dataesr/scientific-paragraphs-categorization huggingface dataset:
e. one repetition). For all four analyses both accuracy and reaction times were analyzed with linear mixed effects models run in R with the package lme4  [47]. The dependent variable was either accuracy (correct or incorrect), analyzed with a binomial generalized linear mixed effects model, or the log 10 transform of reaction times, analyzed with a linear mixed effects model. For the reaction time analysis only correct responses were analyzed. Reaction times of 0 ms were removed to allow for the log transformation. All fixed effects were coded with contrast coding with the exception of trial number in the second analysis, which was coded as a continuous variable. For all models, we included by-participant and by-item random slopes and intercepts and kept the maximal random structure that converged  [48].
This work was supported by the  Agence Nationale de la recherche  grant  ANR-11-JSH2-0006  (http://www. agence-nationale-recherche. fr/? Projet=ANR-11-JSH2-0006 ) (CJ);  Ecole doctorale UniversiteParis-Est Creteil Sciences de la Vie et de la Sante, doctoral scholarship  (bourse MRT) 27433-2007 (SS) and doctoral scholarship 2015/ 58 (http://www. univ-paris-est. fr/fr/-ecole-doctorale-sciences-de-la-vie-et-de-la-sante-svs-/); French Ministry of Health (Reference Center for Huntington's Disease)  (ACBL),  INSERM  Contrat d'interface (ACBL);  Assistance Publique -Hopitaux de Paris: biomarker program  NCT01412125 (ACBL);  Gobierno de España ,  Ministerio de Ciencia e Innovacion (MICINN)   PSI2011-23624  (RDDB); Research was conducted at the  Institut d'Etudes Cognitives (ENS, Paris) , which is supported by grants  ANR-11-0001-02 PSL Ã  and  ANR-10-LABX-0087  (http://www.
Synthesis of sgRNA, Cas9 mRNA and ssODN Template A 20 base pair guide (gHA) (5 -ggttttcaggtgggacgtcg-3 ) targeting the Kcnj13 gene region encoding the extracellular loop of the Kir7. 1 channel was obtained using Optimized CRISPR software 1. The synthesis of the chimera gHA-tracrRNA (sgHA) was based on protocols available at Addgene 2. Briefly, sense and antisense oligonucleotides encoding the guide were synthesized with extra-nucleotides compatible with a digestion product from restriction endonuclease BbsI (5 -CACCGggttttcaggtgggacgtcg-3 and 5 -AAACcgacgtcccacctgaaaaccC-3 respectively). Both phosphorylated oligonucleotides were hybridized and cloned in vector pX330 (Addgene 42230) digested with BbsI  (Cong et al. , 2013). The specific sgHA was obtained by in vitro transcription using as a template amplicons of gHA cloned in pX330 vector that include T7 promoter and the reverse primer located downstream of the transcription termination signal (T7sgHA 5 -ttaatacgactcactatagggttttcaggtgggacgtcg-3 and sgRev 5 -aaaagcaccgactcggtgcc-3 , respectively)  (Yang et al.
Off-Target Analysis Potential off target genome effects for gHA were obtained using the Optimized CRISPR design software. Specific flanking primers were designed to amplify the potential off targets by PCR. Amplicons were then directly sequenced. Cloning of cDNA Kir7. 1-HA Channel From Modified Mouse Total RNA was extracted from an enriched choroid plexus fraction from a heterozygote F1 mouse using Trizol reagent (Life Tech). The cDNA was synthesized using Superscript IV (Invitrogen) and oligo dT primer. The channel open reading frame was amplified by PCR using the Phusion High Fidelity DNA polymerase (Thermo Scientific) and the forward and reverse primers 5 -aagcttgcgatggacagcagtaattg-3 and 5 -tctagatttattctgtcagccctgtttc-3 , including HindIII and XbaI restrictions sites (in italics) respectively.
Heterologous Expression and Electrophysiology HEK-293 were transiently co-transfected with 0. 3 µg of pCR3. 1-CD8 and 1. 5 µg of plasmid (pCR3. 1) containing either Kir7. 1wt or Kir7. 1-HA cDNA using Lipofectamine 3000 (Invitrogen #L3000). At 24 h post-transfection, the cells were visualized applying Dynabeads-CD8 (Invitrogen #11147D) and recordings were performed from isolated cells using standard whole-cell patch-clamp technique as described elsewhere  (Díaz and Sepúlveda, 1995). Currents were recorded using an Axopatch 200B amplifier (Axon Instruments). Acquisition was at 2 kHz with filter at 1kHz employing pClamp10 software (Axon Instruments). For experiments, borosilicate capillaries (Harvard Apparatus GC150F-10, 1. 5 mm OD × 1. 17 mm ID) were fire polished to 2-4 MΩ and covered in beeswax.
The single strand DNA repair template used to incorporate the HA-coding sequence along with an EcoRV site by Homology Directed Repair (HDR) is shown in red. In Figure  1B , PCR amplicons from wild type and homozygous littermates for the HA insertion screening can be seen to have the expected size (420 and 450 bp respectively). EcoRV cuts only the modified gene yielding 2 restricted fragments (219 and 231bp). Sequencing of the amplicon confirms that the DNA edition occurred at position 6210 of the Kcnj13 gene (Ensembl accession number ENSMUSG00000079436). Eight potential off target mutations were predicted within gene coding regions and were analyzed by PCR. Direct sequencing of the amplicons did not demonstrate any mutations (results not shown).
FUNDING This work was funded by the  FONDECYT-Chile  grant  1150735. The  Centro de Estudios Científicos (CECs)  is funded by the  Base Financing Program of Conicyt. Travel support came from  ECOS-Conicyt  grant  C14S01. KL-C is on receipt of a fellowship from the  Chilean Comisión Nacional de Investigación Científica y Tecnológica.
Western Blot Analysis Cytoplasmic proteins from aortas were separated on polyacrylamide-SDS gels and transferred onto polyvinylidene difluoride membranes. Membranes were then incubated overnight with rabbit anti-endothelial NO synthase (eNOS; 1:500; Cell Signaling, Danvers, MA), anti-PSer1177-eNOS (phosphorylation on serine 1177 [1:500; Cell Signaling]), antiinducible NOS (1:500; Cell Signaling), anti-nitrotyrosine (1:2000; Thermo Fisher, Waltham, MA), and anti-mouse actin (1:5000; Sigma-Aldrich, Saint-Quentin-Fallavier, France) antibodies. Blots were then incubated for 1 hour with horseradish peroxidase-conjugated secondary antibodies at room temperature. Bands were visualized by enhanced chemiluminescence and quantified using the software ImageJ (National Institutes of Health, Bethesda, MD).
Procedure Participants sat in a dimly-lit room 80 cm in front of an LED monitor (refresh rate 120 Hz) and viewed stimuli presented against a grey background. A small fixation cross was superimposed over the nasion of the face images throughout the sequence. Each stimulation sequence consisted of a fixation cross for 2 seconds, followed by an 86-second stimulation period, and then another 2-second period during which only the fixation cross was visible. During the stimulation period, we used an in-house developed program (SinStim) to present faces at a rate of 6 Hz using a sinusoidal contrast modulation. In each 166. 66 ms image cycle, the stimulus image contrast was smoothly modulated from 0% to 100% to 0%. During the first 2 s of the stimulation period, the maximum contrast within a cycle gradually increased from 0 to 100% (i.
EEG acquisition and data preprocessing We recorded EEG from 128 active electrodes using a Biosemi Active Two system (Biosemi, the Netherlands). Recordings were grounded using common mode sense and driven right leg electrodes (http:// www. biosemi. com/faq/cms&drl. htm). We added 4 additional channels to the standard montage: two electrodes placed 1 cm from the outer canthi of each eye, and two electrodes placed above and below the right eye. EEG was sampled at 512 Hz (DC-coupled with an anti-aliasing filter, -3 dB at 102 Hz). Electrode offsets were kept within ± 40μV. We processed EEG data using EEGLab 13. 4. 4b (Delorme & Makeig, 2004)  and Letswave 6 (http://nocions. webnode. com/letswave) running in MATLAB (The Mathworks). 50 Hz line noise was identified using Cleanline  (Mullen, 2012)  using a separate 1 Hz high-pass filtered dataset (EEGLab Basic FIR Filter New, zero-phase, finite impulse response, -6 dB cutoff frequency 0.
5 Hz, transition bandwidth 1 Hz). We subtracted this line noise from the unfiltered dataset (as recommended by Bigdely-Shamlo,  Mullen, Kothe, Su, and Robbins, 2015). We identified noisy channels by visual inspection (mean noisy channels by participant 0. 6, median 0, range 0-3) and marked these for exclusion from average referencing and independent components analysis (ICA). We rereferenced the data to the average of the 128 scalp channels, and removed one extra channel (FCz) to correct for the rank deficiency caused by average referencing (as done by  Feuerriegel et al. , 2018). We processed a copy of this dataset in the same way, but additionally applied a 1 Hz high-pass filter (same filter settings as above) to improve stationarity for the ICA. ICA was performed on the 1 Hz high-pass filtered dataset (RunICA extended algorithm,  Jung et al.
, 2000). We then copied the independent component information to the unfiltered dataset (as recommended by  Viola, Debener, Thorne, and Schneider, 2010). We identified and removed independent components generated by blinks and saccades according to guidelines in  Chaumon, Bishop, and Busch (2015). After ICA we interpolated any bad channels (max bad channels within a dataset = 3) and FCz from the cleaned data (spherical spline interpolation).
Frequency domain data processing To isolate responses to expected and surprising oddballs interspersed within the sequences, we epoched EEG data from 0 to 1000 ms relative to each surprising oddball cycle onset, and from the onset of each expected oddball immediately preceding a surprising oddball. This ensured an equal number of epochs for each oddball type. The onesecond epoch length was an exact multiple of the 166. 6 ms base rate stimulus cycle duration. For each oddball type, we concatenated epochs to produce 42-s sequences (the so-called 'false-sequencing' approach, see  Quek & Rossion, 2017). These long sequences could be analysed in the frequency domain with high frequency precision. Concatenated sequences contained periodic responses to oddball faces at a rate of 1 Hz (determined by the one-second epoch length) and periodic responses to base rate faces at 6 Hz.
Participants Eighteen people participated in Experiment 2 (4 males, age range 18-33 years, mean age 23 ± 4. 3 years). All participants had normal or corrected-to-normal vision, no history of psychiatric or neurological disorders or substance abuse. All participants were right-handed as assessed by the Flinders Handedness Survey  (Nicholls, Thomas, Loetscher, & Grimshaw, 2013) , which gives comparable results to the Edinburgh Handedness Inventory used in Experiment 1. All participants showed unimpaired facial recognition ability as measured by the Benton Facial Recognition Test. Experiment 2 was approved by the Human Research Ethics committee of the University of South Australia. Data processing and analyses were performed at the University of South Australia.
Procedure Participants sat in a well-lit room 60 cm in front of a 60 Hz LED monitor. We presented stimuli using PsychToolbox V. 3. 0. 11  (Kleiner et al. , 2007)  running in MATLAB (Mathworks) against a grey background. Stimulation sequence structure and experimental task were identical to Experiment 1, except that participants responded using a one-button response box connected directly to the EEG amplifier. We presented 4 types of oddball stimuli in Experiment 2 (displayed in Fig. 4 ). All oddballs were 20% larger than base rate faces. Oddballs were either a different identity relative to base rate faces (Identity Change) or the same identity (Identity Repetition). The Identity Change oddball was of a single face identity, which did not change throughout a given sequence. Identity Change and Identity Repetition oddballs were presented in two different sequence types within the experiment.
We then epoched the resulting data from -166 ms to 834 ms timelocked to the start of i) each surprising oddball stimulus cycle, and ii) the immediately preceding expected oddball cycle. We baseline-corrected the resulting epochs using the prestimulus interval. Epochs containing ± 100 μV deviations from baseline in any of the 128 scalp channels were excluded from analyses (minimum of 60 epochs retained per oddball type per participant).
Background: Major depressive disorder (MDD) stands among the most frequent psychiatric disorders. Cognitive behavioral therapy (CBT) has been shown to be effective for treating depression, yet its neural mechanisms of action are not well elucidated. The objective of this work is to assess the available neuroimaging studies exploring CBT's effects in adult patients with MDD. Methods: Computerized databases were consulted till April 2018 and a research was conducted according to PRISMA guidelines in order to identify original research articles published at any time in English and French languages on this topic. Results: Seventeen studies were identified. Only one study was randomized comparing CBT to pharmacological interventions, and none included an effective control. Following CBT, changes occurred in cerebral areas that are part of the fronto-limbic system, namely the cingulate cortex, prefrontal cortex and amygdala-hippocampal complex.
Selection Criteria Computerized databases (MEDLINE/PubMed and Scopus) were consulted, and a search was conducted independently by both coauthors according to PRISMA guidelines  [12]  in order to identify original research articles published at any time until 21 May 2018 in English and French languages regarding CBT mechanisms of action in MDD. Only studies that considered CBT mechanisms of action as the primary outcome and included imaging before and after CBT were considered for this review. The following key terms were used: ('cognitive behavioral therapy' OR 'CBT' OR 'cognitive therapy' OR 'CT' OR 'behavioral therapy' OR 'BT' OR 'psychotherapy') AND ('depression' OR 'major depressive disorder' OR 'MDD' OR 'mood disorder' OR 'mood') AND ('mechanisms of action' OR 'underlying mechanisms' OR 'magnetic resonance imaging' OR 'MRI' OR 'fMRI' OR 'positron emission tomography' OR 'PET' OR 'single photon emission computed tomography' OR 'SPECT' or 'spectroscopy').
PET Studies Results of PET studies derive from the same team, are inconsistent with the above seen results and partly support the abovementioned data linking CBT with the cognitive model of depression. In the first (nonrandomized) one, Goldapple and colleagues employed resting-state fluorine-18 labeled deoxy-glucose PET in patients with MDD and treated with either CBT (≥12 sessions) or antidepressant medications (i. e. , paroxetine)  [66]. In the second trial, patients were randomized to receive either CBT (15-20 sessions) or antidepressant medications (i. e. , venlafaxine) and underwent similar PET scan evaluations  [67]. As is seen in most fMRI studies, a significant increase in ACC activity was noted following CBT. However, unlike the majority of fMRI studies (except  [50, 51] ), PET scan studies revealed a decreased metabolism in frontal regions  [66, 67]  and increased activity in limbic regions (i.
Acknowledgements We thank  Manuela Weitkunat  for the acquisition of Movie S3. We are grateful to  Reinhard Fässler  for generous support. This work was supported by the  EMBO   Young Investigator Program  (F. S. ), the  European Research Council  under the European Union's  Seventh Framework Programme  (FP/2007-2013)/ ERC  Grant  310939  (F. S. ), the  Max Planck Society  (S. B. L. , F. S. ), the  Centre National de la Recherche Scientifique (CNRS)  (F. S. ), the  excellence initiative Aix-Marseille University AMIDEX  (F. S. ), the  LabEX-INFORM  (F. S. ) and the  Boehringer Ingelheim Fonds  (S. B. L. ).
Commercial partners will also share technological innovations for research purposes. Research-specific work package 1. "meaningful individual differences" Co-ordinated by Lopez-Escamez, work package 1 seeks to determine meaningful individual differences in tinnitus by integrating knowledge and experience from all relevant clinical and scientific disciplines, and combining it with patient-centered and commercial perspectives. This will be achieved through interdisciplinary  ESIT    3a) ESIT will standardize measurements used for diagnostic assessment and inclusion/exclusion criteria for research by developing an evidence-based protocol that will be thoroughly tested using analysis of empirical data, and collecting expert opinions, and patient experiences. 3b) ESIT will integrate large-scale patient data in a central database to support descriptive and inferential analyses.
3c) ESIT will create a standardized framework for collecting longitudinal tinnitus data by implementing novel methods for mobile data collection together with standard assessment tools for validating the crowd-sensing data. 3d) ESIT will collect population-based epidemiological data across many EU countries using the same standardized questions and response options. This brief overview of the research projects illustrates how the ESIT consortium is characterized by interdisciplinary partnerships both within and across research-specific work packages 1-3. Many projects benefit from the exchange of measurement tools, data sharing, intersectoral knowledge transfer, and dissemination. The overall research program is designed to promote synergies between projects.
partnerships with the Meniere's Disease Society (patient organization), Tinnitus Research Initiative Foundation (non-profit research organization), Sensorion Pharmaceuticals (commercial sector), Julius Maximilian's University Würzburg, and the Knowledge Management and Discovery Laboratory at the Otto von Guericke University. Through this work package: 1a) ESIT will create a conceptual framework, as an end goal, that describes an individual's tinnitus profile. This framework will be based on multi-disciplinary data deposited in a centralized ESIT database that then enables the integration of common data variables gathered from all ESIT projects and data analyses targeted toward informing the tinnitus profile framework. 1b) ESIT will assess the genetic contribution to the development and maintenance of specific subtypes of tinnitus.
ACKNOWLEDGMENTS ESIT derives from a current  EU   COST Action   BM1306  (TINNET,  2014-2018 ) 1 , whose main ambition is to understand the tinnitus heterogeneity. We thank the current 250 contributors to TINNET (www. tinnet. tinnitusresearch. net), and who made ESIT possible. The  Tinnitus Research Initiative (TRI) Foundation  financed and founded by  Matteo de Nora  has laid the groundwork for a multidisciplinary international research network from which the  ESIT program  developed.
Augmenting sensory information by providing auditory, visual and vibrotactile bio-feedback of body sway improved also the postural performance of BVH patients  (15). All the data indicate that extra-vestibular signals substitute for vestibular input in BVH patients' spatial orientation, perception and posture control  (16) (17) (18). Among the main sensory inputs substituting for the missing vestibular afferents in chronic bilateral vestibular failure are however the visual cues  (19, 20). In the present study, we tried to determine how the visual input can stabilize the postural performance of chronic BVH patients. A dynamic approach with a stable force platform was used to investigate the patients' posture control system. Recordings of the Center of foot Pressure (CoP) were made during quiet standing in four conditions: eyes open in total darkness, with vision of a stable space-fixed target, and during pursuit of a moving visual target in stroboscopic light with either high (4.
The data collected in the BVH patients were compared to those recorded in a control group made of 21 sex-and agematched healthy participants (11 female, 10 male, mean age: 58. 3 years; range: 32-82 years). The vestibular clinical tests have not been performed in the controls who, however, reported to be free of vestibular disorders. All the patients and healthy controls provided informed consent before their participation. The experimental protocol was approved by the local Ethics Committee (CCPPRB Paris) and followed the recommendations of the Helsinki declaration.
Data Processing The CoP displacements were computed in the antero-posterior (AP) and medio-lateral (ML) directions and used to measure the postural performance of the patients. A non-linear analysis of CoP displacements was performed in order to accurately evaluate the posture control system [see  (21) , for review]. It consisted of applying both the wavelet transform and the fractional Brownian-motion analysis (PosturoPro software, Framiral) to the AP and ML stabilograms. The wavelet analysis consisted of describing body sway frequencies as a function of time, a method we have described in details in our previous papers  (21, 23, 24). This method has not the limitations of the Fast-Fourier Transform and provides a time-frequency chart of body sway in three dimensional space, giving access to the changes in the body sway frequency components with time.
Statistical Analysis Four parameters describing body sway during quiet standing were analyzed: the global score of posture control given by the Postural Instability index (PII), the Spectral Power Density (SPD) expressed in the frequency domain of the visual system (0. 05-0. 5 Hz frequency part), the amplitude of the critical point (CP amplitude) and the frequency of the Hausdorff points accounted by the stochastic process of posture control. To measure the effects of visual condition on posture control, i. e. , darkness, visual fixation, visual pursuit with low (saccades) and high (smooth pursuit) flicker frequencies, the four postural parameters were analyzed using a 4-way ANOVA followed by a post-hoc analysis with the Tuckey test (Stateview II software). Results were considered significant for p < 0.
Data Analysis Raw data were preprocessed using custom-written functions in MATLAB (MathWorks). Briefly, raw data were explored to detect MUA, followed by raw data downsampling to 1000 Hz for further analysis of LFP. The analysis was conducted in 500 ms windows: (1) after the stimulus to define evoked activity and (2) before the stimulus to characterize spontaneous activity to estimate the baseline. MUA was detected at a band-passed signal (>200 and <4000 Hz) when all negative events exceeding 3. 5 SD were considered as spikes (>99. 9% confidence)  (Mitrukhina et al. , 2015). Because of a high level of MUA variation between the animals, the power of the MUA in different stimulation conditions was normalized to MUA response to PW stimulation in the animal. Spectral features of MUA and its coherency to LFP were calculated using the Chronux toolbox functions  (Bokil et al.
For that, the LFP from the barrel of interest was first filtered using continuous time-frequency analysis. Morlet mother wavelet was applied to LFP consistently with the frequency increment of 1 Hz starting from 5 to 100 Hz. Secondly, Hilbert transform of filtered data was used to extract instantaneous phases of the LFP. Each spike phase was defined from filtered LFP according to its timestamp. The significance of the MUA phase lock was calculated using estimated angles of randomly distributed MUA versus its LFP. The threshold of significance was set at 2. 5 Jackknife standard deviation + mean value of the results calculated on shuffled data (100 iterations). Jackknife standard deviation was calculated using the Jackknife method provided in the Chronux toolbox. The reliable peaks (for coherence and phase lock analysis) were defined as peaks exceeding the threshold and consisted of the more than two interlinked points.