Cortical neurite microstructural correlates of time perception in healthy older adults.

The human experience is significantly impacted by timing as it structures how information is processed. Nevertheless, the neurological foundation of time perception remains largely unresolved. Understanding cortical microstructure related to timing is crucial for gaining insight into healthy aging and recognizing structural alterations that are typical of neurodegenerative diseases associated with age. Given the importance, this study aimed to determine the brain regions that are accountable for predicting time perception in older adults using microstructural measures of the brain. In this study, elderly healthy adults performed the Time-Wall Estimation task to measure time perception through average error time. We used support vector regression (SVR) analyses to predict the average error time using cortical neurite microstructures derived from orientation dispersion and density imaging based on multi-shell diffusion magnetic resonance imaging (dMRI). We found significant correlations between observed and predicted average error times for neurite arborization (ODI) and free water (FISO). Neurite arborization and free water properties in specific regions in the medial and lateral prefrontal, superior parietal, and medial and lateral temporal lobes were among the most significant predictors of timing ability in older adults. Further, our results revealed that greater branching along with lower free water in cortical structures result in shorter average error times. Future studies should assess whether these same networks are contributing to time perception in older adults with mild cognitive impairment (MCI) and whether degeneration of these networks contribute to early diagnosis or detection of dementia.

1H-MRS neurometabolites and associations with neurite microstructures and cognitive functions in amnestic mild cognitive impairment.

Alzheimer's disease (AD) pathogenesis is associated with alterations in neurometabolites and cortical microstructure. However, our understanding of alterations in neurochemicals in the prefrontal cortex and their relationship with changes in cortical microstructure in AD remains unclear. Here, we studied the levels of neurometabolites in the left dorsolateral prefrontal cortex (DLPFC) in healthy older adults and patients with amnestic Mild Cognitive Impairments (aMCI) using single-voxel proton-magnetic resonance spectroscopy (1H-MRS). N-acetyl aspartate (NAA), glutamate+glutamate (Glx), Myo-inositol (mI), and γ-aminobutyric acid (GABA) brain metabolite levels were quantified relative to total creatine (tCr = Cr + PCr). aMCI had significantly decreased NAA/tCr, Glx/tCr, NAA/mI, and increased mI/tCr levels compared with healthy controls. Further, we leveraged advanced diffusion MRI to extract neurite properties in the left DLPFC and found a significant positive correlation between NAA/tCr, related to neuronal intracellular compartment, and neurite density (ICVF, intracellular volume fraction), and a negative correlation between mI/tCr and neurite orientation (ODI) only in healthy older adults. These data suggest a potential decoupling in the relationship between neurite microstructures and NAA and mI concentrations in DLPFC in the early stage of AD. Together, our results confirm altered DLPFC neurometabolites in prodromal phase of AD and provide unique evidence regarding the imbalance in the association between neurometabolites and neurite microstructure in early stage of AD.

Quantitative MRI Evidence for Cognitive Reserve in Healthy Elders and Prodromal Alzheimer's Disease.

BACKGROUND: Cognitive reserve (CR) has been postulated to contribute to the variation observed between neuropathology and clinical outcomes in Alzheimer's disease (AD). OBJECTIVE: We investigated the effect of an education-occupation derived CR proxy on biological properties of white matter tracts in patients with amnestic mild cognitive impairment (aMCI) and healthy elders (HC). METHODS: Educational attainment and occupational complexity ratings (complexity with data, people, and things) from thirty-five patients with aMCI and twenty-eight HC were used to generate composite CR scores. Quantitative magnetic resonance imaging (qMRI) and multi-shell diffusion MRI were used to extract macromolecular tissue volume (MTV) across major white matter tracts. RESULTS: We observed significant differences in the association between CR and white matter tract MTV in aMCI versus HC when age, gender, intracranial volume, and memory ability were held constant. Particularly, in aMCI, higher CR was associated with worse tract pathology (lower MTV) in the left and right dorsal cingulum, callosum forceps major, right inferior fronto-occipital fasciculus, and right superior longitudinal fasciculus (SLF) tracts. Conversely higher CR was associated with higher MTV in the right parahippocampal cingulum and left SLF in HC. CONCLUSION: Our results support compensatory CR mechanisms in aMCI and neuroprotective mechanisms in HC and suggest differential roles for CR on white matter macromolecular properties in healthy elders versus prodromal AD patients.

Neurite Imaging Reveals Widespread Alterations in Gray and White Matter Neurite Morphology in Healthy Aging and Amnestic Mild Cognitive Impairment.

