dataesr/scientific-paragraphs-categorization huggingface dataset:
(N=308, after QC N=294): The images from the International Consortium for Brain Mapping (ICBM) dataset (http://www. loni. usc. edu/ICBM/) used in this study consist of 308 normal subjects obtained through the LONI website. The MRI are T1-weighted MPRAGE (fast field echo, TR = 17 ms, TE = 10 ms, flip angle = 30 °, 256×256 matrix, 1 mm 2 in plane resolution, 1 mm thick slices) acquired on a 1. 5T Philips GyroScan imaging system (Philips Medical Systems, Best, The Netherlands). • OASIS (N=315, after QC N=298): The images from the Open Access Series of Imaging Studies (OASIS) database (http://www. oasis-brains. org) used in this study consist of 315 control subjects. The MRI are T1-weighted MPRAGE image (TR = 9. 7 ms, TE = 4 ms, TI = 20 ms, flip angle = 10 degrees, slice thickness = 1. 25 mm, matrix size = 256×256, voxel dimensions = 1×1×1.
(N=588, after QC N=573): The images from the Information eXtraction from Images (IXI) database (http://brain-development. org/ixi-dataset/ ) used in this study consist of 588 normal subjects. The MRI are T1weighted images collected at 3 sites with 1. 5 and 3T scanners (FoV = 256 mm × 256 mm, matrix size = 0. 9375 × 0. 9375 × 1. 2 mm 3 ). • ADNI1 (.
N=228, after QC N=223): The images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://adni. loni. usc. edu ) used in this study consist of 228 control subjects from the 1. 5T baseline collection. These images were acquired on 1. 5T MR scanners at 60 different sites across the United States and Canada. A standardized MRI protocol to ensure cross-site comparability was used. Typical MRI are 3D sagittal MPRAGE (repetition time (TR): 2400 ms, minimum full TE, inversion time (TI): 1000 ms, flip angle: 8°, 24 cm field of view, and a 192×192×166 acquisition matrix in the x-, y-, and z- dimensions, yielding a voxel size of 1. 25×1. 25×1. 2 mm 3 , later reconstructed to get 1 mm 3 isotropic voxel resolution). • ADNI2.
(N=213): The images from the ADNI2 database (second phase of the ADNI project) consist of 215 control subjects. Images were acquired on 3T MR scanners with the standardized ADNI-2 protocol, available online (www. loni. usc. edu). Typical MRI are T1-weighted 3D MPRAGE sequence (repetition time 2300 ms, echo time 2. 98 ms, flip angle 9°, field of view 256 mm, resolution 1. 1 x 1. 1 x 1. 2 mm 3 ). • AIBL (N=233): The Australian Imaging, Biomarkers and Lifestyle (AIBL) database (http://www. aibl. csiro. au/) used in this study consists of 236 control subjects. The imaging protocol was defined to follow ADNI's guideline on the 3T scanner (http://adni. loni. ucla. edu/research/protocols/mri-protocols) and a custom MPRAGE sequence was used on the 1. 5T scanner.
The research was conducted according to the guidelines of the Declaration of Helsinki. It was preliminarily approved by the local ethics committee of the Department of Psychology, Catholic University of Milan. The project was approved in its final version. The data files were stored in the Department repository, as requested by the local ethics committee. The legal responsibility for the data custody is entrusted to the Department Director, who can be contacted to receive a copy of the data. No payment was provided for the subjects' performance, and they provided their consent to participate in the research.
The following channels were reported: Ch 1 (FC3-F3) and Ch 3 (FC4-F4) correspond to the left and right (respectively) DLPFC (Brodmann Area 9). Ch 2 (FC3-FC1) and Ch 4 (FC4-FC2) correspond to the left and right (respectively) Dorsal Pre-motor Cortex (DPMC, Brodmann Area 6). Ch 5 (F1-F3) and Ch 7 (F2-F4) corresponding to the left and right (respectively) Frontal Eye Fields (FEF, Brodmann Area 8). Ch 6 (F1-FC1) and Ch 8 (F2-FC2) correspond to the left and right (respectively) Superior Frontal Gyrus (SFG, Brodmann Area 6)  [27]. Changes in the concentration of oxygenated (O2Hb) and deoxygenated hemoglobin (HHb) were recorded continuously throughout the task with NIRStar Acquisition Software that started from a 120-s resting baseline. Signals obtained from the 8 NIRS channels were acquired with a sampling rate of 6.
