Impact of brain parcellation on prediction performance in models of cognition and demographics.

Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predictive model performance. In this work, structural, functional and combined connectivity were each defined with five different parcellation schemes. The resolution and modality of the parcellation schemes were varied. Each connectivity defined with each parcellation was used to predict individual differences in age, education, sex, executive function, self-regulation, language, encoding and sequence processing. It was found that low-resolution functional parcellation consistently performed above chance at producing generalisable models of both demographics and cognition. However, no single parcellation scheme showed a superior predictive performance across all cognitive domains and demographics. In addition, although parcellation schemes impacted the graph theory measures of each connectivity type (structural, functional and combined), these differences did not account for the out-of-sample predictive performance of the models. Taken together, these findings demonstrate that while high-resolution parcellations may be beneficial for modelling specific individual differences, partial voluming of signals produced by the higher resolution of the parcellation likely disrupts model generalisability.

InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels.

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and γ -aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget .

Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression: a UK biobank study.

The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.

Cerebellar connectome alterations and associated genetic signatures in multiple sclerosis and neuromyelitis optica spectrum disorder.

BACKGROUND: The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown. METHODS: Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles. RESULTS: Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained > 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases. CONCLUSIONS: We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases.

Using graph theory as a common language to combine neural structure and function in models of healthy cognitive performance.

Graph theory has been used in cognitive neuroscience to understand how organisational properties of structural and functional brain networks relate to cognitive function. Graph theory may bridge the gap in integration of structural and functional connectivity by introducing common measures of network characteristics. However, the explanatory and predictive value of combined structural and functional graph theory have not been investigated in modelling of cognitive performance of healthy adults. In this work, a Principal Component Regression approach with embedded Step-Wise Regression was used to fit multiple regression models of Executive Function, Self-regulation, Language, Encoding and Sequence Processing with a collection of 20 different graph theoretic measures of structural and functional network organisation used as regressors. The predictive ability of graph theory-based models was compared to that of connectivity-based models. The present work shows that using combinations of graph theory metrics to predict cognition in healthy populations does not produce a consistent benefit relative to making predictions based on structural and functional connectivity values directly.

The Influence of Personality on Interpersonal Emotion Regulation in the Context of Psychosocial Stress.

Interpersonal emotion regulation is common in everyday life and important to various outcomes. However, there is a lack of understanding about the personality profiles of people who are good at regulating others' emotions. We conducted a dyadic study, pairing 89 'regulators' and 'targets', with the targets subjected to a psychosocial stressor in the form of a job interview, and the regulators instructed to manage the targets' feelings prior to the interview. We did not observe any relationship between the regulators' personality traits and the strategies that they reported using when trying to manage the targets' feelings, nor between the regulators' personalities and the targets' job interview performance. However, the anxiety levels of the targets who were paired with more extraverted regulators fluctuated less across the multiple measures throughout the study, suggesting more effective interpersonal emotion regulation. Our findings suggest that extraversion may be the most relevant trait in shaping interpersonal emotion regulation, and that the influence of personality on regulatory effectiveness is unlikely to arise due to preferences for using different types of strategies.

Relating Cognition to both Brain Structure and Function: A Systematic Review of Methods.

Introduction: Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Many studies have combined structural and functional neuroimaging techniques to uncover the complex relationship between them. In this study, we report the first systematic review that assesses how information from structural and functional neuroimaging methods can be integrated to investigate the brain substrates of cognition. Procedure: Web of Science and Scopus databases were searched for studies of healthy young adult populations that collected cognitive data and structural and functional neuroimaging data. Results: Five percent of screened studies met all inclusion criteria. Next, 50% of included studies related cognitive performance to brain structure and function without quantitative analysis of the relationship. Finally, 31% of studies formally integrated structural and functional brain data. Overall, many studies consider either structural or functional neural correlates of cognition, and of those that consider both, they have rarely been integrated. We identified four emergent approaches to the characterization of the relationship between brain structure, function, and cognition; comparative, predictive, fusion, and complementary. Discussion: We discuss the insights provided in each approach about the relationship between brain structure and function and how it impacts cognitive performance. In addition, we discuss how authors can select approaches to suit their research questions. Impact statement The relationship between structural and functional brain networks and their relationship to cognition is a matter of current investigations. This work surveys how researchers have studied the relationship between brain structure and function and its impact on cognitive function in healthy adult populations. We review four emergent approaches of quantitative analysis of this multivariate problem; comparative, predictive, fusion, and complementary. We explain the characteristics of each approach, discuss the insights provided in each approach, and how authors can combine approaches to suit their research questions.

Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function.

The relationship between structural and functional brain networks has been characterised as complex: the two networks mirror each other and show mutual influence but they also diverge in their organisation. This work explored whether a combination of structural and functional connectivity can improve the fit of regression models of cognitive performance. Principal Component Analysis (PCA) was first applied to cognitive data from the Human Connectome Project to identify latent cognitive components: Executive Function, Self-regulation, Language, Encoding and Sequence Processing. A Principal Component Regression approach with embedded Step-Wise Regression (SWR-PCR) was then used to fit regression models of each cognitive domain based on structural (SC), functional (FC) or combined structural-functional (CC) connectivity. Executive Function was best explained by the CC model. Self-regulation was equally well explained by SC and FC. Language was equally well explained by CC and FC models. Encoding and Sequence Processing were best explained by SC. Evaluation of out-of-sample models' skill via cross-validation showed that SC, FC and CC produced generalisable models of Language performance. SC models performed most effectively at predicting Language performance in unseen sample. Executive Function was most effectively predicted by SC models, followed only by CC models. Self-regulation was only effectively predicted by CC models and Sequence Processing was only effectively predicted by FC models. The present study demonstrates that integrating structural and functional connectivity can help explaining cognitive performance, but that the added explanatory value (in-sample) may be domain-specific and can come at the expense of reduced generalisation performance (out-of-sample).

The effects of stress across the lifespan on the brain, cognition and mental health: A UK biobank study.

Repeated overstimulation of the stress response system, caused by exposure to prolonged highly stressful experiences, is thought to affect brain structure, cognitive ability, and mental health. We tested the effects of highly stressful experiences during childhood and adulthood using data from the UK Biobank, a large-scale national health and biomedical study with over 500,000 participants. To do this, we defined four groups with high or low levels of childhood and/or adulthood stress. We then used T1-and diffusion-weighted MRI data to assess the macrostructure of grey matter and microstructure of white matter within limbic brain regions, commonly associated with the stress response. We also compared executive function and working memory between these groups. Our findings suggest that in females, higher levels of Childhood stress were associated with reduced connectivity within the posterior thalamic radiation and cingulum of the hippocampus. In males however, higher levels of Adulthood stress is associated with similar changes in brain microstructure in the posterior thalamic radiation and cingulum of the hippocampus. High stress in Childhood and Adulthood was associated with decreases in executive function and working memory in both males and females. Stress across the lifespan was also positively associated with the number of diagnosed mental health problems, with a stronger effect in females than in males. Finally, our findings also suggest that cognitive and mental health outcomes due to stress may be mediated by the sex specific stress related changes in brain microstructure. Together our findings demonstrate clear links between stress at distinct phases of the lifespan, changes in measures of brain microstructure, impairments in cognitive abilities and negative mental health outcomes.

Neuroanatomical correlates of working memory performance in Neurofibromatosis 1.

Introduction: Neurofibromatosis 1 (NF1) is a single-gene disorder associated with cognitive impairments, particularly with deficits in working memory. Prior research indicates that brain structure is affected in NF1, but it is unclear how these changes relate to aspects of cognition. Methods: 29 adolescents aged 11-17 years were compared to age and sex-matched controls. NF1 subjects were assessed using detailed multimodal measurements of working memory at baseline followed by a 3T MR scan. A voxel-based morphometry approach was used to estimate the total and regional gray matter(GM) volumetric differences between the NF1 and control groups. The working memory metrics were subjected to a principal component analysis (PCA) approach. Results: The NF1 groups showed increased gray matter volumes in the thalamus, corpus striatum, dorsal midbrain and cerebellum bilaterally in the NF1 group as compared to controls. Principal component analysis on the working memory metrics in the NF1 group yielded three independent factors reflecting high memory load, low memory load and auditory working memory. Correlation analyses revealed that increased volume of posterior cingulate cortex, a key component of the default mode network (DMN) was significantly associated with poorer performance on low working memory load tasks. Conclusion: These results are consistent with prior work showing larger subcortical brain volumes in the NF1 cohort. The strong association between posterior cingulate cortex volume and performance on low memory load conditions supports hypotheses of deficient DMN structural development, which in turn may contribute to the cognitive impairments in NF1.

