NeuroImage
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Comparative Study
Near-infrared spectroscopy versus magnetic resonance imaging to study brain perfusion in newborns with hypoxic-ischemic encephalopathy treated with hypothermia.
The measurement of brain perfusion may provide valuable information for assessment and treatment of newborns with hypoxic-ischemic encephalopathy (HIE). While arterial spin labeled perfusion (ASL) magnetic resonance imaging (MRI) provides noninvasive and direct measurements of regional cerebral blood flow (CBF) values, it is logistically challenging to obtain. Near-infrared spectroscopy (NIRS) might be an alternative, as it permits noninvasive and continuous monitoring of cerebral hemodynamics and oxygenation at the bedside. ⋯ NIRS is an effective bedside tool to monitor and understand brain perfusion changes in term asphyxiated newborns, which in conjunction with precise measurements of CBF obtained by MRI at particular times, may help tailor neuroprotective strategies in term newborns with HIE.
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Neuroplasticity, which is the dynamic structural and functional reorganization of central nervous system connectivity due to environmental and internal demands, is recognized as a major physiological basis for adaption of cognition, and behavior, and thus of utmost importance for normal brain function. Pathological alterations of plasticity are increasingly explored as pathophysiological foundation of diverse neurological and psychiatric diseases. ⋯ In the last years its efficacy to treat neuropsychiatric diseases has been explored increasingly. In this review, we will give an overview of pathological alterations of plasticity in neuropsychiatric diseases, gather clinical studies involving tDCS to ameliorate symptoms, and discuss future directions of application, with an emphasis on optimizing stimulation effects.
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Functional near-infrared spectroscopy (fNIRS) has now become widely accepted as a common functional imaging modality. In order for fNIRS to achieve genuine neuroimaging citizenship, it would ideally be equipped with functional and structural image analyses. However, fNIRS measures cortical activities from the head surface without anatomical information of the object being measured. ⋯ Eighth, we provide practical guidance on how these techniques are implemented in software. Finally, we provide information on current resources and limitations for spatial registration of child and infant data. Through these technical descriptions, we stress the importance of presenting fNIRS data on a common platform to facilitate both intra- and inter-modal data sharing among the neuroimaging community.
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Cancer and cancer treatment-related neurocognitive dysfunction (CRND) (e.g., impairments in key cognitive domains of attention, memory, processing speed, and executive function), commonly referred to as "chemobrain" or "chemo-fog", can negatively impact patients' psychosocial functioning and quality of life. CRND is a debilitating and enduring adverse effect experienced by 17% to 75% of patients during and after completion of treatment. However, few studies have systematically characterized and tested interventions to treat CRND. ⋯ This paper presents a comprehensive model for characterizing, assessing and monitoring cancer and treatment-related neurocognitive dysfunction, with functional near-infrared spectroscopy (fNIRS) as an important component of this model. The benefits of fNIRS to the characterization and longitudinal assessment and monitoring of CRND are discussed. Strategies for integrating optical imaging spectroscopy in biobehavioral oncology research, strength and limitations, and directions for future CRND studies using fNIRS are examined.
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One of the main challenges in functional diffuse optical tomography (DOT) is to accurately recover the depth of brain activation, which is even more essential when differentiating true brain signals from task-evoked artifacts in the scalp. Recently, we developed a depth-compensated algorithm (DCA) to minimize the depth localization error in DOT. ⋯ Computer simulations and human measurements of sensorimotor activation were conducted to examine and prove the depth specificity and quantification accuracy of brain atlas-based DC-DOT. In addition, node-wise statistical analysis based on the general linear model (GLM) was also implemented and performed in this study, showing the robustness of DC-DOT that can accurately identify brain activation at the correct depth for functional brain imaging, even when co-existing with superficial artifacts.