Functional connectivity correlates of attentional networks in insomnia disorder: A pilot study.

Insomnia disorder has been associated with poor executive functioning. Functional imaging studies of executive functioning in insomnia are scarce and inconclusive. Because the Attentional Network Test relies on well-defined cortical networks and sensitively distinguishes different aspects of executive function, it might reveal brain functional alterations in relatively small samples of patients. The current pilot study assessed functional connectivity during the Attentional Network Test performed using magnetic resonance imaging in 12 participants with insomnia and 13 self-defined good sleepers. ANCOVAs were used to evaluate group differences in performance and functional connectivity in the regions of interest representing the attentional networks (i.e. alerting, orienting and executive control) at p < 0.05, uncorrected. During the orienting part, participants with insomnia showed weaker connectivity of the precentral gyrus with the superior parietal lobe (false discovery rate-corrected), while they showed stronger connectivity between premotor and visual regions. Individual differences in connectivity between premotor and visual regions correlated inversely with reaction time. Reaction times suggested more efficient executive control in participants with insomnia compared with good sleepers. During the executive control part, participants with insomnia showed stronger connectivity of thalamic parts of the arousal circuit with the middle frontal and the occipital gyri. Conversely, connectivity between the inferior and superior frontal gyri was weaker. Participants with insomnia seem to recruit more cortical resources in visuo-motor regions to orient attention than good sleepers do, and seem to have enhanced executive control that relates to stronger connectivity of arousal-related thalamic areas. This latter result should be treated with caution and requires confirmation.

Reduced dynamic functional connectivity between salience and executive brain networks in insomnia disorder.

Research into insomnia disorder has pointed to large-scale brain network dysfunctions. Dynamic functional connectivity is instrumental to cognitive functions but has not been investigated in insomnia disorder. This study assessed between-network functional connectivity strength and variability in patients with insomnia disorder as compared with matched controls without sleep complaints. Twelve-minute resting-state functional magnetic resonance images and T1-weighed images were acquired in 65 people diagnosed with insomnia disorder (21-69 years, 48 female) and 65 matched controls without sleep complaints (22-70 years, 42 female). Pairwise correlations between the activity time series of 14 resting-state networks and temporal variability of the correlations were compared between cases and controls. After false discovery rate correction for multiple comparisons, people with insomnia disorder and controls did not differ significantly in terms of mean between-network functional connectivity strength; people with insomnia disorder did, however, show less functional connectivity variability between the anterior salience network and the left executive-control network. The finding suggests less flexible interactions between the networks during the resting state in people with insomnia disorder.

Haunted by the past: old emotions remain salient in insomnia disorder.

Studies suggest that sleep supports persistent changes in the neuronal representation of emotional experiences such that they are remembered better and less distressful when recalled than when they were first experienced. It is conceivable that sleep fragmentation by arousals, a key characteristic of insomnia disorder, could hamper the downregulation of distress. In this study, we sought further support for the idea that insomnia disorder may involve a lasting deficiency to downregulate emotional distress. We used functional MRI in insomnia disorder (n = 27) and normal sleepers (n = 30) to identify how brain activation differs between novel and relived self-conscious emotions. We evaluated whether brain activity elicited by reliving emotional memories from the distant past resembles the activity elicited by novel emotional experiences more in insomnia disorder than in normal sleepers. Limbic areas were activated during novel shameful experiences as compared to neutral experiences in both normal sleepers and insomnia disorder. In normal sleepers, reliving of shameful experiences from the past did not elicit a limbic response. In contrast, participants with insomnia disorder recruited overlapping parts of the limbic circuit, in particular the dorsal anterior cingulate cortex, during both new and relived shameful experiences. The differential activity patterns with new and old emotions in normal sleepers suggest that reactivation of the long-term memory trace does not recruit the limbic circuit. The overlap of activations in insomnia disorder is in line with the hypothesis that the disorder involves a deficiency to dissociate the limbic circuit from the emotional memory trace. Moreover, the findings provide further support for a role of the anterior cingulate cortex in insomnia.

Increased hippocampal-prefrontal functional connectivity in insomnia.