A tractometry principal component analysis of white matter tract network structure and relationships with cognitive function in relapsing-remitting multiple sclerosis.

Understanding the brain changes underlying cognitive dysfunction is a key priority in multiple sclerosis (MS) to improve monitoring and treatment of this debilitating symptom. Functional connectivity network changes are associated with cognitive dysfunction, but it is less well understood how changes in normal appearing white matter relate to cognitive symptoms. If white matter tracts have network structure it would be expected that tracts within a network share susceptibility to MS pathology. In the present study, we used a tractometry approach to explore patterns of variance in white matter metrics across white matter (WM) tracts, and assessed how such patterns relate to neuropsychological test performance across cognitive domains. A sample of 102 relapsing-remitting MS patients and 27 healthy controls underwent MRI and neuropsychological testing. Tractography was performed on diffusion MRI data to extract 40 WM tracts and microstructural measures were extracted from each tract. Principal component analysis (PCA) was used to decompose metrics from all tracts to assess the presence of any co-variance structure among the tracts. Similarly, PCA was applied to cognitive test scores to identify the main cognitive domains. Finally, we assessed the ability of tract co-variance patterns to predict test performance across cognitive domains. We found that a single co-variance pattern which captured microstructure across all tracts explained the most variance (65% variance explained) and that there was little evidence for separate, smaller network patterns of pathology. Variance in this pattern was explained by effects related to lesions, but one main co-variance pattern persisted after this effect was regressed out. This main WM tract co-variance pattern contributed to explaining a modest degree of variance in one of our four cognitive domains in MS. These findings highlight the need to investigate the relationship between the normal appearing white matter and cognitive impairment further and on a more granular level, to improve the understanding of the network structure of the brain in MS.

Neural substrates of expectancy violation associated with social feedback in individuals with subthreshold depression.

BACKGROUND: Abnormal processing of social feedback is an important contributor to social dysfunction in depression, however the exact mechanisms remain unclear. One important factor may be the extent to which social processing depends on expectations, in particular whether social feedback confirms or violates expectations. METHODS: To answer this question, we studied behavioral and brain responses during the evaluative processing of social feedback in 25 individuals with subthreshold depression (SD) and 25 healthy controls (HCs). Participants completed a Social Judgment Task in which they first indicated expectation about whether a peer would like them or not, and then received peer's feedback indicating acceptance or rejection. RESULTS: Individuals with SD who reported greater depressive symptoms gave fewer positive expectations. Compared to HCs, individuals with SD showed reduced activation in the medial prefrontal cortex when expecting positive feedback. They also exhibited increased dorsal anterior cingulate cortex after receipt of unexpected social rejection, and reduced ventral striatum activity after receipt of unexpected social acceptance. CONCLUSIONS: The observed alternations are specific to unexpected social feedback processing and highlight an important role of expectancy violation in the brain dysfunction of social feedback perception and evaluation in individuals at risk for depression.

The effects of psychosocial stress on item, cued-pair and emotional memory.

Physical stress, such as from the cold-pressor test, has been robustly associated with altered memory retrieval, but it is less clear whether the same happens following psychosocial stress. Studies using psychosocial stressors report mixed effects on memory, leading to uncertainty about the common cognitive impact of both forms of stress. The current study uses a series of four carefully designed experiments, each differing by only a single critical factor to determine the effects of psychosocial stress on specific aspects of episodic memory. In three experiments, we induced psychosocial stress after participants encoded words, then assessed retrieval of those words after a prolonged delay. These experiments found no effect of post-encoding stress on recognition of neutral words or cued recall of word-pairs, but a small effect on recollection of semantically related words. There were, however, positive relationships within the stress group between measures of stress (cortisol in experiment 1 and self-reported-anxiety in experiment 3) and recollection of single word stimuli. In the fourth experiment, we found that psychosocial stress immediately before retrieval did not influence word recognition. Recollection, particularly for semantically related stimuli, may therefore be more susceptible to the effects of psychosocial stress, and future studies can assess how this relates to other forms of stress. Overall, our findings suggest that the effects of psychosocial stress on episodic memory may be more subtle than expected, warranting further exploration in larger studies.

A Systematic Review of Resting-State Functional MRI Connectivity Changes and Cognitive Impairment in Multiple Sclerosis.

