dataesr/scientific-paragraphs-categorization huggingface dataset:
Additionally, rs-fMRI data were temporally filtered using a least squares linearphase finite impulse response filter design bandpass (0. 01-0. 1 Hz). For each participant and hROI (the same 185 homotopic ROIs as those used in the task-induced analysis), an individual BOLD rs-fMRI time series was computed by averaging the BOLD fMRI time series of all voxels located within the hROI volume.
Reliability of the network identification across individuals We used multiscale bootstrap resampling  (Efron et al. 1996)  to assess the reliability of the identification of each cluster. In total, 10,000 multiscale bootstrap resampling datasets, including 50-140% of sample data from the 138 participants, were processed. Applying the R package "pvclust"  (Suzuki and Shimodaira 2006)  function to the multiscale bootstrap resampling outputs, we measured the approximately unbiased (AU) p value for each cluster. The AU p value for a network, the probability of this network occurring among the 138 participants, indicates the network's reliability.
Robustness of the networks identification with respect to the clustering method We also assessed the robustness of the clustering method by comparing its output to those of three other clustering methods: aHCA with the average distance method (instead of Ward's), Gaussian mixture model, and k-means (see supplementary material). Gaussian mixture modelling was conducted with the "Rmixmod" package with Normalized Entropy Criterion to find well-separated clusters and with a Gaussian model with diagonal variance matrices  (Lebret et al. 2015). We then compared the four different partitions through the adjusted Rand index  (Hubert and Arabie 1985)  allowing to get a similarity measure between two different classifications, an adjusted Rand index of 1 indicating similar partitions.
Summary of results Conjunction analysis of left-activated and leftward asymmetrical hROIs in 144 right-handed participants performing three language tasks (PROD SENT-WORD , READ SENT-WORD and LISN SENT-WORD ) uncovered a set of 32 supramodal regions involved in lexico-syntactic processing. The hierarchical bottom-up clustering of the intrinsic connectivity between these 32 hROIs led to the identification of 3 networks, including a network of essential language areas (SENT_CORE) with strong positive correlations at rest across its 18 hROIs in more than 90% of the participants. The two other identified   2  networks had lower inter-individual consistency, one including visual language areas at the interface between visual and syntactic processing (SENT_VISU) and the other including posterior DMN areas including posterior hippocampus (SENT_MEM).
Intrinsic connectivity analysis showed that SENT_CORE was negatively correlated with SENT_MEM but was not correlated with SENT_VISU. Graph analysis metrics obtained for the SENT_CORE network revealed that F3t, STS3, and STS4 were hubs of both degree and betweenness centrality, and F3t and ST3 were also hubs of participation, meaning that these are key areas for both intra-network communication and inter-network communication between SENT_CORE and the other 2 networks. Importantly, a positive correlation across individuals was observed between the DC measured at rest and the strength of activation in most SENT_CORE regions, meaning that participants with higher DC values in a given region had higher activations than participants with lower DC values. Table  5  Correlation analysis between the degree centrality measured in the SENT_CORE network and the mean activation in each of the three language tasks Correlations (R) were calculated within each hROI of the left hemisphere constituting the SENT_CORE network, and the DC values were calculated in the SENT_CORE network.
Methodological issues In this study, we selected right-handers from the BIL&GIN database because we previously demonstrated that these participants have a left hemisphere dominance for language at both the group level (Tzourio-  Mazoyer et al. 2016 ) and the individual level  (Zago et al. 2017) , with only 5 (3%) of the 144 participants having a co-dominant right hemisphere. This sample group is optimal for selecting areas specific for sentence processing based on a conjunction of activations and leftward asymmetries. In addition, the inclusion of a fairly considerable number of participants (N = 144) provided us a high sensitivity for detecting supramodal sentence areas while minimizing the risk of overlooking some. However, we must underline that the present atlas is not all-inclusive. First, we selected map regions involved in only high-order language processing and lexico-syntactic processing.
Other areas contributing to sentence tasks Because there was a low inter-individual consistency in the segregation of the networks labelled SENT_VISU and SENT_MEM, we will discuss the potential role of the 14 hROIs that were not part of SENT_CORE together. Since each event of the sentence tasks included task monitoring, such as shifting between the word list and sentence tasks when a picture was presented or providing a motor response at the end of sentence processing, the involvement of executive areas was expected. Conjunction analyses indeed revealed that, in addition to the anterior insula at play in the three tasks (see above), putamen hROIs were involved and are a key neural support of executive functions and task monitoring  (Monchi et al. 2006; Sefcsik et al. 2009 ). Moreover, a recent meta-analysis involving connectivity modelling showed that the left and right putamen areas are different in terms of their respective co-activations, which are specifically co-involved in language areas (Viñas-Guasch and Wu 2017).