Insomnia Disorder (ID) is the second-most common mental disorder and has a far-reaching impact on daytime functioning. A meta-analysis indicates that, of all cognitive domains, declarative memory involving the hippocampus is most affected in insomnia. Hippocampal functioning has consistently been shown to be sensitive to experimental sleep deprivation. Insomnia however differs from sleep deprivation in many aspects, and findings on hippocampal structure and function have been equivocal. The present study used both structural and resting-state functional Magnetic Resonance Imaging in a larger sample than previously reported to evaluate hippocampal volume and functional connectivity in ID. Included were 65 ID patients (mean age = 48.3 y ±â€¯14.0, 17 males) and 65 good sleepers (mean age = 44.1 y ±â€¯15.2, 23 males). Insomnia severity was assessed with the Insomnia Severity Index (ISI), subjective sleep with the Consensus Sleep Diary (CSD) and objective sleep by two nights of polysomnography (PSG). Seed-based analysis showed a significantly stronger connectivity of the bilateral hippocampus with the left middle frontal gyrus in ID than in controls (p = .035, cluster based correction for multiple comparisons). Further analyses across all participants moreover showed that individual differences in the strength of this connectivity were associated with insomnia severity (ISI, r = 0.371, p = 9.3e-5) and with subjective sleep quality (CSD sleep efficiency, r = -0.307, p = .009) (all p FDR-corrected). Hippocampal volume did not differ between ID and controls. The findings indicate more severe insomnia and worse sleep quality in people with a stronger functional connectivity between the bilateral hippocampus and the left middle frontal gyrus, part of a circuit that characteristically activates with maladaptive rumination and deactivates with sleep.

Disrupted brain network topology in Parkinson's disease: a longitudinal magnetoencephalography study.

Although alterations in resting-state functional connectivity between brain regions have previously been reported in Parkinson's disease, the spatial organization of these changes remains largely unknown. Here, we longitudinally studied brain network topology in Parkinson's disease in relation to clinical measures of disease progression, using magnetoencephalography and concepts from graph theory. We characterized whole-brain functional networks by means of a standard graph analysis approach, measuring clustering coefficient and shortest path length, as well as the construction of a minimum spanning tree, a novel approach that allows a unique and unbiased characterization of brain networks. We observed that brain networks in early stage untreated patients displayed lower local clustering with preserved path length in the delta frequency band in comparison to controls. Longitudinal analysis over a 4-year period in a larger group of patients showed a progressive decrease in local clustering in multiple frequency bands together with a decrease in path length in the alpha2 frequency band. In addition, minimum spanning tree analysis revealed a decentralized and less integrated network configuration in early stage, untreated Parkinson's disease that also progressed over time. Moreover, the longitudinal changes in network topology identified with both techniques were associated with deteriorating motor function and cognitive performance. Our results indicate that impaired local efficiency and network decentralization are very early features of Parkinson's disease that continue to progress over time, together with reductions in global efficiency. As these network changes appear to reflect clinically relevant phenomena, they hold promise as markers of disease progression.

The caudate: a key node in the neuronal network imbalance of insomnia?

Insomnia is prevalent, severe and partially heritable. Unfortunately, its neuronal correlates remain enigmatic, hampering the development of mechanistic models and rational treatments. Consistently reported impairments concern fragmented sleep, hyper-arousal and executive dysfunction. Because fronto-striatal networks could well play a role in sleep, arousal regulation and executive functioning, the present series of studies used an executive task to evaluate fronto-striatal functioning in disturbed sleep. Patients with insomnia showed reduced recruitment of the head of the left caudate nucleus during executive functioning, which was not secondary to altered performance or baseline perfusion. Individual differences in caudate recruitment were associated with hyper-arousal severity. Seed-based functional connectivity analysis suggested that attenuated input from a projecting orbitofrontal area with reduced grey matter density contributes to altered caudate recruitment in patients with insomnia. Attenuated caudate recruitment persisted after successful treatment of insomnia, warranting evaluation as a potential vulnerability trait. A similar selective reduction in caudate recruitment could be elicited in participants without sleep complaints by slow-wave sleep fragmentation, providing a model to facilitate investigation of the causes and consequences of insomnia.

Insomnia Subtypes Have Differentiating Deviations in Brain Structural Connectivity.

