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60 results for “spontaneous activity”
Data from: Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes
<p><span>Movement-correlated brain activity has been found across species and brain regions. Here, we used fast whole-brain lightfield imaging in adult <em>Drosophila </em>to investigate the relationship between walk and brain-wide neuronal activity. We observed a global change in activity that tightly correlated with spontaneous bouts of walk. While imaging specific sets of excitatory, inhibitory, and neuromodulatory neurons highlighted their joint contribution, spatial heterogeneity in walk- and turning-induced activity allowed parsing unique responses from subregions and sometimes individual candidate neurons. For example, previously uncharacterized serotonergic neurons were inhibited during walk. While activity onset in some areas preceded walk onset exclusively in spontaneously walking animals, spontaneous and forced walk elicited similar activity in most brain regions. These data suggest a major contribution of walk and walk-related sensory or proprioceptive information to global activity of all major neuronal classes.</span></p>
Data from: Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness
<p class="MsoNormal">SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While<em> <span>i</span>n vitro </em>studies showed PTV reduce action potential firing, consequences at <em>in vivo</em> network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon <span>Ca<sup>2+</sup></span> imaging and electrocorticography (ECoG) in awake mice showed that spontaneous <span>Ca<sup>2+</sup></span> transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.</p>
Data from: Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes
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Data from: Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness
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Data from: Stability of spontaneous, correlated activity in mouse auditory cortex
<p>Neural systems can be modeled as complex networks in which neural elements are represented as nodes linked to one another through structural or functional connections. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the system's topological organization and to better understand its function. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work indicates a framework for studying spontaneous activity measured by two-photon calcium imaging using computational methods and graphical models from network science. The methods are flexible and easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease.</p>
Multielectrode array recordings of spontaneous activity in developing neuronal cultures
<p>These data are to accompany the following paper:</p> <p>Charlesworth P, Morton A, Eglen SJ, Komiyama NH, Grant SGN (2015) Canalization of genetic and pharmacological perturbations in developing primary neuronal activity patterns. Neuropharmacology</p> <p>Available at: http://dx.doi.org/10.1016/j.neuropharm.2015.07.027.</p> <p> </p> <p>For further details about the data, please see h<span>ttp://damtp.cam.ac.uk/user/sje30/papers/charlesworth2015_data.pdf</span></p>
Data from: Stability of spontaneous, correlated activity in mouse auditory cortex
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Supplementary Figure 6 spontaneous brain activity data
<p>This data set contains a single ten-minute run of spontaneous brain activity. This data was collected using a CMOS camera that costs approximately $750. Wide field images of the mouse brain at four different wavelengths are provided as .tif files. Processed data are included in a .h5 file that contains relative changes in neuronal calcium activity, extracellular acetylcholine, oxyhemoglobin, and deoxyhemoglobin. A video of the mouse face and a recording from an accelerometer placed under the mouse are also included. A trigger file recorded by the data acquisition system shows the timing of measurements. This data was used to produce the spontaneous activity part of supplementary figure 6 in the following article.</p> <p>Doran, P., Fomin-Thunemann, N., Tang, R., Zimmerman, B., Kilic, K., Kura, S., Fisher, H., Chabbot, G., Herbert, J., Jiang, J., Sakadzic, S., Boas, D., Devor, A., Chen, I., & Thunemann, M. (2023). Widefield in vivo imaging system with two fluorescence and two reflectance channels, a single sCMOS detector, and shielded illumination. bioRxiv. <a href="https://doi.org/https:/doi.org/10.1101/2023.11.07.566086do">https://doi.org/https://doi.org/10.1101/2023.11.07.566086do</a></p>
Pose-estimated 3D data of infant spontaneous activity from Helsinki and Pisa
<p>This dataset contains pose-estimated 3D (and 2D proxy) data as well as trained models for generating infant Kinetic Age, collected from research trials in Helsinki and Pisa. The dataset is organized into separate archives for metadata, data streams, trained models, and predictions. Below is a detailed breakdown of the dataset contents:</p> <p><strong>Metadata</strong></p> <ul> <li><em>metadata/combined.csv</em><br> - test_id: Unique identifier for each infant.<br> - corrected_age: Corrected age of the infant in days.<br> - outcome: Neurodevelopmental outcome labels (0 typical, 1 weak impairment, 2 MNI).</li> </ul> <p><strong>Data</strong></p> <ul> <li><em>data/features.csv</em><br> - Handcrafted movement features computed for each, by experts annotated, useful video segment.</li> <li><em>data/streams/combined/*.feather</em><br> - 3D recording segment, with 18 J, B, V, A streams over 600 time steps.</li> <li><em>data/streams_2d/combined/*.feather </em><br> - 2D recording segment, with 18 J, B, V, A streams over 600 time steps.</li> </ul> <p><strong>Results</strong></p> <ul> <li><em>results/model/fold_n/...</em><br> - train_predictions.npy: Predictions made on the training set.<br> - val_predictions.npy: Predictions made on the validation set.<br> - best_model.ckpt: Checkpoint file containing the saved model weights.<br> - metadata.json: Metadata describing the fold, including training parameters and validation segments.<br> - scatter_*.png: Regression results.</li> </ul> <p><strong>Predictions</strong></p> <ul> <li><em>predictions/jb-aagcn-coord-xy_predictions.csv</em><br> - Model predictions for the 2D model on MNI samples.</li> <li><em>predictions/jb-aagcn-coord_predictions.csv</em><br> - Model predictions for the 3D model on MNI samples.</li> </ul>
Data for Cell Reports paper "Cortex-wide spontaneous activity non-linearly steers propagating sensory-evoked activity in awake mice"
<p>Datasets for Cell Reports paper "Cortex-wide spontaneous activity non-linearly steers propagating sensory-evoked activity in awake mice", including mouse cortical neural activity recording (preprocessed), behavioral recording and other analysis results during intermedia computation steps.</p>
Separation of memory span and learning rate: evidence from behavior and spontaneous brain activity in older adults
<p>The data file includes two small files. The first file is Behavioral data. The second file is fMRI data. </p>
Evaluating Prognostic Contribution of Lactate on Recovery of Spontaneous Cardiac Activity After Cardiac Arrest
ClinicalTrials.gov study NCT03325452. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Early Echographic Asystole as a Predictive Factor of Absence of Spontaneous Circulatory Activity Recovery (SCAR) in Prehospital Cardio Respiratory Arrests (CRA)
ClinicalTrials.gov study NCT03494153. IPD Sharing: Not stated. Countries: 1. Publications: 3.