Funding This work was supported by a grant from the  FLAG-ERA  Human  Brain Project 2015  ( ANR-15-HBPR-0001-03-MULTI-LAT-ERAL ) awarded to FC, BM, NTM, and MJ and the  Ginesis-Lab project  ( ANR 16 LCV2 0006 01 ), a grant awarded to MJ, BM, NTM, EM, CF, and LP.
Materials and Methods Participants. Sixteen female subjects (26. 4 ± 4. 3 years old) with no neurological history participated in the study. We determined the required sample size through the G* power software  41  by setting the expected effect size at 0. 41 (estimated from  13  ), the significance level at 0. 05, and the desired power at 0. 95. All participants had normal or corrected-to-normal vision. They were right-handed as assessed by the Edinburgh Handedness Inventory  42  and naïve with regard to the purpose of the study. The protocol was approved by the ethic committee of the University of Leipzig and written informed consent was requested. The research was performed in accordance with relevant safety guidelines  43. Procedure and experimental design. The experiment followed a within-participants design, with the independent variables STROKING ("Synchronous/Self ", during synchronous stroking, see below, vs.
The optimal scalp position from which MEPs with maximal amplitude were elicited in both resting FDI and ADM muscles was detected by moving the coil over the left motor cortex while delivering TMS pulses at constant intensity. The stimulus intensity employed for spTMS stimulation was set at 120% of each subject's resting motor threshold (rMT) (mean of maximal stimulator output: rMT 75. 7 ± 7. 9% in the first day and 75. 2 ± 8. 1 in the 2nd day). The rMT is defined as the lowest stimulator output that evokes at least five of ten successive MEPs with amplitude greater than 50 μV in the relaxed FDI and ADM muscles. Analysis. The Skewness and Kurtosis values of the data (except the Kurtosis of the proprioceptive drift in the cTBS Synchronous condition in EB) were within the limits of ± 2 considered acceptable in order to prove normal univariate distribution  53.
Behavioural data. To assess the proprioceptive drift, we first computed the difference between the objective and the subjective localisation of the participant's index finger. Then, we subtracted the measure obtained before from that obtained after each condition to obtain the proprioceptive drift. The conditions were the following: TBS (cTBS and imTBS), BLOCK (IB and EB) and STROKING (Synchronous/Self and Asynchronous/Other). The resulting data were submitted to a non-parametric Friedman ANOVA. The mean agreement ratings to each of the first three statements in the RHI questionnaire were entered into a multivariate analysis of variances (MANOVA) with the within-participants variable TBS and STROKING, BLOCK and the three questionnaire items assessing the experience of ownership over the model's hand as dependent variables.
The overall number of excluded trials did not differ across conditions (oneway ANOVA F < 1; p = 0. 6). The average number of trials in each condition was 17. 9 ± 1. 7 (mean number of trials ± standard deviation), with a range from 13 to 20. The data were analysed using linear mixed models  54  implemented in the lme4 package  55  in R  56. We used deviation coding for each of our fixed effects. Our model included the fixed effects STROKING and TBS, and the interaction between them. The random effect in our model was participant id, with maximal random intercepts and slopes  57. Restricted maximum likelihood estimation was used to generate the model parameters. Degrees of freedom for the t-statistics were approximated using the Satterthwaite method. Follow up tests on the significant interaction effect were conducted using the emmeans package  58  with Bonferroni corrected p-values and the Kenward-Roger method to approximate degrees of freedom.
g. the cell surface) to selectively conduct ions (yellow), thus contributing to cellular functions. Only two of the four subunits are represented. In ref  [57] , Anap (red star) was introduced at the intra-cellular end of S1 (V234), close to S4, while a cysteine in the S3-S4 loop (A359) was labeled with TMR (green asterisks). Lower panel: Gating currents (I) and fluorescence responses (FAnap and FTMR) of TMR-labeled Shaker-V234Anap-A359C channels. From ref  [57]. The introduction of UAAs calls for high-level molecular precision. Hence, protein engineering using UAAs benefits from existing structural and molecular information, facilitating technical processes including mutagenesis, experimental design, and data interpretation. Prior investigating novel, poorly resolved domains, introduce the UAA at well characterized ion channel regulatory sites to gain first broad ideas about the efficiency of UAA incorporation, the resulting ion channel functional properties, and their behavior following optical modulation.
