Biology subjects

Fu, Z.

Publications and source records attributed to Fu, Z..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

First identification and investigation of piRNAs in the larval guts of Asian honey bee, Apis cerana

Piwi-interacting RNAs (piRNAs), a kind of small non-coding RNAs (ncRNAs), play pivotal parts in maintaining the genomic stability and modulating biological processes such as growth and development via regulation of gene expression. However, piRNAs in Asian honey bee (Apis cerana) is still largely unknown at present. In this current work, on basis of previously gained high-quality small RNA-seq datasets, piRNAs in the larval guts of Apis cerana cerana, the nominate species of A. cerana, was for the first time identified, followed by in-depth investigation of the regulatory roles of differentially expressed piRNAs (DEpiRNAs) in the developmental process of the A. c. cerana. Here, a total of 621 piRNAs were identified in the A. c. cerana larval guts, among which 499 piRNAs were shared by 4- (Ac4 group), 5- (Ac5 group), and 6-day-old (Ac6 group) larval guts, while the numbers of unique ones were 79, 37, and 11, respectively. piRNAs each group were ranged from 24 nt to 33 nt in length, and the first base of piRNAs had a cytosine (C) bias. Additionally, five up-regulated and five down-regulated piRNAs were identified in the Ac4 vs. Ac5 comparison group, 9 of which could target 9, 011 mRNAs; these targets were involved in 41 GO terms and 137 pathways. Comparatively, 22 up-regulated piRNAs were detected in the Ac5 vs. Ac6 comparison group, 21 of which could target 28, 969 mRNAs; these targets were engaged in 46 functional terms and 164 pathways. The results suggested the overall alteration of expression pattern of piRNAs during the developmental process of A. c. cerana larvae. Regulatory network analysis showed that piR-bmo-748815 and piR-bmo-512574 in the Ac4 vs. Ac5 comparison group as well as piR-bmo-716466 and piR-bmo-828146 in the Ac5 vs. Ac6 comparison group linked to the highest number of targets. Further investigation indicated that targets of DEpiRNAs in the above-mentioned two comparison groups could be annotated to several growth and development-associated pathways, such as Jak/STAT, TGF-{beta}, and Wnt signaling pathways, indicating the involvement of DEpiRNAs in modulating larval gut development via these crucial pathways. Moreover, the expression trends of six randomly selected DEpiRNAs were verified using a combination of stem-loop RT-PCR and RT-qPCR. These results not only provide a novel insight into the development of the A. c. cerana larval guts, but also lay a foundation for uncovering the epigenetic mechanism underlying the larval gut development.

molecular biology↗

bioRxiv2022

Mechanism of dual pharmacological correction and potentiation of human CFTR

Cystic fibrosis (CF) is caused by mutations in a chloride channel called the human Cystic Fibrosis Transmembrane Conductance Regulator (hCFTR). We used cryo-EM global conformational ensemble reconstruction to characterize the mechanism by which the breakthrough drug VX445 (Elexacaftor) simultaneously corrects both protein-folding and channel-gating defects caused by CF mutations. VX445 drives hCFTR molecules harboring the gating-defective G551D mutation towards the open-channel conformation by binding to a site in the first transmembrane domain. This binding interaction reverses the usual pathway of allosteric structural communication by which ATP binding activates channel conductance, which is blocked by the G551D mutation. Our ensemble reconstructions include a 3.4 [A] non-native structure demonstrating that detachment of the first nucleotide-binding domain of hCFTR is directly coupled to local unfolding of the VX445 binding site. Reversal of this unfolding transition likely contributes to its corrector activity by cooperatively stabilizing NBD1 and the transmembrane domains of hCFTR during biogenesis. SummaryCryo-EM global conformational ensemble reconstruction has been used to characterize the mechanism-of-action of a breakthrough pharmaceutical that corrects fatal protein-folding and channel-gating defects in the human cystic fibrosis transmembrane conductance regulator (CFTR).

