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9 results for “neuronal synchronization”

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dryad40/100

Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

<p>Neuronal oscillations, their inter-areal synchronization, and scale-free dynamics constitute fundamental mechanisms for cognition by regulating communication in neuronal networks. These oscillatory dynamics have large inter-individual variability that is partly heritable. We hypothesized that this variability could be partially explained by genetic polymorphism in neuromodulatory genes. We recorded resting-state magnetoencephalography (MEG) from 82 healthy participants and investigated whether oscillation dynamics were influenced by genetic polymorphisms in Catechol-O-methyltransferase (COMT) Val<sup>158</sup>Met and brain-derived neurotrophic factor (BDNF) Val<sup>66</sup>Met. Both COMT and BDNF polymorphisms influenced local oscillation amplitudes and their long-range temporal correlations (LRTCs), while only BDNF polymorphism affected the strength of large-scale synchronization. Our findings demonstrate that COMT and BDNF genetic polymorphisms contribute to inter-individual variability in neuronal oscillation dynamics. Comparison of these results to computational modeling of near-critical synchronization dynamics further suggested that COMT and BDNF polymorphisms influenced local oscillations by modulating the excitation-inhibition balance according to the brain criticality framework.</p>

opencc-zeroNov 2021View details →
dryad40/100

Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

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publicJan 2023View details →
zenodo32/100

Dynamics, synchronization and analog circuit implementation of a discrete neuron-like map with pulsating spiral dynamics

<p>These are experimental time series for an electronic model of neural dynamics. They are provided to support the replication of the results reported in the associated publication, as well as any further public-domain academic research in the field of neural dynamics, nonlinear electronic circuits, and related aspects, in compliance with the specified license terms and all applicable legal clauses.</p> <p>The following reference must be cited when using these data:</p> <div> <div> <div>Zhu W, Sun K, Wang H, Fu L, Minati L, Dynamics, synchronization and analog circuit implementation of a discrete neuron-like map with pulsating spiral dynamics, Chaos, Solitons and Fractals 186 (2024) 115281, DOI &nbsp;10.1016/j.chaos.2024.115281</div> </div> </div> <p>This document is the results of the research project funded by the National Natural Science Foundation of China (Nos. 62071496, 62061008), and the Innovation Project of Graduate of Central South University (Nos. 2024ZZTS0241). L.M. gratefully acknowledges the support of the "Hundred Talents" program of the University of Electronic Science and Technology of China, of the "Outstanding Young Talents Program (Overseas)" program of the National Natural Science Foundation of China, and of the talent programs of the Sichuan province and Chengdu municipality.</p>

opencc-by-4.0Apr 2024View details →
zenodo28/100

Figure 2 from: Vyshedskiy A, Dunn R (2015) Mental synthesis involves the synchronization of independent neuronal ensembles. Research Ideas and Outcomes 1: e7642. https://doi.org/10.3897/rio.1.e7642

Figure 2 - On a neurological level, mentally forming the image of Bill Clinton and the lion consists of the following steps: Step 1 - Recall of Bill Clinton: The prefrontal cortex (PFC) activates the ensemble of neurons representing Bill Clinton to fire synchronous actions potentials. Bill Clinton is perceived by the patient. The electrode implanted into the temporal lobe (TL) records an increased rate of action potentials. Step 2 - Recall of the lion: The PFC activates the ensemble of neurons representing the lion to fire synchronous actions potentials. The lion is perceived. The second electrode implanted into the TL records an increased rate of action potentials. Step 3 - The patient mentally integrates the images of Bill Clinton and the lion into one scene. The Mental Synthesis Theory hypothesizes that integration is accomplished by the PFC synchronizing the two neuronal ensembles in time. Step 4 - When synchronization of the Clinton and the lion neuronal ensembles is achieved, a new, never-before-seen mental image of Bill Clinton holding the lion on his lap is perceived by the patient. At that moment the two implanted electrodes are predicted to record synchronous action potentials, implying the synchronization of the Clinton and lion neuronal ensembles.

opencc-by-4.0Dec 2015View details →
zenodo28/100

Figure 1 from: Vyshedskiy A, Dunn R (2015) Mental synthesis involves the synchronization of independent neuronal ensembles. Research Ideas and Outcomes 1: e7642. https://doi.org/10.3897/rio.1.e7642

Figure 1 - Mental synthesis of Bill Clinton holding a lion. Once selective neurons for Bill Clinton and the lion are identified, a subject can be asked to imagine Bill Clinton holding the lion on his lap. The Mental Synthesis theory predicts that both the Clinton neuron and the lion neuron will increase their firing rate and that their activity will be synchronized.  Images modified from: 1. William J. Clinton at the Parliament in London, United Kingdom, November 29, 1995.  https://commons.wikimedia.org/wiki/File:Bill_Clinton_1995_im_Parlament_in_London.jpg 2. Lioness in the Olomouc Zoo at Svatý kopeček, Czech Republic. This image is licensed under the CC BY-SA license. https://commons.wikimedia.org/wiki/File:Lioness,_Olomouc.jpg

opencc-by-4.0Dec 2015View details →
dryad28/100

Data from: Frontoparietal structural connectivity mediates the top-down control of neuronal synchronization associated with selective attention

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publicAug 2016View details →
dryad28/100

Data from: Synchronized excitability in a network enables generation of internal neuronal sequences

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publicApr 2017View details →
geo24/100

Rapid and synchronous clearance of PcG histone modifications from Hox genes anticipates motor neuron differentiation

GEO Series GSE19450. Mus musculus. 33 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Genome binding/occupancy profiling by genome tiling array.

openGEO-OpenDec 2012View details →
geo20/100

Patch-Seq of synchronized and non-synchronized neurons in zebrafish dorsal pallium in response to CAS treatment

GEO Series GSE253039. Danio rerio. 20 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2024View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record