BACKGROUND: Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. In the current study, we investigated whether structural brain connectivity deviations differed between recently discovered and validated insomnia subtypes. METHODS: Structural and diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted of 73 control participants without sleep complaints and 204 participants with insomnia who were grouped into 5 insomnia subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex was used to evaluate group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density, and mean diffusivity and evaluated within 3 different atlases. RESULTS: Insomnia subtypes showed differentiating profiles of deviating structural connectivity that were concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in 4 of the 5 subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive, and slightly distressed high reactive. Connectivity deviation profile significance ranged from p = .001 to p = .049 for different resolutions of brain parcellation and connectivity weight. CONCLUSIONS: Our results provide an initial indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping insomnia may be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

Evaluating imaging biomarkers for neurodegeneration in pre-symptomatic Huntington's disease using machine learning techniques.

The development of MRI measures as biomarkers for neurodegenerative disease could prove extremely valuable for the assessment of neuroprotective therapies. Much current research is aimed at developing such biomarkers for use in people who are gene-positive for Huntington's disease yet exhibit few or no clinical symptoms of the disease (pre-HD). We acquired structural (T1), diffusion weighted and functional MRI (fMRI) data from 39 pre-HD volunteers and 25 age-matched controls. To determine whether it was possible to decode information about disease state from neuroimaging data, we applied multivariate pattern analysis techniques to several derived voxel-based and segmented region-based datasets. We found that different measures of structural, diffusion weighted, and functional MRI could successfully classify pre-HD and controls using support vector machines (SVM) and linear discriminant analysis (LDA) with up to 76% accuracy. The model producing the highest classification accuracy used LDA with a set of six volume measures from the basal ganglia. Furthermore, using support vector regression (SVR) and linear regression models, we were able to generate quantitative measures of disease progression that were significantly correlated with established measures of disease progression (estimated years to clinical onset, derived from age and genetic information) from several different neuroimaging measures. The best performing regression models used SVR with neuroimaging data from regions within the grey matter (caudate), white matter (corticospinal tract), and fMRI (insular cortex). These results highlight the utility of machine learning analyses in addition to conventional ones. We have shown that several neuroimaging measures contain multivariate patterns of information that are useful for the development of disease-state biomarkers for HD.

Automated structural imaging analysis detects premanifest Huntington's disease neurodegeneration within 1 year.

Intense efforts are underway to evaluate neuroimaging measures as biomarkers for neurodegeneration in premanifest Huntington's disease (preHD). We used a completely automated longitudinal analysis method to compare structural scans in preHD individuals and controls. Using a 1-year longitudinal design, we analyzed T(1) -weighted structural scans in 35 preHD individuals and 22 age-matched controls. We used the SIENA (Structural Image Evaluation, using Normalization, of Atrophy) software tool to yield overall percentage brain volume change (PBVC) and voxel-level changes in atrophy. We calculated sample sizes for a hypothetical disease-modifying (neuroprotection) study. We found significantly greater yearly atrophy in preHD individuals versus controls (mean PBVC controls, -0.149%; preHD, -0.388%; P = .031, Cohen's d = .617). For a preHD subgroup closest to disease onset, yearly atrophy was more than 3 times that of controls (mean PBVC close-to-onset preHD, -0.510%; P = .019, Cohen's d = .920). This atrophy was evident at the voxel level in periventricular regions, consistent with well-established preHD basal ganglia atrophy. We estimated that a neuroprotection study using SIENA would only need 74 close-to-onset individuals in each arm (treatment vs placebo) to detect a 50% slowing in yearly atrophy with 80% power. Automated whole-brain analysis of structural MRI can reliably detect preHD disease progression in 1 year. These results were attained with a readily available imaging analysis tool, SIENA, which is observer independent, automated, and robust with respect to image quality, slice thickness, and different pulse sequences. This MRI biomarker approach could be used to evaluate neuroprotection in preHD.

Basal ganglia atrophy in prodromal Huntington's disease is detectable over one year using automated segmentation.

