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Dataset results
25 results for “feedback modulation”
The integration of sensory feedback in the modulation of anuran landing preparation
<p class="MsoBodyText">Controlled landing requires preparation. Mammals and bipedal birds vary how they prepare for landing by predicting the timing and magnitude of impact from the integration of visual and non-visual information. Here we explore how an animal that moves primarily through hopping, <i>Rhinella marina</i>, the cane toad, integrates sensory information to modulate landing preparation. Earlier work suggests toads may modulate landing preparation using predictions of impact timing and/or magnitude based on non-visual sensory feedback during takeoff rather than visual cues about the landing itself. Here we disentangled takeoff and landing conditions by hopping toads off platforms of different heights and measured electromyographic (EMG) activity of an elbow extensor, <i>m. anconeus</i>, and used high-speed motion capture to quantify whole body and forelimb kinematics to test how toads integrate visual and non-visual information in landing preparation. We asked two questions: 1) when they conflict, do toads correlate landing preparation with takeoff or landing conditions? And 2) for hops with the same takeoff conditions, does visual information alter the timing of landing preparation? We found that takeoff conditions are a better predictor of the onset of landing preparation than landing conditions, but that visual information is not ignored. When hopping off higher platforms, toads start to prepare for landing later when takeoff conditions are invariant. This suggests that, unlike mammals, toads prioritize non-visual sensory feedback about takeoff conditions to coordinate landing, but that they do integrate visual information to fine-tune landing preparation.</p>
Dataset (Part II) accompanying the paper "In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1"
<p><strong>This is Part II of the dataset (from sub-06 to sub-09).</strong> Due to size constraints, the remaining subjects can be found in the following records: <em>Dataset (Part I) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (from sub-01 to sub-05) and <em>Dataset (Part III) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (sub-10)</p>
Dataset (Part III) accompanying the paper "In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1"
<p><strong>This is Part III of the dataset (sub-10). </strong> Due to size constraints, the remaining subjects can be found in the following records: <em>Dataset (Part I) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (from sub-01 to sub-05) and <em>Dataset (Part II) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (from sub-06 to sub-09) </p>
Dataset (Part I) accompanying the paper "In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1"
<p><strong>This is Part I of the dataset (from sub-01 to sub-05).</strong> Due to size constraints, the remaining subjects can be found in the following records: <em>Dataset (Part II) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (from sub-06 to sub-09) and <em>Dataset (Part III) accompanying the paper 'In the Brain of the Beholder: Bi-Stable Motion Reveals Mesoscopic-Scale Feedback Modulation in V1'</em> (sub-10)</p>
Data - "Suppressing feedback signals to visual cortex abolishes attentional modulation"
<p>Data associated with article "Suppressing feedback signals to visual cortex abolishes attentional modulation"</p>
Recorded neural data from: Nonlinear feedback modulation contributes to the optimization of flexible decision-making
Open the record for dataset details and reuse information.
The integration of sensory feedback in the modulation of anuran landing preparation
Open the record for dataset details and reuse information.
Macrosystems EDDIE Module 4: Macro-Scale Feedbacks
Environmental phenomena are often driven by multiple factors that interact across space and over time. In freshwater lakes and reservoirs worldwide, carbon cycling and subsequent carbon dioxide (CO2) and methane (CH4) fluxes are changing due to local, regional, and continental drivers. In this module, students will learn how to set up a lake model and "force" the model with climate scenarios to test hypotheses about how local and global drivers will interact to promote or suppress greenhouse gas fluxes in different lakes. The overarching goal of this module is for students to explore new modeling and computing tools while learning fundamental concepts about how non-linear macrosystem-level phenomena (e.g., lake greenhouse gas fluxes) can occur through macro-scale feedbacks. The A-B-C structure of this module makes it flexible and adaptable to a range of student levels and course structures. This dataset contains instructional materials and the files necessary to run the complete module. Readers are referred to the GLM science manual (Hipsey et al. 2014; 2019) for further details on model configuration.
