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122 results for “Brain dynamics”
Brain Dynamics During Flow Experiences
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Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning (Open Data and Open Materials)
<p><strong>Open Data and Open Materials of: Sperl, M. F. J., Wroblewski, A., Mueller, M., Straube, B., & Mueller, E. M. (2021). Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning. <em>NeuroImage</em>, <em>226</em>, 117569.</strong></p> <p>Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of neural fear processes remain opaque and require EEG. To date, studies on electrophysiological brain signals in humans have helped to elucidate underlying perceptual and attentional processes, but have widely ignored how fear memory traces <em>evolve</em> over time. The low signal-to-noise ratio of EEG demands aggregations across high numbers of trials, which will wash out transient neurobiological processes that are induced by learning and prone to habituation. Here, our goal was to unravel the plasticity and temporal emergence of EEG responses during fear conditioning. To this end, we developed a new sequential-set fear conditioning paradigm that comprises three successive acquisition and extinction phases, each with a novel CS+/CS- set. Each set consists of two different neutral faces on different background colors which serve as CS+ and CS-, respectively. Thereby, this design provides sufficient trials for EEG analyses while tripling the relative amount of trials that tap into more transient neurobiological processes. Consistent with prior studies on ERP components, data-driven topographic EEG analyses revealed that ERP amplitudes were potentiated during time periods from 33–60 ms, 108–200 ms, and 468–820 ms indicating that fear conditioning prioritizes early sensory processing in the brain, but also facilitates neural responding during later attentional and evaluative stages. Importantly, averaging across the three CS+/CS- sets allowed us to probe the temporal evolution of neural processes: Responses during each of the three time windows gradually increased from early to late fear conditioning, while long-latency (460–730 ms) electrocortical responses diminished throughout fear extinction. Our novel paradigm demonstrates how short-, mid-, and long-latency EEG responses change during fear conditioning and extinction, findings that enlighten the learning curve of neurophysiological responses to threat in humans.</p>
Dynamic reconfiguration of macaque brain networks during natural vision
<p>Raw data acquired under awake imaging conditions in the macaque monkey during free-viewing on natural scenes. The movie presented is also shared which is based on 30 sec 0N and OFF periods. Time-series echo planar imaging (EPI) data for each subject (AL, DP, FL and VL). Data is named based on the subject.session.run. The format structure is on NIFTI. Anatomical files are also named according to the same nomenclature. EPI mask are also available for each in-session subject. </p>
Analysis accompanying "Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the Drosophila larval brain"
<p>This repository documents the raw data processing and figure generation for the article “Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the <em>Drosophila </em>larval brain”, doi: 10.1261/rna.079552.122.</p>
Method to assess the functional role of noisy brain signals by mining envelope dynamics
<p>Preprocessed envelope EEG features based on a spatial filter approach. The features were computed across multiple within-trial SVIPT events for a large hyperparameter space on data of an exemplary subject.</p> <p>The file "components.bsv" contains the preprocessed envelope features of all investigated configurations and provides underlying parameters as well as a relative path for the key ``record_dir'' to additional component information. Specifically, for each configuration the spatial filter, spatial activity pattern and the time-resolved within-trial envelope signal is provided under "records/". </p>
Subgraphs of functional brain networks identify dynamical constraints of cognitive control
<p>Post-processed BOLD fMRI functional connectivity data from human subjects performing two distinct cognitive control tasks.</p> <p>See enclosed README file for information regarding data organization and handling.</p>
Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain
<p>This dataset was acquired for the DGE and fiber photometry study published in NeuroImage ( <a href="https://doi.org/10.1016/j.neuroimage.2022.119762">https://doi.org/10.1016/j.neuroimage.2022.119762</a>).<br> Comprises of three datasets: DGE MRI, fiber photometry and two-photon microscopy.</p>
Stroke data from: Robust dynamic brain coactivation states estimated in individuals
<p><span>A confluence of evidence indicates that brain functional connectivity (FC) is not static but rather dynamic. </span><span>Capturing transient </span><span>network interactions in the individual brain requires a technology that offers sufficient within-subject reliability. Here, we introduce an </span><span>individualized network-based dynamics analysis technique and demonstrate that it is reliable in detecting subject-specific brain states during both resting state and a cognitively challenging language task.</span> <span>Moreover, we evaluated the extent to which brain states showed hemispheric asymmetries and how various phenotypic factors such as handedness and gender might influence network dynamics. </span><span>W</span><span>e discovered a right-lateralized brain state that occurred more frequently in men than in women, and more frequently in right-handed versus left-handed individuals. Lastly, we demonstrated longitudinal brain state changes in 42 patients with subcortical stroke over 6 months. Taken together, this approach could quantify subject-specific dynamic brain states and has potential for use in both basic and clinical neuroscience research.</span></p>
Petrucco et al, Neural dynamics and architecture of the heading direction circuit in a vertebrate brain [Dataset]
<p>Data supporting the paper <a href="https://www.biorxiv.org/content/10.1101/2022.04.27.489672v1.full">Neural dynamics and architecture of the heading direction circuit in a vertebrate brain</a>. </p>
Stroke data from: Robust dynamic brain coactivation states estimated in individuals
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Data sets comparing Ca(2+) dynamics in whole-cell and β-escin-based perforated patch clamp recordings in adult mouse brain slices.
