Age-associated patterns in gray matter volume, cerebral perfusion and BOLD oscillations in children and adolescents

The Role of Blood Oxygen Level Dependent Signal Variability in Pediatric Neuroscience: A Systematic Review

BACKGROUND

As pediatric BOLD Signal Variability (SV) analysis is relatively novel, there is a need to provide a foundational framework that gives researchers an entry point into engaging with the topic. This begins with clarifying the definition of BOLD signal variability by identifying and categorizing the various metrics utilized to measure BOLD SV.

METHODS

A systematic review of the literature was conducted. Inclusion criteria were restricted to studies utilizing any metric of BOLD SV and with individuals younger than 18 in the study population. The definition of BOLD SV was any measure of intra-individual variability in the BOLD signal. Five databases were searched: Psychinfo, Healthstar, MEDLINE, Embase, and Scopus.

RESULTS

A total of 17 observational studies, including male (n = 1796) and female (n = 1324) pediatric participants were included. Eight studies quantified variability as the amount of deviation from the average BOLD signal, seven used complexity-based metrics, three used correlation measures of variability, and one used the structure of the hemodynamic response function. In this study, 10 methods of quantifying signal variability were identified. Associations and trends in BOLD SV were commonly found with age, factors specific to mental and/or neurological disorders such as attention deficit disorder, epilepsy, psychotic symptoms, and performance on psychological and behavioral tasks.

CONCLUSIONS

BOLD SV is a potential biomarker of neurodevelopmental and neurological conditions and symptom severity in mental disorders for defined pediatric populations. Studies that establish clinical trends and identify the mechanisms underlying BOLD SV with a low risk of bias are needed before clinical applications can be utilized by physicians.

Altered Neurovascular Coupling for Multidisciplinary Intensive Rehabilitation in Parkinson's Disease

Effective rehabilitation in Parkinson's disease (PD) is related to brain reorganization with restoration of cortico-subcortical networks and compensation of frontoparietal networks; however, further neural rehabilitation evidence from a multidimensional perspective is needed. To investigate how multidisciplinary intensive rehabilitation treatment affects neurovascular coupling, 31 PD patients (20 female) before and after treatment and 30 healthy controls (17 female) underwent blood oxygenation level-dependent functional magnetic resonance imaging and arterial spin labeling scans. Cerebral blood flow (CBF) was used to measure perfusion, and fractional amplitude of low-frequency fluctuation (fALFF) was used to measure neural activity. The global CBF-fALFF correlation and regional CBF/fALFF ratio were calculated as neurovascular coupling. Dynamic causal modeling (DCM) was used to evaluate treatment-related alterations in the strength and directionality of information flow. Treatment reduced CBF-fALFF correlations. The altered CBF/fALFF exhibited increases in the left angular gyrus and the right inferior parietal gyrus and decreases in the bilateral thalamus and the right superior frontal gyrus. The CBF/fALFF alteration in right superior frontal gyrus showed correlations with motor improvement. Further, DCM indicated increases in connectivity from the superior frontal gyrus and decreases from the thalamus to the inferior parietal gyrus. The benefits of rehabilitation were reflected in the dual mechanism, with restoration of executive control occurring in the initial phase of motor learning and compensation of information integration occurring in the latter phase. These findings may yield multimodal insights into the role of rehabilitation in disease modification and identify the dorsolateral superior frontal gyrus as a potential target for noninvasive neuromodulation in PD.SIGNIFICANCE STATEMENT Although rehabilitation has been proposed as a promising supplemental treatment for PD as it results in brain reorganization, restoring cortico-subcortical networks and eliciting compensatory activation of frontoparietal networks, further multimodal evidence of the neural mechanisms underlying rehabilitation is needed. We measured the ratio of perfusion and neural activity derived from arterial spin labeling and blood oxygenation level-dependent fMRI data and found that benefits of rehabilitation seem to be related to the dual mechanism, restoring executive control in the initial phase of motor learning and compensating for information integration in the latter phase. We also identified the dorsolateral superior frontal gyrus as a potential target for noninvasive neuromodulation in PD patients.

Longitudinal Changes in Resting State FMRI Spectra in Children

Longitudinal studies can provide more precise measure of brain development, as they focus on within-subject variability, as opposed to cross-sectional studies. In this study, we track longitudinal changes in resting state fMRI data using spectrum of time-courses generated via group independent component analysis (gICA), in a multi time point dataset containing healthy children 8-18 years old, collected on both eyes open and eyes closed resting state conditions. Clinical Relevance - Tracking normal brain development and identifying biomarkers of healthy brain development are critically important to diagnose mental disorders at early ages. We found increased spectral power in low frequencies and decreased spectral power in high frequencies in children with typical development in both the eyes open and eyes closed conditions though the eyes closed condition showed greater changes with development mostly in the visual networks. Results are also replicated on an independent dataset.

