Hub Regions Research Articles

Local synchronicity in dopamine-rich caudate nucleus influences Huntington's disease motor phenotype.

Structural grey and white matter changes precede the manifestation of clinical signs of Huntington's disease by many years. Conversion to clinically manifest disease therefore likely reflects not merely atrophy but a more widespread breakdown of brain function. Here, we investigated the structure-function relationship close to and after clinical onset, in important regional brain hubs, particularly caudate nucleus and putamen, which are central to maintaining normal motor behaviour. In two independent cohorts of patients with premanifest Huntington's disease close to onset and very early manifest Huntington's disease (total n = 84; n = 88 matched controls), we used structural and resting state functional MRI. We show that measures of functional activity and local synchronicity within cortical and subcortical regions remain normal in the premanifest Huntington's disease phase despite clear evidence of brain atrophy. In manifest Huntington's disease, homeostasis of synchronicity was disrupted in subcortical hub regions such as caudate nucleus and putamen, but also in cortical hub regions, for instance the parietal lobe. Cross-modal spatial correlations of functional MRI data with receptor/neurotransmitter distribution maps showed that Huntington's disease-specific alterations co-localize with dopamine receptors D1 and D2, as well as dopamine and serotonin transporters. Caudate nucleus synchronicity significantly improved models predicting the severity of the motor phenotype or predicting the classification into premanifest Huntington's disease or motor manifest Huntington's disease. Our data suggest that the functional integrity of the dopamine receptor-rich caudate nucleus is key to maintaining network function. The loss of caudate nucleus functional integrity affects network function to a degree that causes a clinical phenotype. These insights into what happens in Huntington's disease could serve as a model for what might be a more general relationship between brain structure and function in neurodegenerative diseases in which other brain regions are vulnerable.

Investigation of Unsteady Rotor–Stator Interaction and Deterministic Correlation Analysis in a Transonic Compressor Stage

Abstract Unsteady blade row interaction (UBRI) has a large impact on performance in high-speed axial compressors. Thus, the influence of UBRI should be accurately predicted in compressor routine design. In this study, the unsteady rotor–stator interaction in a transonic single-stage compressor, NASA Stage 35, is studied by steady and unsteady Reynolds-Averaged Navier–Stokes methods. First, the UBRI is analyzed. Periodic separation bubbles on the stator suction surface induced by the rotor wake are observed. Comparisons between steady and unsteady results show that the radial distribution of flow angle near the hub and tip region of the stator is strongly influenced by UBRI. Second, deterministic correlations are analyzed based on the average-passage equation system. The distribution of deterministic stress and the relationship between spatial correlations and deterministic correlations are analyzed. Results show that a strong nonlinear interaction caused by the rotor wake and the stator potential field is found in the rotor–stator gap, which is responsible for the generation of spatial–time correlation. Then, the anisotropy of deterministic correlations is analyzed using the Lumley triangle. Results show that the deterministic stress is highly anisotropic in the stator passage, which can be considered in the modeling using a similar strategy of turbulence modeling. At last, the relationships between the harmonics and decay rate of deterministic correlations are analyzed. The decay rate of deterministic correlation is highly related to the corresponding harmonics, and the higher-order harmonic exhibits a higher decay rate. A modified exponential decay model is proposed for deterministic correlation based on harmonics, which provides improved performance.

Cross-modality comparison between structural and metabolic networks in individual brain based on the Jensen-Shannon divergence method: a healthy Chinese population study.