Plant landscape abundance and soil fungi modulate drought effects on plant-soil feedbacks
<p class="MsoNormal"><span>Plant-soil feedbacks (PSF) play an important role in determining plant community structure and dynamics. However, previous studies have provided mixed results for the relationship between PSF and plant landscape abundance (i.e., abundance across local communities). This may reflect the mediation of climate factors on PSF. Here, we tested how PSF of tree species varied with local abundances by growing seedlings in conspecific versus heterospecific soil and how simulated drought altered PSF-plant abundance relationships. Six tree species were selected and half of the seedlings were grown under ambient moisture conditions, while the others experienced a 2-month period of drought following 3-months of growth under ambient moisture conditions. Fungal communities in the rhizosphere soil were analysed using DNA </span><span>amplicon</span><span> sequencing to link shifts in soil fungi to the observed PSF. We found that drought reduced negative PSF for all plant species except one species (</span><em><span>Lithocarpus lohangwu</span></em><span>)</span><span>. In the drought treatments, PSF were positively correlated with the relative abundance of total putative pathogens, but negatively correlated with the proportion of unique pathogens (those pathogens that were present in conspecific soil rather than heterospecific soil, thereby potentially species-specific). </span><span>In addition, we found that PSF </span><span>only significantly predicted plant relative abundance in the drought treatment, indicating that abiotic stress made PSF a stronger predictor of plant landscape abundance. This finding also implies that future extreme drought events could promote the dominance of the abundant plant species, thereby leading to the loss of biodiversity.</span><span> Collectively, our results provide evidence for microbial mechanisms of PSF and suggest that accounting for abiotic stress can make PSF a stronger predictor of plant landscape abundance due to the omnipresence of stress under natural conditions.</span></p>
Aphasia Rehabilitation: Modulating Cues, Feedback & Practice
ClinicalTrials.gov study NCT01597037. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Plant landscape abundance and soil fungi modulate drought effects on plant-soil feedbacks
Open the record for dataset details and reuse information.
Data for "Visual feedback modulates the 1/f structure of movement amplitude time series"
<p>The spreadsheet "Time-series, power-spectra, ANOVA, and figure data.xlsx" contains data relevant to the article "Visual feedback modulates the 1/<em>f</em> structure of movement amplitude time series." The file contains movement amplitude time series and the corresponding power spectra for all participants in all conditions. In addition, the file includes data submitted to ANOVA and data used to plot all article figures.</p>
Key data used in "Western North Pacific tropical cyclone activity modulated by phytoplankton feedback under global warming" submitted to Nature Climate Change
<p>Key data</p>
MicroRNA-221/222 modulate intestinal T helper 17 cell response as a negative feedback rheostat downstream of IL-23
GEO Series GSE160250. Mus musculus. 43 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Evaluation of Neuroprosthesis with Sensory Feedback for Modulation of Phantom Limb Pain and Enhancing Quality of Life
ClinicalTrials.gov study NCT06702904. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Role of Oxytocin in Modulating the Effects of Social Feedback on Achieving Personal Goals
ClinicalTrials.gov study NCT02740101. IPD Sharing: Not stated. Countries: 1. Publications: 0.
An NKX2-1/ERK/WNT feedback loop modulates gastric identity and response to targeted therapy in lung adenocarcinoma.
GEO Series GSE145152. Mus musculus. 21 samples. Type: Expression profiling by high throughput sequencing.
An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feedback Interactions [gene expression]
GEO Series GSE31791. Mus musculus. 12 samples. Type: Expression profiling by array.
An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feedback Interactions [ChIP-seq]
GEO Series GSE31640. Mus musculus. 14 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feedback Interactions [methylation]
GEO Series GSE33191. Mus musculus. 24 samples. Type: Methylation profiling by genome tiling array.
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.