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Sleep research has evolved considerably since the first sleep electroencephalography (EEG) recordings in the 1930s and the discovery of well-distinguishable sleep stages in the 1950s. While electrophysiological recordings have been used to describe the sleeping brain in much detail, since the 1990s neuroimaging techniques are applied to uncover the brain organization and functional connectivity of human sleep with greater spatial resolution. The combination of EEG with different neuroimaging modalities such as Positron Emission Tomography (PET), structural MRI (sMRI) and functional Magnetic Resonance Imaging (fMRI) impose several challenges for sleep studies. For instance, difficulties maintaining and consolidating sleep in an unfamiliar and restricted environment, scanner-related distortions with physiological artifacts may contaminate polysomnography recordings, and the necessity to account for all physiological changes throughout the sleep cycles to better data interpretability. Here, we review the field of sleep neuroimaging in healthy non-sleep-deprived populations, from early findings to more recent developments, discuss the challenges of applying concurrent EEG and imaging techniques to sleep, and possible future directions the field will greatly benefit from.

The diameter of the human pupil tracks working memory processing and is associated with activity in the frontoparietal network. At the same time, recent neuroimaging research has linked human pupil fluctuations to activity in the salience network. In this combined functional magnetic resonance imaging (fMRI)/pupillometry study, we recorded the pupil size of healthy human participants while they performed a blockwise organized working memory task (N‐back) inside an MRI scanner in order to monitor the pupil fluctuations associated neural activity during working memory processing. We first confirmed that mean pupil size closely followed working memory load. Combining this with fMRI data, we focused on blood oxygen level dependent (BOLD) correlates of mean pupil size modeled onto the task blocks as a parametric modulation. Interrogating this modulated task regressor, we were able to retrieve the frontoparietal network. Next, to fully exploit the within‐block dynamics, we divided the blocks into 1 s time bins and filled these with corresponding pupil change values (first‐order derivative of pupil size). We found that pupil change within N‐back blocks was positively correlated with BOLD amplitudes in the areas of the salience network (namely bilateral insula, and anterior cingulate cortex). Taken together, fMRI with simultaneous measurement of pupil parameters constitutes a valuable tool to dissect working memory subprocesses related to both working memory load and salience of the presented stimuli., The present report is a combined functional magnetic resonance imaging/pupillometry study investigating neural correlates of pupil fluctuations during working memory processing. We showed that pupil size between task conditions with varying working memory load correlates with the frontoparietal network and pupil change within conditions correlates with the salience network. This combined setup allows for a differentiation between working memory subprocesses related to cognitive load and salience of the presented stimuli.

Background A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are “transdiagnostic”, meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications. Methods BeCOME intends to include at least 1000 individuals with a broad spectrum of affective, anxiety and stress-related mental disorders as well as 500 individuals unaffected by mental disorders. After a screening visit, all participants undergo in-depth phenotyping procedures and omics assessments on two consecutive days. Several validated paradigms (e.g., fear conditioning, reward anticipation, imaging stress test, social reward learning task) are applied to stimulate a response in a basic system of human functioning (e.g., acute threat response, reward processing, stress response or social reward learning) that plays a key role in the development of affective, anxiety and stress-related mental disorders. The response to this stimulation is then read out across multiple levels. Assessments comprise genetic, molecular, cellular, physiological, neuroimaging, neurocognitive, psychophysiological and psychometric measurements. The multilevel information collected in BeCOME will be used to identify data-driven biologically-informed categories of mental disorders using cluster analytical techniques. Discussion The novelty of BeCOME lies in the dynamic in-depth phenotyping and omics characterization of individuals with mental disorders from the depression and anxiety spectrum of varying severity. We believe that such biology-based subclasses of mental disorders will serve as better treatment targets than purely symptom-based disease entities, and help in tailoring the right treatment to the individual patient suffering from a mental disorder. BeCOME has the potential to contribute to a novel taxonomy of mental disorders that integrates the underlying pathomechanisms into diagnoses. Trial registration Retrospectively registered on June 12, 2019 on ClinicalTrials.gov (TRN: NCT03984084).