Future clinical trials of neuroprotection in prodromal Huntington's (known as preHD) will require sensitive in vivo imaging biomarkers to track disease progression over the shortest period. Since basal ganglia atrophy is the most prominent structural characteristic of Huntington's pathology, systematic assessment of longitudinal subcortical atrophy holds great potential for future biomarker development. We studied 36 preHD and 22 age-matched controls using a novel method to quantify regional change from T(1) -weighted structural images acquired 1 year apart. We assessed cross-sectional volume differences and longitudinal volumetric change in 7 subcortical structures-the accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. At baseline, accumbens, caudate, pallidum, and putamen volumes were reduced in preHD versus controls (all P < .01). Longitudinally, atrophy was greater in preHD than controls in the caudate, pallidum, and putamen (all P < .01). Each structure showed a large between-group effect size, especially the pallidum where Cohen's d was 1.21. Using pallidal atrophy as a biomarker, we estimate that a hypothetical 1-year neuroprotection study would require only 35 preHD per arm to detect a 50% slowing in atrophy and only 138 preHD per arm to detect a 25% slowing in atrophy. The effect sizes calculated for preHD basal ganglia atrophy over 1 year are some of the largest reported to date. Consequently, this translates to strikingly small sample size estimates that will greatly facilitate any future neuroprotection study. This underscores the utility of this automatic image segmentation and longitudinal nonlinear registration method for upcoming studies of preHD and other neurodegenerative disorders.

Olfactory testing combined with dopamine transporter imaging as a method to detect prodromal Parkinson's disease.

Objective Olfactory dysfunction is an early and common symptom in Parkinson disease (PD). Previously, the authors demonstrated that idiopathic olfactory dysfunction in first-degree relatives of PD patients is associated with an increased risk of developing PD within 2 years. The aim of the present study was to determine the value of combined olfactory testing and SPECT scanning in predicting future PD in the same population of relatives over a 5-year period. Methods In a cohort of 361 non-parkinsonian, non-demented first-degree relatives of PD patients, a combination of olfactory processing tasks was used to select groups of hyposmic (n=40) and normosmic (n=38) individuals for a 5-year clinical follow-up evaluation and sequential SPECT scanning, using a dopamine transporter ligand to assess nigrostriatal dopaminergic function at baseline and 5 years from baseline. A validated questionnaire, sensitive to the presence of parkinsonism, was used in the follow-up of the remaining 283 relatives. Results Five years from baseline, five out of the 40 hyposmic relatives fulfilled clinical diagnostic criteria for PD. None of the other 349 relatives available for follow-up developed PD. All hyposmic individuals developing PD had an abnormal baseline SPECT scan. Discussion In conclusion, idiopathic hyposmia in first-degree relatives of PD patients is associated with an increased risk of developing clinical PD of 12.5% over a 5-year period. The present data suggest that a two-step approach using olfactory testing followed by SPECT scanning in hyposmic individuals has a very high sensitivity and specificity in detecting PD. The usefulness of this two-step approach needs to be confirmed in larger populations.

Consistent altered internal capsule white matter microstructure in insomnia disorder.

STUDY OBJECTIVES: Suggested neural correlates of insomnia disorder have been hard to replicate. Even the most consistent finding, altered white matter microstructure in the anterior limb of the internal capsule, is based on handful studies. The urge for replicable targets to understand the underlying mechanisms of insomnia made us study white matter fractional anisotropy (FA) across three samples of cases and controls. METHODS: 3-Tesla MRI diffusion tensor imaging data of three independent samples were combined for analysis, resulting in n = 137 participants, of whom 73 were diagnosed with insomnia disorder and 64 were matched controls without sleep complaints. Insomnia severity was measured with the Insomnia Severity Index (ISI). White matter microstructure was assessed with FA. White matter tracts were skeletonized and analyzed using tract-based spatial statistics. We performed a region-of-interest analysis using linear mixed-effect models to evaluate case-control differences in internal capsule FA as well as associations between internal capsule FA and insomnia severity. RESULTS: FA in the right limb of the anterior internal capsule was lower in insomnia disorder than in controls (ß = -9.76e-3; SE = 4.17e-3, p = .034). In the entire sample, a higher ISI score was associated with a lower FA value of the right internal capsule (ß = -8.05e- 4 FA/ISI point, SE = 2.60e- 4, p = .008). Ancillary whole brain voxel-wise analyses showed no significant group difference or association with insomnia severity after correction for multiple comparisons. CONCLUSIONS: The internal capsule shows small but consistent insomnia-related alterations. The findings support a circuit-based approach to underlying mechanisms since this tract connects many brain areas previously implicated in insomnia.

