Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models.

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.

Treatment and outcomes of patients with chronic lung disease and acute myocardial infarction: Insights from the nationwide AMIS plus registry.

BACKGROUND: Limited data are available on patients with chronic lung disease (CLD) presenting with acute myocardial infarction (AMI). We aimed to analyse baseline characteristics, treatment and outcome of those patients enrolled in the Swiss nationwide prospective AMIS Plus registry. METHODS: All AMI patients enrolled between January 2002 and December 2021 with data on CLD, as defined in the Charlson Comorbidity Index, were included. The primary endpoints were in-hospital mortality and major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, reinfarction and cerebrovascular events. Baseline characteristics, in-hospital treatments and outcomes were analysed using descriptive statistics and logistic regression. RESULTS: Among 53,680 AMI patients enrolled during this time, 5.8% had CLD. Compared with patients without CLD, CLD patients presented more frequently with non-ST-elevation myocardial infarction (MI) and type 2 MI (12.8% vs. 6.5%, p < 0.001). With respect to treatment, CLD patients were less likely to receive P2Y12 inhibitors (p < 0.001) and less likely to undergo percutaneous coronary interventions (68.7% vs. 82.5%; p < 0.001). In-hospital mortality declined in AMI patients with CLD over time (from 12% in 2002 to 7.3% in 2021). Multivariable regression analysis showed that CLD was an independent predictor for MACCE (adjusted OR was 1.28 [95% CI 1.07-1.52], p = 0.006). CONCLUSION: Patients with CLD and AMI were less likely to receive evidence-based pharmacologic treatments, coronary revascularization and had a higher incidence of MACCE during their hospital stay compared to those without CLD. Over 20 years, in-hospital mortality was significantly reduced in AMI patients, especially in those with CLD.

Shared genetic influences on resting-state functional networks of the brain.

The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

Evaluation of data imputation strategies in complex, deeply-phenotyped data sets: the case of the EU-AIMS Longitudinal European Autism Project.

An increasing number of large-scale multi-modal research initiatives has been conducted in the typically developing population, e.g. Dev. Cogn. Neur. 32:43-54, 2018; PLoS Med. 12(3):e1001779, 2015; Elam and Van Essen, Enc. Comp. Neur., 2013, as well as in psychiatric cohorts, e.g. Trans. Psych. 10(1):100, 2020; Mol. Psych. 19:659-667, 2014; Mol. Aut. 8:24, 2017; Eur. Child and Adol. Psych. 24(3):265-281, 2015. Missing data is a common problem in such datasets due to the difficulty of assessing multiple measures on a large number of participants. The consequences of missing data accumulate when researchers aim to integrate relationships across multiple measures. Here we aim to evaluate different imputation strategies to fill in missing values in clinical data from a large (total N = 764) and deeply phenotyped (i.e. range of clinical and cognitive instruments administered) sample of N = 453 autistic individuals and N = 311 control individuals recruited as part of the EU-AIMS Longitudinal European Autism Project (LEAP) consortium. In particular, we consider a total of 160 clinical measures divided in 15 overlapping subsets of participants. We use two simple but common univariate strategies-mean and median imputation-as well as a Round Robin regression approach involving four independent multivariate regression models including Bayesian Ridge regression, as well as several non-linear models: Decision Trees (Extra Trees., and Nearest Neighbours regression. We evaluate the models using the traditional mean square error towards removed available data, and also consider the Kullback-Leibler divergence between the observed and the imputed distributions. We show that all of the multivariate approaches tested provide a substantial improvement compared to typical univariate approaches. Further, our analyses reveal that across all 15 data-subsets tested, an Extra Trees regression approach provided the best global results. This not only allows the selection of a unique model to impute missing data for the LEAP project and delivers a fixed set of imputed clinical data to be used by researchers working with the LEAP dataset in the future, but provides more general guidelines for data imputation in large scale epidemiological studies.

Medial prefrontal decoupling from the default mode network benefits memory.

In the last few years the involvement of the medial prefrontal cortex (mPFC) in memory processing has received increased attention. It has been shown to be centrally involved when we use prior knowledge (schemas) to improve learning of related material. With the mPFC also being one of the core hubs of the default mode network (DMN) and the DMN's role in memory retrieval, we decided to investigate whether the mPFC in a schema paradigm acts independent of the DMN. We tested this with data from a cross-sectional developmental study with a schema paradigm. During retrieval of schema items, the mPFC decoupled from the DMN with the degree of decoupling predicting memory performance. This finding suggests that a demand specific reconfiguration of the DMN supports schema memory. Additionally, we found that in the control condition, which relied on episodic memory, activity in the parahippocampal gyrus was positively related to memory performance. We interpret these results as a demand specific network reconfiguration of the DMN: a decoupling of the mPFC to support schema memory and a decoupling of the parahippocampal gyrus facilitating episodic memory.