The study aimed to investigate the consistency and diversity between metabolic and structural brain networks at individual level constructed with divergence-based method in healthy Chinese population. The 18F-FDG PET and T1-weighted images of brain were collected from 209 healthy participants. The Jensen-Shannon divergence (JSD) was used to calculate metabolic or structural connectivities between any pair of brain regions and then individual brain networks were constructed. The global and regional topological properties of both networks were analyzed with graph theoretical analysis. Regional properties including nodal efficiency, degree, and betweenness centrality were used to define hub regions of networks. Cross-modality similarity of brain connectivity was analyzed with differential power (DP) analysis. The default mode network (DMN) had the largest number of brain connectivities with high DP values. The small-worldness indexes of metabolic and structural networks in all participants were greater than 1. The structural network showed higher assortativity and local efficiency than metabolic network, while hierarchy and global efficiency were greater in the metabolic network (all P < 0.001). Most of hubs in both networks were symmetrically spatial distributed in the regions of the DMN and subcortical nuclei including thalamus and amygdala, etc. The human brain presented small-world architecture both in perspective of individual metabolic and structural networks. There was a structural substrate that supported the brain to globally and efficiently integrate and process metabolic interaction across brain regions. The cross-modality cooperation or specialization in both networks might imply mechanisms of achieving higher-order brain functions.

Functional brain network properties of healthy full-term newborns quantified by scalp and source-reconstructed EEG

ObjectiveIdentifying the functional brain network properties of term low-risk newborns using high-density EEG (HD-EEG) and comparing these properties with those of established functional magnetic resonance image (fMRI) – based networks. MethodsHD-EEG was collected from 113 low-risk term newborns before delivery hospital discharge and within 72 hours of birth. Functional brain networks were reconstructed using coherence at the scalp and source levels in delta, theta, alpha, beta, and gamma frequency bands. These networks were characterized for the global and local network architecture. ResultsSource-level networks in all the frequency bands identified the presence of the efficient small world (small-world propensity (SWP) > 0.6) architecture with four distinct modules linked by hub regions and rich-club (coefficient > 1) topology. The modular regions included primary, association, limbic, paralimbic, and subcortical regions, which have been demonstrated in fMRI studies. In contrast, scalp-level networks did not display consistent small world architecture (SWP < 0.6), and also identified only 2–3 modules in each frequency band.The modular regions of the scalp-network primarily included frontal and occipital regions. ConclusionsOur findings show that EEG sources in low-risk newborns corroborate fMRI-based connectivity results. SignificanceEEG source analysis characterizes functional connectivity at the bedside of low-risk newborn infants soon after birth.

Clinical relevance of disrupted topological organization of anatomical connectivity in behavioral variant frontotemporal dementia

Graph theory is a novel approach used to examine the balance of brain connectomes. However, the clinical relevance of white matter (WM) connectome changes in the behavioral variant frontotemporal dementia (bvFTD) is not well understood. We aimed to investigate the clinical relevance of WM topological alterations in bvFTD. Thirty patients with probable bvFTD and 30 healthy controls underwent diffusion tensor imaging, structural MRI, and neuropsychological assessment. WM connectivity between 90 brain regions was calculated and the graph approach was applied to capture the individual characteristics of the anatomical network. Voxel-based morphometry and tract-based spatial statistics were used to present the gray matter atrophy and disrupted WM integrity. The topological organization was disrupted in patients with bvFTD both globally and locally. Compared to controls, bvFTD data showed a different pattern of hub region distributions. Notably, the nodal efficiency of the right superior orbital frontal gyrus was associated with apathy and disinhibition. Topological measures may be potential image markers for early diagnosis and disease severity monitoring of bvFTD.

Dissociable salience and default mode network modulation in generalized anxiety disorder: a connectome-wide association study.

