Brain
Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies. Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.
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This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/
The DataPort Repository contains the data used primarily for generating Figure 1.
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Synaptic vesicle glycoprotein 2A (SV2A) is the most widely distributed transmembrane glycoprotein present on secretory vesicles in the pre-synaptic terminal of neurons throughout the central nervous system (Bajjalieh et al., 1994). SV2A can be used as a marker to visualize pre-synaptic density distribution in vivo using positron emission tomography (PET) imaging thanks to the SV2A radioligands available, including [11C]UCB-J (Nabulsi et al., 2016). Given the brain-wide distribution of SV2A, regional analysis of SV2A PET data may be limiting the amount of information that can be obtained.
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This is a code to correlate and process a dataset of epilepsy EEG signals。
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Data and Reuslts from this work:
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The use of modern Mobile Brain-Body imaging techniques, combined with hyperscanning (simultaneous and synchronous recording of brain activity of multiple participants) has allowed researchers to explore a broad range of different types of social interactions from the neuroengineering perspective. In specific, this approach allows to study such type of interactions under an ecologically valid approach.
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It mainly includes the original BONN epilepsy EEG data set, as well as the EEG signals after the revised tunable Q-factor wavelet transform decomposition and reconstruction of the data set.
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EEG consists of collecting information from brain activity in the form of electrical voltage. Epileptic Seizure prediction and detection is a major sought after research nowadays. This dataset contains data from 11 patients of whom seizures are observed in EEG for 2 patients.
The total duration of seizures is 170 seconds. The number of channels is 16 and data is collected at 256Hz sampling rate.
The final dataset files in .csv format contain 87040 rows x 17 columns,
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The Open Big Healthy Brains (OpenBHB) dataset is a large (N>5000) multi-site 3D brain MRI dataset gathering 10 public datasets (IXI, ABIDE 1, ABIDE 2, CoRR, GSP, Localizer, MPI-Leipzig, NAR, NPC, RBP) of T1 images acquired across 93 different centers, spread worldwide (North America, Europe and China). Only healthy controls have been included in OpenBHB with age ranging from 6 to 88 years old, balanced between males and females.
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Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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