Clinical spectrum and documentation patterns of cerebral palsy among children at Arthur Davison Children's Hospital and Kitwe Teaching Hospital, Zambia: a retrospective record review.

With the expansion of tourism and economic development in high-altitude (HA) environments, more people are exposed to the negative health effects of HA conditions. Among the various environmental stressors at HA environments, hypoxia stands out as the most critical physiological challenge. The brain, as a high oxygen-consuming organ, is sensitive to alterations in oxygen supply. Although it represents approximately 2% of the total body mass, the brain consumes more than 20% of the body’s oxygen intake. Consequently, HA conditions can impose substantial strain on brain function. A growing body of research has demonstrated that exposure to HA environments can induce neuropsychological impairments, including deficits in memory, learning, and psychomotor performance. As a specific example, Wang et al. reported reduced accuracy and prolonged response times in the backward digit task under hypoxic conditions relative to normoxia. Additionally, Chen et al. found that chronic hypoxia exposure leads to significantly lower accuracy on memory tests as well as to longer reaction times. While multiple studies have attempted to characterize the physiological and neurological alterations that occur after ascent to HA environments, few studies have investigated the alterations that occur in cognitive and brain functions after long-term exposure to HA conditions. As an advanced neuroimaging technique, resting-state functional magnetic resonance imaging (rs-fMRI) has been widely employed to identify differences in brain functions in patients with various neurological and cognitive disorders. rs-fMRI allows the measurement of spontaneous brain activity at rest via non-invasive detection of fluctuations in the blood-oxygen-level-dependent (BOLD) signal, which reflect hemodynamic changes associated with neuronal activity. Accordingly, rs-fMRI offers unique advantages in terms of both temporal and spatial resolution as well as good sensitivity to both cortical and subcortical neuronal activities. The rs-fMRI metrics most commonly used to assess the spontaneous activity characteristics of local brain regions include regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF). ReHo reflects the local synchronization of neural activity by quantifying the temporal coherence of BOLD signals within a given voxel and its immediate neighbors. The ALFF is a measurement of the regional intensity of spontaneous oscillations within the low-frequency range and is calculated as the square root of the power spectrum integrated over this band. The fALFF provides refined specificity relative to the ALFF based on computation of the ratio of low-frequency power to the total frequency spectrum, which serves to mitigate contamination due to physiological noise. Previous studies have identified alterations in ReHo, ALFF, and fALFF in association with Alzheimer’s disease (AD) and suggested that these metrics may serve as biomarkers for AD diagnosis and therapeutic targeting. For example, Khatri and Kwon conducted a meta-analysis to investigate multimodal alterations in ALFF and fALFF in patients with AD or preclinical AD compared with healthy controls (HCs) and showed that patients with AD exhibit decreased ALFF/fALFF in the bilateral posterior cingulate gyrus (PCC), precuneus (PCUN), and right angular gyrus (ANG) as well as increased ALFF/fALFF in the bilateral parahippocampal gyrus (PHG) compared with HCs. We previously studied a group of college students who had immigrated to an HA plateau for 1 or 2 years; we observed significant decreases in ReHo in the left putamen (PUT), superior temporal gyrus (STG), superior parietal lobule (SPG), anterior cingulate gyrus (ACG), and medial frontal gyrus (MFG) along with an increase in ReHo in the hippocampus after exposure to HA conditions. The human brain exhibits remarkable structural and functional complexity, with cognitive processes emerging from the interplay of distinct neural substrates in different brain regions, which form interconnected networks to support cognitive function. Hence, evaluation of regional (local) metrics offers limited value in correlation research, as such metrics predominantly reflect the circumscribed neural activity within a specific brain region and cannot represent the network-level interactions essential for cognitive function. Accordingly, studies in the past decade have increasingly focused on the cooperation that occurs across large-scale brain networks. Interregional brain activity is now commonly assessed in terms of functional connectivity (FC), with different forms including static FC (sFC) and dynamic FC (dFC). sFC is determined by evaluating the temporal correlations in BOLD signals among distinct brain regions with the assumption that intrinsic activity remains stable over time, offering critical insight into normal and abnormal brain organization. In contrast, dFC captures time-varying