In line with this view, the report from Neumann and colleagues offers exciting new data that nicely complete the seizure generation puzzle. Neumann and colleagues performed extracellular local field potential (LFP) and single unit recordings in the dorsal CA1 region of the hippocampus in chronically epileptic rats. Like several groups before them, they used the characteristic extracellular waveform shapes to identify putative interneurons and pyramidal cells. What distinguishes this study from others is the ability to record large number of neurons at the same time, also during seizures. Two major findings can be extracted from this study. The first is that ictal discharges are dominated by the activity of fast-spiking, putative inhibitory neurons rather than pyramidal cells. Importantly, these interneurons displayed unusually strong coupling to oscillations in the LFP, even before seizures.
Robust α-β coupling during time production Ahead of PAC calculation, we assessed the power spectrum during the timed interval (from 0. 4 to 1. 2 s following R1 to avoid evoked responses) by averaging the PSD across all sensors, conditions and individuals. Two peaks were readily visible in the spectrum at α (~10 Hz) and β (~25 Hz) frequencies, suggesting the existence of two plausible regimes for oscillatory multiplexing (Fig. S1A ). The α PSD was mainly localized in occipital and parietal regions (Fig. S1B ). To assess whether any form of PAC was present during interval production, we computed the modulation index (MI) in this same interval  (Tort et al. , 2009). Visual inspection of grand average data across all individuals and sensors revealed a strong MI between the α phase and the β power in centro-parietal sensors (Fig.
α-β coupling is specific to the interval being timed Although we showed that α-β coupling was present during the production of temporal intervals, one may argue that the observed coupling was strictly relevant to motor preparation as opposed to timing. To test this, we capitalized on our experimental design, which required that participants self-initiate their time productions. As participants volitionally initiated their first button press (R1) with no explicit time requirement or pressure, we used the data ranging from -0. 8 s to R1 as control for motor preparation. We specifically tested whether the MI during the production of the time interval was significantly increased compared to baseline (before R1). A cluster-based permutation t-test on comodulograms averaged across the selected sensors and across participants showed that α-β PAC was significantly larger during time production than during the volitional trial initiation (P = 0.
Participants Nineteen right-handed volunteers (11 females, mean age: 24 years old) with no selfreported hearing/vision loss or neurological pathology took part in the experiment and received monetary compensation for participation. Each participant provided a written informed consent in accordance with the Declaration of Helsinki (  2008 ) and the Ethics Committee on Human Research at Neurospin (Gif-sur-Yvette). The data of seven participants could not be included in the analysis due to the absence of anatomical MRI, problems with head positioning system, abnormal artifacts during MEG recordings, and two participants not finishing the experiment. These datasets were excluded a priori and were not visualized or inspected. Hence, the final sample comprised twelve participants (7 females, mean age: 24).
MEG and EEG recordings were sampled at 1 kHz and band-pass filtered between 0. 03 Hz and 330 Hz. The electro-occulograms (EOG, horizontal and vertical eye movements), -cardiograms (ECG), and -myograms (EMG) were simultaneously recorded. Feedback was presented using a PC running Psychtoolbox software  (Brainard, 1997)  in MATLAB (R2012, The Mathworks).
Phase amplitude coupling calculation and statistical assessment In order to prevent the contamination of the timed interval from evoked responses, we solely focused on the time segment from 0. 4 s to 1. 2 s following R1. PAC was assessed using the Modulation Index or MI  (Tort et al. , 2009) , namely: raw data were band-pass filtered (slow-frequency bandwidth = 2 Hz, high-frequency bandwidth = 20 Hz); the instantaneous amplitude of the high-frequency and the phase of the slow-frequency were extracted from the Hilbert transform applied to the epoch data. To assess whether the distributions diverged from uniformity, the Kullback-Leibler (KL) distance was calculated then normalized to give the MI. The KL distance was estimated between histograms with 18 bins. The slow-frequency component ranged from 3.
M/EEG-aMRI coregistration Anatomical Magnetic Resonance Imaging (aMRI) was used to provide high-resolution structural images of each individual's brain. The anatomical MRI was recorded using a 3-T Siemens Trio MRI scanner. Parameters of the sequence were: voxel size: 1. 0 x 1. 0 x 1. 1 mm; acquisition time: 466s; repetition time TR = 2300 ms; and echo time TE= 2. 98 ms. Volumetric segmentation of participants' anatomical MRI and cortical surface reconstruction was performed with the FreeSurfer software (http://surfer. nmr. mgh. harvard. edu/). A multiecho FLASH pulse sequence with two flip angles (5 and 30 degrees) was also acquired  (Fischl et al. , 2004; Jovicich et al. , 2006)  to improve co-registration between EEG and aMRI. These procedures were used for group analysis with the MNE software  (Gramfort et al.