Altered resting fMRI spectral power in data-driven brain networks during development: A longitudinal study

BACKGROUND

Longitudinal studies provide a more precise measure of brain development over time, as they focus on within subject variability, as opposed to cross-sectional studies. This is especially important in children, where rapid brain development occurs, and inter-subject variability can be large. Tracking healthy brain development and identifying markers of typical development are also critically important to diagnose mental disorders at early ages.

NEW METHOD

We track longitudinal changes in spectral power of time-courses using a unique non-binning approach assessed with group independent component analysis, in a large multi time-point resting state functional magnetic resonance imaging dataset (N = 124) containing healthy children from 8.2 to 17.6 years old (m=12.6) called the Developmental Chronnecto-Genomics study. We examined how eyes open (EO) and eyes closed (EC) resting states play a role in age-related spectral differences, as several studies have reported differences in these conditions.

RESULTS

Typical brain development shows increased spectral power in low frequencies and decreased spectral power in high frequencies in as children grow and develop, for both the EO and EC conditions. In addition, we observed significant differences in power spectra between EO and EC and between sexes, mainly suggesting higher spectral power in females at middle and high frequencies. A replication analysis using the Adolescent Brain Cognitive Development data (N = 3371, mean age 9.9 years old) further supported this result, also showing general increases in low frequencies and decreases in higher frequencies, though some network level differences are present comparing to the main dataset.

COMPARISON WITH EXISTING METHOD

Our results indicate that spectral power changes significantly with typical development and our non-binning approach shows these changes with more detailed frequency resolution comparing to binning approaches. This is important as many studies reported an association of higher frequency power with brain disorders.

CONCLUSION

Our findings of decreased spectral power in the high frequencies with development may be a general marker of typical development., though this needs further investigation.

A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.

Age-dependent Intracranial Artery Morphology in Healthy Children

PURPOSE

Evaluation of intracranial artery morphology plays an important role in diagnosing a variety of neurovascular diseases. In addition to clinical symptoms, diagnosis currently relies on qualitative rather than quantitative evaluation of vascular imaging sequences, such as magnetic resonance angiography (MRA). However, there is a paucity of literature on normal arterial morphology in the pediatric population across brain development. We aimed to quantitatively assess normal, age-related changes in artery morphology in children.

METHODS

We performed retrospective analysis of pediatric MRA data obtained from a tertiary referral center. An MRA dataset from 98 children (49 boys/49 girls) aged 0.6-20 years (median = 11.5 years) with normal intracranial vasculature was retrospectively collected between 2011 and 2018. All arteries were automatically segmented to determine the vessel radius. Using an atlas-based approach, the average radius and density of arteries were measured in the three main cerebral vascular territories and the radius of five major arteries was determined at corresponding locations.

RESULTS

The radii of the major arteries as well as the average artery radius and density in the different vascular territories in the brain remained constant throughout childhood and adolescence (|r| < 0.369 in all cases).

CONCLUSION

This study presents the first automated evaluation of intracranial vessel morphology on MRA across childhood. Our results can serve as a framework for quantitative evaluation of cerebral vessel morphology in the setting of pediatric neurovascular diseases.

Developmental Differences in Affective Representation Between Prefrontal and Subcortical Structures

Developmental studies have identified differences in prefrontal and subcortical affective structures between children and adults, which correspond with observed cognitive and behavioral maturations from relatively simplistic emotional experiences and expressions to more nuanced, complex ones. However, developmental changes in the neural representation of emotions have not yet been well explored. It stands to reason that adults and children may demonstrate observable differences in the representation of affect within key neurological structures implicated in affective cognition. Forty-five participants (25 children; 20 adults) passively viewed positive, negative, and neutral clips from popular films while undergoing functional magnetic resonance imaging (fMRI). Using representational similarity analysis (RSA) to measure variability in neural pattern similarity, we found developmental differences between children and adults in the amygdala, nucleus accumbens (NAcc), and ventromedial prefrontal cortex (vmPFC), such that children generated less pattern similarity within subcortical structures relative to the vmPFC; a phenomenon not replicated among their older counterparts. Furthermore, children generated valence-specific differences in representational patterns across regions; these valence-specific patterns were not found in adults. These results may suggest that affective representations grow increasingly dissimilar over development as individuals mature from visceral affective responses to more evaluative analyses.

Resting-State Power and Regional Connectivity After Pediatric Mild Traumatic Brain Injury

BACKGROUND

Physiological recovery from pediatric mild traumatic brain injury (pmTBI) as a function of age remains actively debated, with the majority of studies relying on subjective symptom report rather than objective markers of brain physiology.