Introduction: Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting-state functional MRI (rs-fMRI) functional connectivity (FC). However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology. Methods: Embase, Medline, and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS. Results: Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different magnetic resonance (MR) metrics. There was no clear link to increased FC during the early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings. Discussion: These results indicate an urgent need for greater standardization in the field-in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.

Psychosocial stress has weaker than expected effects on episodic memory and related cognitive abilities: A meta-analysis.

The impact of stress on episodic memory and related cognitive abilities is well documented in both animal and human literature. However, it is unclear whether the same cognitive effects result from all forms of stress - in particular psychosocial stress. This review systematically explored the effects of psychosocial stress on episodic memory and associated cognitive abilities. PubMed, PsycInfo, and Web of Science databases were searched. Fifty-one studies were identified and compared based on the timing of stress induction. A small positive effect of post-learning psychosocial stress with a long retention interval was shown. No other effects of psychosocial stress were seen. Re-analysis of previous meta-analyses also showed no significant effect of psychosocial stress on episodic memory, highlighting potentially different effects between stressor types. Psychosocial stress also had a moderately different effect when emotional vs. neutral stimuli were compared. Finally, psychosocial stress also decreased performance on executive function, but not working memory tasks. Our findings demonstrate that psychosocial stress may not have the clear effects on episodic memory previously ascribed to it.

Mechanisms of Network Changes in Cognitive Impairment in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Cognitive impairment in multiple sclerosis (MS) is associated with functional connectivity abnormalities. While there have been calls to use functional connectivity measures as biomarkers, there remains to be a full understanding of why they are affected in MS. In this cross-sectional study, we tested the hypothesis that functional network regions may be susceptible to disease-related "wear and tear" and that this can be observable on co-occurring abnormalities on other magnetic resonance metrics. We tested whether functional connectivity abnormalities in cognitively impaired patients with MS co-occur with (1) overlapping, (2) local, or (3) distal changes in anatomic connectivity and cerebral blood flow abnormalities. METHODS: Multimodal 3T MRI and assessment with the Brief Repeatable Battery of Neuropsychological tests were performed in 102 patients with relapsing-remitting MS and 27 healthy controls. Patients with MS were classified as cognitively impaired if they scored ≥1.5 SDs below the control mean on ≥2 tests (n = 55) or as cognitively preserved (n = 47). Functional connectivity was assessed with Independent Component Analysis and dual regression of resting-state fMRI images. Cerebral blood flow maps were estimated, and anatomic connectivity was assessed with anatomic connectivity mapping and fractional anisotropy of diffusion-weighted MRI. Changes in cerebral blood flow and anatomic connectivity were assessed within resting-state networks that showed functional connectivity abnormalities in cognitively impaired patients with MS. RESULTS: Functional connectivity was significantly decreased in the anterior and posterior default mode networks and significantly increased in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients with MS (threshold-free cluster enhancement corrected at p ≤ 0.05, 2 sided). Networks showing functional abnormalities showed altered cerebral blood flow and anatomic connectivity locally and distally but not in overlapping locations. DISCUSSION: We provide the first evidence that functional connectivity abnormalities are accompanied by local cerebral blood flow and structural connectivity abnormalities but also demonstrate that these effects do not occur in exactly the same location. Our findings suggest a possibly shared pathologic mechanism for altered functional connectivity in brain networks in MS.

Brain structure correlates of expected social threat and reward.

Prospection (mentally simulating future events) generates emotionally-charged mental images that guide social decision-making. Positive and negative social expectancies-imagining new social interactions to be rewarding versus threatening-are core components of social approach and avoidance motivation, respectively. Interindividual differences in such positive and negative future-related cognitions may be underpinned by distinct neuroanatomical substrates. Here, we asked 100 healthy adults to vividly imagine themselves in a novel self-relevant event that was ambiguous with regards to possible social acceptance or rejection. During this task we measured participants' expectancies for social reward (anticipated feelings of social connection) or threat (anticipated feelings of rejection). On a separate day they underwent structural MRI; voxel-based morphometry was used to explore the relation between social reward and threat expectancies and regional grey matter volumes (rGMV). Increased rGMV in key default-network regions involved in prospection, socio-emotional cognition, and subjective valuation, including ventromedial prefrontal cortex, correlated with both higher social reward and lower social threat expectancies. In contrast, social threat expectancies uniquely correlated with rGMV of regions involved in social attention (posterior superior temporal sulcus, pSTS) and interoception (somatosensory cortex). These findings provide novel insight into the neurobiology of future-oriented cognitive-affective processes critical to adaptive social functioning.

