the basis of the single voxel or cluster, multivariate methods like support vector machines (SVM) identify the complex neuroanatomical patterns of GM differences. Using multivariate linear SVM analysis and leave-one-out cross-validation, we aimed at identifying neuroanatomical GM patterns relevant for individual classification of MS patients. We used SVM to separate GM segmentations of T1-weighted three-dimensional magnetic resonance (MR) imaging scans within different age- and sex-matched groups of MS patients with either early (n = 17) or late MS (n = 17) (contrast I), low (n = 20) or high (n = 20) white matter lesion load (contrast II), and benign MS (BMS, n = 13) or non-benign MS (NBMS, n = 13) (contrast III) scanned on a single 1.5 T MR scanner. GM patterns most relevant for individual separation of MS patients comprised cortical areas of all the cerebral lobes as well as deep GM structures, including the thalamus and caudate. The patterns detected were sufficiently informative to separate individuals of the respective groups with high sensitivity and specificity in 85% (contrast I), 83% (contrast II) and 77% (contrast III) of cases. The study demonstrates that neuroanatomical spatial patterns of GM segmentations contain information sufficient for correct classification of MS patients at the single case level, thus making multivariate SVM analysis a promising clinical application.

Purpose: To evaluate the feasibility of multicenter tractography of the cingulate bundle (CB) in Alzheimer's disease (AD). Materials and Methods: Automated deterministic tractography of the CB was applied to scans of 45 patients with probable AD and 58 healthy controls (HC) acquired with Siemens Sonata (1.5T; 60 gradients), Trio (3T; 61 gradients), and Avanto (1.5T; 30 gradients). Diagnosis and center effects on the tracking indices fractional anisotropy (FA), mean diffusivity (MD), track density, and volume were estimated with analysis of variance. Results: The multicenter coefficients of variance (CVs) in HC and AD patients were 7% and 7% for FA, 10% and 8% for MD, 18% and 20% for density, and 21% and 21% for volume. Multicenter and single-center CVs were within a similar range. Significant center effects declined in the order MD > FA > density > volume. After adjustment for center and age, the AD group showed significantly higher MD (P < 0.001) and lower FA (P < 0.05) as compared with the HC group. Conclusion: Despite strong center effects, we detected significantly altered microstructural integrity of the CB in AD patients. Diffusion-tensor imaging indices of the CB as obtained by automated tractography might qualify as a biologically sustained surrogate marker for diagnostic and monitoring purposes in multicenter AD trials. J. Magn. Reson. Imaging 2012;36:84–91. © 2012 Wiley Periodicals Inc.

The European DTI Study on Dementia (EDSD) is a multicenter framework created to study the diagnostic accuracy and inter-site variability of DTI-derived markers in patients with manifest and prodromal Alzheimer's disease (AD). The dynamically growing database presently includes 493 DTI, 512 T1-weighted MRI, and 300 FLAIR scans from patients with AD dementia, patients with Mild Cognitive Impairment (MCI) and matched Healthy Controls, acquired on 13 different scanner platforms. The imaging data is publicly available, along with the subjects' demographic and clinical characterization. Detailed neuropsychological information, cerebrospinal fluid information on biomarkers and clinical follow-up diagnoses are included for a subset of subjects. This paper describes the rationale and structure of the EDSD, summarizes the available data, and explains how to gain access to the database. The EDSD is a useful database for researchers seeking to investigate the contribution of DTI to dementia diagnostics.

White matter hyperintensities (WMH) are the focus of intensive research and have been linked to cognitive impairment and depression in the elderly. Cumbersome manual outlining procedures make research on WMH labour intensive and prone to subjective bias. This study compares fully automated supervised detection methods that learn to identify WMH from manual examples against unsupervised approaches on the combination of FLAIR and T1 weighted images. Data were collected from ten subjects with mild cognitive impairment and another set of ten individuals who fulfilled diagnostic criteria for dementia. Data were split into balanced groups to create a training set used to optimize the different methods. Manual outlining served as gold standard to evaluate performance of the automated methods that identified each voxel either as intact or as part of a WMH. Otsu's approach for multiple thresholds which is based only on voxel intensities of the FLAIR image produced a high number of false positives at grey matter boundaries. Performance on an independent test set was similarly disappointing when simply applying a threshold to the FLAIR that was found from training data. Among the supervised methods, precision-recall curves of support vector machines (SVM) indicated advantages over the performance achieved by K-nearest-neighbor classifiers (KNN). The curves indicated a clear benefit from optimizing the threshold of the SVM decision value and the voting rule of the KNN. Best performance was reached by selecting training voxels according to their distance to the lesion boundary and repeated training after replacing the feature vectors from those voxels that did not form support vectors of the SVM. The study demonstrates advantages of SVM for the problem of detecting WMH at least for studies that include only FLAIR and T1 weighted images. Various optimization strategies are discussed and compared against each other.