PURPOSE

To examine potential abnormalities in fractional amplitude of low-frequency fluctuations (fALFF) or regional homogeniety (ReHo) during resting-state fMRI following pmTBI.

STUDY TYPE

Prospective cohort.

POPULATION

Consecutively recruited pmTBI (N = 105; 8-18 years old) and age- and sex-matched healthy controls (HC; N = 113).

FIELD STRENGTH/SEQUENCE

3T multiecho gradient T1 -weighted and single-shot gradient-echo echo-planar imaging.

ASSESSMENT

All pmTBI participants were assessed 1 week and 4 months postinjury (HC assessed at equivalent timepoints after the first visit). Comprehensive demographic, clinical, and cognitive batteries were performed in addition to primary investigation of fALFF and ReHo. All pmTBI were classified as "persistent" or "recovered" based on both assessment periods.

STATISTICAL TESTS

Chi-square, nonparametric, and generalized linear models for demographic data. Generalized estimating equations for clinical and cognitive data. Voxelwise general linear models (AFNI's 3dMVM) for fALFF and ReHo assessment.

RESULTS

Evidence of recovery was observed for some, but not all, clinical and cognitive measures at 4 months postinjury. fALFF was increased in the left striatum for pmTBI relative to HC both at 1 week and 4 months postinjury; whereas no significant group differences (P > 0.001) were observed for ReHo. Age-at-injury did not moderate either resting-state metric across groups. In contrast to analyses of pmTBI as a whole, there were no significant (P > 0.001) differences in either fALFF or ReHo in patients with persistent postconcussive symptoms compared to recovered patients and controls at 4 months postinjury.

DATA CONCLUSIONS

Our findings suggest prolonged clinical recovery and alterations in the relative amplitude of resting-state fluctuations up to 4 months postinjury, but no clear relationship with age-at-injury or subjective symptom report.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: 2 J. MAGN. RESON. IMAGING 2020;52:1701-1713.

Associations between cerebral blood flow and structural and functional brain imaging measures in individuals with neuropsychologically defined mild cognitive impairment

Reduced cerebral blood flow (CBF), an indicator of neurovascular processes and metabolic demands, is a common finding in Alzheimer's disease. However, little is known about what contributes to CBF deficits in individuals with mild cognitive impairment (MCI). We examine regional CBF differences in 17 MCI compared with 21 age-matched cognitively healthy older adults. Next, we examined associations between CBF, white matter lesion (WML) volume, amplitude of low-frequency fluctuations, and cortical thickness to better understand whether altered CBF was detectable before other markers and the potential mechanistic underpinnings of CBF deficits in MCI. MCI had significantly reduced CBF, whereas cortical thickness and amplitude of low-frequency fluctuation were not affected. Reduced CBF was associated with the WML volume but not associated with other measures. Given the presumed vascular etiology of WML and relative worsening of vascular health in MCI, it may suggest CBF deficits result from early vascular as opposed to metabolic deficits in MCI. These findings may support vascular mechanisms as an underlying component of cognitive impairment.

Adolescent depression and brain development: evidence from voxel-based morphometry

BACKGROUND

Investigating adolescents and young adults may provide a unique opportunity to understand developmental aspects of the neurobiology of depression. During adolescence, a considerable physiologic reorganization of both grey and white matter of the brain takes place, and it has been suggested that differences in grey-matter volumes during adolescence may reflect different maturational processes.

METHODS

We investigated grey-matter volumes in a comparatively large sample (n = 103) of adolescents and young adults (aged 12 to 27 years), 60 of them with a diagnosis of current depression.

RESULTS

Replicating previous studies, we found a clear wholebrain effect of age: the older the participants, the lower their global grey-matter volumes, particularly in the paracingulate and prefrontal cortices. Contrasting depressed and healthy youth in a whole-brain approach, we found greater grey-matter volumes in the dorsolateral prefrontal cortex of those with depression. Furthermore, a region-of-interest analysis indicated lower grey-matter volumes in the hippocampus in participants with depression compared with healthy controls.

LIMITATIONS

The present study was limited because of a skewed sex distribution, its cross-sectional design and the fact that some participants were taking an antidepressant.

CONCLUSION

During adolescence, restructuring of the brain is characterized by marked decreases in prefrontal grey-matter volumes, interpreted as a correlate of brain maturation. Findings of greater volumes in the prefrontal cortex, particularly in younger adolescents with depression, may suggest that these participants were more prone to delayed brain maturation or increased neuroplasticity. This finding may represent a risk factor for depression or constitute an effect of developing depression.