Cortical and subcortical functional specificity associated with response inhibition.

Is motor response inhibition supported by a specialised neuronal inhibitory control mechanism, or by a more general system of action updating? This pre-registered study employed a context-cueing paradigm requiring both inhibitory and non-inhibitory action updating in combination with functional magnetic resonance imaging to test the specificity of responses under different updating conditions, including the cancellation of actions. Cortical regions of activity were found to be common to multiple forms of action updating. However, functional specificity during response inhibition was observed in the anterior right inferior frontal gyrus. In addition, fronto-subcortical activity was explored using a novel contrast method. These exploratory results indicate that the specificity for response inhibition observed in right prefrontal cortex continued downstream and was observed in right hemisphere subcortical activity, while left hemisphere activity was associated with right-hand response execution. Overall, our findings reveal both common and distinct correlates of response inhibition in prefrontal cortex, with exploratory analyses supporting putative models of subcortical pathways and extending them through the demonstration of lateralisation.

The role of phosphodiesterase 4 in excessive daytime sleepiness in Parkinson's disease.

INTRODUCTION: Preclinical studies suggest a link between cAMP/PKA signalling, phosphodiesterase 4 (PDE4) expression and excessive daytime sleepiness (EDS). Here, we investigated in vivo the association between PDE4 expression and EDS in Parkinson's disease (PD) patients using [11C]rolipram PET and MR imaging. METHODS: Eighteen participants, 12 PD and 6 healthy controls, underwent one [11C]rolipram PET and a multi-modal MRI scan. Probabilistic tractography was performed on subjects' diffusion data to functionally parcellate the striatum according with projections to limbic cortical areas. The severity of EDS was assessed using the Epworth Sleepiness Scale (ESS). To assess PDE4 expression in PD patients with EDS, the PD cohort was divided according to the presence (n = 5) or absence (n = 7) of EDS, defined using validated cut-off of score ≥10 on the ESS as score ≥10 on the ESS. RESULTS: PD patients with EDS showed significantly increased [11C]rolipram volume of distribution (VT) in the caudate (P = 0.029), hypothalamus (P = 0.013), hippocampus (P = 0.036) and limbic striatum (P = 0.030) compared to patients without EDS. Furthermore, higher ESS scores correlated with increased [11C]rolipram VT in the caudate (r = 0.77; P = 0.003), hypothalamus (r = 0.84; P = 0.001), hippocampus (r = 0.81; P = 0.001) and limbic subdivisions of the striatum (r = 0.80; P = 0.003). CONCLUSION: Our findings translate into humans preclinical data indicating that EDS is associated with elevated PDE4 in regions regulating sleep. The severity of EDS in PD was associated with elevated PDE4 expression; thus, suggesting a role of PDE4 in the pathophysiology of EDS in PD.

Reduced dynamics of functional connectivity and cognitive impairment in multiple sclerosis.

BACKGROUND: In multiple sclerosis (MS), abnormalities of brain network dynamics and their relevance for cognitive impairment have never been investigated. OBJECTIVES: The aim of this study was to assess the dynamic resting state (RS) functional connectivity (FC) on 62 relapsing-remitting MS patients and 65 sex-matched healthy controls enrolled at 7 European sites. METHODS: MS patients underwent clinical and cognitive evaluation. Between-group network FC differences were evaluated using a dynamic approach (based on sliding-window correlation analysis) and grouping correlation matrices into recurrent FC states. RESULTS: Dynamic FC analysis revealed, in healthy controls and MS patients, three recurrent FC states: two characterized by strong intra- and inter-network connectivity and one characterized by weak inter-network connectivity (State 3). A total of 23 MS patients were cognitively impaired (CI). Compared to cognitively preserved (CP), CI-MS patients had reduced RS-FC between subcortical and default-mode networks in the low-connectivity State 3 and lower dwell time (i.e. time spent in a given state) in the high-connectivity State 2. CI-MS patients also exhibited a lower number and a less frequent switching between meta-states, as well as a smaller distance traveled through connectivity states. CONCLUSION: Time-varying RS-FC was markedly less dynamic in CI- versus CP-MS patients, suggesting that slow inter-network connectivity contributes to cognitive dysfunction in MS.