Precision has been computed as coefficient of variation over TP on a per block and participant basis, whereas accuracy has been calculated as by subtracting mean TP from the target duration in a given block. Note that in the first three blocks target duration was 1. 45, however it has been dynamically assigned in the blocks from four to six. Sensor level analyses were performed using linear regression and model comparison framework to check if other factor other than PAC were needed to explain behavior. All statistical analyses have been performed in R v3. 3. 2 statistical programming language (R Development  Core 2008). For illustrative purposes, correlations in the source space were computed using Spearman correlations. Byesian ANOVA  (Rouder et al. , 2012)  was performed using BayesFactor R package.
Calculating precision and accuracy metrics and accounting for inflated degrees of freedom. Precision was quantified by the Coefficient of Variation (CV): the CV were calculated by dividing the standard deviation by the mean duration production. Accuracy was quantified by Error Ratio (ER): ER was calculated by dividing the mean temporal production in a given set of data by the target interval in that set. Both metrics were computed separately per block and per participant. As splitting the data per block and per individual could inflate the degrees of freedom, we accounted for this in our analysis by assessing the impact of block factor in the overall model fit by model comparison approach. In none of the analyses, the block factor altered the main effects and this is systematically and explicitly reported in our Results section when relevant.
This work was supported by the  Paris-Saclay IDEX NoTime  to V. D. , A. G. and V. vW, the  ERC Starting  Grant  MINDTIME ERC-YStG-263584  grant to V. vW, the  ERC Starting  Grant  SLAB ERC-YStG-676943  to A. G. , and the  ANR-16-CE37-0004-04 AutoTime  to V. D. and V. vW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Preliminary results of this work were presented at the  International Cognitive Neuroscience workshop (Amsterdam, Netherlands ,.
Magnetic resonance imaging (MRI) analysis MRI analyses were performed on 1, 3, 7, 14 and 21 days post-injection. Experiments were carried out on a Pharmascan 7 T MRI (Bruker, Germany). T2-weighted images were acquired using a multislice/multiecho sequence: TE/ TR 12. 7 ms/2500 ms and a flip angle of 180°with spatial resolution of 70 μm*70 μm and slice thickness 350 μm interpolated to an isotropic resolution of 70 μm (acquisition time = 8 min). Lesion sizes were quantified on these images by an experimenter blinded to the genotype using ImageJ (NIH software v1. 49e, National Institute of Health, Bethesda, MD, USA). Immunohistochemistry 1, 3, 7, 14 and 21 days post-injection mice were deeply anesthetized and perfused transcardially with 20 ml of cold heparinized NaCl 0. 9%, followed by 2% paraformaldehyde and 0.
After 24 h, cells were fixed with 4% paraformaldehyde (PFA; for 10 min at RT), washed 3 times with phosphate buffer saline (PBS, pH 7. 4) and the non-migratory cells on the upper membrane surface were removed with a cotton swab. The presence of transmigrated OPCs in the lower chamber was evaluated by immunostaining with Olig2 antibody (1:200, AB9610 Millipore) and its corresponding fluorescent secondary antibody. After immunostaining, the Boyden filters were examined and images were digitally captured using a Leica DM6000 microscope-coupled coolsnap camera and visualized with Metamorph 5. 0 software (Molecular Devices). To quantify chemokinesis, 16 fields per well (×20 objective) taken randomly were photographed and the number of transmigrated OPCs per field was counted using ImageJ 1. 49e software (NIH).
Funding This work was supported by the  French Insitut National de la Santé et de la Recherche Médicale (Inserm) , the  Fondation pour la recherche médicale (FRM) , the  Spanish Ministerio de Economía y Competitividad-MINECO  (grants  SAF2012-40023 ,  RD12-0032-12  and  PI15/00963 , partially funded by F. E. D. E. R. ) and Association française de recherche sur la sclérose en plaques (ARSEP foundation). CL and AF were funded by the  Conseil regional de Normandie. MP was funded by fellowships from the  French Ministère de la recherche et de  l'enseignement supérieur and from  FRM.
