dataesr/scientific-paragraphs-categorization huggingface dataset:
We also excluded individuals experiencing substance abuse or dependence (alcohol and other drugs), which is not uncommon in the student population and can affect ANS activity and emotion processing  [48, 49]. Modules J and K from the Mini International Neuropsychiatric Interview (MINI) were used to assess these disorders and information on the risks as well as a specialized service were provided. The final exclusion criterion was the presence of Post-Traumatic Stress Disorder (PTSD) because the elicitation procedure uses films that could relate to traumatic events and trigger flashbacks  [50]. We used module I from the MINI and found no participants suffering from PTSD. Among the 70 participants, seven had to be excluded because of technical problems that made the physiological data unusable.
Instruments Emotional videos. In the present study, anger was selected from different basic emotions for several reasons: (a) it is one of the emotions most often investigated  [13] , (b) it is a basic emotion whose recognition is independent of cultural differences  [51, 52] ; (c) it is linked to interpersonal interactions, which facilitates its use in the laboratory; and (d) it engages emotion regulation strategies  [53]. We first selected a video from the FilmStim database [54] because its elicitation properties were known. The FilmStim database consists of 64 film excerpts selected by 50 experts and rated on multiple dimensions by 364 undergraduate students. Ratings included the PANAS scales  [55]  and a 7-point scale of subjective emotional arousal  [56, 57]. We selected video number 5 (code 15): a 93-sec excerpt from the film American History X  [58] , predominantly categorized as eliciting anger with a high arousal score (5.
84/7) and the maximum negative affect score among databases (2. 73/5). Although this clip has good qualities for our experiment, we wanted to add a more ecological stimulus to our video set, even if it had not been previously tested. The FilmStim database contains only film excerpts performed by actors, which could diminish elicitation in people with emotion regulation difficulties  [59]. So, we first reviewed a dozen videos available on the web and selected two: a 69-sec video showing a real fight between two people and a 60-sec public service advertising campaign by the Department of the Environment in Northern Ireland and the Republic of Ireland's Road Safety Authority named The Faster the Speed, the Bigger the Mess (viewable for example: http://www. youtube. com/watch?v = Lw8GPiiOCpI).
Physiological data analysis All data processing was performed off-line using a commercial software package (MATLAB R2009b, The MathWorks Inc. , Natick, MA, 2000). EDA measurements were low-pass filtered by a zero-phase digital filter with a -3 dB cut-off frequency of 1 Hz. SCL was partitioned and averaged into 80-sec epochs for baseline and recovery. Regarding cardiovascular measurements, the ECG signal was band-pass filtered at 0. 5 and 35 Hz with a notch filter set at 50 Hz in BIOPAC acquisition software. The R-R intervals were calculated with BIOPAC software and then corrected with a visual examination by an experimenter who was blinded to the experimental hypotheses. HR was averaged for each period. For HRV quantification, we referred to HRV guidelines  [67, 68]  as well as the Kubios software user's guide  [69].
Assessment of the model quality relates to: (a) the adjustment of the MVs to their respective LV by examining the unidimensionality of each LV with Dillon-Goldstein's rho (DG-rho) and crossloading (loadings of an MV with the other LV); (b) the proportion of explained variance between LVs, with the R 2 determination coefficient. Moreover, a global criterion to evaluate the general performance of the model is given by a pseudo Goodness of Fit index (GoF). It is usually interpreted as the prediction power of the model but there is no threshold to enable its statistical significance to be determined and no guidance about what number could be considered a good GoF value  [72]. For this part, we used the plspm package  [74]  (version 0. 4. 1) available from R software  [75]  (version 3. 0. 2).
This work was supported by a grant from the  French Ministry of Research  (program "Investments for the Future") and managed by the  French National Research Agency  under the reference  ANR-11-EQPX-0023 , as well as by European funds through the program  FEDER SCV-IrDIVE. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Results VSD Imaging on the Single-Trial and Trial-Averaged Level. For the experiments analysed in this study, the primary and secondary visual areas (V1 and V2) of the macaque monkey were imaged under spontaneous and stimulus-evoked conditions. The recording chamber was positioned over an area spanning portions of these cortical areas (18 mm diameter, Fig. 1a ; see Methods). Stimulation with a short (50 ms), small Gaussian blob evoked a fast response, which peaked within 50-100 ms after stimulus onset (Fig. 1b , mean±s. d. ). Noting the temporal characteristics, we selected a frequency band encompassing this fast response (5-20 Hz) for all further analysis. Figure  1c  illustrates the difference between the single-trial and trial-averaged level in these data. Smoothed surface plots of the stimulus-evoked VSD responses in three trials are plotted alongside the trial-averaged data (animations available online as Supplementary Movies 1-4).