Generalized anxiety disorder (GAD) is a common anxiety disorder experiencing psychological and somatic symptoms. Here, we explored the link between the individual variation in functional connectome and anxiety symptoms, especially psychological and somatic dimensions, which remains unknown. In a sample of 118 GAD patients and matched 85 healthy controls (HCs), we used multivariate distance-based matrix regression to examine the relationship between resting-state functional connectivity (FC) and the severity of anxiety. We identified multiple hub regions belonging to salience network (SN) and default mode network (DMN) where dysconnectivity associated with anxiety symptoms (P < 0.05, false discovery rate [FDR]-corrected). Follow-up analyses revealed that patient's psychological anxiety was dominated by the hyper-connectivity within DMN, whereas the somatic anxiety could be modulated by hyper-connectivity within SN and DMN. Moreover, hypo-connectivity between SN and DMN were related to both anxiety dimensions. Furthermore, GAD patients showed significant network-level FC changes compared with HCs (P < 0.01, FDR-corrected). Finally, we found the connectivity of DMN could predict the individual psychological symptom in an independent GAD sample. Together, our work emphasizes the potential dissociable roles of SN and DMN in the pathophysiology of GAD's anxiety symptoms, which may be crucial in providing a promising neuroimaging biomarker for novel personalized treatment strategies.

Rich-club reorganization of white matter structural network in schizophrenia patients with auditory verbal hallucinations following 1 Hz rTMS treatment

The human brain comprises a large-scale structural network of regions and interregional pathways, including a selectively defined set of highly central and interconnected hub regions, often referred to as the “rich club”, which may play a pivotal role in the integrative processes of the brain. A quintessential symptom of schizophrenia, auditory verbal hallucinations (AVH) have shown a decrease in severity following low-frequency repetitive transcranial magnetic stimulation (rTMS). However, the underlying mechanism of rTMS in treating AVH remains elusive. This study investigated the effect of low-frequency rTMS on the rich-club organization within the brain in patients diagnosed with schizophrenia who experience AVH using diffusion tensor imaging data. Through by constructing structural connectivity networks, we identified several critical rich hub nodes, which constituted a rich-club subnetwork, predominantly located in the prefrontal cortices. Notably, our findings revealed enhanced connection strength and density within the rich-club subnetwork following rTMS treatment. Furthermore, we found that the decreased connectivity within the subnetwork components, including the rich-club subnetwork, was notably enhanced in patients following rTMS treatment. In particular, the increased connectivity strength of the right median superior frontal gyrus, which functions as a critical local bridge, with the right postcentral gyrus exhibited a significant correlation with improvements in both positive symptoms and AVH. These findings provide valuable insights into the role of rTMS in inducing reorganizational changes within the rich-club structural network in schizophrenia and shed light on potential mechanisms through which rTMS may alleviate AVH.

Brain instability in dynamic functional connectivity in schizophrenia

Schizophrenia is a severe psychiatric disorder associated with altered connectivity of brain functional networks (BFNs). Researchers have observed a profound disruption in prefrontal-temporal interactions, damage to hub regions in brain networks and modified topological organization of BFNs in schizophrenia (SCZ) individuals. Assessment of BFNs with dynamic approaches allow the characterization of new functional structures, such as topological stability patterns and temporal connectivity, which are not accessible through static methods. In this perspective, the present study investigated the physiological processes of brain connectivity in SCZ. A resting-state EEG dataset of 14 SCZ individuals and 14 healthy controls (HC) was obtained at a sampling rate of 250Hz. Dynamic BFNs were constructed using time-varying graphs combined with the motifs' synchronization method and the indexes were evaluated in different scales: global averages, by hemispheres, by regions, and by electrodes for both groups. The SCZ group exhibited lower temporal connectivity, lesser hub probability, and fewer number of edges in right and left temporal lobes over time, besides increased temporal connectivity in the central-parietal region. Neither differences for the full synchronization time of BFNs were observed, nor for intra- and inter-hemispheric connections between groups. These results indicate that SCZ BFNs exhibit a dynamic fluctuation pattern with abrupt increases in connectivity over time for the regions studied. This elucidates an attempted interaction of the temporal area with other regions (frontal, central-parietal, and occipital) that is not sufficient to maintain a connectivity pattern in schizophrenia individuals similar to that of healthy subjects. Our results suggest that changes in interaction of dynamic BFNs connections in SCZ can be better approached by dynamic analyses that enable a thorough glance at brain changes over time.