biophysics↗

bioRxiv2022

Transcriptome-wide characterization of piRNAs during the developmental process of European honey bee larval guts

piRNAs play pivotal roles in suppressing transposons, maintaining genome stability, regulating gene expression, and modulating development and immunity. However, there are few piRNA-associated studies on honey bee, and the regulatory role of piRNAs in the development of bee guts is largely unknown. In this current work, the differential expression pattern of piRNAs during the developmental process of the European honey bee (Apis mellifera) was analyzed, and target prediction of differentially expressed piRNAs (DEpiRNAs) was then conducted, followed by investigation of regulatory networks and the potential function of DEpiRNAs in regulating larval gut development. Here, a total of 843 piRNAs were identified in the larval guts of A. mellifera; among these, 764 piRNAs were shared by 4- (Am4 group), 5- (Am5 group), and 6-day-old (Am6 group) larval guts, while 11, 67, and 1, respectively, were unique. The first base of piRNAs in each group had a cytosine (C) bias. Additionally, 61 up-regulated and 17 down-regulated piR-NAs were identified in the Am4 vs. Am5 comparison group, further targeting 9, 983 genes, which were involved in 50 GO terms and 142 pathways, while two up-regulated and five down-regulated piRNAs were detected in the Am5 vs. Am6 comparison group, further targeting 1, 936 genes, which were engaged in 41 functional terms and 101 pathways. piR-ame-742536 and piR-ame-856650 in the Am4 vs. Am5 comparison group as well as piR-ame-592661 and piR-ame-31653 in the Am5 vs. Am6 comparison group were found to link to the highest number of targets. Further analysis indicated that targets of DEpiRNAs in these two comparison groups were seven development-associated signaling pathways such as Hippo and Notch signaling pathways, seven immune-associated pathways including endocytosis and the Jak/STAT signaling pathway, and three energy metabolism pathways, namely sulfur metabolism, nitrogen metabolism, and oxidative phosphorylation. Moreover, the expression trends of five randomly selected DEpiRNAs were verified based on stem-loop RT-PCR and RT-qPCR. These results were suggestive of the overall alteration of piRNAs during the larval developmental process and demonstrated that DEpiRNAs potentially modulate development-, immune-, and energy metabolism-associated pathways by regulating expression of corresponding genes via target binding, further affecting the development of A. mellifera larval guts. Our data offer novel insights into the development of bee guts and lay a basis for clarifying the developmental mechanism underlying the larval guts of European honey bee.

molecular biology↗

bioRxiv2022

Canonical and Replicable Multi-Scale Intrinsic Connectivity Networks in 100k+ Resting-State fMRI Datasets

Resting-state functional magnetic resonance imaging (rsfMRI) has shown considerable promise for improving our understanding of brain function and characterizing various mental and cognitive states in the healthy and disordered brain. However, the lack of accurate and precise estimations of comparable functional patterns across datasets, individuals, and ever-changing brain states in a way that captures both individual variation and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. We posit that using reliable network templates and advanced group-informed network estimation approaches to accurately and precisely obtain individualized (dynamic) networks that retain cross-subject correspondence while maintaining subject-specific information is one potential solution to overcome the aforementioned barrier when considering cross-study comparability, independence of subject-level estimates, the limited data available in single studies, and the low signal-to-noise ratio (SNR) of rsfMRI. Toward this goal, we first obtained a reliable and replicable network template. We combined rsfMRI data of over 100k individuals across private and public datasets and selected around 58k that meet quality control (QC) criteria. We then applied multi-model-order independent component analysis (ICA) and subsampling to obtain reliable canonical intrinsic connectivity networks (ICNs) across multiple spatial scales. The selected ICNs (i.e., network templates) were also successfully replicated by independently analyzing the data that did not pass the QC criteria, highlighting the robustness of our adaptive template to data quality. We next studied the feasibility of estimating the corresponding subject-specific ICNs using a multivariate-spatially constrained ICA as an example of group-informed network estimation approaches. The results highlight that several factors, including ICNs themselves, data length, and spatial resolution, play key roles in successfully estimating the ICNs at the subject level. Large-scale ICNs, in general, require less data to achieve a specific level of spatial similarity with their templates (as well as within- and between-subject spatial similarity). Moreover, increasing data length can reduce an ICNs subject-level specificity, suggesting longer scans might not always be desirable. We also show spatial smoothing can alter results, and the positive linear relationship we observed between data length and spatial smoothness (we posit that it is at least partially due to averaging over intrinsic dynamics or individual variation) indicates the importance of considering this factor in studies such as those focused on optimizing data length. Finally, the consistency in the spatial similarity between ICNs estimated using the full-length of data and subset of it across different data lengths may suggest that the lower within-subject spatial similarity in shorter data lengths is not necessarily only defined by lower reliability in ICN estimates; rather, it can also be an indication of brain dynamics (i.e., different subsets of data may reflect different ICN dynamics), and as we increase the data length, the result approaches the average (also known as static) ICN pattern, and therefore loses its distinctiveness.

