Functional network (FN) analyses play a pivotal role in uncovering insights into brain function and understanding the pathophysiology of various brain disorders. This paper focuses on classical and advanced methods for deriving brain FNs from functional magnetic resonance imaging (fMRI) data. We systematically review their foundational principles, advantages, shortcomings, and interrelations, encompassing both static and dynamic FN extraction approaches. In the context of static FN extraction, we present hypothesis-driven methods such as region of interest (ROI)-based approaches as well as data-driven methods including matrix decomposition, clustering, and deep learning. For dynamic FN extraction, both window-based and windowless methods are surveyed with respect to the estimation of time-varying FN and the subsequent computation of FN states. We also discuss the scope of application of the various methods and avenues for future improvements.

Three-photon fluorescence microscopy (3PFM) is a promising brain research tool with submicrometer spatial resolution and high imaging depth. However, only limited materials have been developed for 3PFM owing to the rigorous requirement of the three-photon fluorescence (3PF) process. Herein, under the guidance of a band gap engineering strategy, CdTe/CdSe/ZnS quantum dots (QDs) emitting in the near-infrared window are designed for constructing 3PF probes. The formation of type II structure significantly increased the three-photon absorption cross section of QDs and caused the delocalization of electron-hole wave functions. The time-resolved transient absorption spectroscopy confirmed that the decay of biexcitons was significantly suppressed due to the appropriate band gap alignment, which further enhanced the 3PF efficiency of QDs. By utilizing QD-based 3PF probes, high-resolution 3PFM imaging of cerebral vasculature was realized excited by a 1600 nm femtosecond laser, indicating the possibility of deep brain imaging with these 3PF probes.

The study aimed to develop and validate a gamified cognitive flexibility task through brain imaging, and to investigate behavioral and brain activation differences between young and older adults during task performance. Thirty-one young adults (aged 18-35) and 31 older adults (aged 60-80) were included in the present study. All participants underwent fMRI scans while completing the gamified cognitive flexibility task. Results showed that young adults outperformed older adults on the task. The left inferior frontal junction (IFJ), a key region of cognitive flexibility, was significantly activated during the task in both older and young adults. Comparatively, the percent signal change in the left IFJ was stronger in older adults than in young adults. Moreover, older adults demonstrated more precise representations during the task in the left IFJ. Additionally, the left inferior parietal lobule (IPL) and superior parietal lobule in older adults and the left middle frontal gyrus (MFG) and inferior frontal gyrus in young adults were also activated during the task. Psychophysiological interaction analyses showed significant functional connectivity between the left IFJ and the left IPL, as well as the right precuneus in older adults. In young adults, significant functional connectivity was found between the left IFJ and the left MFG, as well as the right angular. The current study provides preliminary evidence for the validity of the gamified cognitive flexibility task through brain imaging. The findings suggest that this task could serve as a reliable tool for assessing cognitive flexibility and for exploring age-related differences of cognitive flexibility in both brain and behavior.

Alzheimer\'s disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.

Optical-based imaging has improved from early single-location research to further sophisticated imaging in 2D topography and 3D tomography. These techniques have the benefit of high specificity and non-radiative safety for brain detection and therapy. However, their performance is limited by complex tissue structures. To overcome the difficulty in successful brain imaging applications, we conducted a simulation using 16 optical source types within a brain model that is based on the Monte Carlo method. In addition, we propose an evaluation method of the optical propagating depth and resolution, specifically one based on the optical distribution for brain applications. Based on the results, the best optical source types were determined in each layer. The maximum propagating depth and corresponding source were extracted. The optical source propagating field width was acquired in different depths. The maximum and minimum widths, as well as the corresponding source, were determined. This paper provides a reference for evaluating the optical propagating depth and resolution from an optical simulation aspect, and it has the potential to optimize the performance of optical-based techniques.

暂无摘要。

We explored the structural and functional changes of the healthy hemisphere of the brain after surgery in children with intracranial space-occupying lesions. We enrolled 32 patients with unilateral intracranial space-occupying lesions for brain imaging and cognitive assessment. Voxel-based morphometry and surface-based morphometry analyses were used to investigate the structural images of the healthy hemisphere. Functional images were analyzed using regional homogeneity, amplitude of low-frequency fluctuations, and fractional-amplitude of low-frequency fluctuations. Voxel-based morphometry and surface-based morphometry analysis used the statistical model built into the CAT 12 toolbox. Paired t-tests were used for functional image and cognitive test scores. For structural image analysis, we used family-wise error correction of peak level (p < 0.05), and for functional image analysis, we use Gaussian random-field theory correction (voxel p < 0.001, cluster p < 0.05). We found an increase in gray matter volume in the healthy hemisphere within six months postoperatively, mainly in the frontal lobe. Regional homogeneity and fractional-amplitude of low-frequency fluctuations also showed greater functional activity in the frontal lobe. The results of cognitive tests showed that psychomotor speed and motor speed decreased significantly after surgery, and reasoning increased significantly after surgery. We concluded that in children with intracranial space-occupying lesions, the healthy hemisphere exhibits compensatory structural and functional effects within six months after surgery. This effect occurs mainly in the frontal lobe and is responsible for some higher cognitive compensation. This may provide some guidance for the rehabilitation of children after brain surgery.