BACKGROUND Conventional T2 *-weighted functional magnetic resonance imaging (fMRI) is performed with echo-planar imaging (EPI) sequences that create substantial acoustic noise. The loud acoustic noise not only affects the activation of the auditory cortex, but may also interfere with resting state and task fMRI experiments. PURPOSE To demonstrate the feasibility of a novel, quiet, T2 *, whole-brain blood oxygenation level-dependent (BOLD)-fMRI method, termed Looping Star, compared to conventional multislice gradient-echo EPI. STUDY TYPE Prospective. PHANTOM/SUBJECTS Glover stability QA phantom; 10 healthy volunteers. FIELD STRENGTH/SEQUENCE 3.0T: gradient echo (GE)-EPI and T2 * Looping Star fMRI. ASSESSMENT Looping Star fMRI was presented and compared to GE-EPI with a working memory (WM) task and resting state (RS) experiments. Temporal stability and acoustic measurements were obtained for both methods. Functional maps and activation accuracy were compared to evaluate the performance of the novel sequence. STATISTICAL TESTS Mean and standard deviation values were analyzed for temporal stability and acoustic noise tests. Activation maps were assessed with one-sample t-tests and contrast estimates (CE). Paired t-tests and receiver operator characteristic (ROC) were used to compare fMRI sensitivity and performance. RESULTS Looping Star presented a 98% reduction in sound pressure compared with GE-EPI, with stable temporal stability (0.09% percent fluctuation), but reduced temporal signal-to-noise ratio (tSNR) (mean difference = 15.9%). The novel method yielded consistent activations for RS and WM (83.4% and 69.5% relative BOLD sensitivity), which increased with task difficulty (mean CE 2-back = 0.56 vs. 0-back = 0.08, P

Fear-related disorders are characterized by hyperexcitability in reflexive circuits and maladaptive associative learning mechanisms. The startle reflex is suited to investigate both processes, either by probing it under baseline conditions or by deriving it in fear conditioning studies. In anxiety research, the amplitude of the fear-potentiated startle has been shown to be influenced by amygdalar circuits and has typically been the readout of interest. In schizophrenia research, prolonged startle peak latency under neutral conditions is an established readout, thought to reflect impaired processing speed. We therefore explored whether startle latency is an informative readout for human anxiety research.We investigated potential similarities and differences of startle peak latency and amplitude derived from a classical fear conditioning task in a sample of 206 participants with varying severity levels of anxiety disorders and healthy control subjects. We first reduced startle response to stable components and regressed individual amygdala gray matter volumes onto the resulting startle measures. We then probed time, stimulus, and group effects of startle latency.We showed that startle latency and startle amplitude were 2 largely uncorrelated measures; startle latency, but not amplitude, showed a sex-specific association with gray matter volume of the amygdala; startle latencies showed a fear-dependent task modulation; and patients with fear-related disorders displayed shorter startle latencies throughout the fear learning task.These data provide support for the notion that probing startle latencies under threat may engage amygdala-modulated threat processing, making them a complementary marker for human anxiety research.

Although mice mostly communicate in the ultrasonic range, they also emit audible calls. We demonstrate that mice selectively bred for high anxiety-related behavior (HAB) have a high disposition for emitting sonic calls when caught by the tail. The vocalization was unrelated to pain but sensitive to anxiolytics. As revealed by manganese-enhanced MRI, HAB mice displayed an increased tonic activity of the periaqueductal gray (PAG). Selective inhibition of the dorsolateral PAG not only reduced anxiety-like behavior but also completely abolished sonic vocalization. Calls were emitted at a fundamental frequency of 3.8 kHz, which falls into the hearing range of numerous predators. Indeed, playback of sonic vocalization attracted rats if associated with a stimulus mouse. If played back to HAB mice, sonic calls were repellent in the absence of a conspecific but attractive in their presence. Our data demonstrate that sonic vocalization attracts both predators and conspecifics depending on the context.