Aerodynamic Design of Cooling Guide for Electrical Machine in Electric Ducted Fan

Abstract Electric ducted fan has newly emerged as the most compact type of propulsion fan for flying cars, because of its flexible configuration arrangement, low noise level and high safety level operation. Typically, an electric ducted fan is composed of a hub-driven fan and a hub-mounted inner rotor electrical machine. The thermal management of the hub-mounted electrical machine is essential because it determines the machine's continuous output power and reliability, as well as the fan thrust force. The heat transmitted from the stator winding to the cooling guide vane (CGV) is dissipated by introducing the air flow at hub region to the CGV. Therefore, in order to better improve the thermal performance of the CGV, an aerodynamic design of CGV is proposed in this paper for better thermal management of stator end-windings. First, for a certain desired power output of electrical machine under temperature constraints of stator winding, lumped thermal network is established to derive the requirement of heat transfer coefficients of the CGV. Then, from engineering feasibility, three different CGVs including straight type, arc-shape type and airfoil-shape type are tested by computational fluid dynamics. The evaluation of the CGV designs include the flow characteristics, power requirements, and thermal characteristics for stator winding cooling purposes. In comparison with the conventionally straight type CGV, improvements are gained from the designed arc-shape type and airfoil-shape type cooling configurations, whereas the fan thrust force remains the same simultaneously. It is verified that the arc-shape type and airfoil-shape type CGVs are promising in enhancing the thermal management performance of the electrical machine stator winding without power requirement.

Thalamocortical contributions to cognitive task activity.

Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here, we show how task-evoked thalamic activity is organized to support these broad cognitive abilities. We analyzed functional magnetic resonance imaging (MRI) data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found a basis set of activity patterns evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamic activity and thalamocortical functional connectivity, we built a data-driven thalamocortical model to test whether thalamic activity can be used to predict cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippocampal, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how the human thalamocortical system supports cognitive task activity.

Functional hyperconnectivity is associated with higher levels of sPDGFRβ, a marker of blood brain barrier breakdown, in older adults

AbstractBackgroundApolipoprotein E4 (APOE4) has toxic effects on the cerebrovascular system, neuronal function, and functional connectivity of brain networks (e.g., default‐mode, frontal‐attention, and salience networks). The thalamus, a vital structure that acts as a relay station between many networks, has become of interest in AD research with studies showing atrophy among those with early AD and diminished cortical‐thalamic connections among those with vascular impairment. Additionally, CSF soluble platelet‐derived growth factor receptor‐β (sPDGFRβ), a marker of blood‐brain barrier breakdown, has been associated with AD risk, especially in APOE4 carriers. The present study investigated the relationship between CSF sPDGFRβ and functional connectivity in APOE4 carriers and non‐carriers.MethodOne hundred sixty‐six older adults from the Los Angeles area were selected from a larger cohort (96 females, mean age+SD=67.4+10.7, 68 APOE4 carriers) based on availability of rsfMRI data. Image data was processed using CONN‐toolbox v19c. Grey matter was parcellated using Harvard/Oxford brain atlas, excluding cerebellum. ROI‐to‐ROI analyses were conducted selecting the thalamus as seed region averaging mean connectivity between the left and right structure of other parcellated brain regions. Linear regression models evaluated significant associations between blood oxygen level‐dependent (BOLD) and network connectivity among seed‐target regions and CSF sPDGFRβvalues, while covarying for age and sex. Comparison of averaged functional connectivity values between seed and all target regions among APOE4 carriers and non‐carriers was also examined.ResultHigher functional connectivity between the thalamus and resting state network hub regions were associated with higher CSF sPDGFRβ (Fig 1A, 1C). Cortical regions within the networks included posterior cingulate gyrus, anterior cingulate gyrus, and frontal eye field. Averaged functional connectivity between these areas was significantly higher in APOE4 carriers compared to non‐carriers (Fig 1B).ConclusionThe thalamus is a key subcortical structure for relaying signals across the brain for memory, attention and sleep/wakefulness cycles, and more recently with relevance to AD. These findings suggest a link between early BBB breakdown and elevated functional connectivity in brain regions known to have high synaptic activity and early pathology among non‐demented older adults at risk for AD.

