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155
datasets available to search
ShareScore release 0.9.0
Dataset results
155 results for “learning and memory”
Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance
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Memory reactivation in slow wave sleep enhances relational learning
<p>EEG raw files in Brain Product format (3 files per participant). Sleep EEG recordings from healthy volunters under TMR stimulation. </p> <p>Two conditions: up-going slow oscillation stimulation / down-going oscillation stimulations</p> <p>Two type of sounds: experimental (they hear them before) and control (completely new)</p> <p>Triggers: 100-112 up experimental sounds / >112 up control sounds / 1-12 down experimetal sounds / 12-100 down control</p> <p>Please cite:</p> <p>"Memory reactivation in slow wave sleep enhances relational learning" ( https://doi.org/10.1101/2022.03.29.486197 )</p> <p> </p>
Raw data for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning"
<p>This is the raw dataset for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning". Each .xlsx file represents an experimental results of a single participant.</p> <p>Directory description:</p> <p>Eng_sham - the results from experiments without stimulation on English sample from Medvedeva, 2019.</p> <p>Eng_vlPFC - the results from experiments with vLPFC stimulation on English sample from Medvedeva, 2019.</p> <p>enc_off_new - the results from experiments with dLPFC offline encoding stimulation on Russian sample.</p> <p>enc_on_new - the results from experiments with dLPFC online encoding stimulation on Russian sample.</p> <p>sham_no stimulation - the results from experiments without stimulation offline encoding stimulation on Russian sample.</p> <p>vlPFC_stimulation - the results from experiments with vLPFC stimulation on Russian sample.</p> <p>Age.xlsx - the ages of the participants</p> <p> </p>
Data from two studies of learning in visual span working memory tasks.
<p>Data from two working memory span tasks. The span set size could be up to six, and each row in each .csv is one response (i.e., one "click" on an item). Thus, each trial's data is spread out on multiple rows, with accuracy being a binary variable.</p>
Extracting Session Keys From the Main Memory Using Brute-force and Machine Learning
<p>This dataset contains:</p> <ol> <li>Heap dump of three version of OpenSSH (V_7_9_P1, V_8_0_P1 and V_8_1_P1)</li> <li>Heap dump of two applications that uses TLS (lynx and curl)</li> <li>Network recording in format of pcap</li> <li>JSON file that contains the keys' information</li> </ol> <p>The source code is available at: https://github.com/smartvmi/SSH-TLS-key-extraction</p>
Data from: Long-term anti-predator learning and memory N. canaliculata
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Simulation data from: Dynamics of immune memory and learning in bacterial communities
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STM, locomotion and survival raw data for: A neural m6A/Ythdf pathway is required for learning and memory in Drosophila
<p>The files contain raw and summarized data files for the STM, locomotion and survival experiments published in the manuscript entitled " A neural m6A/Ythdf pathway is required for learning and memory in Drosophila". Instructions on how to process data and further information is found in the "summary" file.<br> </p>
Physical Activity is Associated with Reduced Implicit Learning but Enhanced Relational Memory and Executive Functioning in Young Adults
<p>This file contains all data reported in the main analyses of our paper, including age, gender, BMI, Stroop effect, implicit learning sessions 1 and 2, relational memory, and all physical activity variables</p>
The role and mechanism of TLR4-siRNA in the impairment of learning and memory in young mice induced by isofurane
<p>This package contains six files:</p> <p>Supplementary Table 1. Morris water maze test results of each group;</p> <p>Supplementary Table 2. TLR4, TNF-ɑ and IL-6 expressions in the hippocampus of each group detected with qPCR and WB;</p> <p>Supplementary Table 3. Serum TNF-ɑ and IL-6 levels of mice in each group detected with ELISA;</p> <p>Supplementary Table 4. Apoptosis rate detected with TUNEL staining;</p> <p>Supplementary Table 5. BDNF and CREB1 mRNA expressions detected with qPCR;</p> <p>Supplementary Table 6. BDNF, CREB1, ERK1/2 and JNK protein expressions detected with WB.</p>
Dataset for "A Double Dissociation between Savings and Long-Term Memory in Motor Learning"
<p>Data for "A Double Dissociation between Savings and Long-Term Memory in Motor Learning"<br> <br> For analysis code and any updates, please visit https://github.com/AlkisMH/Savings_vs_Long_Term_Memory<br> <br> For any questions, please contact Alkis Hadjiosif (alkis [at] seas [dot] harvard [dot] edu; ahadjiosif [at] gmail [dot] com)</p> <p>These .mat files contain data collected for Experiments 1-4 and S1, used to reproduce Figures 1-6 and S1 in the paper. Data for each experiment are in the form of a Matlab structure, with each field consisting of a [Num_trials x Num_participants] matrix.</p> <p>The fields are:</p> <p><strong>TN:</strong> Trial Number</p> <p><strong>VF:</strong> Whether visual feedback was given during the trial (1: online visual feedback; 2: no visual feedback)</p> <p><strong>Rotation:</strong> The visuomotor rotation imposed on each trial (in degrees). CCW is positive, CW is negative.</p> <p><strong>Wait:</strong> Whether, right before the trial, a wait time was imposed (1) or not (0). Trials immediately following breaks are indicated by (2).</p> <p><strong>Instruction:</strong> Whether an instruction was given for the trial (1) or not (0). Only present in Experiment 3. Note that Experiment 3 includes:</p> <p>-> Two specific instruction trials during learning and and two during relearning, before and after the 1-minute wait ("Move your hand to the center of the target","Move your hand to the far end of the target")</p> <p>-> Six random instruction trials before initial learning and six before relearning ("Move your hand to the left/right/near/far end of the target"), to familiarize participants with the instruction process</p> <p><strong>ITI:</strong> Time (in seconds) since the last trial (regardless of direction).</p> <p><strong>theta_target:</strong> Target direction (in degrees) relative to the 12 o'clock position. Only included for Experiment 4: target is always at 12 o'clock for Experiments 1-3.</p> <p><strong>theta:</strong> = reaching direction relative to theta_target, measured 150ms into the movement. Note that this is flipped based on the rotation sign so that adaptation towards the imposed visuomotor rotation is always positive.</p> <p><strong>theta_end:</strong> = reaching direction relative to theta_target, measured at the end of movement. Only included for Experiment 4: it is to be used for the no visual feedback blocks in Experiment 4.</p> <p>Note for <strong>Experiment 4</strong>: the last two blocks (last 114 trials) were done on day 2.</p>