neuroscience↗

bioRxiv2022

Ketolysis is a metabolic driver of CD8+ T cell effector function through histone acetylation

Environmental nutrient availability influences T cell metabolism, impacting T cell function and shaping immune outcomes. However, the metabolic pathways critical for optimal T cell responses remain poorly understood. Here, we identify ketone bodies (KBs) - including {beta}-hydroxybutyrate ({beta}OHB) and acetoacetate (AcAc) - as essential fuels supporting CD8+ T cell metabolism and effector function. Ketolysis is an intrinsic feature of highly functional CD8+ T effector (Teff) cells and {beta}OHB directly increases CD8+ Teff cell IFN-{gamma} production and cytolytic activity. Using metabolic tracers, we establish that CD8+ Teff cells preferentially use KBs over glucose to fuel the tricarboxylic acid (TCA) cycle in vitro and in vivo. KBs directly boost the respiratory capacity of CD8+ T cells and TCA cycle-dependent metabolic pathways that fuel T cell growth. Mechanistically, we find that {beta}OHB is a major substrate for acetyl-CoA production in CD8+ T cells and regulates effector responses through effects on histone acetylation. Together, our results identify cell-intrinsic ketolysis as a metabolic and epigenetic driver of optimal CD8+ T cell effector responses. One Sentence summaryKetone bodies promote CD8+ T cell metabolism and effector function through regulation of epigenetic programming

immunology↗

bioRxiv2022

Elastic properties and shape of the Piezo dome underlying its mechanosensory function

In a companion paper we show that the free membrane shape of lipid bilayer vesicles containing the mechanosensitive ion channel Piezo can be predicted, with no free parameters, from membrane elasticity theory together with measurements of the protein geometry and vesicle size (accompanying paper). Here we use these results to determine the force that Piezo exerts on the free membrane and, hence, that the free membrane exerts on Piezo, for a range of vesicle sizes. From vesicle shape measurements alone, we thus obtain a force-distortion relationship for Piezo, from which we deduce Piezos intrinsic radius of curvature, 42 {+/-} 12 nm, and bending stiffness, 18 {+/-} 2.1 kB T, in free-standing lipid bilayer membranes mimicking cell membranes. Applying these estimates to a spherical cap model of Piezo embedded in a lipid bilayer, we suggest that Piezos intrinsic curvature, surrounding membrane footprint, small stiffness, and large area are the key properties of Piezo that give rise to low-threshold, high-sensitivity mechanical gating.

biophysics↗

bioRxiv2022

Quantitative prediction and measurement of Piezo's membrane footprint

Piezo proteins are mechanosensitive ion channels that can locally curve the membrane into a dome shape (Y. R. Guo, R. MacKinnon, 2017). The curved shape of the Piezo dome is expected to deform the surrounding lipid bilayer membrane into a membrane footprint, which may serve to amplify Piezos sensitivity to applied forces (C. A. Haselwandter, R. MacKinnon, 2018). If Piezo proteins are embedded in lipid bilayer vesicles, the membrane shape deformations induced by the Piezo dome depend on the vesicle size. We employ here membrane elasticity theory to predict, with no free parameters, the shape of such Piezo vesicles outside the Piezo dome, and show that the predicted vesicle shapes agree quantitatively with the corresponding measured vesicle shapes obtained through cryo-electron tomography, for a range of vesicle sizes (Helfrich W. 1973). On this basis, we explore the coupling between Piezo and membrane shape, and demonstrate that the features of the Piezo dome affecting Piezos membrane footprint follow approximately a spherical cap geometry. Our work puts into place the foundation for deducing key elastic properties of the Piezo dome from membrane shape measurements and provides a general framework for quantifying how proteins deform bilayer membranes. ClassificationBiophysicss

biophysics↗

bioRxiv2022

Therapeutic activation of endothelial sphingosine 1-phosphate receptor-1 by chaperone-bound S1P suppresses proliferative retinal vasculopathy