Maladaptive stress responses are important risk factors in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk.Using an established psychosocial stress task flanked by two resting states, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 participants with and without mood and anxiety disorders. To estimate blockwise changes in stress-induced activation and FC, we used hierarchical mixed-effects models based on denoised time series within predefined stress-related regions. We predicted inter- and intraindividual differences in stress phases (anticipation vs. stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines.We identified four subnetworks showing distinct changes in FC over time. FC but not activation trajectories predicted the stress phase (accuracy = 70%, pSpatiotemporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension of negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.

BackgroundChronic stress is an important risk factor in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk.MethodsUsing an established psycho-social stress task flanked by two resting-state scans, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 unmedicated participants with and without mood and anxiety disorders. To estimate block-wise changes in stress-induced brain activation and FC, we used hierarchical mixed-effects models based on denoised timeseries within a predefined stress network. We predicted inter- and intra-individual differences in stress phases (anticipation vs. acute stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines.ResultsWe identified four subnetworks showing distinct changes in FC over time. Subnetwork trajectories predicted the stress phase (accuracy: 71%,ppermR2=.10,ppermR2=.08,pperm=.009), but not the presence or absence of a mood and anxiety disorder.ConclusionsSpatio-temporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.

Post-traumatic stress disorder (PTSD) is a chronic disease caused by traumatic incidents. Numerous studies have revealed grey matter volume differences in affected individuals. The nature of the disease renders it difficult to distinguish between a priori versus a posteriori changes. To overcome this difficulty, we studied the consequences of a traumatic event on brain morphology in mice before and 4 weeks after exposure to brief foot shocks (or sham treatment), and correlated morphology with symptoms of hyperarousal. In the latter context, we assessed hyperarousal upon confrontation with acoustic, visual, or composite (acoustic/visual/tactile) threats and integrated the individual readouts into a single Hyperarousal Score using logistic regression analysis. MRI scans with subsequent whole-brain deformation-based morphometry (DBM) analysis revealed a volume decrease of the dorsal hippocampus and an increase of the reticular nucleus in shocked mice when compared to non-shocked controls. Using the Hyperarousal Score as regressor for the post-exposure MRI measurement, we observed negative correlations with several brain structures including the dorsal hippocampus. If the development of changes with respect to the basal MRI was considered, reduction in globus pallidus volume reflected hyperarousal severity. Our findings demonstrate that a brief traumatic incident can cause volume changes in defined brain structures and suggest the globus pallidus as an important hub for the control of fear responses to threatening stimuli of different sensory modalities.

Mnemonic training boosts long-lasting memories, supported by optimized brain processing and consolidation., Mnemonic techniques, such as the method of loci, can powerfully boost memory. We compared memory athletes ranked among the world’s top 50 in memory sports to mnemonics-naïve controls. In a second study, participants completed a 6-week memory training, working memory training, or no intervention. Behaviorally, memory training enhanced durable, longer-lasting memories. Functional magnetic resonance imaging during encoding and recognition revealed task-based activation decreases in lateral prefrontal, as well as in parahippocampal and retrosplenial cortices in both memory athletes and participants after memory training, partly associated with better performance after 4 months. This was complemented by hippocampal-neocortical coupling during consolidation, which was stronger the more durable memories participants formed. Our findings advance knowledge on how mnemonic training boosts durable memory formation through decreased task-based activation and increased consolidation thereafter. This is in line with conceptual accounts of neural efficiency and highlights a complex interplay of neural processes critical for extraordinary memory.