Neuroimaging studies of subjects who are gene-expanded for Huntington Disease, but not yet diagnosed (termed prodromal HD), report that the cortex is "spared," despite the decrement in striatal and cerebral white-matter volume. Measurement of whole-cortex volume can mask more subtle, but potentially clinically relevant regional changes in volume, thinning, or surface area. The current study addressed this limitation by evaluating cortical morphology of 523 prodromal HD subjects. Participants included 693 individuals enrolled in the PREDICT-HD protocol. Of these participants, 523 carried the HD gene mutation (prodromal HD group); the remaining 170 were non gene-expanded and served as the comparison group. Based on age and CAG repeat length, gene-expanded subjects were categorized as "Far from onset," "Midway to onset," "Near onset," and "already diagnosed." MRI scans were processed using FreeSurfer. Cortical volume, thickness, and surface area were not significantly different between the Far from onset group and controls. However, beginning in the Midway to onset group, the cortex showed significant volume decrement, affecting most the posterior and superior cerebral regions. This pattern progressed when evaluating the groups further into the disease process. Areas that remained mostly unaffected included ventral and medial regions of the frontal and temporal cortex. Morphologic changes were mostly in thinning as surface area did not substantially change in most regions. Early in the course of HD, the cortex shows changes that are manifest as cortical thinning and are most robust in the posterior and superior regions of the cerebrum.

Huntington disease (HD) is a fatal neurodegenerative disorder caused by an expanded CAG repeat. Its length can be used to estimate the time of clinical diagnosis, which is defined by overt motor symptoms. Non-motor symptoms begin before motor onset, and involve changes in hypothalamus-regulated functions such as sleep, emotion and metabolism. Therefore we hypothesized that hypothalamic changes occur already prior to the clinical diagnosis. We performed voxel-based morphometry and logistic regression analyses of cross-sectional MR images from 220 HD gene carriers and 75 controls in the Predict-HD study. We show that changes in the hypothalamic region are detectable before clinical diagnosis and that its grey matter contents alone are sufficient to distinguish HD gene carriers from control cases. In conclusion, our study shows, for the first time, that alterations in grey matter contents in the hypothalamic region occur at least a decade before clinical diagnosis in HD using MRI.

Healthy sleep restores the brain's ability to adapt to novel input through memory formation based on activity-dependent refinements of the strength of neural transmission across synapses (synaptic plasticity). In line with this framework, patients with primary insomnia often report subjective memory impairment. However, investigations of memory performance did not produce conclusive results. The aim of this study was to further investigate memory performance in patients with primary insomnia in comparison to healthy controls, using two well-characterized learning tasks, a declarative virtual water maze task and emotional fear conditioning. Twenty patients with primary insomnia according to DSM-IV criteria (17 females, three males, 43.5 ± 13.0 years) and 20 good sleeper controls (17 females, three males, 41.7 ± 12.8 years) were investigated in a parallel-group study. All participants completed a hippocampus-dependent virtual Morris water maze task and amygdala-dependent classical fear conditioning. Patients with insomnia showed significantly delayed memory acquisition in the virtual water maze task, but no significant difference in fear acquisition compared with controls. These findings are consistent with the notion that memory processes that emerge from synaptic refinements in a hippocampal-neocortical network are particularly sensitive to chronic disruptions of sleep, while those in a basic emotional amygdala-dependent network may be more resilient.

The early identification of brain anatomy deviating from the normal pattern of growth and atrophy, such as in Alzheimer's disease (AD), has the potential to improve clinical outcomes through early intervention. Recently, Davatzikos et al. (2009) supported the hypothesis that pathologic atrophy in AD is an accelerated aging process, implying accelerated brain atrophy. In order to recognize faster brain atrophy, a model of healthy brain aging is needed first. Here, we introduce a framework for automatically and efficiently estimating the age of healthy subjects from their T(1)-weighted MRI scans using a kernel method for regression. This method was tested on over 650 healthy subjects, aged 19-86 years, and collected from four different scanners. Furthermore, the influence of various parameters on estimation accuracy was analyzed. Our age estimation framework included automatic preprocessing of the T(1)-weighted images, dimension reduction via principal component analysis, training of a relevance vector machine (RVM; Tipping, 2000) for regression, and finally estimating the age of the subjects from the test samples. The framework proved to be a reliable, scanner-independent, and efficient method for age estimation in healthy subjects, yielding a correlation of r=0.92 between the estimated and the real age in the test samples and a mean absolute error of 5 years. The results indicated favorable performance of the RVM and identified the number of training samples as the critical factor for prediction accuracy. Applying the framework to people with mild AD resulted in a mean brain age gap estimate (BrainAGE) score of +10 years.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale—Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P

BACKGROUND AND PURPOSE: VBM is increasingly used in the study of neurodegeneration, and recently there has been interest in its potential as a biomarker. However, although it is largely “automated,” VBM is rarely implemented consistently across studies, and changing user-specified options can alter the results in a way similar to the very biologic differences under investigation. MATERIALS AND METHODS: This work uses data from patients with HD to demonstrate the effects of several user-specified VBM parameters and analyses: type and level of statistical correction, modulation, smoothing kernel size, adjustment for brain size, subgroup analysis, and software version. RESULTS: The results demonstrate that changing these options can alter results in a way similar to the biologic differences under investigation. CONCLUSIONS: If VBM is to be useful clinically or considered for use as a biomarker, there is a need for greater recognition of these issues and more uniformity in its application for the method to be both reproducible and valid. CAG : cytosine adenine guanine DARTEL : Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra EHDN : European Huntington' Disease Network FDR : false discovery rate FWE : family-wise error FWHM : full width at half-maximum GM : gray matter HD : Huntington disease Mod. : modulation NA : not applicable SPM : statistical parametric mapping/statistical parametric map TFC : total functional capacity TIV : total intracranial volume UHDRS : Unified Huntington Disease Rating Scale Uncor. : uncorrected VBM : voxel-based morphometry