Sphingosine-1-phosphate (S1P), a bioactive lipid mediator that signals via G protein-coupled S1P receptors (S1PR), is required for normal vascular development. The role of this signaling axis in vascular retinopathies is largely unexplored. Here we show in a mouse model of oxygen-induced retinopathy (OIR) that endothelial overexpression of S1pr1 suppresses while endothelial knockout (KO) of S1pr1 worsens neovascular tuft formation. Furthermore, neovascular tufts are increased in Apom KO mice which lack HDL-bound S1P while they are suppressed in Apom TG mice which has more circulating HDL-S1P. These results suggest that circulating HDL-S1P activation of endothelial S1PR1 specifically suppresses proliferative retinal vasculopathy. Moreover, systemic administration of ApoM-Fc-bound S1P or a small molecule Gi-biased S1PR1 agonist suppressed neovascular tuft formation. Circulating HDL-S1P activation of endothelial S1PR1 may be a key protective mechanism to guard against neovascular retinopathies that occur not only in premature infants but also in diabetes and aging.

pathology↗

bioRxiv2022

Machine Learning Predicts Treatment Response in Bipolar & Major Depressive Disorders

Diagnosis of bipolar disorder (BD) patients with complex symptoms presents a challenge to clinicians. Patients tend to spend more time in a depressive state than a manic state. In such complex cases, the current Diagnostic and Statistical Manual (DSM), which is not based on pathophysiology, can lead to misdiagnosis as major depressive disorder (MDD) and an imperfect or even harmful medication response. A biologically-based classification algorithm is needed to improve the accuracy of diagnosis. Osuch et al. (2018) presented a kernel support vector machine (SVM) algorithm to predict the medication-class of response from new patient samples whose diagnoses were unclear. Here we also utilize the kernel support vector machine (SVM) algorithm but with a few novel contributions. We applied the robust, fully automated neuromark independent component analysis (ICA) framework to extract comparable features in a multi-dataset setting and learn a kernel function for support vector machine (SVM) on multiple feature subspaces. The neuromark framework successfully replicates the prior result with 95.45% accuracy (sensitivity 90.24%, specificity 92.3%). To further evaluate the generalizability of our approach, we incorporated two additional datasets comprising bipolar disorder (BD) and major depressive disorder (MDD) patients. We validated the trained algorithm on these datasets, resulting in a testing accuracy of up to 89% (sensitivity 0.88, specificity 0.89) without using site or scanner harmonization techniques. We also translated the model to predict improvement scores of major depressive disorder (MDD) with up to 70% accuracy. This approach reveals some salient biological markers of medication-class of response within mood disorders. HighlightsO_LIWe demonstrate a DSM-free approach for predicting treatment response from resting-state functional magnetic resonance imaging (fMRI) data. C_LIO_LIWe identify several replicable biomarkers using the approach. C_LIO_LIOur work has potential for clinical application by replacing trial-and-error in treating complex psychiatric disorders. C_LI

neuroscience↗

bioRxiv2022

Endothelial-derived sphingolipids are required for vascular development and systemic lipid homeostasis