Different aspects of cognitive functions are affected in patients with Alzheimer\'s disease. To date, little is known about the associations between features from brain-imaging and individual Alzheimer\'s disease (AD)-related cognitive functional changes. In addition, how these associations differ among different imaging modalities is unclear. Here, we trained and investigated 3D convolutional neural network (CNN) models that predicted sub-scores of the 13-item Alzheimer\'s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13) based on MRI and FDG-PET brain-imaging data. Analysis of the trained network showed that each key ADAS-Cog13 sub-score was associated with a specific set of brain features within an imaging modality. Furthermore, different association patterns were observed in MRI and FDG-PET modalities. According to MRI, cognitive sub-scores were typically associated with structural changes of subcortical regions, including amygdala, hippocampus, and putamen. Comparatively, according to FDG-PET, cognitive functions were typically associated with metabolic changes of cortical regions, including the cingulated gyrus, occipital cortex, middle front gyrus, precuneus cortex, and the cerebellum. These findings brought insights into complex AD etiology and emphasized the importance of investigating different brain-imaging modalities.

Copper dysmetabolism is associated with various neurodegenerative disorders, making high-spatiotemporal-resolution imaging of Cu2+ in the brain essential for understanding the underlying pathophysiological processes. Nevertheless, the current probes encounter obstacles in crossing the blood-brain barrier (BBB) and providing high-spatial-resolution in deep tissues. Herein, we present a photoacoustic probe capable of imaging Cu2+ dynamics in the mouse brain with high-spatiotemporal-resolution. The probe demonstrates selective ratiometric and reversible responses to Cu2+ , while also efficiently crossing the BBB. Using the probe as the imaging agent, we successfully visualized Cu2+ in the brain of Parkinson\'s disease (PD) model mouse with a remarkable micron-level resolution. The imaging results revealed a significant increase in Cu2+ levels in the cerebral cortex as PD progresses, highlighting the close association between Cu2+ alternations in the region and the disease. We also demonstrated that the probe can be used to monitor changes in Cu2+ distribution in the PD model mouse brain during L-dopa intervention. Mechanism studies suggest that the copper dyshomeostasis in the PD mouse brain was dominated by the expression levels of divalent metal transporter 1. The application of our probe in imaging Cu2+ dynamics in the mouse brain offers valuable insights into the copper-related molecular mechanisms underlying neurodegenerative diseases.

OBJECTIVE: Recent work has shown MRI is able to measure and quantify signals of phospholipid membrane-bound protons associated with myelin in the human brain. This work seeks to develop an improved technique for characterizing this brain ultrashort- T 2 ∗ $$ {\\mathrm{T}}_2\\ast $$ component in vivo accounting for T 1 $$ {\\mathrm{T}}_1 $$ weighting.
METHODS: Data from ultrashort echo time scans from 16 healthy volunteers with variable flip angles (VFA) were collected and fitted into an advanced regression model to quantify signal fraction, relaxation time, and frequency shift of the ultrashort- T 2 ∗ $$ {\\mathrm{T}}_2\\ast $$ component.
RESULTS: The fitted components show intra-subject differences of different white matter structures and significantly elevated ultrashort- T 2 ∗ $$ {\\mathrm{T}}_2\\ast $$ signal fraction in the corticospinal tracts measured at 0.09 versus 0.06 in other white matter structures and significantly elevated ultrashort- T 2 ∗ $$ {\\mathrm{T}}_2\\ast $$ frequency shift in the body of the corpus callosum at - $$ - $$ 1.5 versus - $$ - $$ 2.0 ppm in other white matter structures.
CONCLUSIONS: The significantly different measured components and measured T 1 $$ {\\mathrm{T}}_1 $$ relaxation time of the ultrashort- T 2 ∗ $$ {\\mathrm{T}}_2\\ast $$ component suggest that this method is picking up novel signals from phospholipid membrane-bound protons.