Stress is an everyday experience and maladaptive responses play a crucial role in the etiology of affective disorders. Despite its ubiquity, the neural underpinnings of subjective stress experiences have not yet been elucidated, particularly at an individual level. In an important advance, Goldfarb et al.1showed recently that subjective stress and arousal levels in response to threatening stimuli were successfully predicted based on changes in hippocampal connectivity during the task using a machine learning approach. Crucially, stress responses were predicted by interpretable hippocampal connectivity networks, shedding new light on the role of the hippocampus in regulating stress reactivity2. However, the authors induced stress by displaying aversive pictures, while stress research often relies on the extensively validated Trier social stress task (TSST)3. The TSST incorporates crucial factors such as unpredictability of success and the social-evaluative threat of the stressor thereby eliciting cortisol responses more robustly compared to threatening images4. Towards generalization, cross validation within a sample as conducted by Goldfarb et al.1or independent replications are important steps, but the generalizability to different stressors allows to draw broader conclusions about the potential use of hippocampal connectivity to predict subjective stress5. Arguably, translating these findings to clinical applications would require a broad generalization of the results or the prediction algorithm to psychosocial stress. Here, we assessed the predictive performance of Goldfarb et al’s1algorithm for subjective stress in an independent sample using an MR adaption of the TSST6,7. In line with Goldfarb et al.1, we observed robust stress-induced changes in hippocampal connectivity. However, the spatial correlation of the changes in connectivity was low indicating little convergence across alleged stress paradigms. Critically, stress-induced changes of hippocampal connectivity were not robustly predictive of subjective stress across a multiverse of analyses based on connectivity changes. Collectively, this indicates that the generalizability of the reported stress connectivity fingerprint to other stressors is limited at best, suggesting that specific tasks might require tailored algorithms to robustly predict stress above chance levels.

BACKGROUND Stress exposure as well as psychiatric disorders are often associated with abnormalities in brain structure or connectivity. The co-chaperone FK506-binding protein 51 (FKBP51) is a regulator of the stress system and is associated with a risk to develop stress-related mental illnesses. PURPOSE To assess the effect of a general FKBP51 knockout on brain structure and connectivity in male mice. STUDY TYPE Animal study. ANIMAL MODEL Two cohorts of FKBP51 knockout (51KO) and wildtype (WT) mice. The first cohort was comprised of n = 18 WT and n = 17 51KOs; second cohort n = 10 WT and n = 9 51KOs. FIELD STRENGTH/SEQUENCE 9.4T/3D gradient echo (VBM), DTI-EPI (DTI). ASSESSMENT Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). For VBM, all procedures were executed in SPM12. DTI: FMRIB Software Library (FSL) Tract Based Statistics (TBSS) were integrated within DTI-TK, allowing the creation of a mean FA skeleton. A voxelwise statistical analysis was applied between WT and 51KO mice. STATISTICAL TEST Volumetric differences were collected at a threshold of P

Depression is a debilitating disorder with high prevalence and socioeconomic cost, but the central processes that are altered during depressive states remain largely elusive. Here, we build on recent findings in macaques that indicate a direct causal relationship between pupil dilation and anterior cingulate cortex mediated arousal during anticipation of reward. Using pupillometry and concurrent fMRI in a sample of unmedicated participants diagnosed with major depression and healthy controls, we observed reduced pupil dilation during reward anticipation in depressed participants with acute symptomatology. We further observed that individual differences in arousal during reward anticipation track the load and impact of depressive symptoms, a correlation that we replicated in a second sample of unmedicated depressed participants. Moreover, these group differences and correlations were mirrored at the neural level. The upregulation and maintenance of arousal during reward anticipation is a translational and well-traceable process that could prove a promising gateway to a physiologically informed patient stratification.