Serine palmitoyl transferase (SPT), the rate-limiting enzyme in the de novo synthesis of sphingolipids (SL), is needed for embryonic development, physiological homeostasis, and response to stress. The functions of de novo SL synthesis in vascular endothelial cells (EC), which line the entire circulatory system, are not well understood. Here we show that the EC de novo synthesis not only impacts vascular development but also maintains normal SL metabolic homeostasis in the circulatory system and peripheral organs. Mice with an endothelial-specific gene knockout of SPTLC1 (Sptlc1 ECKO), an essential subunit of the SPT complex, exhibited EC-intrinsic effects including reduced EC proliferation and tip/stalk cell differentiation, resulting in delayed retinal vascular development. In addition, Sptlc1 ECKO mice had reduced pathological retinal neovascularization in the oxygen-induced retinopathy model, suggesting that EC SL produced from the de novo pathway are needed for efficient VEGF signaling within the vascular system. Post-natal deletion of the EC Sptlc1also showed cell-extrinsic effects, including rapid reduction of several SL metabolites in plasma, red blood cells and peripheral organs (lung and liver) but not in the retina, part of the central nervous system (CNS). In the liver, EC de novo SL synthesis was required for acetaminophen-induced ceramide elevation and hepatotoxicity. These results suggest that EC-derived SL metabolites are in constant flux between the vasculature, circulatory elements, and parenchymal cells of non-CNS organs. Taken together, our data point to the central role of the endothelial SL biosynthesis in maintaining vascular development and neovascular proliferation, non-CNS tissue metabolic homeostasis and hepatocyte response to stress.

developmental biology↗

bioRxiv2022

Impact of Nosema ceranae invasion on sucrose solution consumption, midgut epithelial cell structure, and lifespan of Apis cerana cerana workers

Nosema ceranae is an intracellular fungal parasite for honeybees, leading to chronic disease named bee nosemosis with worldwide distribution. Asian honeybee (Apis cerana) is the original host for N. ceranae, but the impact of N. ceranae infection on A. cerana physiology is largely unknown. In this current work, workers of Apis cerana cerana, a subspecies of Asian honeybee, were artificially inoculated with N. ceranae spores and reared under lab conditions, followed by detection of fungal spore load as well as host sucrose solution consumption, midgut epithelial cell structure, and lifespan. The result of spore counting suggested that the spore load in the host midgut decreased significantly during 1 dpi-2 dpi, whereas that displayed an elevated trend among 2 dpi-13 dpi. The sucrose solution consumption of workers in N. ceranae-inoculated groups among 1 dpi-20 dpi was always higher than that of workers in un-inoculated groups; additionally, the difference of sucrose solution consumption between these two groups at 4 dpi, 5 dpi, and 13 dpi was of significance. Based on microscopic observation of paraffin sections, darkly stained parasites were clearly detected in the midgut epithelial cells of N. ceranae-inoculated workers at 7 dpi-10 dpi, whereas no parasite was observed in those of un-inoculated workers. In addition, the boundaries of un-inoculated host epithelial cells were intact and the darkly stained nucleus were clear, while the boundaries of midgut epithelial cells of N. ceranae-inoculated workers were blurred, the nucleus were almost disappeared, and the nucleic acid substances were diffused. Moreover, the survival rates of workers in both N. ceranae-inoculated groups and un-inoculated groups at 1 dpi-5 dpi were pretty high and then started to decrease at 5 dpi; the survival rate of workers in N. ceranae-inoculated groups was always lower than that in un-inoculated groups, with significant difference between these two groups during 11 dpi-20 dpi. These results together indicate that the quantity of fungal spores continuously elevated with the microsporidian multiplication, causing energetic stress for workers and host cell structure damage, which further negatively affected the host lifespan. Our findings offer a solid basis not only for exploring the molecular mechanism underlying N. ceranae infection but also for investigating the interaction between N. ceranae and eastern honeybee.

molecular biology↗

bioRxiv2021

Learning Active Multimodal Subspaces in the Brain

Here we introduce a multimodal framework to identify subspaces in the human brain that are defined by collective changes in structural and functional measures and are actively linked to demographic, biological and cognitive indicators in a population. We determine the multimodal subspaces using principles of active subspace learning (ASL) and demonstrate its application on a sample learning task (biological ageing) on a Schizophrenia dataset. The proposed multimodal ASL method successfully identifies latent brain representations as subsets of brain regions and connections forming co-varying subspaces in association with biological age. We show that Schizophrenia is characterized by different subspace patterns compared to those in a cognitively normal brain. The multimodal features generated by projecting structural and functional MRI components onto these active subspaces perform better than several PCA-based transformations and equally well when compared to non-transformed features on the studied learning task. In essence, the proposed method successfully learns active brain subspaces associated with a specific brain condition but inferred from the brain imaging data along with the biological/cognitive traits of interest.

neuroscience↗

bioRxiv2021

Multi-model Order ICA: A Data-driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales

BackgroundWhile functional connectivity is widely studied, there has been little work studying functional connectivity at different spatial scales. Likewise, the relationship of functional connectivity between spatial scales is unknown. MethodsWe proposed an independent component analysis (ICA) - based approach to capture information at multiple model orders (component numbers) and to evaluate functional network connectivity (FNC) both within and between model orders. We evaluated the approach by studying group differences in the context of a study of resting fMRI (rsfMRI) data collected from schizophrenia (SZ) individuals and healthy controls (HC). The predictive ability of FNC at multiple spatial scales was assessed using support vector machine (SVM)-based classification. ResultsIn addition to consistent predictive patterns at both multiple-model orders and single model orders, unique predictive information was seen at multiple-model orders and in the interaction between model orders. We observed that the FNC between model order 25 and 50 maintained the highest predictive information between HC and SZ. Results highlighted the predictive ability of the somatomotor and visual domains both within and between model orders compared to other functional domains. Also, subcortical-somatomotor, temporal-somatomotor, and temporal-subcortical FNCs had relatively high weights in predicting SZ. ConclusionsIn sum, multi-model order ICA provides a more comprehensive way to study FNC, produces meaningful and interesting results which are applicable to future studies. We shared the spatial templates from this work at different model orders to provide a reference for the community, which can be leveraged in regression-based or fully automated (spatially constrained) ICA approaches. Impact StatementMulti-model order ICA provides a comprehensive way to study brain functional network connectivity within and between multiple spatial scales, highlighting findings that would have been ignored in single model order analysis. This work expands upon and adds to the relatively new literature on resting fMRI-based classification and prediction. Results highlighted the differentiating power of specific intrinsic connectivity networks on classifying brain disorders of schizophrenia patients and healthy participants, at different spatial scales. The spatial templates from this work provide a reference for the community, which can be leveraged in regression-based or fully automated ICA approaches.

neuroscience↗

bioRxiv2021

Amino acid transporter SLC38A5 regulates developmental and pathological retinal angiogenesis

Amino acid metabolism in vascular endothelium is important for sprouting angiogenesis. SLC38A5 (solute carrier family 38 member 5), an amino acid (AA) transporter, shuttles neutral AAs across cell membrane, including glutamine, which may serve as metabolic fuel for proliferating endothelial cells (ECs) to promote angiogenesis. Here we found that Slc38a5 is highly enriched in normal retinal vascular endothelium, and more specifically in pathological sprouting neovessels. Slc38a5 is suppressed in retinal blood vessels from Lrp5-/- and Ndpy/- mice, both genetic models of defective retinal vascular development with Wnt signaling mutations. Additionally, Slc38a5 transcription is directly regulated by Wnt/{beta}-catenin signaling. Genetic deficiency of Slc38a5 in mice substantially delays retinal vascular development and suppresses pathological neovascularization in oxygen-induced retinopathy modeling ischemic proliferative retinopathies. Inhibition of SLC38A5 in retinal vascular ECs impairs EC proliferation and angiogenic function, suppresses glutamine uptake, and dampens vascular endothelial growth factor receptor 2 (VEGFR2). Together these findings suggest that SLC38A5 is a new metabolic regulator of retinal angiogenesis by controlling AA nutrient uptake and homeostasis in ECs. Significance StatementAmino acid metabolism in vascular endothelium is important for angiogenesis. SLC38A5 (solute carrier family 38 member 5) is an amino acid (AA) transporter for shuttling neutral AAs such as glutamine across cell membrane. Our work demonstrate that Slc38a5 is highly enriched in retinal vascular endothelium. SLC38A5 regulates endothelial cell glutamine uptake and vascular growth factor receptors to impact blood vessels growth in retinal development and in retinopathies. This work uncovered a novel role of SLC38A5 as a metabolic regulator of retinal angiogenesis by controlling AA nutrient uptake and homeostasis in blood vessel endothelium. Findings from this study also suggest that targeting SLC38A5 or relevant AAs can be a new way to protect against retinopathy.

developmental biology↗

bioRxiv2021

The geometry of domain-general performance monitoring representations in the human medial frontal cortex