Discovering the shared biology of cognitive traits determined by genetic overlap.

Investigating the contribution of biology to human cognition has assumed a bottom-up causal cascade where genes influence brain systems that activate, communicate, and ultimately drive behavior. Yet few studies have directly tested whether cognitive traits with overlapping genetic underpinnings also rely on overlapping brain systems. Here, we report a step-wise exploratory analysis of genetic and functional imaging overlaps among cognitive traits. We used twin-based genetic analyses in the human connectome project (HCP) dataset (N â€‹= â€‹486), in which we quantified the heritability of measures of cognitive functions, and tested whether they were driven by common genetic factors using pairwise genetic correlations. Subsequently, we derived activation maps associated with cognitive tasks via functional imaging meta-analysis in BrainMap (N â€‹= â€‹4484), and tested whether cognitive traits that shared genetic variation also exhibited overlapping brain activation. Our genetic analysis determined that six cognitive measures (cognitive flexibility, no-go continuous performance, fluid intelligence, processing speed, reading decoding and vocabulary comprehension) were heritable (0.3 â€‹< â€‹h2 â€‹< â€‹0.5), and genetically correlated with at least one other heritable cognitive measure (0.2 â€‹< â€‹ρg â€‹< â€‹0.35). The meta-analysis showed that two genetically-correlated traits, cognitive flexibility and fluid intelligence (ρg â€‹= â€‹0.24), also had a significant brain activation overlap (ρperm â€‹= â€‹0.29). These findings indicate that fluid intelligence and cognitive flexibility rely on overlapping biological features, both at the neural systems level and at the molecular level. The cross-disciplinary approach we introduce provides a concrete framework for data-driven quantification of biological convergence between genetics, brain function, and behavior in health and disease.

Lesion locations influencing baseline severity and early recovery in ischaemic stroke.

BACKGROUND AND PURPOSE: Strokes caused by lesions to certain brain areas are associated with poor outcome, which is important both prognostically and to understand the neural basis for recovery. However, lesion anatomy associations with outcome may occur because of effects on baseline severity rather than because of effects on recovery per se. Here, all common stroke locations were surveyed to determine the strongest lesion anatomy associations separately for baseline functional severity and proportional recovery. Since most recovery occurs early, the focus here is on functional changes over the first week. METHOD: Global functional scores (National Institutes of Health Stroke Scale) at baseline and proportional recovery over 1 week were derived from the records of 550 ischaemic stroke patients and related to magnetic resonance imaging lesion location using voxel-lesion mapping. The effects of lesions extending over more than one location were also considered. Cross-validation estimated the percentage of recovery rate variance (r(2) ) accountable by lesion location information. RESULTS: High baseline severity was associated with lesions to the left capsule, striatum and thalamocortical white matter, whereas high recovery rate was associated with lesions to more superficial left fronto-temporal areas. Low recovery rates were associated with lesions to bilateral parietal, right insula, medial frontal, capsule and brainstem. Inclusion of these regions into a multivariate model of proportional recovery rate increased r(2) from 8% to 45%. CONCLUSION: The strongest stroke lesion location associations with 1-week recovery were identified, and it was shown that anatomical information accounts for a sizeable proportion of early recovery variability.

Gastrointestinal pathogens detected by multiplex nucleic acid amplification testing in stools of pediatric patients and patients returning from the tropics.