Genuine high-order interactions in brain networks and neurodegeneration

Brain functional networks have been traditionally studied considering only interactions between pairs of regions, neglecting the richer information encoded in higher orders of interactions. In consequence, most of the connectivity studies in neurodegeneration and dementia use standard pairwise metrics. Here, we developed a genuine high-order functional connectivity (HOFC) approach that captures interactions between 3 or more regions across spatiotemporal scales, delivering a more biologically plausible characterization of the pathophysiology of neurodegeneration. We applied HOFC to multimodal (electroencephalography [EEG], and functional magnetic resonance imaging [fMRI]) data from patients diagnosed with behavioral variant of frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and healthy controls. HOFC revealed large effect sizes, which, in comparison to standard pairwise metrics, provided a more accurate and parsimonious characterization of neurodegeneration. The multimodal characterization of neurodegeneration revealed hypo and hyperconnectivity on medium to large-scale brain networks, with a larger contribution of the former. Regions as the amygdala, the insula, and frontal gyrus were associated with both effects, suggesting potential compensatory processes in hub regions. fMRI revealed hypoconnectivity in AD between regions of the default mode, salience, visual, and auditory networks, while in bvFTD between regions of the default mode, salience, and somatomotor networks. EEG revealed hypoconnectivity in the γ band between frontal, limbic, and sensory regions in AD, and in the δ band between frontal, temporal, parietal and posterior areas in bvFTD, suggesting additional pathophysiological processes that fMRI alone can not capture. Classification accuracy was comparable with standard biomarkers and robust against confounders such as sample size, age, education, and motor artifacts (from fMRI and EEG). We conclude that high-order interactions provide a detailed, EEG- and fMRI compatible, biologically plausible, and psychopathological-specific characterization of different neurodegenerative conditions.

Formation and fate of an engram in the lateral amygdala supporting a rewarding memory in mice.

Memories allow past experiences to guide future decision making and behavior. Sparse ensembles of neurons, known as engrams, are thought to store memories in the brain. Most previous research has focused on engrams supporting threatening or fearful memories where results show that neurons involved in a particular engram ("engram neurons") are both necessary and sufficient for memory expression. Far less is understood about engrams supporting appetitive or rewarding memories. As circumstances and environments are dynamic, the fate of a previously acquired engram with changing circumstances is unknown. Here we examined how engrams supporting a rewarding cue-cocaine memory are formed and whether this original engram is important in reinstatement of memory-guided behavior following extinction. Using a variety of techniques, we show that neurons in the lateral amygdala are allocated to an engram based on relative neuronal excitability at training. Furthermore, once allocated, these neurons become both necessary and sufficient for behavior consistent with recall of that rewarding memory. Allocated neurons are also critical for cocaine-primed reinstatement of memory-guided behavior following extinction. Moreover, artificial reactivation of initially allocated neurons supports reinstatement-like behavior following extinction even in the absence of cocaine-priming. Together, these findings suggest that cocaine priming after extinction reactivates the original engram, and that memory-guided reinstatement behavior does not occur in the absence of this reactivation. Although we focused on neurons in one brain region only, our findings that manipulations of lateral amygdala engram neurons alone were sufficient to impact memory-guided behavior indicate that the lateral amygdala is a critical hub region in what may be a larger brain-wide engram.