Hyposmia and executive dysfunction as predictors of future Parkinson's disease: a prospective study.

Olfactory deficits and executive dysfunction are early and common symptoms in Parkinson's disease (PD). Previous studies have shown that hyposmia can be a first sign of PD. The aim of the present study was to determine which of three olfactory tests and two selected tests of executive function would be the best predictor of future PD over a 5 year period. In a cohort of 361 nonparkinsonian, nondemented first-degree relatives of PD patients, in whom alternative causes of olfactory dysfunction were excluded, we measured baseline performance on three olfactory and two executive function tasks. Five years from baseline, clinical neurological evaluation and/or a screening questionnaire, sensitive to the presence of Parkinsonism, were used to detect individuals developing clinical PD. Our results show that in first degree relatives of PD patients worse performance on each of three olfactory processing tasks was associated with an increased risk of developing PD within 5 years, whereas performance on selected tests of executive dysfunction was not associated with an increased risk of developing PD. Interestingly, impaired odor discrimination was the best predictor for future PD.

Restless REM Sleep Impedes Overnight Amygdala Adaptation.

Animal studies show that insufficient silencing of the locus coeruleus (LC) during REM sleep impairs sleep-related brain plasticity. Restless REM sleep, a characteristic of several psychiatric disorders, likely reflects insufficient LC silencing. We investigated whether endogenous REM sleep interruptions interfere with overnight reorganization of limbic circuits in human volunteers with a wide range of insomnia severity, from no insomnia complaints to fulfilling community-sample criteria for insomnia disorder. We induced a self-conscious emotion during two functional MRI sessions and recorded sleep EEG in between. Amygdala reactivity decreased overnight in proportion to the total duration of consolidated REM sleep. Restless REM sleep, in contrast, impeded overnight amygdala adaptation. Using targeted memory reactivation with odors tagged to the self-conscious emotional stimulus, we could experimentally enhance both the favorable effect of consolidated REM sleep and the unfavorable effect of restless REM sleep. The findings reveal a maladaptive type of sleep, providing a target for interventions in mental disorders characterized by restless REM sleep.

Brain structural connectivity network alterations in insomnia disorder reveal a central role of the right angular gyrus.

Insomnia Disorder (ID) is a prevalent and persistent condition, yet its neural substrate is not well understood. The cognitive, emotional, and behavioral characteristics of ID suggest that vulnerability involves distributed brain networks rather than a single brain area or connection. The present study utilized probabilistic diffusion tractography to compare the whole-brain structural connectivity networks of people with ID and those of matched controls without sleep complaints. Diffusion-weighted images and T1-weighed images were acquired in 51 people diagnosed with ID (21-69 years of age, 37 female) and 48 matched controls without sleep complaints (22-70 years of age, 31 female). Probabilistic tractography was performed to construct the whole-brain structural connectivity network of each participant. Case-control differences in connectivity strength and network efficiency were evaluated with permutation tests. People with ID showed structural hyperconnectivity within a subnetwork that spread over frontal, parietal, temporal, and subcortical regions and was anchored at the right angular gyrus. The result was robust across different edge-weighting strategies. Moreover, converging support was given by the finding of heightened right angular gyrus nodal efficiency (harmonic centrality) across varying graph density in people with ID. Follow-up correlation analyses revealed that subnetwork connectivity was associated with self-reported reactive hyperarousal. The findings demonstrate that the right angular gyrus is a hub of enhanced structural connectivity in ID. Hyperconnectivity within the identified subnetwork may contribute to increased reactivity to stimuli and may signify vulnerability to ID.

Insomnia disorder subtypes derived from life history and traits of affect and personality.

