Using fMRI to assess brain activity in people with Down Syndrome: A systematic review

Background: In the last few years, many investigations have focused on brain activity in general and in populations with different pathologies using non-invasive techniques such as electroencefalography (EEG), positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and magnetic resonance imaging (MRI). However, the use of non-invasive techniques to detect brain signals to evaluate the cognitive activity of people with Down syndrome (DS) has not been sufficiently addressed. The objective of this study is to describe the state-of-the-art in fMRI techniques for recording brain signals in people with DS. Method: A systematic review was performed based on PRISMA recommendations; only nine papers on this topic have been published. Three independent researchers selected all relevant information from each paper. Analyses of information concordance showed a high value of agreement between researchers. Results: Although few relevant works have been published, the use of fMRI in people with DS is becoming an appropriate option to study brain function in this population. Of the nine identified papers, five used task designs, and four used resting-state paradigms. Conclusion: Thus, we emphasize the need to incorporate rigorous cognitive activity procedures in evaluations of the DS population. We suggest several factors (such as head correction movements and paired sample techniques) that must be considered when designing an fMRI study with a task or a resting-state paradigm in a DS population

Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity.

Down's syndrome is a chromosomal disorder that invariably results in both intellectual disability and Alzheimer's disease neuropathology. However, only a limited number of studies to date have investigated intrinsic brain network organisation in people with Down's syndrome, none of which addressed the links between functional connectivity and Alzheimer's disease. In this cross-sectional study, we employed 11 C-Pittsburgh Compound-B (PiB) positron emission tomography in order to group participants with Down's syndrome based on the presence of fibrillar beta-amyloid neuropathology. We also acquired resting state functional magnetic resonance imaging data to interrogate the connectivity of the default mode network; a large-scale system with demonstrated links to Alzheimer's disease. The results revealed widespread positive connectivity of the default mode network in people with Down's syndrome (n = 34, ages 30-55, median age = 43.5) and a stark lack of anti-correlation. However, in contrast to typically developing controls (n = 20, ages 30-55, median age = 43.5), the Down's syndrome group also showed significantly weaker connections in localised frontal and posterior brain regions. Notably, while a comparison of the PiB-negative Down's syndrome group (n = 19, ages 30-48, median age = 41.0) to controls suggested that alterations in default mode connectivity to frontal brain regions are related to atypical development, a comparison of the PiB-positive (n = 15, ages 39-55, median age = 48.0) and PiB-negative Down's syndrome groups indicated that aberrant connectivity in posterior cortices is associated with the presence of Alzheimer's disease neuropathology. Such distinct profiles of altered connectivity not only further our understanding of the brain physiology that underlies these two inherently linked conditions but may also potentially provide a biomarker for future studies of neurodegeneration in people with Down's syndrome

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects

Environmental and genetic influences on neurocognitive development: the importance of multiple methodologies and time-dependent intervention

Genetic mutations and environmental factors dynamically influence gene expression and developmental trajectories at the neural, cognitive, and behavioral levels. The examples in this article cover different periods of neurocognitive development—early childhood, adolescence, and adulthood—and focus on studies in which researchers have used a variety of methodologies to illustrate the early effects of socioeconomic status and stress on brain function, as well as how allelic differences explain why some individuals respond to intervention and others do not. These studies highlight how similar behaviors can be driven by different underlying neural processes and show how a neurocomputational model of early development can account for neurodevelopmental syndromes, such as autism spectrum disorders, with novel implications for intervention. Finally, these studies illustrate the importance of the timing of environmental and genetic factors on development, consistent with our view that phenotypes are emergent, not predetermined

Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI

Tourette syndrome (TS) is a developmental neuropsychiatric disorder characterized by motor and vocal tics. Individuals with TS would benefit greatly from advances in prediction of symptom timecourse and treatment effectiveness. As a first step, we applied a multivariate method - support vector machine (SVM) classification - to test whether patterns in brain network activity, measured with resting state functional connectivity (RSFC) MRI, could predict diagnostic group membership for individuals. RSFC data from 42 children with TS (8-15 yrs) and 42 unaffected controls (age, IQ, in-scanner movement matched) were included. While univariate tests identified no significant group differences, SVM classified group membership with ~70% accuracy (p < .001). We also report a novel adaptation of SVM binary classification that, in addition to an overall accuracy rate for the SVM, provides a confidence measure for the accurate classification of each individual. Our results support the contention that multivariate methods can better capture the complexity of some brain disorders, and hold promise for predicting prognosis and treatment outcome for individuals with TS

Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome.

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study

Building an adaptive brain across development: targets for neurorehabilitation must begin in infancy

Much progress has been made toward behavioural and pharmacological intervention in intellectual disability, which was once thought too difficult to treat. Down syndrome research has shown rapid advances, and clinical trials are currently underway, with more on the horizon. Here, we review the literature on the emergent profile of cognitive development in Down syndrome, emphasizing that treatment approaches must consider how some “end state” impairments, such as language deficits, may develop from early alterations in neural systems beginning in infancy. Specifically, we highlight evidence suggesting that there are pre- and early postnatal alterations in brain structure and function in Down syndrome, resulting in disturbed network function across development. We stress that these early alterations are likely amplified by Alzheimer’s disease progression and poor sleep. Focusing on three network hubs (prefrontal cortex, hippocampus, and cerebellum), we discuss how these regions may relate to evolving deficits in cognitive function in individuals with Down syndrome, and to their language profile in particular

Typical and atypical development of the brain’s functional network architecture

The human brain is a complex organ that gives rise to many behaviors. Specialized neural regions cooperate as functional networks that form an intricate functional architecture. Development provides a unique window into how brain functioning and human thinking are affected if the necessary neural features and connections are not fully formed. Similarly, developmental disorders can shed light on atypical trajectories of neural systems that may lead to or be a consequence of symptomatic behavior. A description of the typical and atypical development of functional networks is essential to identify the features of brain organization critical for mature human thinking and to provide better diagnosis, treatment, and prognosis in neurodevelopmental disorders. Recently, resting state functional MRI has been found to illuminate functionally related regions, giving access to functional networks and the organization of brain’s functional architecture. This thesis aims to harness resting-state functional connectivity to explore how functional networks coordinate over the course of development. First, I present our work investigating the organizing principles of typical developmental patterns in functional networks (Chapter 2). Then, I apply these approaches to the atypical development of functional networks in Tourette syndrome (TS), a developmental disorder characterized by motor and vocal tics. In this work, we tested whether the patterns in functional networks that distinguish individuals with TS from controls differ between children and adults and alter the typical developmental pattern of functional networks (Chapter 3). Lastly, I present our work to identify and describe the coordination of specific functional networks that develop atypically in TS (Chapter 4)

Neuroimaging of typical and atypical development: A perspective from multiple levels of analysis

To date, research involving functional neuroimaging of typical and atypical development has depended on several assumptions about the postnatal maturation of the brain. We consider evidence from multiple levels of analysis that brings into question these underlying assumptions and advance an alternative view. This alternative view, based on an “interactive specialization” approach to postnatal brain development, indicates that there is a need to: obtain data from early in development; focus more on differences in interregional interactions rather than searching for localized, discrete lesions; examine the temporal dynamics of neural processing; and move away from deficits to image tasks in which atypical participants perform as well as typically developing participant

Resting-state default mode network connectivity in young individuals with Down syndrome

Background: Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using restingstate fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years). Method: A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups). Results: The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated. Conclusions: A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS