The last decade has witnessed an increasing interest in exploring the network connectivity
of brain areas and communities. The disruption of brain networks has been linked to
variable levels of neuropsychological dysfunctions observed in individual patients
with brain disorders (Collin and van den Heuvel, 2013; Crossley et al., 2014). Understanding
the course of these changes may help understand how they contribute to risk and resilience
for both developing and aging brain disorders, and may offer personalized treatment
opportunities. The balancing act of disruptions and compensations in large-scale structural-functional
brain network organization across individuals in various brain disorders is still
unclear (Bullmore and Sporns, 2009).
The transformative brain changes occurring during the course of childhood and adolescence
are critical for the shaping of individual developmental trajectories in cognitive
and social functions, adaptability, personality, and mental health (Dosenbach et al.,
2010). The tremendous potential for neuroplasticity and environmental sensitivity
also characterized this period of development and individualized the brain functional
connectome during the course of adolescence and related patterns of maturation (Zielinski
et al., 2010; Fair et al., 2012). The progress made on both neuroscience and computational
sciences has motivated new approaches for studying brain structure and function from
a complex systems perspective (Hagmann et al., 2008; Sharp et al., 2014). These current
trends have suggested that connectivity-based methods may provide good tools in order
to understand brain functioning in healthy subjects, as well as to study changes during
lifespan, or during the time course of neurodegenerative diseases.
Brain connectivity refers to patterns of links connecting distinct units within the
nervous system. It can be studied at different scales, and therefore, units or nodes
can be defined as individual neurons, neural populations, or segregated brain regions,
described by anatomical or functional landmarks. Structural connectivity networks
can be measured through white matter tracts quantified by diffusion tractography or
correlations of morphological metrics; it can provide clue into structural architectural
features. By contrast, functional connectivity networks mainly describe the connective
properties of temporal coherences between blood oxygen level-dependent functional
MRI signals from both local and distant brain regions; thus functional connectivity
networks provide insight of a network perspective on brain dynamics. This Research
Topic “Balancing act: structural-functional circuit disruptions and compensations
in developing and aging brain disorders” brings together basic, clinical, and translational
neuroscience research with brain circuit disruptions and compensations in developing
and aging Brain Disorders. The discussions in this Research Topic report new integrated
knowledge to understand developing and aging brain disorders.
Neurovascular imbalance is generally noted in the aging population and Alzheimer's
disease (AD). It has been shown that regional cerebral blood flow (rCBF) is closely
coupled with cerebral metabolism, and the relationship between network measures and
rCBF provides insights into the mechanisms of connectivity disruptions in brain disorders.
Hu et al. discussed the coupling of rCBF and functional connectivity strength (FCS)
in Wilson's disease (WD) associated with mild cognitive impairments (MCI). They found
that the CBF-FCS correlations of patients with WD were significantly decreased in
the basal ganglia and the cerebellum and slightly increased in the prefrontal cortex
and thalamus. Qi et al. evaluated the pattern of activity in the cerebral limbic network
from the perspective of the cerebellum. Results indicated that the cerebellum was
not compromised by Alzheimer pathology in the early stages of AD, and this pattern
indicates that the sub-scale ventral attention network may play a pivotal role in
functional compensation through the coupled cerebro-cerebellar limbic network in MCI,
and the cerebellum may be a key node in the modulation of social cognition. Moreover,
patients with cerebral vascular diseases exhibit widespread differences in functional
connectivity across multiple cortical networks. Leukoaraiosis (LA) is associated with
cognitive impairment in older people and associated with dysfunctional communications
between the three basic brain networks, consisting of the default-mode network (DMN),
salience networks (SNs), and the central executive network (CEN). Chen et al. presented
the diminished negative correlations between the SN and DMN while positive correlation
between the SN and CEN were enhanced as the cognitive impairment loads increased in
patients with LA.
Traumatic brain injury (TBI) is a substantial public health problem, and can accelerate
the aging process, leading to long-term structural and functional alterations to the
brain. Wang et al. aimed to investigate the sex difference on whole-brain functional
connectivity at the network level from a cohort of acute mild TBI patients since there
were differential cognitive outcome by sex. Ye et al. investigated the changes of
α-synuclein in blood serum and its relationship with default mode network (DMN) connectivity
after acute mild TBI. The chronic consequences of TBI may contribute to the increased
risk for early cognitive decline and dementia, primarily due to diffusion axonal injury.
Yin et al. investigated longitudinal changes of white matter (WM) using diffusion
tensor imaging (DTI) and their correlations with neuropsychological tests following
mild TBI. They reported that increased fractional anisotropy values in some tracts
at 1 month post-injury were positively associated with better performance on cognitive
information processing speed at initial assessment.
Synaptic failure may critically impair information processing in the brain and may
underlie many neurodegenerative diseases. Budak and Zochowski systematically analyzed
how two types of synaptic failure (activity-independent and targeted, activity-dependent)
affect two complementary (incoming and outgoing) scale-free network structures. Williams
and Sun explored the layer and spectrotemporal architecture and laminar distribution
of high-frequency oscillations (HFOs) in a neonatal freeze lesion model of focal cortical
dysplasia (FCD). They provided the evidence that HFOs, particularly fast ripples,
is a biomarker to help define the cortical seizure zone and understand cellular level
changes underlying the HFOs. Infarction or aging in regions project to the pyramidal
tract (PyT) would result in incomplete transmission of information to the PyT and
concomitant decreases in motor planning and coordination abilities. Using the large
population data of the HCP and high magnet gradient HARDI data, Wang et al. visualized
the existence of the PyT in humans.
Cognitive aging research has identified several general patterns of compensatory neural
activity. Most studies of neural compensation limited to a between-subject design,
Samuel et al. examined the neural compensation from a fatigue paradigm and reflect
neural activities typically associated with aging-related cognitive impairment. In
the young cohort, they found that both behavioral performance and neural activity
declined as the experiment progressed, reflecting the deleterious effects of cognitive
fatigue. Both behavioral performance and neural activity did not decline as the experiment
progressed in the older cohort, in contrast to the young. Pelzer et al. reviewed the
literature regarding quantitative susceptibility mapping (QSM), MEG, and rs-fMRI detected
changes in motor and non-motor symptoms in Parkinson's disease (PD).
Finally, the morphological features of gyri and sulci change during aging and development-related
psychiatric disorders such as schizophrenia, reflecting a potential of gyral-sulcal
indices as a biomarker for developmental and aging related disorders. Fluid intelligence,
as a measure of higher-order relational reasoning, has been argued to be linked to
specific functional outcomes and to variations in human neuronal structure and function.
Yang et al. explored the temporal variability of cortical gyral-sulcal resting state
functional activity and its association with fluid intelligence measures on the Human
Connectome Project dataset, which provided novel insights to understand the functional
relevance of gyri and sulci. Social anxiety and risk of mental disorders have increased
in the left-behind children (LBC). Fu et al. provided empirical evidence of altered
brain structure in LBC compared to non-LBC, responsible for emotion regulation and
processing, which may account for mental disorders and negative life outcome of LBC.
Author Contributions
LB and TZ drafted the work and revised it critically for important intellectual content.
All of the authors provide approval for publication of the content, agree to be accountable
for all aspects of the work in ensuring that questions related to the accuracy or
integrity of any part of the work are appropriately investigated and resolved, and
made substantial contributions to the conception and design of the work.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.