Acute and chronic stress are important factors in the development of mental disorders. Reliable measurement of stress reactivity is therefore pivotal. Critically, experimental induction of stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or simple additive effects on following events. Here, we investigated the effect of the individual cortisol response to intravenous catheter placement (IVP) on subsequent neural, psychological, endocrine, and autonomous stress reactivity. We used an established psychosocial stress paradigm to measure the acute stress response (Stress) and recovery (PostStress) in 65 participants. Higher IVP‐induced cortisol responses were associated with lower pulse rate increases during stress recovery (b = −4.8 bpm, p = .0008) and lower increases in negative affect after the task (b = −4.2, p = .040). While the cortisol response to IVP was not associated with subsequent specific stress‐induced neural activation patterns, the similarity of brain responses Pre‐ and PostStress was higher IVP‐cortisol responders (t[64] = 2.35, p = .022) indicating faster recovery. In conclusion, preparatory stress induced by IVP reduced reactivity in a subsequent stress task by modulating the latency of stress recovery. Thus, an individually stronger preceding release of cortisol may attenuate a second physiological response and perceived stress suggesting that relative changes, not absolute levels are crucial for stress attribution. Our study highlights that considering the entire trajectory of stress induction during an experiment is important to develop reliable individual biomarkers., Stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or additive effects. Here, we show that a cortisol response to the placement of an intravenous catheter attenuated reactivity to a subsequent psychosocial stress task on the neural, endocrine, autonomous, and subjective level.

Manganese-enhanced magnetic resonance imaging (MEMRI) exploits the biophysical similarity of Ca2+ and Mn2+ to map the brain's activity in vivo. However, to what extent different Ca2+ channels contribute to the enhanced signal that MEMRI provides and how Mn2+ dynamics influence Mn2+ brain accumulation after systemic administration of MnCl2 are not yet fully understood. Here, we demonstrate that mice lacking the L-type Ca2+ channel 1.2 (Cav1.2) in the CNS show approximately 50% less increase in MEMRI contrast after repeated systemic MnCl2 injections, as compared to control mice. In contrast, genetic deletion of L-type Ca2+ channel 1.3 (Cav1.3) did not reduce signal. Brain structure- or cell type-specific deletion of Cav1.2 in combination with voxel-wise MEMRI analysis revealed a preferential accumulation of Mn2+ in projection terminals, which was confirmed by local MnCl2 administration to defined brain areas. Taken together, we provide unequivocal evidence that Cav1.2 represents an important channel for neuronal Mn2+ influx after systemic injections. We also show that after neuronal uptake, Mn2+ preferentially accumulates in projection terminals.

Standard T2* weighted functional magnetic resonance imaging (fMRI) performed with echo-planar imaging (EPI) suffers from signal loss in the ventromedial prefrontal cortex (vmPFC) due to macroscopic field inhomogeneity. However, this region is of special interest to affective neuroscience and psychiatry. The Multi-echo EPI (MEPI) approach has several advantages over EPI but its performance against EPI in the vmPFC has not yet been examined in a study with sufficient statistical power using a task specifically eliciting activity in this region. We used a fear conditioning task with MEPI to compare the performance of MEPI and EPI in vmPFC and control regions in 32 healthy young subjects. We analyzed activity associated with short (12ms), standard (29ms) and long (46ms) echo times, and a voxel-wise combination of these three echo times. Behavioral data revealed successful differentiation of the conditioned versus safety stimulus; activity in the vmPFC was shown by the contrast "safety stimulus > conditioned stimulus" as in previous research and proved significantly stronger with the combined MEPI than standard single-echo EPI. Then, we aimed to demonstrate that the additional cluster extent (ventral extension) detected in the vmPFC with MEPI reflects activation in a relevant cluster (i.e., not just non-neuronal noise). To do this, we used resting state data from the same subjects to show that the time-course of this region was both connected to bilateral amygdala and the default mode network. Overall, we demonstrate that MEPI (by means of the weighted sum combination approach) outperforms standard EPI in vmPFC; MEPI performs always at least as good as the best echo time for a given brain region but provides all necessary echo times for an optimal BOLD sensitivity for the whole brain. This is relevant for affective neuroscience and psychiatry given the critical role of the vmPFC in emotion regulation.

Conscious experience varies considerably, not only between wakefulness and sleep but also within sleep. Consciousness during sleep can be rich and vivid in its perceptual content but is typically poor in self-reflective consciousness/meta-consciousness. A notable exception is lucid dreaming: the phenomenon of becoming aware that one is dreaming while continuing to dream during ongoing sleep. As a research topic, lucid dreaming initially faced considerable skepticism; however, this area has begun to receive increasing attention due to its relevance to the emerging neuroscience of consciousness. Here, we present a brief overview of the existing neuroscientific literature on lucid dreaming and discuss some of its clinical and practical applications. Together, recent findings highlight the emerging potential of lucid dreaming as a methodology for research on consciousness within sleep science.