Research of authors is supported by the  French government  under the  program 'Investissements d'Avenir'  ( ANR-10-LABX-54   MEMO LIFE  and  ANR-11-IDEX-0001-02 PSL* Research University ), the  European Research Council  ( ERC Advanced Grant  # 693021  to PP), the  European Commission  ( Marie Sklodowska-Curie  fellowship  H2020-MSCA-IF-2015  Grant # 701467  to LM), and the  Deutsche Forschungsgemeinschaft  (DFG; postdoctoral fellowship # KL 2935/1-1  to VK).
Whether this signal integration Fig. 1  Calcium signal dynamics reveal differential astrocyte responses to PV and SST interneuron activation. a Schematic of the in vivo experimental approach (left) and of the optogenetic stimulation of ChR2-PV or ChR2-SST interneurons (right). b Top, images of a representative GCaMP6f-astrocyte in layer 2/3 SSCx from an adult ChR2-PV-GCaMP6f mouse with the ROIs defined by GECIquant software for the Ca 2+ response to the first 30 light pulse stimulation (blue lines) of PV interneurons at the soma (yellow), proximal processes (red), and microdomains (blue), scale bar, 20 μm (see Supplementary Movie 3). Bottom, Ca 2+ signal dynamics at different astrocytic compartments before and after successive 10 and 30 light pulse PV interneuron activations. Scale bars, 50 s, 20% dF/F 0.
Single-cell recordings were performed in voltage-or currentclamp configuration using a multiclamp 700B amplifier (Molecular Devices, USA). Signals were filtered at 1 kHz and sampled at 10 kHz with a Digidata 1440 s interface and pClamp 10 software (Molecular Devices). The pipette resistance was 3-4 MΩ. Access resistance was monitored throughout the recordings and was between 8. 4 and 24. 2 MΩ. Neurons that had a >15% change in access resistance were discarded. Whole-cell intracellular pipette solution was (in mM): 145 Kgluconate, 5 MgCl 2 , 0. 5 EGTA, 2 Na 2 ATP, 0. 2 Na 2 GTP, 10 HEPES, to pH 7. 2 with KOH, osmolarity, 280 ÷ 290 mOsm. Data were not corrected for the liquid junction potential. Recordings were analyzed with Clampfit 10. 3. Drug applications. Drugs applied to the slice perfusion solution were: SCH50911 (20-50 μM), CYN 154806 (20 μM), and somatostatin (SST, 1-2 μM) from Tocris (UK), Tetrodotoxin (1 μM), CGP52432 (20 μM), HC030031 (80 μM), NBQX (10 μM), APV (50 μM), MPEP (50 μM), PPADS (100 μM) from Abcam (UK).
Electrical signals were amplified by a Multiclamp 700B, low-pass filtered at 10 kHz, digitized at 50 kHz with a Digidata 1440 and acquired with pClamp 10 (Axon instruments, USA). Electrophysiological traces were analyzed using Clampfit 10 software. Pre-embedding electron microscopy. Three C57BL/6 (P21) mice were anesthetized with chloral hydrate (12% i. p. , 300 mg/kg) and perfused through the ascending aorta with physiological saline solution followed by a mixture of 4% paraformaldehyde (PFA) and 0. 2% glutaraldheyde in PBS. Brains were post-fixed in the same fixative used for perfusion for 3 days and parietal cortex was cut serially in the coronal plane (40 μm sections) with a vibratome and immediately processed for immunoperoxidase according to previous pre-embedding electron microscopy protocols  62.
Data analysis. Detection of astrocyte ROI containing Ca 2+ elevations was performed with ImageJ in a semi-automated manner using the GECIquant plugin  20. The software was used to identify ROIs corresponding first to the soma (>30 μm 2 ; confirmed by visual inspection), then to the proximal processes (>20 μm 2 and not corresponding to the soma) and finally to the microdomains (between 1 and 20 μm 2 corresponding to neither the soma nor the proximal processes). All pixels within each ROI were averaged to give a single time course F(t). Analysis of Ca 2+ signals was performed with ImageJ (NIH) and a custom software developed in MATLAB 7. 6. 0 R2008 A (Mathworks, Natick, MA, USA). To compare relative changes in fluorescence between different cells, we expressed the Ca 2+ signal for each ROI as dF/F 0 = (F(t) -F 0 )/(F 0 ).