BACKGROUND: Gastrointestinal infections are caused by a broad spectrum of pathogens. Conventional diagnostic procedures are resource and time consuming due to single pathogen testing, often in different laboratories. METHOD: We analyzed 312 consecutive stool samples from pediatric patients (n = 127) with gastroenteritis or from adult travelers returning from the tropics with suspected parasite infestation (n = 185) using commercial multiplex nucleic acid amplification testing (NAT) (xTAG gastrointestinal pathogen panel, Luminex) covering 15 diarrhea-causing pathogens. The results of the positive samples and a representative number of negative samples were compared to standard methods, including NAT, direct antigen detection (DAD), bacterial culture and microscopy. RESULTS: Of the 185 samples from adult travelers, 21 (11 %) were multiplexNAT-positive, with enterotoxigenic Escherichia coli (4 %) being the predominant pathogen. Microscopic examination revealed Blastocystis hominis in 23 % not covered by the panel. MultiplexNAT scored positive in 66 pediatric samples (52 %), with rotavirus (27 %) being the most prevalent. All adenovirus-, rotavirus-, Clostridium difficile- and Cryptosporidium-positive samples were confirmed in external laboratories, but only 40 % of norovirus- and 29 % of Giardia-positive samples. Analysis of frozen specimens by bacterial culture showed the highest discrepancies with the multiplexNAT. CONCLUSION: Our study demonstrates broad detection of relevant gastroenteritis pathogens by multiplexNAT with a short turnaround time. This is important for diagnosis, infection control and empiric management of gastroenteritis patients, but may be selectively complemented by bacterial culture and resistance testing.

From egg to hatchling: preferential retention of fatty acid biomarkers in young-of-the-year Port Jackson sharks Heterodontus portusjacksoni.

The muscle and liver fatty acid composition of young-of-the-year (YOY) Port Jackson sharks Heterodontus portusjacksoni were investigated to determine the effects of a known dietary lipid source v. maternal input as demonstrated by egg yolk fatty acid profiles. Ten Heterodontus portusjacksoni egg yolks were collected in situ and compared with four hatched H. portusjacksoni fed a known diet in a controlled feeding experiment of 185 days. This study demonstrated that fatty acids are probably conservatively transferred from egg yolks to YOY H. portusjacksoni, while diet did not have a large effect on the fatty acid composition of the liver or muscle.

[Resting state functional MRI of the brain]. / Funktionelle MRT des Gehirns im Ruhezustand.

The article presents an introduction to studies of the brain using functional magnetic resonance imaging during rest (rsfMRI). These studies are based on the fact that the resting brain exhibits a certain level of constant background activity. These spontaneous rsfMRT activities are characterized by fluctuations of the blood oxygenation level-dependent (BOLD) signal (typically in the low frequency part of the power spectrum < 0.1 Hz), which correlate with the local neuronal activity and can be seen as a result of neuronal coupling of monosynaptic and polysynaptic connections. The first network, described in detail is the so-called default mode network (DMN). This includes the medial prefrontal cortex (MPC), the posterior cingulate cortex (PCC), the precuneus (PrC), parts of the medial temporal lobe and the lateral inferior parietal lobe. In addition, a number of other resting state networks (RSNs), such as a motor, somatosensory, visual, auditory and cognitive system has been described, which partly process long-term connections from the cerebral cortex to the diencephalon, brain stem and cerebellum.

Distinct frontal systems for response inhibition, attentional capture, and error processing.

Stopping an action in response to an unexpected event requires both that the event is attended to, and that the action is inhibited. Previous neuroimaging investigations of stopping have failed to adequately separate these cognitive elements. Here we used a version of the widely used Stop Signal Task that controls for the attentional capture of stop signals. This allowed us to fractionate the contributions of frontal regions, including the right inferior frontal gyrus and medial frontal cortex, to attentional capture, response inhibition, and error processing. A ventral attentional system, including the right inferior frontal gyrus, has been shown to respond to unexpected stimuli. In line with this evidence, we reasoned that lateral frontal regions support attentional capture, whereas medial frontal regions, including the presupplementary motor area (pre-SMA), actually inhibit the ongoing action. We tested this hypothesis by contrasting the brain networks associated with the presentation of unexpected stimuli against those associated with outright stopping. Functional MRI images were obtained in 26 healthy volunteers. Successful stopping was associated with activation of the right inferior frontal gyrus, as well as the pre-SMA. However, only activation of the pre-SMA differentiated stopping from a high-level baseline that controlled for attentional capture. As expected, unsuccessful attempts at stopping activated the anterior cingulate cortex. In keeping with work in nonhuman primates these findings demonstrate that successful motor inhibition is specifically associated with pre-SMA activation.

Genetic control over the resting brain.