Ablation of axons were performed in OPs of 20 s wild-type embryos injected with ngn1:gfp DNA to obtain mosaic GFP expression. The conditions of ablation (microscope, laser power, frequence) for cells and axons were similar to those used for severing cell/cell contacts. Image analysis. Individual cells were tracked in 3D using the Manual Tracking plugin in ImageJ. The orientation of the movement represents the angle between the cell track and the AP axis, as shown in Supplementary Fig. 4c. 3D MSD analysis was performed with the MSD analyser tool in MATLAB  62. Plots representing cell tracks merged at their origin were produced with the DiPer program  63. Rose plots and 3D cell trajectories were generated in MATLAB. 3D counting of nuclei and 3D cell reconstruction analysis were achieved in ImageJ with the 3D ImageJ suite  64  and the 3D Object Counter plugin  65.
Analysis of the correlation between tracks was performed using MATLAB. For each pair of tracks we computed the two-dimensional correlation coefficient as follows: For t-tests exact p values are indicated in the figures. Welch's correction was applied when standard deviations were not equal. We did not check for normality before performing parametric tests (t-tests), but a non-parametric Mann-Whitney test was carried out in parallel on all data sets and led to the same conclusions than t-tests. No statistical method was used to estimate sample size and no randomisation was performed. Blinding was performed for the analysis of laser ablation experiments (see Laser ablation section in the Methods).
Acknowledgements This work was funded by the  Agence Nationale pour la Recherche  ( ANR  blanc project  11-BSV2-0006  to S. S. M. ), the  Fondation pour la Recherche Médicale (Equipe FRM   DEQ20140329544  to S. S. M. ), the  'Association pour la Recherche sur le Cancer' (ARC ,  PJA 20131200051  grant to M. A. B. ), the  Centre National pour la Recherche Scientifique (CNRS 'Défi mécanobiologie'  grant to M. A. B. ) and  Sorbonne Universités  ( Emergence 2016  grant to M. A. B. ,  SU-16-R-EMR-11 ). M. A. B. was supported by a postdoctoral fellowship from the  FRM. I. B. belongs to the  CNRS research consortium (GdR) 'CellTiss'. We also thank  PICT-IBiSA  of the UMR3215 and the imaging platform of the IBPS for assistance with microscopy, the IBPS aquatic platform for fish care,  P. Marcq  and  F.
These bouts were presented in random order. Once the subjects reached the target pedaling frequency (typically after ∼1-2 s), data were collected continuously for 10 s. Both tests were performed at 90 ± 5 RPM. Surface EMGs were recorded from nine muscles on the right side of the body: 1) tibialis anterior (TA); 2) soleus (Sol); 3) gastrocnemuis medialis (GM); 4) vastus laterali (VL); 5) vastus medialis (VM); 6) rectus femoris (RF); 7) biceps femori (BF); 8) semitendinosus (ST); and 9) gluteus maximus (Gmax). Prior to electrode application, the skin was shaved and cleaned with alcohol. The electrodes were active parallel bar sensors (Delsys DE 2. 1 type, Delsys Inc, Boston, MA, USA; 1 cm interelectrode distance) and were placed in the middle of the muscle belly, longitudinally with respect to the underlying muscle fibers (as recommended by the SENIAM project-Surface Electromyography for the Non-Invasive Assessment of Muscles  22  ).
Muscle synergy extractions were performed by non-negative matrix factorization using an implementation of the Lee and Seung algorithm. 25 At each iteration of the algorithm, the synergy vectors were normalized by their norm. Synergies were extracted separately for each position and included all power output conditions, insuring that substantial motor variability was present. 26 he variance accounted for (VAF) was computed as: VAF = 1 -SSE/SST where SSE is the sum of squared residuals between the actual EMG data and its decomposition, and SST the total sum of the squared values. The number of synergies was defined as the smallest number explaining at least 90% of the total data variance and at least 75% of each muscle VAF. 17 ormality of the data was checked using Shapiro-Wilk's tests. Repeated measures ANOVAs with position = seated or standing and power output = 20-120% (in 20% increments) as repeated measures were used to analyze iEMGs.
In silico binding model To explore the possible binding modes of compounds 12a-b, 19a-b and 21a-b, each compound was docked into the crystal structure of mGlu 5 (PDB id 4OO9, minus its mavoglurant co-crystallized ligand). For each respective docking, the top-ranked protein-ligand complex was energy-minimized to optimize intermolecular interactions. From the results shown in Figure  4 , the 1,3-compounds are able to bind at the bottom of the allosteric pocket because their structures are easily accommodated within the distinctive angular binding-site, displaying a similar binding pose to the previously cocrystallized mGlu 5 NAMs: mavoglurant (in PDB id 4OO9  [26] ) and HTL14242 (in PDB id 5CGD  [37] ). In doing so, each 1,3-compound achieves a favourable docking score (Table  2 ), making an H-bond with S809 on TM7 (after energy minimization), and in the case of 19a and 21a, an additional H-bond with N747 on TM5.
