Altered functional connectivity and spatiotemporal dynamics in individuals with sleep disorders.

Idiopathic hypersomnia (IH) is a sleep disorder characterized by highly disruptive symptoms. Like narcolepsy type 1, a well-characterized sleep disorder, individuals with IH suffer from excessive daytime sleepiness, though there is little overlap in metabolic or neural biomarkers across these two disorders. This lack of common pathophysiology, combined with the clear overlap in symptoms presents an ideal paradigm for better understanding the impact of IH on an individual's functional activity and organization, and potentially, the underlying pathophysiology. This study examines the observed functional connectivity in patients with IH, and patients with narcolepsy type 1 (NT1) against healthy control individuals. Static functional connectivity is compared, as are quasi-periodic patterns, acquired from the BOLD timecourse, for all groups. In addition to baseline data comparison, the study also included a post-nap condition, where the individuals included in this analysis napped for at least 10 minutes prior to the scanning session, to explore why individuals with IH do not feel refreshed after a nap like individuals with NT1 do. Assessing the groups' spatiotemporal patterns revealed key differences across both disorders and conditions: static connectivity revealed at baseline higher subcortical connectivity in the NT1 group. There was also observably less connectivity in the IH group both at baseline and post-nap, though none of these static analyses survived multiple comparisons correction to reach significance. The QPP results however found significant differences in the IH group in key networks, particularly the DAN/FPCN correlation is significantly different at baseline vs. post-nap, a trend not observed in either the control or NT1 groups. The DAN and FPCN are drastically altered both at baseline and post-nap when compared to the other groups, and may likely be a disorder-specific result. This study demonstrates that key networks for arousal are more heavily disrupted in IH patients, who are less affected by a nap, confirmed through both subject reporting and functional evidence through spatiotemporal patterns.

Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention.

Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.

Creative tempo: Spatiotemporal dynamics of the default mode network in improvisational musicians.

The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs. In the present study, we compare the outputs of two QPP detection approaches, sliding window algorithm and complex principal components analysis (cPCA). We apply both methods to an existing dataset of musicians captured with resting state fMRI, grouped as either classical, improvisational, or minimally trained non-musicians. The original time-averaged functional connectivity (FC) analysis of this dataset used improvisation as a proxy for creative thinking and found that the DMN and visual networks (VIS) display higher connectivity in improvisational musicians. We expand upon this dataset's original study and find that QPP analysis detects convergent results at the group level with both methods. In improvisational musicians, dynamic functional correlation in the group-averaged QPP was found to be increased between the DMN-VIS and DMN-FPN for both the QPP algorithm and complex principal components analysis (cPCA) methods. Additionally, we found an unexpected increase in FC in the group-averaged QPP between the dorsal attention network and amygdala in improvisational musicians; this result was not reported in the original seed-based study of this dataset. The current study represents a novel application of two dynamic FC detection methods with results that replicate and expand upon previous seed-based FC findings. The results show the robustness of both the QPP phenomenon and its detection methods. This study also demonstrates the value of dynamic FC methods in reproducing seed-based findings and their promise in detecting group-wise or individual differences that may be missed by traditional seed-based resting state fMRI studies.

otpb functions in a Lef1-dependent transcriptional network required for expression of the stress response inhibitor crhbp in the zebrafish hypothalamus.

The vertebrate hypothalamus regulates physiological and behavioral responses to environmental stimuli through the function of evolutionarily-conserved neuronal subpopulations. Our previous work found that mutation of zebrafish lef1 , which encodes a transcriptional mediator of the Wnt signaling pathway, leads to the loss of hypothalamic neurons and behavioral phenotypes that are both associated with stress-related human mood disorders However, the specific Lef1 target genes that link neurogenesis to behavior remain unknown. One candidate is otpb , which encodes a transcription factor with known roles in hypothalamic development. Here we show that otpb expression in the posterior hypothalamus is Lef1-dependent, and that like lef1 , its function is required for the generation of crhbp + neurons in this region. Transgenic reporter analysis of a crhbp conserved noncoding element suggests that otpb participates in a transcriptional regulatory network with other Lef1 targets. Finally, consistent with a role for crhbp in inhibiting the stress response, zebrafish otpb mutants exhibit decreased exploration in a novel tank diving assay. Together our findings suggest a potential evolutionarily-conserved mechanism for the regulation of innate stress response behaviors through Lef1-mediated hypothalamic neurogenesis.

Spatiotemporal patterns of spontaneous brain activity: a mini-review.

The brain exists in a state of constant activity in the absence of any external sensory input. The spatiotemporal patterns of this spontaneous brain activity have been studied using various recording and imaging techniques. This has enabled considerable progress to be made in elucidating the cellular and network mechanisms that are involved in the observed spatiotemporal dynamics. This mini-review outlines different spatiotemporal dynamic patterns that have been identified in four commonly used modalities: electrophysiological recordings, optical imaging, functional magnetic resonance imaging, and electroencephalography. Signal sources for each modality, possible sources of the observed dynamics, and future directions are also discussed.

Lef1-dependent hypothalamic neurogenesis inhibits anxiety.

While innate behaviors are conserved throughout the animal kingdom, it is unknown whether common signaling pathways regulate the development of neuronal populations mediating these behaviors in diverse organisms. Here, we demonstrate that the Wnt/ß-catenin effector Lef1 is required for the differentiation of anxiolytic hypothalamic neurons in zebrafish and mice, although the identity of Lef1-dependent genes and neurons differ between these 2 species. We further show that zebrafish and Drosophila have common Lef1-dependent gene expression in their respective neuroendocrine organs, consistent with a conserved pathway that has diverged in the mouse. Finally, orthologs of Lef1-dependent genes from both zebrafish and mouse show highly correlated hypothalamic expression in marmosets and humans, suggesting co-regulation of 2 parallel anxiolytic pathways in primates. These findings demonstrate that during evolution, a transcription factor can act through multiple mechanisms to generate a common behavioral output, and that Lef1 regulates circuit development that is fundamentally important for mediating anxiety in a wide variety of animal species.