LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Electrophysiological dataset from macaque visual cortical area MST in response to a novel motion stimulus

Photo from wikipedia

Establishing the cortical neural representation of visual stimuli is a central challenge of systems neuroscience. Publicly available data would allow a broad range of scientific analyses and hypothesis testing, but… Click to show full abstract

Establishing the cortical neural representation of visual stimuli is a central challenge of systems neuroscience. Publicly available data would allow a broad range of scientific analyses and hypothesis testing, but are rare and largely focused on the early visual system. To address the shortage of open data from higher visual areas, we provide a comprehensive dataset from a neurophysiology study in macaque monkey visual cortex that includes a complete record of extracellular action potential recordings from the extrastriate medial superior temporal (MST) area, behavioral data, and detailed stimulus records. It includes spiking activity of 172 single neurons recorded in 139 sessions from 4 hemispheres of 3 rhesus macaque monkeys. The data was collected across 3 experiments, designed to characterize the response properties of MST neurons to complex motion stimuli. This data can be used to elucidate visual information processing at the level of single neurons in a high-level area of primate visual cortex. Providing open access to this dataset also promotes the 3R-principle of responsible animal research. Measurement(s) spike train • eye movement measurement Technology Type(s) single-unit recording • eye tracking device Factor Type(s) direction, location, and speed of moving random dot patterns Sample Characteristic - Organism Macaca mulatta Sample Characteristic - Environment laboratory environment Sample Characteristic - Location Germany

Keywords: area; response; stimulus; dataset; macaque; motion

Journal Title: Scientific Data
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.