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Brain imaging (fMRI, EEG), neural recordings, connectome, cognitive experiments, psychology
1,736 datasets
A study by Xuru Wang collected functional near-infrared spectroscopy (fNIRS) data from 43 undergraduate students during an emotion regulation task before and after a 30-minute moderate-intensity cycling session. The dataset, last updated in March 2026, includes measurements of prefrontal cortex activation under conditions of viewing neutral and negative images, cognitive reappraisal, and expressive suppression. The data is shared under a CC-BY-4.0 license on figshare.
A 72.4 ks Chandra ACIS exposure from 2000 January 24-25 analyzed the globular cluster Omega Centauri. The catalog contains 180 detected X-ray sources to a limiting flux of ~4.3 x 10^-16 erg/cm^2/s, with an estimated 45-70 sources identified as cluster members. The analysis, published by NASA, explores the population of accreting compact binaries like cataclysmic variables and active binaries.
Sifan Wang published a dataset on figshare in March 2026. It contains EEG functional connectivity data from 48 patients with disorders of consciousness, comparing minimally conscious state and unresponsive wakefulness syndrome groups. The data includes measurements during resting state and four emotional music conditions, quantified using weighted phase lag index.
Histology images from Oprm1-cre rats for analysis of dopamine neurons in the substantia nigra pars compacta (SNc) after striosomal manipulation. The dataset was contributed by author Salcido, Alexis and hosted on Harvard Dataverse, with a last update recorded on 2026-05-26.
A 20.9 MB worksheet details brain sampling regions for counting Fos protein expression following cortical neuron stimulation. The dataset is based on the Paxinos & Watson rat brain atlas and was authored by Ileana Morales. It was last updated on April 12, 2026, and is shared under a CC-BY-4.0 license.
Raw counts of Fos+ neurons in distant brain structures following targeted stimulation of OFC hotspot, insula hotspot, or a caudal OFC/rostral insula coldstrip. The dataset is a 233.0 KB XLSX file authored by Ileana Morales and last updated on April 12, 2026. It likely contains tabular data quantifying neuronal activity in response to specific experimental manipulations.
A study of 80 participants (40 young, 40 older adults) investigated the relationship between glutathione (GSH) levels and cognitive integrity, effort, and endurance. Data includes GSH measurements via magnetic resonance spectroscopy (HERMES) in the inferior frontal and parietal cortices, collected at baseline and during cognitive tasks. The dataset was authored by Geraldine Rodríguez-Nieto and last updated on 2026-03 18.
Sara Santos Silva recorded single-unit activity from three pigeon brain regions (MVL, Wulst, NCL) while birds viewed videos of conspecifics and control shapes performing behaviors like courtship and flying. The dataset, shared on figshare in March 2026, contains neural recordings used to analyze population feature coding of motion features. The findings suggest avian visual structures use sparse coding principles similar to the visual cortex.
A finite element brain model incorporating axonal fiber tracts derived from a group-averaged tractography atlas. The model was validated against experimental data from postmortem human subject tests and used in reconstruction simulations of eight real-world mTBI cases. The dataset, authored by Noritoshi Atsumi and last updated in March 2026, is a 3.4 MB PDF file shared under a CC-BY-4.0 license.
A single clinical case report documents a 61-year-old female patient with a 22-year history of drug-refractory nausea and vomiting later diagnosed as Neuronal Intranuclear Inclusion Disease (NIID). The report details diagnostic findings from diffusion-weighted imaging, genetic analysis of the NOTCH2NLC gene, and skin biopsy, along with the patient's response to corticosteroid therapy over a six-month follow-up. The dataset, a 19.1 KB DOCX file, was authored by Long Luo and published on figshare under a CC-BY-4.0 license.
Elena Carbone's study dataset from 2026 includes survey responses from 552 participants aged 50–84 years. It examines relationships between personal views of aging, quality of life, and cognitive reserve proxies. The data was collected using standardized questionnaires including the Attitudes Toward Own Aging scale and the Awareness of Age-Related Change questionnaire.
Avinash Veerappa published this dataset on figshare in March 2026. It contains transcriptomic data from four brain regions—midbrain, DLPFC, NAc, and amygdala—profiled to study substance use disorders. The analysis identified unique and shared gene signatures, including 186 genes exclusive to the midbrain and 442 in the amygdala.
186 to 442 unique genes were identified in four key brain regions of substance-use cases versus controls. This dataset contains transcriptomic profiles from the midbrain, dorsolateral prefrontal cortex, nucleus accumbens, and amygdala, analyzed with clustering and network methods. The data was uploaded by Avinash Veerappa in March 2026 under a CC-BY-4.0 license.
Avinash Veerappa published this transcriptomic dataset on figshare in March 2026. It contains gene expression profiles from four brain regions—midbrain, dorsolateral prefrontal cortex, nucleus accumbens, and amygdala—comparing cases with chronic substance use to controls. The analysis identified unique and shared differentially expressed genes and enriched pathways related to addiction neurocircuitry.
A 2026 study by Avinash Veerappa profiles gene expression in four brain regions to investigate substance use disorders. The dataset contains transcriptomic signatures from the midbrain, dorsolateral prefrontal cortex, nucleus accumbens, and amygdala, identifying unique and shared genes. Analysis includes clustering, biclustering, WGCNA, and pathway enrichment results.
Transcriptomic data from four brain regions—midbrain, dorsolateral prefrontal cortex (DLPFC), nucleus accumbens (NAc), and amygdala—profiled to study substance use disorders. The dataset identifies 186, 29, 160, and 442 unique differentially expressed genes for each region respectively, along with shared signatures. It was published by Avinash Veerappa on figshare under a CC-BY-4.0 license and last updated in March 2026.
186 to 442 unique differentially expressed genes were identified across four brain regions (midbrain, DLPFC, NAc, amygdala) in a study of chronic substance use. The dataset contains results from transcriptome profiling, clustering, and network analysis, authored by Avinash Veerappa and last updated in March 2026. It is shared under a CC-BY-4.0 license on figshare.
186 to 442 unique differentially expressed genes were identified in each of four brain regions (midbrain, DLPFC, NAc, amygdala) from cases versus controls. The dataset contains results from transcriptome profiling and network analysis, authored by Avinash Veerappa and last updated in March 2026. It is a 27.5 KB Excel file shared under a CC-BY-4.0 license on figshare.
186 unique genes were identified in the midbrain, 29 in the DLPFC, 160 in the NAc, and 442 in the amygdala in this transcriptomic study of substance use disorders. The dataset, created by Avinash Veerappa and last updated in March 2026, profiles gene expression across four brain regions to identify shared and unique molecular signatures associated with addiction. It results from clustering, biclustering, WGCNA, and pathway enrichment analyses of case versus control samples.
Avinash Veerappa published transcriptomic data from four brain regions in 2026. The dataset contains gene expression signatures from the midbrain, dorsolateral prefrontal cortex, nucleus accumbens, and amygdala, comparing cases with chronic substance use to controls. Analysis identified 186, 29, 160, and 442 unique differentially expressed genes per region, respectively, and shared pathways like CREB Signaling in Neurons.