Acknowledgements We are grateful to  T. Pozzan ,  S. Vicini , and  P. Magalhaes  for their valuable comments on the manuscript and discussions. We also thank  B. S. Khakh  and  R. Srinivasan  for help in the use of the GECIquant software. The work was supported by  Telethon Italy  Grant  GGP12265 ,  Cariparo Foundation, National Research Council Aging Project, Fondo per gli Investimenti della Ricerca di Base  Grant  RBAP11×42L ,  PRIN 2015-W2N883_001  and  Marie Skłodowska-Curie ITN ,  EU-GliaPhD  to G. C. ,  Istituto Italiano di Tecnologia, European Research Council  ( ERC, NEURO-PATTERNS ),  FP7-Health (DESIRE) , and  MIUR FIRB  ( RBAP11×42L ) to T. F. and  PRIN  ( 2010JFYFY2 ), INRCA intramural funds,  UNIVPM , and  Fondazione di Medicina Molecolare  to F. C.
DOI: https://doi. org/10. 7554/eLife. 32517. 003 (4,24) = 6. 6, p=0. 0010; CNO: Block, F(4,24) = 7. 4, p=0. 0005). Thus, responding was initially higher and then declined to comparable rates for both saline-and CNO-treated groups suggesting that the impairment in the CNO group was not the result of a performance deficit. Collectively, these data therefore suggest that the CNO treatment produced a mild deficit in the ability to update goal value representation and/or its use to guide behavior. Importantly, a consumption test performed immediately after the devaluation test confirmed the effectiveness of the sensory-specific satiety, which was left unaltered by CNO administration. That is, both saline-and CNO-treated rats preferably consumed the still valued outcome when they could freely select from the two outcomes (Devaluation (F (1,12) = 25.
A retractable lever (4 Â 1 Â 2 cm) could be inserted next to the magazine as did a 'tilt', a vertical rod hinged on the ceiling and terminated by a small plastic ball. Pressing the lever or pushing the tilt in any direction were therefore the two distinct actions that rats could perform during instrumental tasks. Activation of either the lever or the tilt produced the delivery of the associated outcome, as a function of the current procedure (i. e. FR1, RR5 or RR10, see below). A personal computer connected to the operant chambers and equipped with POLY software and interface (Imetronic, France) controlled the equipment and recorded the data.
Data analysis The data were submitted to ANOVAs on StatView software (SAS Institute Inc. ). For both experiments, Drug (saline/CNO) was the between subject factor, and Devaluation (Devalued/Non Devalued), Degradation (Degraded/Non degraded) and Session (averaged over both actions) were repeated measures when appropriate. The alpha value for rejection of the null hypothesis was 0. 05 throughout. Thus, altogether, these supplemental data confirmed that CNO treatment alone could not account for the effects observed in the main study.
Acknowledgements We thank  Angelique Fauge  `re and  Yoan Salafranque  for histological assistance and animal care. This work was supported by an  Independent Investigator NARSAD  grant # 27402  to MW and a grant from the  French agency for research   ANR-14-CE13-0014  to EC. FA was supported by a  BRAIN LabEx PhD extension grant. The microscopy was done in the  Bordeaux Imaging Center , a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure  France BioImaging , with help from  Christel Poujol  and  Sebastien Marais.
Funding Funder Grant reference number  Author Agence Nationale de la Recherche   ANR-14-CE13-0014   Etienne Coutureau Brain and Behavior Research Foundation   NARSAD Independent Investigator Grant #24702 Mathieu Wolff Labex Brain LABEX PhD Extension Grant 2015 Fabien Alcaraz The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
This aspect gives sense to the movement  (Bril and Goasdoué 2009, Bril 2015). To study and analyse motor variability, it is important to provide the means to give sense to a movement when planning it. It was with this objective in mind that the task analysed in this study was designed. The task involves collecting parts stored at floor-level, for their assembly with another part on a mounting table. A previous paper presented results from classical movement analysis performed on the same task  (Gilles et al. , 2017). This exhaustive analysis of the data provided us with an extensive range of information through which we could understand the physiological limitations involved in performing a task requiring squatting. These limitations were determined by the age of the person executing the task and/or the pace of the work.