Data were Z-scored via standard methods for further analysis. Temporal filtering. Temporal filtering was carried out with an 8th-order digital Butterworth filter, forward-reverse in time to prevent phase distortion (see MATLAB function filtfilt). The cutoff frequencies were 5 and 20 Hz, unless otherwise noted. All results were checked with multiple cutoff frequencies to ensure against parametric sensitivity. Phase-latency maps. In the analytic signal framework, a real-valued, narrowband time series is transformed into a phasor rotating in the complex plane. After selecting an appropriate temporal point within the oscillation cycle and before the phase crossing threshold ( þ 72. 7 ms for all panels in Fig. 4 ), we look for the temporal latency to a given phase crossing (throughout this work, 0/2p) at each channel in the unsmoothed, temporally filtered data.
For these simulations, we used the PyNN interface  66  to the NEST simulation environment  67  , with a standard IF neuron model and conductancebased alpha-function synaptic inputs (IF_cond_alpha). The relevant parameters for the cells and the network are given in Supplementary Table  1. All other parameters for the model neurons may be found in the PyNN documentation (http:// www. neuralensemble. org/docs/PyNN/standardmodels. html). To deliver a stimulus to the middle 100 excitatory neurons in the network, we used the Gaussian pulse packet module in NEST (pulsepacket_generator), which distributes N sp spikes to each target neuron, following a Gaussian distribution in time, with parameters m sp and s sp. As mentioned in the main text, the pulse packet stimulus ignites a wave of subthreshold activity, that is, only 10-20% of spikes in the network occur outside the stimulation zone.
Acknowledgements We are grateful to  T. Movshon  and  Y. Fre  ´gnac for helpful comments on the manuscript;  I. Balansard  for veterinarian assistance;  S. Takerkart  for help with the linear model;  A. De Moya ,  X. De Giovanni ,  M. Martin  and  J. Baurberg  for excellent technical support; and  Q. Montardy  for help with some experiments. This work was supported by  CNRS ,  ANR  ( Complex-V1 ) and the  European Community  ( FET grants   FACETS FP6-015879  and  BrainScaleS FP7-269921 ). L. M. is a PhD fellow from  E ´cole des Neurosciences de Paris (ENP). A. R. was supported by  FACETS  and  Fondation des Aveugles et Handicapes Visuels de France.
Retrospective analysis of gene array datasets of the striatum of HD patients and transgenic mouse models of HD confirms that Crym mRNA levels are reduced in HD  (31, 32). Thus, it is possible that Crym may be involved in striatal vulnerability through two possible ways: reduction of Crym expression could be a causal event leading to death/dysfunction, pointing to Crym as a neuroprotective/pro-survival protein. On the opposite, decreased expression of Crym in HD could be a regulatory/compensatory mechanism, if the presence Crym (like Rhes for instance) contributes to the vulnerability of striatal neurons. The objective of the present study was to investigate whether the levels of Crym expression in the mouse striatum could change the toxicity of mHtt. We first characterized the enrichment of the protein Crym in the striatum in mouse, rat and cynomolgus monkey.
Mice were N3 (B6) on a 129 Sv × C57BL/6 J background. The resulting different genotypes were used for the present study. At this age, homozygous and heterozygous KI140 mice showed no major striatal atrophy, although these animals had motor deficits (Rotarod, CAtWalk and open field) (data not shown). Genotyping was determined from PCR of tail snips taken at 10-15 days of age for BACHD and KI140 mice.
Quantitative histological evaluation The area of the striatal lesions resulting from LV-Htt171-82Q infection was delineated manually by identifying the border of the lesion (loss of DARPP-32 and NeuN immunolabeling). Lesion area was delineated using ×5 and ×10 objectives. Depending on the antero-posterior extension of the lesions, 3-8 coronal sections were analyzed for each mouse. Observation of sections and calculation of the surface of lesioned area were performed using a Leica DM6000 equipped with a motorized stage and an automated image acquisition and analysis system (Mercator software, Explora Nova, La Rochelle, France). The volume of the striatal lesion (V) was determined using the Cavalieri method  (34, 36, 38). The number of ubiquitin-positive inclusions was quantified as previously described  (34, 36, 38)  with the following modifications: the intersection distance was 320 μm (i.