Aging is the major risk factor for neurodegenerative diseases and affects neurite distributions throughout the brain, yet underlying neurobiological mechanisms remain unclear. Multi-shell diffusion-weighted imaging and neurite orientation dispersion and density imaging (NODDI) now provide in vivo biophysical measurements that explain these biological processes in the cortex and white matter. In this study, neurite distributions were evaluated in the cortex and white matter in healthy older adults and patients with amnestic mild cognitive impairment (aMCI) that provides fundamental contributions regarding healthy aging and neurodegeneration. Older age was associated with reduced neurite density and neurite orientation dispersion (ODI) in widespread cortical regions. In contrast, increased ODI was only observed in the right thalamus and hippocampus with age. For the first time, we also reported a widespread age-associated decrease in neurite density along major white matter tracts correlated with decreased cortical neurite density in the tract endpoints in healthy older adults. We further examined alterations in cortical and white matter neurite microstructures in aMCI patients and found significant neurite morphology deficits in memory networks correlated with memory performance. Our findings indicate that neurite parameters provide valuable information regarding cortical and white matter microstructure and complement myeloarchitectural information in healthy aging and aMCI.

Quantitative measurement of macromolecular tissue properties in white and gray matter in healthy aging and amnestic MCI.

Healthy and pathological aging influence brain microstructure via complex processes. Discerning these processes requires measurements that are sensitive to specific biological properties of brain tissue. We integrated a novel quantitative R1 measure with multi-shell diffusion weighted imaging to map age-associated changes in macromolecular tissue volume (MTV) along major white matter tracts in healthy older adults and patients with amnestic Mild Cognitive Impairment (aMCI). Reduced MTV in association tracts was associated with older age in healthy aging, was correlated with memory performance, and distinguished aMCI from controls. We also mapped changes in gray matter tissue properties using quantitative R1 measurements. We documented a widespread decrease in R1 with advancing age across the cortex and decreased R1 in aMCI compared with controls in regions implicated in episodic memory. Our data are the first to characterize MTV loss along major white matter tracts in aMCI and suggest that qMRI is a sensitive measure for detecting subtle degeneration of white and gray matter tissue that cannot be detected by conventional MRI and diffusion measures.

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodevelopmental deficits. Deep learning models typically require training on large datasets, and unfortunately, large neuroimaging datasets with clinical outcome annotations are typically limited, especially in neonates. Transfer learning represents an important step to solve the fundamental problem of insufficient training data in deep learning. In this work, we developed a multi-task, multi-stage deep transfer learning framework using the fusion of brain connectome and clinical data for early joint prediction of multiple abnormal neurodevelopmental (cognitive, language and motor) outcomes at 2 years corrected age in very preterm infants. The proposed framework maximizes the value of both available annotated and non-annotated data in model training by performing both supervised and unsupervised learning. We first pre-trained a deep neural network prototype in a supervised fashion using 884 older children and adult subjects, and then re-trained this prototype using 291 neonatal subjects without supervision. Finally, we fine-tuned and validated the pre-trained model using 33 preterm infants. Our proposed model identified very preterm infants at high-risk for cognitive, language, and motor deficits at 2 years corrected age with an area under the receiver operating characteristic curve of 0.86, 0.66 and 0.84, respectively. Employing such a deep learning model, once externally validated, may facilitate risk stratification at term-equivalent age for early identification of long-term neurodevelopmental deficits and targeted early interventions to improve clinical outcomes in very preterm infants.

Focal white matter disruptions along the cingulum tract explain cognitive decline in amnestic mild cognitive impairment (aMCI).

White matter abnormalities of the human brain are implicated in typical aging and neurodegenerative diseases. However, our understanding of how fine-grained changes in microstructural properties along white matter tracts are associated with memory and cognitive decline in normal aging and mild cognitive impairment remains elusive. We quantified tract profiles with a newer method that can reliably measure fine-grained changes in white matter properties along the tracts using advanced multi-shell diffusion magnetic resonance imaging in 25 patients with amnestic mild cognitive impairment (aMCI) and 23 matched healthy controls (HC). While the changes in tract profiles were parallel across aMCI and HC, we found a significant focal shift in the profile at specific locations along major tracts sub-serving memory in aMCI. Particularly, our findings depict white matter alterations at specific locations on the right cingulum cingulate, the right cingulum hippocampus and anterior corpus callosum (CC) in aMCI compared to HC. Notably, focal changes in white matter tract properties along the cingulum tract predicted memory and cognitive functioning in aMCI. The results suggest that white matter disruptions at specific locations of the cingulum bundle may be a hallmark for the early prediction of Alzheimer's disease and a predictor of cognitive decline in aMCI.

Neonatal Functional and Structural Connectivity Are Associated with Cerebral Palsy at Two Years of Age.

OBJECTIVE: The accuracy of structural magnetic resonance imaging (MRI) to predict later cerebral palsy (CP) in newborns with perinatal brain injury is variable. Diffusion tensor imaging (DTI) and task-based functional MRI (fMRI) show promise as predictive tools. We hypothesized that infants who later developed CP would have reduced structural and functional connectivity as compared with those without CP. STUDY DESIGN: We performed DTI and fMRI using a passive motor task at 40 to 48 weeks' postmenstrual age in 12 infants with perinatal brain injury. CP was diagnosed at age 2 using a standardized examination. RESULTS: Five infants had CP at 2 years of age, and seven did not have CP. Tract-based spatial statistics showed a widespread reduction of fractional anisotropy (FA) in almost all white matter tracts in the CP group. Using the median FA value in the corticospinal tracts as a cutoff, FA was 100% sensitive and 86% specific to predict CP compared with a sensitivity of 60 to 80% and a specificity of 71% for structural MRI. During fMRI, the CP group had reduced functional connectivity from the right supplemental motor area as compared with the non-CP group. CONCLUSION: DTI and fMRI obtained soon after birth are potential biomarkers to predict CP in newborns with perinatal brain injury.