Even in the absence of neurodegenerative diseases, progressing age often coincides with cognitive decline and morphological changes. However, longitudinal studies that directly link these two processes are missing. In this proof-of-concept study we therefore performed repeated within-subject testing of healthy male R26R mice in a spatial learning task in combination with manganese-enhanced volumetric MRI analyses at the ages of 8, 16, and 24 months. We grouped the mice into good and poor performers (n = 6, each), based on their spatial learning abilities at the age of 24 months. Using this stratification, we failed to detect a priori volume differences, but observed a significant decrease in total hippocampal volume over time for both groups. Interestingly, this volume decrease was specific for the dorsal hippocampus and significantly accelerated in poor performers between 16 and 24 months of age. This is the first time that individual changes in hippocampal volume were traced alongside cognitive performance within the same subjects over 1½ years. Our study points to a causal link between volume loss of the dorsal hippocampus and cognitive impairments. In addition, it suggests accelerated degenerative processes rather than a priori volume differences as determining trajectories of age-related cognitive decline. Despite the relatively small sample sizes, the strong behavioral and moderate morphological alterations demonstrate the general feasibility of longitudinal studies of age-related decline in cognition and hippocampus integrity. This article is protected by copyright. All rights reserved.

Expression of the lacZ-sequence is a widely used reporter-tool to assess the transgenic and/or transfection efficacy of a target gene in mice. Once activated, lacZ is permanently expressed. However, protein accumulation is one of the hallmarks of neurodegenerative diseases. Furthermore, the protein product of the bacterial lacZ gene is s-galactosidase, an analog to the mammalian senescence-associated s-galactosidase, a molecular marker for aging. Therefore we studied the behavioral, structural and molecular consequences of lacZ expression in distinct neuronal sub-populations. lacZ expression in cortical glutamatergic neurons resulted in severe impairments in hippocampus-dependent memory accompanied by marked structural alterations throughout the CNS. In contrast, GFP expression or the expression of the ChR2/YFP fusion product in the same cell populations did not result in either cognitive or structural deficits. GABAergic lacZ expression caused significantly decreased hyper-arousal and mild cognitive deficits. Attenuated structural and behavioral consequences of lacZ expression could also be induced in adulthood, and lacZ transfection in neuronal cell cultures significantly decreased their viability. Our findings provide a strong caveat against the use of lacZ reporter mice for phenotyping studies and point to a particular sensitivity of the hippocampus formation to detrimental consequences of lacZ expression. © 2016 Wiley Periodicals, Inc.

Purpose Diffusional kurtosis imaging (DKI) is an approach to characterizing the non-Gaussian fraction of water diffusion in biological tissue. However, DKI is highly susceptible to the low signal-to-noise ratio of diffusion-weighted images, causing low precision and a significant bias due to Rician noise distribution. Here, we evaluate precision and bias using weighted linear least squares fitting of different acquisition schemes including several multishell schemes, a diffusion spectrum imaging (DSI) scheme, as well as a compressed sensing reconstruction of undersampled DSI scheme. Methods Monte Carlo simulations were performed to study the three-dimensional distribution of the apparent kurtosis coefficient (AKC). Experimental data were acquired from one healthy volunteer with multiple repetitions, using the same acquisition schemes as for the simulations. Results The angular distribution of the bias and precision were very inhomogeneous. While axial kurtosis was significantly overestimated, radial kurtosis was underestimated. The precision of radial kurtosis was up to 10-fold lower than axial kurtosis. Conclusion The noise bias behavior of DKI is highly complex and can cause overestimation as well as underestimation of the AKC even within one voxel. The acquisition scheme with three shells, suggested by Poot et al, provided overall the best performance. Magn Reson Med 76:1684–1696, 2016. © 2016 International Society for Magnetic Resonance in Medicine