Meta-connectomic analysis maps consistent, reproducible, and transcriptionally relevant functional connectome hubs in the human brain

Human brain connectomes include sets of densely connected hub regions. However, the consistency and reproducibility of functional connectome hubs have not been established to date and the genetic signatures underlying robust hubs remain unknown. Here, we conduct a worldwide harmonized meta-connectomic analysis by pooling resting-state functional MRI data of 5212 healthy young adults across 61 independent cohorts. We identify highly consistent and reproducible connectome hubs in heteromodal and unimodal regions both across cohorts and across individuals, with the greatest effects observed in lateral parietal cortex. These hubs show heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using post-mortem transcriptome datasets, we show that as compared to non-hubs, connectome hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes. These results highlight the robustness of macroscopic connectome hubs and their potential cellular and molecular underpinnings, which markedly furthers our understanding of how connectome hubs emerge in development, support complex cognition in health, and are involved in disease.

Age-related reorganization of functional network architecture in semantic cognition.

Cognitive aging is associated with widespread neural reorganization processes in the human brain. However, the behavioral impact of such reorganization is not well understood. The current neuroimaging study investigated age differences in the functional network architecture during semantic word retrieval in young and older adults. Combining task-based functional connectivity, graph theory and cognitive measures of fluid and crystallized intelligence, our findings show age-accompanied large-scale network reorganization even when older adults have intact word retrieval abilities. In particular, functional networks of older adults were characterized by reduced decoupling between systems, reduced segregation and efficiency, and a larger number of hub regions relative to young adults. Exploring the predictive utility of these age-related changes in network topology revealed high, albeit less efficient, performance for older adults whose brain graphs showed stronger dedifferentiation and reduced distinctiveness. Our results extend theoretical accounts on neurocognitive aging by revealing the compensational potential of the commonly reported pattern of network dedifferentiation when older adults can rely on their prior knowledge for successful task processing. However, we also demonstrate the limitations of such compensatory reorganization and show that a youth-like network architecture in terms of balanced integration and segregation is associated with more economical processing.

Reorganized Hubs of Brain Functional Networks after Acute Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI)-associated damage to hub regions can lead to disrupted modular structures of functional brain networks and may result in widespread cognitive and behavioral deficits. The spatial layout of brain connections and modules is essential for understanding the reorganization of brain networks to trauma. We investigated the roles of hubs in inter-subnetwork information coordination and integration using participation coefficients (PCs) in 74 patients with acute mTBI and 51 matched healthy controls. In some brain networks, such as default mode network (DMN) and frontoparietal network (FPN), mild TBI patients had decreased PC levels, while this measure was saliently increased in patients in other networks, such as the visual network. The hub disruption index was defined as the gradient of a straight line fitted to scatterplots of individual mTBI in participation coefficient versus mean participation coefficient of healthy groups. There was a trend of radical reorganization of some efficient "hub" nodes in patients (κ = -0.15), compared with controls (κ close to 0). The PC of brain hubs can also differentiate mTBI patients from controls with an 88% accuracy, and decreased PC levels in FPN can predict patient' s worse cognitive information processing speed (r = 0.36, p < 0.002) and working memory performance (r = 0.35, p < 0.002). Reduced PC within the DMN was associated with patients' complaints of post-concussion symptoms (r = -0.35, p < 0.002). This evidence suggests a trend of spatial transition of hub profiles in acute mTBI, and graph metrics of PC measures can be used as potential diagnostic biomarkers.

Ca2+ Oscillations, Waves, and Networks in Islets From Human Donors With and Without Type 2 Diabetes.

Pancreatic islets are highly interconnected structures that produce pulses of insulin and other hormones, maintaining normal homeostasis of glucose and other nutrients. Normal stimulus-secretion and intercellular coupling are essential to regulated secretory responses, and these hallmarks are known to be altered in diabetes. In the current study, we used calcium imaging of isolated human islets to assess their collective behavior. The activity occurred in the form of calcium oscillations, was synchronized across different regions of islets through calcium waves, and was glucose dependent: higher glucose enhanced the activity, elicited a greater proportion of global calcium waves, and led to denser and less fragmented functional networks. Hub regions were identified in stimulatory conditions, and they were characterized by long active times. Moreover, calcium waves were found to be initiated in different subregions and the roles of initiators and hubs did not overlap. In type 2 diabetes, glucose dependence was retained, but reduced activity, locally restricted waves, and more segregated networks were detected compared with control islets. Interestingly, hub regions seemed to suffer the most by losing a disproportionately large fraction of connections. These changes affected islets from donors with diabetes in a heterogeneous manner.