Funding This work was supported by the ' Commissariat à l'Energie Atomique et aux Energies Alternatives' (CEA)  and  'Centre National de la Recherche Scientifique' (CNRS). L. G. was supported by the  Neuropôle de Recherche Francilien  and the  Fondation pour la Recherche Médicale. L. F. was supported by the  French Research Ministry. The research leading to these results has received funding from the  European Community 's  Seventh Framework Program   FP7/2007-2013  under grant agreement no. HEALTH-F5-2008-222925. We also received financial support from the  IMA-GEN European  integrated project ( EUR617037286 ). Funding to pay the Open Access publication charges for this article was provided by the  Centre National de la Recherche Scientifique (CNRS).
Imaging data acquisition Brain MRI studies were performed using a 1. 5 T imager (GE Healthcare, Milwaukee, WI, USA). Diffusion, FLAIR T2, T2*-weighted GRE sequences and high-resolution T1-weighted 3D MRI volumes were acquired for all subjects before and after the gadolinium administration (Gadobenate dimeglumine, Bracco imaging®, Ceriano Laghetto, Italy). FLAIR T2-weighted and diffusion-weighted images showed the extent of cerebral infarction, whereas the T1-weighted SPGR image was used to allow co-registration with the PET images. After the gadolinium injection, axial volumetric T1 acquisition was performed to clarify the extent of the BBB breakdown. PET studies were performed using a Dual Gemini (Philips Medical Systems, Amsterdam, the Netherlands), a whole-body hybrid PET/CT scanner with a full-widthhalf-maximum (FWHM) resolution of 5 mm in all directions, in 3D acquisition mode.
To perform attenuation correction, a low dose CT helical scan was done (scan field, 600 mm; increments, 5 mm; slice thickness, 3. 2 mm; pitch, 1. 5, 0. 75 second per rotation; 512 × 512 matrix; 120 kV; 80 mAs). Acquisition data were reconstructed with the standard package included with the system (PET view software-Philips Medical Systems). PET sinograms were corrected for tissue attenuation, decay, scatter, and random radiation, and then they were reconstructed using a 3D iterative RAMLA algorithm in voxels of 2 × 2 × 2 mm 3. To limit incidental movement, the patient's head was positioned in a headrest using a 3D laser alignment. All cerebral PET examinations were acquired in list mode over 90 min, after IV injection of 244. 0 ± 27. 4 MBq of 18 F-DPA-714.
Data analysis An integrated PET image was obtained for each subject from the 90-min acquisition. This image was used to perform co-registration with each corresponding MRI image (T1-weighted SPGR and post-contrast images). Non-rigid registration was performed using normalised mutual information and PMOD® 3. 4 software. For each subject, a volume of interest (VOI) was defined over the injured tissue (IT) using individual MRI images. A similar VOI was transposed according to the region on the contralateral (CL) unaffected hemisphere. A VOI was also defined over the ipsilateral cerebellum to the injured tissue. All of VOIs were transposed onto PET images to obtain time activity curves (TACs). TACs were used to evaluate the kinetics of 18 F-DPA-714 over the 90-min acquisition. Ratios between the mean activity of the injured tissue VOIs and the contralateral (IT/CL) and cerebellar (IT/C) VOIs were calculated.
Acknowledgements We thank  Dr Marie Gaudron-Assor  and the technical and nursing staffs of CERRP, the  Service de Médecine Nucléaire ,  INSERM CIC 1415 ,  INSERM CIC 1415-IT , and  CHRU Tours  for their assistance. This work was partially supported by grants from  CHRU Tours  (Grant  NCT 00563537 ),  Radex  and  COSMI Programs  get partially financial supports from the  European Union  (Europe is engaged in Région Centre with the  FEDER, Fonds européen de développement régional) , the  French National Agency for Research  (' Investissements d'Avenir '  n°ANR-11-LABX-0018-01 , IRON), and  Laboratoires Cyclopharma. The research leading to these results has received funding from the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement  n°278850  ( INMiND ).
Statistics Student's t-test or Mann-Whitney test were used to compare values between groups. Half maximal inhibitory concentration (IC50) was calculated using a log(inhibitor) versus response model. Skin graft survival was compared using log-rank test. p < 0. 05 was considered significant. Graph Pad Prism Software Version 5. 0 (GraphPad Software Inc. , La Jolla, CA) was used for calculations.
Consistently, in primed mice treated with ABT-737 we observed a parallel depletion of na€ ıve Tcm and Tem with a statistically nonsignificant increase of Tem in mice exposed to ABT-737 compared to vehicle (data not shown). Thus, Bcl-2 and Bcl-XL, which are selectively inhibited by ABT-737, represent a potential molecular target to deplete Tm. The relevance of these findings was further investigated at the functional level. Bcl-2/Bcl-XL inhibition suppresses allogeneic Tm responses Allogeneic polyclonal memory recall responses were investigated ex vivo and in vivo. In a first experiment, CBA mice were primed with B6 skin grafts. Four months later recipient mice were treated with ABT-737 or vehicle for 5 days and then euthanized. Their splenocytes were stimulated in vitro overnight with T cell-depleted syngeneic (CBA), donor-derived (B6) or third party (BALB/c) splenocytes.
Acknowledgments We thank  Philip D. Bardwell  and  AbbVie Bioresearch (Worcester, USA)  for providing ABT-737,  A. -M. Schmitt-Verhulst  for the BM3. 3 mouse and the Ti98 antibody. The project was supported by the  Swiss National Science Foundation  (grant  323530-133893  to PEC,  310000-121979  to TF), the  Zurich Center of Integrative Human Physiology  (ZIHP, to SSG) and the  Olga Mayenfisch Stiftung.
( BRC-MH ) and Biomedical Research Unit for Dementia at the  South London and Maudsley NHS Foundation Trust and King's College London. CEG and AS were supported by the  UK National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health  ( BRC-MH ) at the  South London and Maudsley NHS Foundation Trust and King's College London  and by the  Guy's and St Thomas' Charitable Foundation  as well as the South London and  Maudsley Trustees. APF has received financial support from the  Region Rhône-Alpes  and the  Université Lumière Lyon 2  through an  ExploraDoc grant.
Furthermore, a large number of repeats of each stimulus was needed to overcome magnetic noise, limiting the number of different stimulus conditions. Stimuli were synthesised in MATLAB (Mathworks) and played out using PureData (http://puredata. info) via ER-2 transducers (Etymotics), which were located in a magnetically shielded box outside the MEG machine and connected to the custom earpiece via ϳ25 cm of 1. 6-mm-inner diameter polythene tubing. Sound levels were calibrated in situ with a microphone (40BF free-field microphone, G. R. A. S Sound & Vibration) inserted into the custom ear piece. Calibrations included a compensation for attenuation of the sound signal between the microphone and the eardrum, which was estimated before the experiments using a simulated ear canal. The frequency response characteristics of the transducers, combined with low-frequency filtering effects of the tubing, limited the range of effectively transmitted sound frequencies to ϳ0.
[Nominal IOIs were augmented by a small amount (1. 14 ms) to ensure that power line interference components (50 Hz and harmonics) were not reinforced by trial averaging. ] At every frequency transition in the tone sequence, the temporal presentation pattern for the next tone series was chosen randomly from among the four possible conditions, so that an equal number of each type of series would be presented in each hour. We aimed to collect a minimum of 6 h of data per subject, with more data collected if conditions permitted. Data acquisition and analysis. MEG and reference data were collected using custom software provided by the Applied Electronics Laboratory (SQUIDLab). Sensor signals were band-pass filtered in hardware between 0. 5 and 500 Hz and sampled at 1 kHz. Sampled signals were digitally high-pass filtered at 1 Hz, smoothed with a four-sample boxcar filter, and then separated into trials of either 350-ms duration (basic response analysis) or 175-ms duration (analysis of response reduction with tone repetition).
Overall, typically 20% of trials were discarded, leaving at least 1000 trials per stimulus condition. TSPCA was applied to the recordings from each channel to suppress environmental noise recorded on the reference sensors. TSPCA projects out magnetic fields recorded from the reference sensors, with time shifts to compensate for any convolutional mismatch between reference and main sensors. The TSPCA-transformed data from all nine MEG sensors was then combined using the DSS procedure, to derive the linear combination of channels that optimised the reliability of stimulus-evoked responses and their differentiation across stimulus conditions. We first applied DSS with a reliability constraint, to obtain the linear combination of channels that optimised the reliability of stimulus-dependent activity.