However, the 1,4compounds are unable to bind at the bottom of the allosteric pocket (at least in the mGlu 5 crystal structure of PDB id 4OO9), as they are unable to accommodate their structures within the angular binding-site. Instead, they bind higher in the pocket with a pose similar to that observed with the co-crystallized ligand FITM in the crystal structure of mGlu 1 (PDB id: 4OR2  [38] ). As a result of this higher binding pose, the 1,4compounds achieve much less favourable docking scores (Table  3 ) and are unable to make an H-bond with S809 on TM7 or any other residue in the allosteric pocket. Although this higher binding pose is apparently functional in terms of mGlu 1 allosterism, it is unlikely to be functional in mGlu 5 , as reflected by the low docking scores observed here (indicating a poor fit) and by experimental data (including current mGlu 5 crystal structures)  [26, 37] , which suggests S809 interaction is critical for correct mGlu 5 NAM functionality  [35].
A B C identify better binding poses at the bottom of the allosteric pocket (more similar in nature to current co-crystallized mGlu 5 NAMs). This alternative receptor conformation was derived from the original mGlu 5 crystal structure (PDB id 4OO9) through computational conformational sampling performed previously  [33]. This process results in a relatively subtle adjustment of side-chain packing between TM6 and TM7 but, more significantly, an enlargement and alteration of the binding pocket from an angular shape to a wider linear shape. Using this alternative receptor conformation, the 1,4compounds instead dock at the bottom of the allosteric pocket, making an H-bond with S809 on TM7 (Figure  5 ), the residue designated as important for interaction with mGlu 5 NAMs  [35] , and packing against hydrophobic residues on TM5 (e.
g. L744) and TM6. In accordance with this changed binding-mode, the docking scores of the 1,4-compounds are improved compared to the previous dockings in the original crystal structure (PDB id 4OO9) (Table  2 ). However, it should be noted that this alternative receptor conformation is perhaps not as readily accessible in energetic terms as the original crystal structure conformation, potentially affecting the pharmacological activity of the 1,4-compounds.
The mobile phase used was a mixture of A = NH 4 HCO 3 aqueous buffer 10 mM pH=7. 4 and B = acetonitrile (AcN) with the method described as follows: flow 0. 3 mL/min, 5%B-100%B 3 min, 100%B 5 min, total runtime 15 min; purity is given as % of absorbance of the cis and trans isomers at 254 nm; UV-Vis spectra were collected every 0. 2 s between 650 and 275 nm and bands are % of maximal absorbance; data from mass spectra were analysed by electrospray ionization in positive and negative mode every 0. 3 s between 50 and 1000 Da and peaks are given m/z (% of basis peak). High-resolution mass spectra (HRMS) and elemental composition were analysed by FIA (flux injected analysis) with ultra-high performance liquid chromatography (UPLC) Aquity (Waters) coupled to LCT Premier orthogonal accelerated time of flight mass spectrometer (TOF) (Waters).
To allow stimulation in both dark conditions and violet light illumination, two-thirds of the 96-well plate bottom was covered with aluminium foil. To avoid effects derived from the fast relaxation of azocompounds in aqueous solution after the 30-min stimulation, we washed cells once in stimulation buffer alone before continuing with the lysis step of the assay protocol. For fluorescence readings with a RUBYstar HTRF HTS microplate reader (BMG Labtech), we transferred cell lysates to a black opaque-bottom 96-well plate. Dose-response data from IP accumulation assays were first normalized by the dose-response to reference allosteric modulator fenobam in both dark and illuminated conditions and then fitted with a standard Hill equation using GraphPad Prism version 6. 0.
Computational The molecular structures of six compounds: 12a-b, 19a-b, 21a-b in trans-isomer state were constructed with Maestro version 9. 8 (Schrӧdinger Release 2014). Each compound was docked into the transmembrane domain crystal structure of mGlu 5 (PDB id 4OO9, minus co-crystallized mavoglurant) using AutoDock4. 2 with default parameters  [45]. For each respective docked compound, the top-ranked complex (according to AutoDock docking score) was energy-minimized in the Amber14SB force-field  [46]  using CHIMERA  [47]  to optimize protein-ligand interactions. The three linear 1,4-compounds in trans-isomer state: 12b, 19b and 21b were also docked (using same parameters) into an alternative mGlu 5 receptor conformation, previously derived from the mGlu 5 crystal structure (PDB id 4OO9) by using a conformational sampling technique  [33].