BACKGROUND: Insomnia disorder is the second most prevalent mental disorder, and it is a primary risk factor for depression. Inconsistent clinical and biomarker findings in patients with insomnia disorder suggest that heterogeneity exists and that subtypes of this disease remain unrecognised. Previous top-down proposed subtypes in nosologies have had insufficient validity. In this large-scale study, we aimed to reveal robust subtypes of insomnia disorder by use of data-driven analyses on a multidimensional set of biologically based traits. METHODS: In this series of studies, we recruited participants from the Netherlands Sleep Registry, a database of volunteers aged 18 years or older, who we followed up online to survey traits, sleep, life events, and health history with 34 selected questionnaires of which participants completed at least one. We identified insomnia disorder subtypes by use of latent class analyses. We evaluated the value of our identified subtypes of insomnia disorder by use of a second, non-overlapping cohort who were recruited through a newsletter that was emailed to a new sample of Netherlands Sleep Registry participants, and by assessment of within-subject stability over several years of follow-up. We extensively tested the clinical validity of these subtypes for the development of sleep complaints, comorbidities (including depression), and response to benzodiazepines; in two subtypes of insomnia disorder, we also assessed the clinical relevance of these subtypes by use of an electroencephalogram biomarker and the effectiveness of cognitive behavioural therapy. To facilitate implementation, we subsequently constructed a concise subtype questionnaire and we validated this questionnaire in the second, non-overlapping cohort. FINDINGS: 4322 Netherlands Sleep Registry participants completed at least one of the selected questionnaires, a demographic questionnaire, and an assessment of their Insomnia Severity Index (ISI) between March 2, 2010, and Oct 28, 2016. 2224 (51%) participants had probable insomnia disorder, defined as an ISI score of at least 10, and 2098 (49%) participants with a lower ISI score served as a control group. With a latent class analysis of the questionnaire responses of 2224 participants, we identified five novel insomnia disorder subtypes: highly distressed, moderately distressed but reward sensitive (ie, with intact responses to pleasurable emotions), moderately distressed and reward insensitive, slightly distressed with high reactivity (to their environment and life events), and slightly distressed with low reactivity. In a second, non-overlapping replication sample of 251 new participants who were assessed between June 12, 2017, and Nov 26, 2017, five subtypes were also identified to be optimal. In both the development sample and replication sample, each participant was classified as having only one subtype with high posterior probability (0·91-1·00). In 215 of the original sample of 2224 participants with insomnia who were reassessed 4·8 (SD 1·6) years later (between April 13, 2017, and June 21, 2017), the probability of maintaining their original subtype was 0·87, indicating a high stability of the classification. We found differences between the identified subtypes in developmental trajectories, response to treatment, the presence of an electroencephalogram biomarker, and the risk of depression that was up to five times different between groups, which indicated a clinical relevance of these subtypes. INTERPRETATION: High-dimensional data-driven subtyping of people with insomnia has addressed an unmet need to reduce the heterogeneity of insomnia disorder. Subtyping facilitates identification of the underlying causes of insomnia, development of personalised treatments, and selection of patients with the highest risk of depression for inclusion in trials regarding prevention of depression. FUNDING: European Research Council and Netherlands Organization for Scientific Research.

Abnormal susceptibility to distracters hinders perception in early stage Parkinson's disease: a controlled study.

BACKGROUND: One of the perceptual abnormalities observed in Parkinson's disease (PD) is a deficit in the suppression of reflexive saccades that are automatically triggered by the onset of a peripheral target. Impairment of substantia nigra function is thought to lead to this reduced ability to suppress reflexive saccades. METHODS: The present study examined whether this perceptual deficit is also present in early stage PD when using hardly noticeable task-irrelevant stimuli. Eleven non-demented de novo, untreated PD patients (mean age 57 yr, range 44-70) participated in the study as well as 12 age-matched controls. Performance on an 'oculomotor capture' task, in which in half of the trials an irrelevant stimulus with sudden onset was added to the display, was compared between patients and controls. Analysis of variance (ANOVA) was performed with group (patients/controls) and age (< 61 yrs/> or = 61 yrs) as independent factors and type of trial (control/distracter) as repeated measurements factor. The factor sex was used as covariate. RESULTS: With respect to Reaction Time (RT), a significant interaction between group and condition was found. RTs increased under the 'irrelevant stimulus' condition in both groups, the patients exhibiting a significantly larger increase in RTs than the control group. Also, a significant interaction effect between group and condition for number of correct responses was found. The number of correct responses was reduced in the onset distracter condition, the reduction being larger in the patients. In the patient group, contrary to the control group, a higher age was associated with fewer correct responses at baseline and in the onset distracter condition, suggesting that perceptual functions in PD are highly susceptible to the effects of ageing. The increased reaction times and larger number of incorrect responses of the PD patients in the onset distracter condition may be related to impairments of substantia nigra function and lower brain stem. CONCLUSION: The capture task seems to be a sensitive instrument to detect early perceptual deficits in PD. The magnitude of the observed deficits suggests that perceptual functions in early stage PD are so substantially impaired that this may interfere with daily activities.