Controlling behavior to flexibly achieve desired goals depends on the ability to monitor ones own performance. It is unknown how performance monitoring can be both flexible to support different tasks and specialized to perform well on each. We recorded single neurons in the human medial frontal cortex while subjects performed two tasks that involve three types of cognitive conflict. Neurons encoding predicted conflict, conflict, and error in one or both tasks were intermixed, forming a representational geometry that simultaneously allowed task specialization and generalization. Neurons encoding conflict retrospectively served to update internal estimates of control demand. Population representations of conflict were compositional. These findings reveal how representations of evaluative signals can be both abstract and task-specific and suggest a neuronal mechanism for estimating control demand.

neuroscience↗

bioRxiv2021

Computational mechanisms for neural representation of words

A critical way for humans to acquire, represent and communicate information is through language, yet the underlying computation mechanisms through which language contributes to our word meaning representations are poorly understood. We compared three major types of word computation mechanisms from large language corpus (simple co-occurrence, graph-space relations and neural-network-vector-embedding relations) in terms of the association of words brain activity patterns, measured by two functional magnetic resonance imaging (fMRI) experiments. Word relations derived from a graph-space representation, and not neural-network-vector-embedding, had unique explanatory power for the neural activity patterns in brain regions that have been shown to be particularly sensitive to language processes, including the anterior temporal lobe (capturing graph-common-neighbors), inferior frontal gyrus, and posterior middle/inferior temporal gyrus (capturing graph-shortest-path). These results were robust across different window sizes and graph sizes and were relatively specific to language inputs. These findings highlight the role of cumulative language inputs in organizing word meaning neural representations and provide a mathematical model to explain how different brain regions capture different types of language-derived information.

neuroscience↗

bioRxiv2021

Moving Beyond the 'CAP' of the Iceberg: Intrinsic Connectivity Networks in fMRI are Continuously Engaging and Overlapping

Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.

neuroscience↗

bioRxiv2021

Dynamic functional connectivity links with treatment response of electroconvulsive therapy in major depressive disorder

BackgroundElectroconvulsive Therapy (ECT) is one of the most effective treatments for major depressive disorder (DEP). There is recently increasing attention to evaluate ECTs effect on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of DEP patients with healthy participants, investigate whether dynamic functional network connectivity network (dFNC) estimated from rs-fMRI predicts the ECT outcome, and explore the effect of ECT on brain network states. MethodResting-state fMRI data were collected from 119 patients with depression or DEP (76 females), and 61 Healthy (HC) participants (34 females) with an age mean of 52.25 (N=180) years old. The pre-ECT and post-ECT Hamilton Depression Rating Scale (HDRS) were 25.59{+/-}6.14 and 11.48{+/-}9.07, respectively. Twenty-four independent components from default mode (DMN) and cognitive control network (CCN) were extracted using group-independent component analysis from pre-ECT and post-ECT rs-fMRI. Then, the sliding window approach was used to estimate the pre-and post-ECT dFNC of each participant. Next, k-means clustering was separately applied to pre-ECT dFNC and post-ECT dFNC to assess three distinct states from each participant. We calculated the amount of time each individual spends in each state, called occupancy rate or OCR. Next, we compared OCR values between HC and DEP participants. We also calculated the partial correlation between pre-ECT OCRs and HDRS change while controlling for age, gender, number of treatment, and site. Finally, we evaluated the effectiveness of ECT by comparing pre-and post-ECT OCR of DEP and HC participants. ResultsThe main findings include: 1) DEP patients had significantly lower OCR values than the HC group in a state, where connectivity between CCN and DMN was relatively higher than other states (corrected p= 0.015), 2) Pre-ECT OCR of state, with more negative connectivity between CCN and DMN components, predicted the HDRS changes (R=0.23 corrected p=0.03). This means that those DEP patients who spend less time in this state showed more HDRS change, and 3) The post-ECT OCR analysis suggested that ECT increased the amount of time DEP patients spend in state 2 (corrected p=0.03). Finally, we found ECT increases the total traveled distance in DEP. ConclusionOur finding suggests that dFNC features, estimated from CCN and DMN, show promise as a predictive biomarker of the ECT outcome of DEP patients. Also, this study identified a possible underlying mechanism associated with the ECT effect in DEP patients.

neuroscience↗