The default-mode network, a coherent resting-state brain network, is thought to characterize basal neural activity. Aberrant default-mode connectivity has been reported in a host of neurological and psychiatric illnesses and in persons at genetic risk for such illnesses. Whereas the neurophysiologic mechanisms that regulate default-mode connectivity are unclear, there is growing evidence that genetic factors play a role. In this report, we estimate the importance of genetic effects on the default-mode network by examining covariation patterns in functional connectivity among 333 individuals from 29 randomly selected extended pedigrees. Heritability for default-mode functional connectivity was 0.424 +/- 0.17 (P = 0.0046). Although neuroanatomic variation in this network was also heritable, the genetic factors that influence default-mode functional connectivity and gray-matter density seem to be distinct, suggesting that unique genes influence the structure and function of the network. In contrast, significant genetic correlations between regions within the network provide evidence that the same genetic factors contribute to variation in functional connectivity throughout the default mode. Specifically, the left parahippocampal region was genetically correlated with all other network regions. In addition, the posterior cingulate/precuneus region, medial prefrontal cortex, and right cerebellum seem to form a subnetwork. Default-mode functional connectivity is influenced by genetic factors that cannot be attributed to anatomic variation or a single region within the network. By establishing the heritability of default-mode functional connectivity, this experiment provides the obligatory evidence required before these measures can be considered as endophenotypes for psychiatric or neurological illnesses or to identify genes influencing intrinsic brain function.

[New spirometric reference values for children and adolescents in Germany considering height and non-linear age effects: the LUNOKID-study]. / Neue spirometrische Referenzwerte für Kinder und Jugendliche in Deutschland unter Berücksichtigung der Größe und nichtlinearer Alterseffekte: Die LUNOKID-Studie.

BACKGROUND: Comparing children's lung function with reference values is important for diagnosing respiratory diseases. The values by Zapletal et al., commonly used nowadays, are not appropriate for the current stage of children's development. We have now developed new reference values and a lower limit of normal (LLN) for children in Germany, divided into small-range age and height categories. MATERIAL AND METHODS: We examined 4- to 18-year-old children in 3 German communities under field conditions. 1943 children were healthy and had a visually acceptable lung function which also fulfilled international quality criteria. We used the regression model LMS, which was introduced by Stanojevic and Quanjer in this context. RESULTS: There were significant differences between the measured lung function and the predicted values according to Zapletal et al. The lung function did not only depend on the child's height, but also in a non-linear way on the age. The variation coefficient did not depend on age. CONCLUSIONS: To avoid diagnostic errors, the currently often used reference values according to Zapletal et al. should no longer be used. The non-linear dependence on age corresponds to the recently published results by Stanojevic and Quanjer.

Age-related adaptations of brain function during a memory task are also present at rest.

Several studies have demonstrated age-related regional differences in the magnitude of the BOLD signal using task-based fMRI. It has been suggested that functional changes reflect either compensatory or de-differentiation mechanisms, both of which assume response to a specific stimulus. Here, we have tested whether ageing affects both task-based and resting brain function, and the extent to which functional changes are mediated by reductions in grey matter (GM) volume. Two groups, of 22 healthy younger and 22 older volunteers, underwent an imaging protocol involving structural and functional MRI, both during a memory task and at rest. The two groups had similar socio-demographical characteristics and cognitive performance. Image analysis revealed both structural and functional differences. Increased BOLD signal in older relative to younger volunteers was mainly observed in the frontal lobes, both during the task and at rest. Functional changes in the frontal lobes were largely located in brain regions spared from GM loss, and adding GM covariates to the fMRI analysis did not significantly alter the group differences. Our results are consistent with the suggestion that, during normal ageing, the brain responds to neuronal loss by fine-tuning connections between spared neurons. Longitudinal studies will be necessary to fully test this hypothesis.

Differential effects of the APOE genotype on brain function across the lifespan.

Increasing age and carrying an APOE ε4 allele are well established risk factors for Alzheimer's disease (AD). The earlier age of onset of AD observed in ε4-carriers may reflect an accelerated aging process. We recently reported that APOE genotype modulates brain function decades before the appearance of any cognitive or clinical symptoms. Here we test the hypothesis that APOE influences brain aging by comparing healthy ε4-carriers and non-carriers, using the same imaging protocol in distinct groups of younger and older healthy volunteers. A cross-sectional factorial design was used to examine the effects of age and APOE genotype, and their interaction, on fMRI activation during an encoding memory task. The younger (N=36; age range 20-35; 18 ε4-carriers) and older (35 middle-age/elderly; age range 50-78 years; 15 ε4-carriers) healthy volunteers taking part in the study were cognitively normal. We found a significant interaction between age and ε4-status in the hippocampi, frontal pole, subcortical nuclei, middle temporal gyri and cerebellum, such that aging was associated with decreased activity in e4-carriers and increased activity in non-carriers. Reduced cerebral blood flow was found in the older ε4-carriers relative to older non-carriers despite preserved grey matter volume. Overactivity of brain function in young ε4-carriers is disproportionately reduced with advancing age even before the onset of measurable memory impairment. The APOE genotype determines age-related changes in brain function that may reflect the increased vulnerability of ε4-carriers to late-life pathology or cognitive decline.

Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity.

Research on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data.We analyzed data from 58 healthy females (mean age = â€¯21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects' large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation.LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found that the abundance of Prevotella genus was associated with the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks.We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans considering the complexity of both systems.

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers.

BACKGROUND: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. METHODS: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). RESULTS: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. LIMITATIONS: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. CONCLUSIONS: Biological motion preference elicits small-to-medium-sized case-control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear.

Somatosensory cortical activation identified by functional MRI in preterm and term infants.

Functional MRI (fMRI) has not previously been used systematically to investigate brain function in preterm infants. We here describe statistically robust and reproducible fMRI results in this challenging subject group using a programmable somatosensory stimulus synchronized with MR image acquisition which induced well-localized positive blood oxygen level dependent (BOLD) responses contralateral to the side of the stimulation in: 11 preterm infants (median post menstrual age 33 weeks and 4 days, range 29+1 to 35+3); 6 control infants born at term gestational age; and 18 infants born preterm (median gestational age at birth 30 weeks and 5 days, range 25+4 to 36+0) but studied at term corrected gestational age. Bilateral signals were identified in 8 of the ex-preterm infants at term age. Anatomical confirmation of appropriate activations was provided with diffusion tensor imaging (DTI) based tractography which identified connecting pathways from the regions of activation through the ipsilateral corticospinal tracts and posterior limb of the internal capsule. These results demonstrate that it is possible to reliably identify positive BOLD signals in the infant brain and that fMRI techniques can also be applied in the study of preterm infants.

Short-term adaptation to a simple motor task: a physiological process preserved in multiple sclerosis.

Short-term adaptation indicates the attenuation of the functional MRI (fMRI) response during repeated task execution. It is considered to be a physiological process, but it is unknown whether short-term adaptation changes significantly in patients with brain disorders, such as multiple sclerosis (MS). In order to investigate short-term adaptation during a repeated right-hand tapping task in both controls and in patients with MS, we analyzed the fMRI data collected in a large cohort of controls and MS patients who were recruited into a multi-centre European fMRI study. Four fMRI runs were acquired for each of the 55 controls and 56 MS patients at baseline and 33 controls and 26 MS patients at 1-year follow-up. The externally cued (1 Hz) right hand tapping movement was limited to 3 cm amplitude by using at all sites (7 at baseline and 6 at follow-up) identically manufactured wooden frames. No significant differences in cerebral activation were found between sites. Furthermore, our results showed linear response adaptation (i.e. reduced activation) from run 1 to run 4 (over a 25 minute period) in the primary motor area (contralateral more than ipsilateral), in the supplementary motor area and in the primary sensory cortex, sensory-motor cortex and cerebellum, bilaterally. This linear activation decay was the same in both control and patient groups, did not change between baseline and 1-year follow-up and was not influenced by the modest disease progression observed over 1 year. These findings confirm that the short-term adaptation to a simple motor task is a physiological process which is preserved in MS.

Reduced resting-state brain activity in the "default network" in normal aging.

Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes, but also alterations in the integration of regional brain activity (functional brain connectivity) underlie the observed age-related deficits. Here, we examined the functional properties of brain networks based on spontaneous fluctuations within brain systems using functional magnetic resonance imaging. We hypothesized that functional connectivity of intrinsic brain activity in the "default-mode" network (DMN) is affected by normal aging and that this relates to cognitive function. Ten younger and 22 older subjects were scanned at "rest," that is, lying awake with eyes closed. Our results show decreased activity in older versus younger subjects in 2 resting-state networks (RSNs) resembling the previously described DMN, containing the superior and middle frontal gyrus, posterior cingulate, middle temporal gyrus, and the superior parietal region. These results remain significant after correction for RSN-specific gray matter volume. The relevance of these findings is illustrated by the correlation between reduced activity of one of these RSNs and less effective executive functioning/processing speed in the older group.