No abstract

Self-associating split fluorescent proteins (FPs) are split FPs whose two fragments spontaneously associate to form a functional FP. They have been widely used for labeling proteins, scaffolding protein assembly and detecting cell-cell contacts. Recently developments have expanded the palette of self-associating split FPs beyond the original split GFP1-10/11. However, these new ones have suffered from suboptimal fluorescence signal after complementation. Here, by investigating the complementation process, we have demonstrated two approaches to improve split FPs: assistance through SpyTag/SpyCatcher interaction and directed evolution. The latter has yielded two split sfCherry3 variants with substantially enhanced overall brightness, facilitating the tagging of endogenous proteins by gene editing. Based on sfCherry3, we have further developed a new red-colored trans-synaptic marker called Neuroligin-1 sfCherry3 Linker Across Synaptic Partners (NLG-1 CLASP) for multiplexed visualization of neuronal synapses in living C. elegans, demonstrating its broad applications.

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

Insomnia disorder is the most common sleep disorder and has drawn increasing attention. Many studies have shown that hyperarousal plays a key role in the pathophysiology of insomnia disorder. However, the specific brain mechanisms underlying insomnia disorder remain unclear. To elucidate the neuropathophysiology of insomnia disorder, we investigated the brain functional networks of patients with insomnia disorder and healthy controls across the sleep-wake cycle. EEG-fMRI data from 33 patients with insomnia disorder and 31 well-matched healthy controls during wakefulness and nonrapid eye movement sleep, including N1, N2 and N3 stages, were analyzed. A medial and anterior thalamic region was selected as the seed considering its role in sleep-wake regulation. The functional connectivity between the thalamic seed and voxels across the brain was calculated. ANOVA with factors "group" and "stage" was performed on thalamus-based functional connectivity. Correlations between the misperception index and altered functional connectivity were explored. A group-by-stage interaction was observed at widespread cortical regions. Regarding the main effect of group, patients with insomnia disorder demonstrated decreased thalamic connectivity with the left amygdala, parahippocampal gyrus, putamen, pallidum and hippocampus across wakefulness and all three nonrapid eye movement sleep stages. The thalamic connectivity in the subcortical cluster and the right Guangyuan Zou and Yuezhen Li contributed equally to this study.

No abstract

According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sleep stages and what are the characteristics and electrophysiological origin of these states remain unclear. The aims of the current study were to investigate the properties of DFC in different sleep stages and to explore the relationship between the characteristics of DFC and slow‐wave activity. We collected both eyes‐closed wakefulness and sleep data from 48 healthy young volunteers with simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. EEG data were employed as the gold standard of sleep stage scoring, and DFC states were estimated based on fMRI data. The results demonstrated that DFC states of the fMRI signals consistently corresponded to wakefulness and nonrapid eye movement sleep stages independent of the number of clusters. Furthermore, the mean dwell time of these states significantly correlated with slow‐wave activity. The inclusion or omission of regression of the global signal and the selection of parcellation schemes exerted minimal effects on the current findings. These results provide strong evidence that DFC states underlying fMRI signals match the fluctuations of vigilance and suggest a possible electrophysiological source of DFC states corresponding to vigilance states.

Arousals commonly occur during human sleep and have been associated with several sleep disorders. Arousals are characterized as an abrupt electroencephalography (EEG) frequency change to higher frequencies during sleep. However, the human brain regions involved in arousal are not yet clear. Simultaneous EEG and functional magnetic resonance imaging (fMRI) data were recorded during the early portion of the sleep period in healthy young adults. Arousals were identified based on the EEG data, and fMRI signal changes associated with 83 arousals from 19 subjects were analyzed. Subcortical regions, including the midbrain, thalamus, basal ganglia, and cerebellum, were activated with arousal. Cortices, including the temporal gyrus, occipital gyrus, and frontal gyrus, were deactivated with arousal. The activations associated with arousal in the subcortical regions were consistent with previous findings of subcortical involvement in behavioral arousal and consciousness. Cortical deactivations may serve as a mechanism to direct incoming sensory stimuli to specific brain regions, thereby monitoring environmental perturbations during sleep.

Hyperthermia may impair vigilance functions and lead to slower reaction times (RTs) in the psychomotor vigilance task (PVT) and possibly disturbing cerebral hemodynamic rhythms. To test these hypotheses, we acquired the resting-state BOLD and cerebral blood flow (CBF) data, as well as PVTRTs from 15 participants in two simulated environmental thermal conditions (50 °C/25 °C). We adopted a data-driven method, frequency component analysis, to quantify the mean frequency of the BOLD series of each voxel. Across-subject correlation analysis was employed to detect the brain areas whose BOLD oscillation frequency was correlated with the RTs. Significant changes of BOLD frequency and CBF within these areas were compared between hyperthermia and normothermia conditions. Spatial correlations between BOLD frequency and CBF were calculated within different brain areas for each subject under both thermal conditions. Results showed that, under both thermal conditions, the RTs correlated with the BOLD frequency positively in the default mode network (DMN) and negatively in the sensorimotor network (SMN). The increase of BOLD frequency in the thalamus and ventral medial prefrontal cortex was correlated with the increase of RTs in hyperthermia compared with normothermia. Hyperthermia decreased BOLD frequency and CBF in the SMN, while it increased CBF in the thalamus and posterior cingulate. In both thermal conditions, the spatial distribution of CBF negatively correlated with the spatial distribution of BOLD oscillation frequency in most cortical areas, especially in cingulate cortices, precuneus, and primary visual cortex. These results suggest that hyperthermia might deteriorate task performance by interfering with the resting-state CBF, and with BOLD rhythms. The overlapping of the thermoregulatory and vigilance functions in the SMN and DMN might underlie the neural mechanisms of the cognitive-behavioral impairments induced by hyperthermia.