Event

User population

Event- & trial-based experiments have an extensive history in behavioral and cognitive psychology. Fundamentally, data collection is carved up in time according to some ontology. Researchers may repeat Trial conditions in some manner to improve statistical power when contrasting a feature of interest versus a neutral baseline. Neuroscientists, in particular, may be interested in the moments before and after an Event to look at neurophysiological factors that predict or are predicted by a subject's behavior. What may differ between research groups is the ontology used to carve up time.

Key Projects

DataJoint has partnered with the following teams to interview key members, and develop individualized pipelines. By comparing across use-cases, the DataJoint team has developed a highly adaptable workflow to meet most needs, and trialize analyses within an existing DataJoint workflow.

Pipeline Development

In addition to the key projects listed above, the DataJoint team met with leaders from both Neurodata Without Borders and the Kepecs Lab, as these groups have both tackled the difficulty of developing ontologies that can cover all possible iterations of behavioral data collection. Our resulting structure is exemplified by the figure below. The language below is tailored to the dependent variable in many neuroscience experiments, behavior.

|----------------------------------------------------------------------------|
|-------------------------------- Session ---------------------------------|__
|------------------------------- Recording ------------------------------|____
|----- Block 1 -----|______|----- Block 2 -----|______|----- Block 3 -----|___
| Trial 1 || Trial 2 |____| Trial 3 || Trial 4 |____| Trial 5 |____| Trial 6 |
|_|e1|_|e2||e3|_|e4|__|e5|__|e6||e7||e8||e9||e10||e11|____|e12||e13|_________|
|----------------------------------------------------------------------------|

Features of Element Event include:

Each level of the hierarchy (Block, Trial, Event) is designed to be optional to suit a given experiment's needs. For example usage, visit our Array Electrophysiology Workflow.