A Randomized, Double-blind, Placebo- and Active-controlled Study of the Electric Current Effects of ABT-639 on the Spontaneous Activity of Pain Sensory Receptors in Patients With Diabetic Peripheral N
ClinicalTrials.gov study NCT01589432. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Walking, Spontaneous Physical Activity and Lipid Oxidation After Dietary Treatment of Obesity
ClinicalTrials.gov study NCT00775970. IPD Sharing: Not stated. Countries: 1. Publications: 11.
Major oscillations in spontaneous home‑cage activity in C57BL/6 mice housed under constant conditions
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Data from: Predicting Stroop effect from spontaneous neuronal activity: a study of regional homogeneity
The Stroop effect is one of the most robust and well-studied phenomena in cognitive psychology and cognitive neuroscience. However, little is known about the relationship between intrinsic brain activity and the individual differences of this effect. In the present study, we explored this issue by examining whether resting-state functional magnetic resonance imaging (rs-fMRI) signals could predict individual differences in the Stroop effect of healthy individuals. A partial correlation analysis was calculated to examine the relationship between regional homogeneity (ReHo) and Stroop effect size, while controlling for age, sex, and framewise displacement (FD). The results showed positive correlations in the left inferior frontal gyrus (LIFG), the left insula, the ventral anterior cingulate cortex (vACC), and the medial frontal gyrus (MFG), and negative correlation in the left precentral gyrus (LPG). These results indicate the possible influences of the LIFG, the left insula, and the LPG on the efficiency of cognitive control, and demonstrate that the key nodes of default mode network (DMN) may be important in goal-directed behavior and/or mental effort during cognitive control tasks.
Data from: Membrane potential dynamics of spontaneous and visually evoked gamma activity in V1 of awake mice
Cortical gamma activity (30–80 Hz) is believed to play important functions in neural computation and arises from the interplay of parvalbumin-expressing interneurons (PV) and pyramidal cells (PYRs). However, the subthreshold dynamics underlying its emergence in the cortex of awake animals remain unclear. Here, we characterized the intracellular dynamics of PVs and PYRs during spontaneous and visually evoked gamma activity in layers 2/3 of V1 of awake mice using targeted patch-clamp recordings and synchronous local field potentials (LFPs). Strong gamma activity patterned in short bouts (one to three cycles), occurred when PVs and PYRs were depolarizing and entrained their membrane potential dynamics regardless of the presence of visual stimulation. PV firing phase locked unconditionally to gamma activity. However, PYRs only phase locked to visually evoked gamma bouts. Taken together, our results indicate that gamma activity corresponds to short pulses of correlated background synaptic activity synchronizing the output of cortical neurons depending on external sensory drive.
Data from: Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks
Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.
Data from: The use of functional data analysis to evaluate activity in a spontaneous model of degenerative joint disease associated pain in cats
Accelerometry is used as an objective measure of physical activity in humans and veterinary species. In cats, one important use of accelerometry is in the study of therapeutics designed to treat degenerative joint disease (DJD) associated pain, where it serves as the most widely applied objective outcome measure. These analyses have commonly used summary measures, calculating the mean activity per-minute over days and comparing between treatment periods. While this technique has been effective, information about the pattern of activity in cats is lost. In this study, functional data analysis was applied to activity data from client-owned cats with (n=83) and without (n=15) DJD. Functional data analysis retains information about the pattern of activity over the 24-hour day, providing insight into activity over time. We hypothesized that 1) cats without DJD would have higher activity counts and intensity of activity than cats with DJD; 2) that activity counts and intensity of activity in cats with DJD would be inversely correlated with total radiographic DJD burden and total orthopedic pain score; and 3) that activity counts and intensity would have a different pattern on weekends versus weekdays. Results showed marked inter-cat variability in activity. Cats exhibited a bimodal pattern of activity with a sharp peak in the morning and broader peak in the evening. Results further showed that this pattern was different on weekends than weekdays, with the morning peak being shifted to the right (later). Cats with DJD showed different patterns of activity from cats without DJD, though activity and intensity were not always lower; instead both the peaks and troughs of activity were less extreme than those of the cats without DJD. Functional data analysis provides insight into the pattern of activity in cats, and an alternative method for analyzing accelerometry data that incorporates fluctuations in activity across the day.
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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.
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.