ACKNOWLEDGMENTS The authors acknowledge the pioneering contributions of  Hisashi Kado  to the development of the small-animal MEG machine used in this work and major role in arranging the collaboration between  University College London  ( UCL ) and the  Kanazawa Institute of Technology  to bring it to London. The authors also thank  Gen Uehara ,  Yoshiaki Adachi ,  Jun Kawai , and  Masakazu Miyamoto  from the  Kanazawa Institute of Technology  for expert technical help with the small-animal MEG machine. Additional technical support was provided by  Duncan Farquardt  ( UCL ).
Of note, this patient participated in another study that demonstrated that she displayed EEG cortical activity related to spontaneous ventilation  [31]. The fMRI study was conducted in the frame of the RESPIRONDINE study (NCT01243697) into which the patient was enrolled. She had given her informed written consent to participate. Assistance Publique -Hopitaux de Paris sponsored the study that was approved by the appropriate local legal and ethics authority (Comitede Protection des Personnes Ile-de-France 6, Pitie-Salpetriere, Paris). Psychometric tests were part of the clinical follow up of the patient. Their study was approved by the institutional review board of the French Society for Respiratory Medicine (''Societede Pneumologie de Langue Francaise'' reference number CEPRO2012-012). The patient gave her consent to anonymous use of her data for research purposes.
EEG recording & processing Continuous EEG data was recorded at 5 kHz from 63 scalp sites (Easycap electrode cap) using MR-compatible amplifiers (BrainAmp MR and Brain Vision Recorder software; Brain Products). One additional electrode was placed on the collarbone to record the electrocardiogram (ECG). Impedances were kept under 15 kV. The EEG signal was corrected for MR related and for pulse artefacts (see SI). Then, for each time sample, we computed the ratio between relative alpha power averaged over occipital electrodes, and theta power averaged over frontal electrodes (see Figure  1A ). This alpha/theta EEG power ratio is a common measure of vigilance  [39] [40] [41]. The data were subsequently downsampled to 250 Hz and rereferenced to a common average reference. Visual inspection of the signal checked for the absence of residual obvious artefacts.
Immediately before each of the four ''resting state'' blocks, the patient received the following instructions: ''please, keep your eyes closed, stay awake during the entire block, and try to let your mind wander to any particular thought''. As for the behavioural tests, we also used an 'ABBA' design with the following order: SB, MV, MV and SB. After each of the 4 scanning blocks a brief interview checked the absence of breathing discomfort, the absence of subjective report of drowsiness, and the effective engagement in the ''mind-wandering'' state. SpO2 was measured during the fMRI experiment. fMRI data processing & analysis. A correction was applied to reduce physiological noise (see SI) using a retrospective estimation and correction of respiration and heart beat  [42]. General linear model.
The precuneus ROI (seed region 1) was defined using A canonical template (automatic anatomical labeling from WFU PickAtlas toolbox of SPM, http://fmri. wfubmc. edu/ software/PickAtlas), from which the time course was extracted. We looked at the brain areas that showed a stronger correlation of their time course with the seed region during MV than during SB. We then used a brainstem ROI (seed region 2) manually defined as corresponding to the medulla oblongata: it was delineated from the pons by a horizontal boundary, and occupying a region extending distance ventrally to the estimated boundary with the spinal cord. The third control ROI (seed region 3) was defined using the Automated Anatomical Labelling atlas in regions of the left and right hemisphere considered to closely represent the auditory cortex, namely Herschl's gyrus  [43].
Acknowledgments We thank the patient for her active collaboration to this research. This work has been supported by the  Fondation pour la Recherche Medicale (FRM)  ('Equipe FRM 2010' grant to  Lionel Naccache ), by the  Institut pour le Cerveau et la Moe ¨lle epiniere  ( ICM Institute, Paris, France ), by  INSERM , by  AP-HP , by the  program ''Investissement d'Avenir   ANR-10-AIHU 06  of the  French Government '', by the  IHU-A-ICM  (' Investissement d'avenir' program ,  ANR-10-IAIHU-06 ), by  Assistance Publique -Hopitaux de Paris (AP-HP) Departement de la Recherche Clinique et du Developpement (DRCD)  ('' RESPIRONDINE '' project), by  Association Francaise du Syndrome d'Ondine (AFSO). We thank  Dr. Marjolaine Georges ,  Dr. Je  ´sus  Gonzales-Bermejo , and  Dr. Elise Morawiec  for managing mechanical ventilation during MRI.