Effects of dexamphetamine-induced dopamine release on resting-state network connectivity in recreational amphetamine users and healthy controls.

Dexamphetamine (dAMPH) is not only used for the treatment of attention deficit hyperactivity disorder (ADHD), but also as a recreational drug. Acutely, dAMPH induces release of predominantly dopamine (DA) in the striatum, and in the cortex both DA and noradrenaline. Recent animal studies have shown that chronic dAMPH administration can induce changes in the DA system following long-term exposure, as evidenced by reductions in DA transporters, D2/3 receptors and endogenous DA levels. However, only a limited number of studies have investigated the effects of dAMPH in the human brain. We used a combination of resting-state functional magnetic resonance imaging (rs-fMRI) and [(123)I]IBZM single-photon emission computed tomography (SPECT) (to assess baseline D2/3 receptor binding and DA release) in 15 recreational AMPH users and 20 matched healthy controls to investigate the short-, and long-term effects of AMPH before and after an acute intravenous challenge with dAMPH. We found that acute dAMPH administration reduced functional connectivity in the cortico-striatal-thalamic network. dAMPH-induced DA release, but not DA D2/3 receptor binding, was positively associated with connectivity changes in this network. In addition, acute dAMPH reduced connectivity in default mode networks and salience-executive-networks networks in both groups. In contrast to our hypothesis, no significant group differences were found in any of the rs-fMRI networks investigated, possibly due to lack of sensitivity or compensatory mechanisms. Our findings thus support the use of ICA-based resting-state functional connectivity as a tool to investigate acute, but not chronic, alterations induced by dAMPH on dopaminergic processing in the striatum.

I Keep a Close Watch on This Heart of Mine: Increased Interoception in Insomnia.

STUDY OBJECTIVES: Whereas both insomnia and altered interoception are core symptoms in affective disorders, their neural mechanisms remain insufficiently understood and have not previously been linked. Insomnia Disorder (ID) is characterized by sensory hypersensitivity during wakefulness and sleep. Previous studies on sensory processing in ID addressed external stimuli only, but not interoception. Interoceptive sensitivity can be studied quantitatively by measuring the cerebral cortical response to one's heartbeat (heartbeat-evoked potential, HEP). We here investigated whether insomnia is associated with increased interoceptive sensitivity as indexed by the HEP amplitude. METHODS: Sixty-four participants aged 21-70 years were recruited through www.sleepregistry.nl including 32 people suffering from ID and 32 age- and sex-matched controls without sleep complaints. HEPs were obtained from resting-state high-density electroencephalography (HD-EEG) recorded during evening wakeful rest in eyes-open (EO) and eyes-closed (EC) conditions of 5-minute duration each. Significance of group differences in HEP amplitude and their topographical distribution over the scalp were assessed by means of cluster-based permutation tests. RESULTS: In particular during EC, and to a lesser extent during EO, people with ID had a larger amplitude late HEP component than controls at frontal electrodes 376-500 ms after the R-wave peak. Source localization suggested increased neural activity time-locked to heartbeats in people with ID mainly in anterior cingulate/medial frontal cortices. CONCLUSIONS: People with insomnia show insufficient adaptation of their brain responses to the ever-present heartbeats. Abnormalities in the neural circuits involved in interoceptive awareness including the salience network may be of key importance to the pathophysiology of insomnia.

Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia.

STUDY OBJECTIVES: Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution. METHODS: A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21-70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons. RESULTS: As compared to controls, participants with ID showed less power in a narrow upper alpha band (11-12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3-40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences. CONCLUSIONS: The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia.