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The database includes clinical and connectome data from a sample of ALS patients carrying the C9orf72 mutation (ALSC9+), non-mutation-carriers ALS patients (ALSC9-), and ALS mimics (ALSmimics). The reported data consist of: demographic data (i.e., Age and Sex assigned at birth), clinical data (i.e., Bulbar/spinal onset, ALSFRS, Survival, disease duration, and King's Staging System scores), and connectome results.

Understanding object-directed actions performed by others is central to everyday life. This ability is thought to rely on the interaction between the dorsal action observation network (AON) and a ventral object recognition pathway. On this view, the AON would encode action kinematics, and the ventral pathway, the most likely intention afforded by the objects. However, experimental evidence supporting this model is still scarce. Here, we aimed to disentangle the contribution of dorsal vs. ventral pathways to action comprehension by exploiting their differential tuning to lowspatial frequencies (LSFs) and high-spatial frequencies (HSFs). We filtered naturalistic action images to contain only LSF or HSF and measured behavioral performance and corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS). Actions were embedded in congruent or incongruent scenarios as defined by the compatibility between grips and intentions afforded by the contextual objects. Behaviorally, participants were better at discriminating congruent actions in intact than LSF images. This effect was reversed for incongruent actions, with better performance for LSF than intact and HSF. These modulations were mirrored at the neurophysiological level, with greater CSE facilitation for congruent than incongruent actions for HSF and the opposite pattern for LSF images. Finally, only for LSF did we observe CSE modulations according to grip kinematics. While results point to differential dorsal (LSF) and ventral (HSF) contributions to action comprehension for grip and context encoding, respectively, the negative congruency effect for LSF images suggests that object processing may influence action perception not only through ventral-to-dorsal connections, but also through a dorsal-to-dorsal route involved in predictive processing.

This archive contains part 2 of Shift Benchmark on Multiple Sclerosis lesion segmentation data. This dataset is provided by the Shifts Project to enable assessment of the robustness of models to distributional shift and the quality of their uncertainty estimates. This part is contains data collected from several different sources and distributed under a CC BY NC SA 4.0 license. Part 1 of the data is available here. A full description of the benchmark is available in https://arxiv.org/pdf/2206.15407. To find out more about the Shifts Project, please visit https://shifts.ai . {"references": ["Malinin, Andrey et al. (2022). \u00a0Shifts 2.0: Extending The Dataset of Real Distributional Shifts, arXiv:2206.15407"]} This work is supported by the Hasler Foundation, Cambridge University Press and Cambridge Assessment and DeepSea

Objective: To understand the progressive nature of amyotrophic lateral sclerosis (ALS) by investigating differential brain patterns of gray and white matter involvement in clinically or genetically defined subgroups of patients using cross-sectional, longitudinal and multimodal MRI. Methods: We assessed cortical thickness, subcortical volumes and white matter connectivity from T1-weighted and diffusion-weighted MRI in 292 ALS patients (follow-up: n=150) and 156 controls (follow-up: n=72). Linear mixed-effects models were used to assess changes in structural brain measurements over time in patients compared to controls. Results: Patients with a C9orf72 mutation (n=24) showed widespread gray and white matter involvement at baseline, and extensive loss of white matter integrity in the connectome over time. In C9orf72-negative patients, we detected cortical thinning of motor and frontotemporal regions, and loss of white matter integrity of connections linked to the motor cortex. Spinal-onset patients displayed widespread white matter involvement at baseline and gray matter atrophy over time, whereas bulbar-onset patients started out with prominent gray matter involvement. Patients with unaffected cognition or behavior displayed predominantly motor system involvement, while widespread cerebral changes, including frontotemporal regions with progressive white matter involvement over time, were associated with impaired behavior or cognition. Progressive loss of gray and white matter integrity typically occurred in patients with shorter disease durations (<13 months), independent of progression rate. Conclusions: Heterogeneity of phenotype and C9orf72 genotype relates to distinct patterns of cerebral degeneration. We demonstrate that imaging studies have the potential to monitor disease progression and early intervention may be required to limit cerebral degeneration. Supplemental Data corresponding to research paper 'A multimodal longitudinal study of structural brain involvement in ALS' It contains appendices, supplemental figures and supplemental tables for this paper.

Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

Dataset to support the findings in the journal paper titled "Investigating the effects of COVID‑19 lockdown on Italian children and adolescents with and without neurodevelopmental disorders: a cross‑sectional study". Each row is a different subject. Each column represents an answer to the questionnaire. For single choice questions, the answer was reported as-is (Italian). For multiple choice questions, the alternatives where splitted in several columns and the answer was coded as 0/1 (one hot encoding). For the "school" column, 2=primary school, 3=middle school, 4=high school. For the "school.class" column, classes from 4 to 8 belong to primary school, from first to fifth grade; classes from 9 to 11 belong to middle school, from first to third grade; classes from 12 to 16 belong to high school, from first to fifth grade.

Data set for: Esmaeili V, Tamura K, Muscinelli SP, Modirshanechi A, Boscaglia M, Lee AB, Oryshchuk A, Foustoukos G, Liu Y, Crochet S, Gerstner W, Petersen CCH (2021) Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response. Neuron 109, doi 10.1016/j.neuron.2021.05.005 There are 2 files in this upload: 1. The file named "2021_Esmaeili_Tamura_Neuron.pdf" is the Open Access pdf of the online publication in Neuron. 2. The file named "Esmaeili_data_code.zip" (~55 GB) is a zipped version of a folder "Esmaeili_data_code" (~63 GB), which contains the data analysed in the study along with the Matlab codes used to generate the published figures. To access the data and codes, first unzip the file. The subfolder “Electrophysiology” contains main codes, data and subfunctions to produce figure panels related to silicon probe recordings. The subfolder “Imaging” contains main codes, data and subfunctions to produce figure panels related to wide-field calcium imaging. Each of these subfolders contains a README.txt file with detailed descriptions of files and required toolboxes to run the codes. When running the code, you need to set the Matlab file path to be "Esmaeili_data_code". In addition, you should add the folder "Esmaeili_data_code" with subfolders to the Matlab path. Some parts of the code rely upon previous results, and need to be executed sequentially in the order of the figure panels in the journal publication. {"references": ["Esmaeili V, Tamura K, Muscinelli SP, Modirshanechi A, Boscaglia M, Lee AB, Oryshchuk A, Foustoukos G, Liu Y, Crochet S, Gerstner W, Petersen CCH (2021) Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response. Neuron 109, doi 10.1016/j.neuron.2021.05.005"]}

F-TRACT atlas release - December 2021 ====================================== The F-TRACT atlas is provided as .csv (comma-separated values) files that can be read in any table editor. In addition, we provide a Matlab routine allowing to read the features of the atlas as Matlab variables. The atlas is provided for free use for research use only, with limited accuracy, which hopefully will improve with subsequent releases. Please cite David et al. (2013) Probabilistic functional tractography of the human cortex, NeuroImage, and Trebaul et al. (2018) Probabilistic functional tractography of the human cortex revisited, NeuroImage, Lemarechal et al. (2022) A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials, Brain, when using the F-TRACT atlas. - f-tract_v2112 : Connectivity probability as well as features describing fibers biophysical properties, estimated from CCEP data recorded in 780 patients, in the AAL, AICHA, Brodmann, Freesurfer, Hammers, HCP-MMP1, Lausanne2008 (resolutions 33, 60, 125, 250, 500) and MarsAtlas parcellation schemes. The CCEP features are: peak and onset latency (LatStart), amplitude, duration, integral, velocity estimated from the onset latency and the fibers distance between the parcels and axonal conduction delays. Synaptic excitatory and inhibitory delays are also provided for each parcel. All features have been estimated separately for patients younger than 15 y.o. (group "0-15") and patients older than 15 y.o. (group "15-100"). - Features maps : Images representing the connectivity probability and response features for all the regions in the Lausanne2008-60 parcellation.

This file details the folder structure for the data files provided corresponding to the experiments and analysis performed in Fuzzy Supertertiary Interactions within PSD-95 Enable Ligand Binding. Correction parameters, results, and methods are detailed in the manuscript. The file “Sample Reference.xlsx” details the naming conventions for different FRET labeling site variants. “RefitDistanceTables.xlsx” provides the distances for all global fits of subsets of samples performed for classification of DMD structures. The .zip file "PDBDev_adtl_Datasets.zip" Contains additional files corresponding to submissions of structures from the corresponding manuscript to wwPDB-Dev. Folder 1. Single Molecule Experimental Data .ht3 and .ptu files corresponding to time-tagged photon records collected using single-photon detectors with Hydra Harp TCSPC software and hardware. Folders are provided for each sample. Selection criteria and correction parameters are detailed in the manuscript. DO data were taken from bursts with SPIE<0.1 while AO data were SPIE>0.9. 1.1 BG Background files from which background signals were calculated for each sample. Subfolder for each sample. 1.2 IRF IRF data files used for generation of IRF curves for fluorescence decay histogram analysis and generation of fFCS filters. Subfolder for each sample. Fluorescence Decay Histograms Data files for photon counts in each time bin following donor excitation pulse for Donor-only (DO), FRET (DA), and Instrument Response Function (IRF) curves used in fluorescence decay histogram analysis. 2.1 Fit Curves Curves fit to decay histograms, in xyxy format (time delay after pulse, fit curve counts, time, residual) Filtered FCS Curves and Filter Files Data corresponding to four fFCS curves per sample: low-FRET-high-FRET (lohi), high-FRET-low-FRET (hilo), low-FRET-low-FRET (lolo), and high-FRET-high-FRET (hihi), as well as filter files generated in the Kristine software package using the .ht3 and .ptu data and IRF files from Single Molecule Experimental Data. 3.1 Fits Fit curves and residuals for all samples. .cor files are simple text files in xy format (third column unused). .res, .fit files follow likewise. Simulation AV-Derived Distance Values Structures from DMD simulations and AV-derived interdye distances used for structural classification against experimental FRET data. Also includes references files for associating distances correctly with structures and FRET pairs. 4.1 CoM AV Contours and PCA Data Files contain AV-derived distance information for all simulation structures from DMD, in compact npy format loadable via numpy.load. The text files contain center-of-mass positions in xyz format for the indicated domains. 5. MFD Histograms Contains text files for MFD contour plot data, as well as FRET line equations for each sample. Text files are in matrix representation, with the first row and column being the x/y axis values and all internal values representing a 2D bin. 6. PDA Histograms Contains time-binned histograms of smFRET data and modeling outputs from PDA fitting.