Developmental changes in functional brain networks from birth through adolescence.

Investigation of the brain connectome using functional magnetic resonance imaging (fMRI) and measures derived from graph theory analysis has emerged as a new approach to study brain development, cognitive function, and neurophysiological disorders. Here we use graph theory analysis to examine the influence of age, sex, and neurocognitive measures on developmental changes to the global and regional topology of functional brain networks derived from fMRI data recorded in 189 healthy subjects from the age of 0-18 years during rest. We observed that Global Efficiency and Rich-Club coefficient increased with age and Local Efficiency and Small-Worldness decreased with age, while Modularity at the global level showed an inverted U-shaped trajectory during development. Marginally significant differences were observed in Local Efficiency, Small-Worldness, and Modularity at a global level between boys and girls throughout development. We also examine the effects of neurocognitive measures in boys and girls globally and locally. Our results provide new insight to understand brain maturation of functional brain connectome and its relation to cognitive development from birth through adolescence.

Altered functional network connectivity in preterm infants: antecedents of cognitive and motor impairments?

Very preterm infants (≤ 31 weeks gestational age) are at high risk for brain injury and delayed development. Applying functional connectivity and graph theory methods to resting state MRI data (fcMRI), we tested the hypothesis that preterm infants would demonstrate alterations in connectivity measures both globally and in specific networks related to motor, language and cognitive function, even when there is no anatomical imaging evidence of injury. Fifty-one healthy full-term controls and 24 very preterm infants without significant neonatal brain injury, were evaluated at term-equivalent age with fcMRI. Preterm subjects showed lower functional connectivity from regions associated with motor, cognitive, language and executive function, than term controls. Examining brain networks using graph theory measures of functional connectivity, very preterm infants also exhibited lower rich-club coefficient and assortativity but higher small-worldness and no significant difference in modularity when compared to term infants. The findings provide evidence that functional connectivity exhibits deficits soon after birth in very preterm infants in key brain networks responsible for motor, language and executive functions, even in the absence of anatomical lesions. These functional network measures could serve as prognostic biomarkers for later developmental disabilities and guide decisions about early interventions.

Functional and structural connectivity of the visual system in infants with perinatal brain injury.

BACKGROUND: Infants with perinatal brain injury are at risk of later visual problems. Advanced neuroimaging techniques show promise to detect functional and structural alterations of the visual system. We hypothesized that infants with perinatal brain injury would have less brain activation during a visual functional magnetic resonance imaging (fMRI) task and reduced task-based functional connectivity and structural connectivity as compared with healthy controls. METHODS: Ten infants with perinatal brain injury and 20 control infants underwent visual fMRI and diffusion tensor imaging (DTI) during natural sleep with no sedation. Activation maps, functional connectivity maps, and structural connectivity were analyzed and compared between the two groups. RESULTS: Most infants in both groups had negative activation in the visual cortex during the fMRI task. Infants with brain injury showed reduced activation in the occipital cortex, weaker connectivity between visual areas and other areas of the brain during the visual task, and reduced fractional anisotropy in white matter tracts projecting to visual regions, as compared with control infants. CONCLUSION: Infants with brain injury sustained in the perinatal period showed evidence of decreased brain activity and functional connectivity during a visual task and altered structural connectivity as compared with healthy term neonates.

Greater Utilization of Neural-Circuits Related to Executive Functions is Associated with Better Reading: A Longitudinal fMRI Study Using the Verb Generation Task.

INTRODUCTION: Reading is an acquired-developmental ability that relies on intact language and executive function skills. Verbal fluency tasks (such as verb generation) also engage language and executive function skills. Performance of such tasks matures with normal language development, and is independent of reading proficiency. In this longitudinal fMRI study, we aim to examine the association between maturation of neural-circuits supporting both executive functions and language (assessed using verb generation) with reading proficiency achieved in adolescence with a focus on left-lateralization typical for language proficiency. METHODS: Normalized fMRI data from the verb generation task was collected from 16 healthy children at ages 7, 11, and 17 years and was correlated with reading scores at 17 years of age. Lateralization indices were calculated in key language, reading, and executive function-related regions in all age groups. RESULTS: Typical development was associated with (i) increasingly left-lateralized patterns in language regions (ii) more profound left-lateralized activation for reading and executive function-related regions when correlating with reading scores, (iii) greater involvement of frontal and parietal regions (in older children), and of the anterior frontal cortex (in younger children). CONCLUSION: We suggest that reading and verb generation share mutual neural-circuits during development with major reliance on regions related to executive functions and reading. The results are discussed in the context of the dual-networks architecture model.