Dynamic network model reveals distinct tau spreading patterns in early- and late-onset Alzheimer disease

BackgroundThe clinical features of Alzheimer’s disease (AD) vary substantially depending on whether the onset of cognitive deficits is early or late. The amount and distribution patterns of tau pathology are thought to play a key role in the clinical characteristics of AD, which spreads throughout the large-scale brain network. Here, we describe the differences between tau-spreading processes in early- and late-onset symptomatic individuals on the AD spectrum.MethodsWe divided 74 cognitively unimpaired (CU) and 68 cognitively impaired (CI) patients receiving 18F-flortaucipir positron emission tomography scans into two groups by age and age at onset. Members of each group were arranged in a pseudo-longitudinal order based on baseline tau pathology severity, and potential interregional tau-spreading pathways were defined following the order using longitudinal tau uptake. We detected a multilayer community structure through consecutive tau-spreading networks to identify spatio-temporal changes in the propagation hubs.ResultsIn each group, ordered tau-spreading networks revealed the stage-dependent dynamics of tau propagation, supporting distinct tau accumulation patterns. In the young CU/early-onset CI group, tau appears to spread through a combination of three independent communities with partially overlapped territories, whose specific driving regions were the basal temporal regions, left medial and lateral temporal regions, and left parietal regions. For the old CU/late-onset CI group, however, continuation of major communities occurs in line with the appearance of hub regions in the order of bilateral entorhinal cortices, parahippocampal and fusiform gyri, and lateral temporal regions.ConclusionLongitudinal tau propagation depicts distinct spreading pathways of the early- and late-onset AD spectrum characterized by the specific location and appearance period of several hub regions that dominantly provide tau.

Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning.

SummaryAdaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior.

Systematic mutagenesis of TFIIH subunit p52/Tfb2 identifies residues required for XPB/Ssl2 subunit function and genetic interactions with TFB6

TFIIH is an evolutionarily conserved complex that plays central roles in both RNA polymerase II (pol II) transcription and DNA repair. As an integral component of the pol II preinitiation complex, TFIIH regulates pol II enzyme activity in numerous ways. The TFIIH subunit XPB/Ssl2 is an ATP-dependent DNA translocase that stimulates promoter opening prior to transcription initiation. Crosslinking-mass spectrometry and cryo-EM results have shown a conserved interaction network involving XPB/Ssl2 and the C-terminal Hub region of the TFIIH p52/Tfb2 subunit, but the functional significance of specific residues is unclear. Here, we systematically mutagenized the HubA region of Tfb2 and screened for growth phenotypes in a TFB6 deletion background in Saccharomyces cerevisiae. We identified six lethal and 12 conditional mutants. Slow growth phenotypes of all but three conditional mutants were relieved in the presence of TFB6, thus identifying a functional interaction between Tfb2 HubA mutants and Tfb6, a protein that dissociates Ssl2 from TFIIH. Our biochemical analysis of Tfb2 mutants with severe growth phenotypes revealed defects in Ssl2 association, with similar results in human cells. Further characterization of these tfb2 mutant cells revealed defects in GAL gene induction, and reduced occupancy of TFIIH and pol II at GAL gene promoters, suggesting that functionally competent TFIIH is required for proper pol II recruitment to preinitiation complexes in vivo. Consistent with recent structural models of TFIIH, our results identify key residues in the p52/Tfb2 HubA domain that are required for stable incorporation of XPB/Ssl2 into TFIIH and for pol II transcription.