Data From: Rapid expansion and visual specialisation of learning and memory centers in the brains of Heliconiini butterflies
<p class="MsoNormal">Changes in the abundance and diversity of neural cell types, and their connectivity, shape brain composition and provide the substrate for behavioral evolution. Although investment in sensory brain regions is understood to be largely driven by the relative ecological importance of particular sensory modalities, how selective pressures impact the elaboration of integrative brain centers has been more difficult to pinpoint. Here, we provide evidence of extensive, mosaic expansion of an integration brain center among closely related species, which is not explained by changes in sites of primary sensory input. By building new datasets of neural traits among a tribe of diverse Neotropical butterflies, the Heliconiini, we detected several major evolutionary expansions of the mushroom bodies, central brain structures pivotal for insect learning and memory. The genus <em>Heliconius</em>, which exhibits a unique dietary innovation, pollen-feeding, and derived foraging behaviors reliant on spatial memory, shows the most extreme enlargement. This expansion is primarily associated with increased visual processing areas and coincides with increased precision of visual processing, and enhanced long-term memory. These results demonstrate that selection for behavioral innovation and enhanced cognitive ability occurred through expansion and localized specialization in integrative brain centers.</p>
The Effect of Cannabidiol in Learning and Memory of Adults
ClinicalTrials.gov study NCT06074172. IPD Sharing: YES. Countries: 1. Publications: 1.
CONNEX-3: A Study to Test Whether Iclepertin Improves Learning and Memory in People With Schizophrenia
ClinicalTrials.gov study NCT04860830. IPD Sharing: YES. Countries: 18. Publications: 1.
Data from: Nematode mind: Exploring the role of the RNAi pathway in learning, memory and beyond
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Impacts of predation risk on learning and memory of free-living mice
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Data From: Rapid expansion and visual specialisation of learning and memory centers in the brains of Heliconiini butterflies
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Single-trial learning leads to mid-term memory formation in an ant during an appetitive but not an aversive task
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Learning strategies and long-term memory in Asian short-clawed otters (Aonyx cinereus) data
<p>Data submitted here, are those used in the writing of our manuscript entitled "Learning strategies and long-term memory in Asian short-clawed otters (<i>Aonyx cinereus</i>)" which has been submitted to Royal Society Open Science for publication. Abstract for that manuscript is below</p> <p>Social learning, namely learning from information acquired from others or their products, is widespread throughout the animal kingdom. There is growing evidence that animals selectively employ 'social learning strategies', which for example, determine when<i> </i>they should copy others instead of learning asocially, and whom they should copy. Furthermore, once animals have acquired new information, it is beneficial for them to commit it to long-term memory, especially when it concerns the discovery of profitable resources. Research into social learning strategies and long-term memory has covered a wide range of taxa. However, otters (subfamily Lutrinae), popular in zoos due to their sociability and playfulness, remained neglected until a recent study provided evidence of social learning in captive smooth-coated otters (<i>Lutrogale perspicillata</i>), but not in Asian short-clawed otters (<i>Aonyx cinereus</i>). We investigated Asian short-clawed otters' learning strategies and long-term memory performance in a foraging context. We presented novel extractive foraging tasks twice to captive family groups and used network-based diffusion analysis to provide evidence of social learning and long-term memory in this species. A major cause of wild Asian short-clawed otter declines is prey scarcity. Furthering our understanding of how they learn about and remember novel food sources could inform key conservation strategies.</p>
Data from: Social foraging extends associative odor-food memory expression in an automated learning assay for Drosophila melanogaster
<p>Animals socially interact during foraging and share information about the quality and location of food sources. The mechanisms of social information transfer during foraging have been mostly studied at the behavioral level, and its underlying neural mechanisms are largely unknown. Fruit flies have become a model for studying the neural bases of social information transfer, because they provide a large genetic toolbox to monitor and manipulate neuronal activity, and they show a rich repertoire of social behaviors. Fruit flies aggregate, they use social information for choosing a suitable mating partner and oviposition site, and they show better aversive learning when in groups. However, the effects of social interactions on associative odor–food learning have not yet been investigated. Here, we present an automated learning and memory assay for walking flies that allows the study of the effect of group size on social interactions and on the formation and expression of associative odor–food memories. We found that both inter-fly attraction and the duration of odor–food memory expression increase with group size. This study opens up opportunities to investigate how social interactions during foraging are relayed in the neural circuitry of learning and memory expression.</p>
ScienceDex guides
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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.