<p># Hess-et-al-beta-escin-2020<br> Data of the "Data in Brief" article concerning the added buffer approach with beta-escin perforated patch.</p> <p>A joint work by: Simon Hess (`simon.hess@uni-koeln.de`), Christophe Pouzat (`christophe.pouzat@math.unistra.fr`), and Peter Kloppenburg (`peter.kloppenburg@uni-koeln.de`).</p> <p>## Content</p> <p>This repository contains:</p> <p>- Directory `data_whole_cell` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the whole-cell configuration.<br> - Directory `data_beta_escin` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the β-escin perforated patch clamp configuration.</p>
Crossing hands behind your back reduces recall of manual action sentences and alters brain dynamics
<p>The experiment involved a 2 Verb (manual, attentional) x 2 Hand posture (front, behind) within-participant design. Half of the participants were assigned randomly to one of the two sets of 120 experimental sentences. The sentences were divided into 12 experimental blocks of 11 sentences each: 5 manual and 5 attentional sentences as experimental materials, and 1 filler sentence that was added at the beginning of each block to discard recall primacy effects and excluded from the analysis. An additional block of 5 sentences was used as practice. Each experimental block consisted of: a) learning phase, including the 10 experimental sentences in random order, plus the initial filler sentence, b) one-minute distractive task, c) recall phase.</p> <p>For more information about the data, please refer to the Corresponding Author</p>
Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment (data)
<p>Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment</p>
Dataset to reproduce the figures of article "Information dynamics of in silico EEG Brain Waves"
<p>Data and code to reproduce results figures.</p>
Dynamic rewiring of electrophysiological brain networks during learning
<p>This space is dedicated to the dataset used in the manuscript "Dynamic rewiring of electrophysiological brain networks during learning" under peer-reviewing process.</p>
Animal data associated with: Pattern dynamics and stochasticity of the brain rhythms
<p>Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored, is the actual structure of the waves–their shapes and patterns over finite timescales. The data published here are used to study brain wave patterning in different physiological contexts using two independent approaches: the first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses "orderliness'' of the waves' features. The corresponding measures capture the waves' characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns' dynamics and the animal's location, speed, and acceleration. Specifically, patterns of θ, γ, and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave's cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns, are derived from the data. The results offer a complementary–mesoscale–perspective on brain wave structure, dynamics, and functionality.</p>
Investigation of Brain Network Dynamics in Depression
ClinicalTrials.gov study NCT01931995. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Brain Dynamics of Oxytocin
ClinicalTrials.gov study NCT01834261. IPD Sharing: Not stated. Countries: 1. Publications: 25.
Effectiveness of Brain Dynamic Audio Stimulation for Improving Insomnia and Sleep Cycles in Healthcare Professionals
ClinicalTrials.gov study NCT07252128. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effects of Videogames on Depression Symptoms and Brain Dynamics
ClinicalTrials.gov study NCT05426265. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.