Apparatus The postures adopted during repeated assembly cycles involving collection of parts from floor-level, were video recorded throughout the experimental sessions. 3D modelling of each assembly cycles was computed with Motion Inspector® software. Modelling was based on three superimposed models: i) an anthropometric model using 67 anthropometric measurements for each subject  (Hanavan, 1964) ; ii) an inverse dynamic model using the forces and moments exerted at ground-level, as recorded using an AMTI®-type force plate, and the forces and moments exerted on the assembly table, recorded using an ATI® sensor. All dynamic signals were recorded at a frequency of 200 Hz. iii) a kinematic model using the displacement of 37 passive markers -placed on the subject in relation to anatomical landmarks -measured at a frequency of 50 Hz using an optoelectronic system (Vicon 460®).
Statistical analysis All statistical analyses were carried out using Stata software (StataCorp LLC, Tx). The first objective of the analysis was to identify postural strategies. An agglomerative hierarchical clustering method based on the Euclidean distance was performed. This clustering algorithm was based on 17 variables after normalisation of each variable, using a complete linkage algorithm that is using the farthest pair of observations between two groups to determine the proximity of the two groups. This normalisation consisted in substracting from each variable its overall mean and dividing by the overall standard deviation. This classification aims to identify, from all the recordings analysed, the different categories of movement used when collecting parts. The strategies were characterised by a side-toside box plot of the 17 variables on which they were based.
Module-Related Differences in Purkinje Cell Physiology One of the first proteins to receive attention in this respect was excitatory amino acid transporter 4, EAAT4, which is expressed in Purkinje cells (PCs) in pattern similar to zebrin II (ZII)  [130]. In ZII+ PCs, the synaptic transport current is several fold larger than in ZII-PCs  [14]. Due to the absence of EAAT4, mGluR1 (metabotropic glutamate receptor 1) currents are larger and mGluR1-dependent long-term depression (LTD) is more likely to occur in ZII-PCs. Conversely, longterm potentiation (LTP) could be induced selectively in patches of ZII+ PCs using high-frequency stimulation of parallel fibers in vivo  [15] , which will be described in the next section. Interestingly, in another dataset, the climbing fiber evoked EPSCs and complex spikes in ZII+ PCs were found to be larger despite the presence of more EAAT4, suggesting that climbing fibers also participate in the modular differentiation  [131].
Acknowledgements RH thanks  Boris Barbour  and  Chris Yeo  for advice on an earlier draft. Funding Information Sugihara was supported by  JSPS  regrant ( 16K070025 ). Wylie was supported by funding from the  Canadian Institutes for Health Research (CIHR)  and the  Natural Sciences and Engineering Research Council of Canada (NSERC). Sillitoe was supported by from  Baylor College of Medicine (BCM)  and  Children's Hospital (TCH). R. V. S. received support from  BCM IDDRC  grant  U54HD083092  ( Neurovisualization Core ), the  National Institutes of Neurological Disorders and Stroke (NINDS)   R01NS089664 , and the  Hamill Foundation. A. M. B. received support from  NINDS   F31NS101891. Schonewille was supported by the  Erasmus MC Rotterdam , the  Dutch Scientific Organization Veni (NWO-ALW Veni) , and the  European Research Counsil Starting Grant  ( ERC-Stg ,  680235 ).
Ebner was supported in part by  NIH  grant  R01 NS18338. Isope was supported by the  CNRS ,  Université de Strasbourg , the  Agence Nationale de la Recherche  (Grant  N°ANR-15-CE37-0001-01 ), and by the  Fondation pour la Recherche Medicale  (Grant  N°D EQ20140329514 ). Ruigrok was supported by the  Erasmus MC Rotterdam  and the  Dutch Ministry of Health , Welfare and Sports (T. R. ), and  JSPS   Institutional Program for Young Researcher Overseas Visits  (S. A. ). Apps was supported by the  Biotechnology and Biological Sciences Research Council (BBSRC, UK ).
Materials and Methods Experimental data set. Experimental task. Participants: Thirty-eight healthy young adults without known neuromuscular disease and with normal or corrected-to-normal vision participated in the experiment (17 females, 27. 7 ± 5. 1 years old, 68. 7 ± 12. 7 kg, 72. 1 ± 4. 8 cm of fully-extended arm's length; mean ± std values). The experimental protocol was approved by the Univ. Paris-Sud EA 4532 local Ethics Committee and conformed to relevant guidelines and regulations. Written informed consent was obtained from each participant in the study as required by the Helsinki declaration. All the participants were naive to the purpose of the experiment. Motor task: Participants performed visually-guided single-joint arm movements in the horizontal plane with their arm fully extended (rotation around the shoulder joint with their dominant arm).