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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
1,805 datasets
Featuring simultaneous recordings from populations of retinal ganglion cells in response to stimuli with varying correlation structures, including natural movies and white noise checkerboards. It was created by Kristina D. Simmons and published in 2020 to investigate how stimulus structure affects neural redundancy and pairwise correlations.
Featuring electrophysiological recordings of hippocampal CA1 single neuron firing and theta activity from rat pups across three developmental stages (P17-19, P21-23, and P24-26). Collected by Jangjin Kim and published in 2020, the data tracks neural responses during six sessions of associative learning using tone and periorbital stimulation.
Neuroscience data from human magnetoencephalography and mouse local field potentials examines transient beta frequency events (15-29Hz) in primary somatosensory neocortex. The dataset supports analysis of how event rate and timing relate to perception and attention across species. It was authored by Hyeyoung Shin and published in 2020.
This dataset accompanies a statistical framework for neuroimaging data analysis based on mutual information estimated via a Gaussian copula. The framework, developed by Robin A. A. Ince, provides a method for analyzing multivariate data from modalities like MEG and EEG, validated on discrete stimulus classes and continuous stimulus features. The associated open-source code was last updated in 2020.
Featuring magnetoencephalography (MEG) and electroencephalography (EEG) data from a study investigating cross-frequency phase synchrony (CFS) during visual working memory maintenance. The data was collected by Felix Siebenhühner and published in 2020 to explore load-dependent synchronization between theta, alpha, beta, and gamma oscillations across visual, fronto-parietal, and dorsal attention brain systems.
A collection of experimental data from an in vitro model of the ischemic penumbra, studying neuronal dynamics under controlled hypoxia. It was created by Joost le Feber and published in 2020. The data documents changes in spontaneous activity and network connectivity over periods of hypoxia ranging from short durations to approximately 30 hours.
Dryad hosts electrophysiological brain recordings from 4–6 month old infants viewing natural object images at 6 images per second. The dataset captures a face-selective neural response at 1.2 Hz over the right hemisphere, absent for phase-scrambled control images. These findings by Adélaïde de Heering, published in 2020, indicate early development of face perception capabilities.
A dataset from a study chemogenetically silencing 21 brain regions to test network hub importance for fear memory consolidation. The data supports the hypothesis that highly connected hub regions, identified via c-fos expression mapping and in silico network analysis, produce the largest memory deficits when silenced. It includes results from independent experiments covering 25% of an 84-region functional network.
Encompassing electrophysiological measurements from 10 healthy individuals performing elbow extension under seated, standing, and unstable wobble board conditions. It quantifies the cutaneous silent period (CSP) and excitatory responses (E1, E2) in the triceps brachii muscle, expressed as percent change from baseline and individual durations. The data was collected to examine how whole-body instability modulates reflex inhibition in the upper limb.
A collection of fMRI data from a study modeling brain activity during naturalistic story reading. The integrated computational model predicts fMRI activity from text passages with 74% accuracy for distinguishing story segments. It tracks diverse reading subprocesses from word perception to narrative character relationships.
Comprising data from a prospective, multi-center study analyzing autonomic and breathing biomarkers for Sudden Unexpected Death in Epilepsy (SUDEP). It includes observations from 148 generalized convulsive seizures across 87 adult patients with intractable epilepsy. The study characterized phenomena such as ictal central apnea, post-convulsive central apnea, and asystole.
Neural activity recordings from the posterior parietal cortex (PPC) of mice performing virtual reality navigation tasks were collected by Michael Krumin and released in 2020. The data captures neuronal firing patterns relative to spatial position, heading angle, and visual decision-making variables during trajectory selection.
Encompassing magnetoencephalography (MEG) data from human participants listening to speech under varying acoustic signal-to-noise ratios and visual contexts. It was collected to investigate the network mechanisms underlying audio-visual speech perception, focusing on local speech encoding and directed functional connectivity. The data was authored by Bruno L. Giordano and last updated in June 2020.
Biophysical models analyze the determinants of chloride ion driving force for synaptic inhibition. The dataset includes numerical and analytic solutions from pump-leak models. It was authored by Kira Michaela Düsterwald and published in 2020.
This dataset contains resting-state EEG signals analyzed to identify large-scale functional brain networks. The data was processed using a two-step method involving EEG-based source localization and spatial independent component analysis, followed by hierarchical clustering for group-level network identification. It was authored by Denis P. Schwartz and published in 2020.
Comprising behavioral data from two psychophysical experiments investigating how categorical choices alter the accumulation of subsequent evidence. The study examines biases in processing abstract numerical and low-level perceptual information, with computational modeling revealing a reduction in sensitivity via multiplicative gain modulation. The author is Zohar Z. Bronfman.
2020 research data from Kevin Caref investigates the role of endogenous opioids in the nucleus accumbens (NAc) on appetitive behavior. The dataset contains simultaneous recordings of NAc neuronal firing and behavioral data from rats performing a cued approach task for high-fat food under conditions of satiety. It was collected to test a specific neural mechanism hypothesis regarding overconsumption.
Data from a psychology experiment investigating how active control influences the interaction between spatial and temporal perception. The study includes participant data from conditions where visual bar height changes were either actively controlled or passively observed, with simultaneous judgments on acoustic tone sequences. The dataset supports the hypothesis that action enhances the coupling of spatial and temporal magnitude processing in the brain.
Nicholas Edward Myers released this dataset in 2020 containing magnetoencephalography (MEG) and electroencephalography (EEG) recordings from a visual target-detection task. The data tracks neural activity trajectories to investigate how internal mnemonic templates interact with sensory evidence.
Multi-muscle electromyographic recordings analyzed to map motoneuron activity and extract locomotor modules during human locomotion. The data reconstructs motoneuron activation patterns for three distinct speed conditions: slow walking, fast walking, and running.