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Interact with the Synaptic Physiology Dataset

The Synaptic Physiology Dataset allows users to explore interactions between cell subclasses in mouse and human cortex. There are a variety of ways to access the data based on your interests.


Online Jupyter notebooks

Hosted by, these notebooks provide an interactive environment for accessing, analyzing, and visualizing results from the Synaptic Physiology Dataset. This provides a quick way to begin interacting with the data in your browser, but some Python experience is recommended.

Note: instances will shut down after 10 minutes of inactivity. These are great for quickly exploring the dataset, but not appropriate for prolonged data analysis.

Explore notebooks in MyBinder

Interactive desktop tools

Explore the Synaptic Physiology Dataset with interactive tools. Choose cell classes of interest and synaptic metrics to see an overview of cortical synaptic physiology. Requires installation of a Python programming environment on your local machine.

Getting started with Synaptic Physiology tools

Access the data directly via our API

The Synaptic Physiology Python programming packages provide access to three sqlite databases, described below, as well as the original NWBv1 (HDF5) data files.

Getting started with the Synaptic Physiology API



Synaptic Physiology Database

The Synaptic Physiology Dataset is available as three different sqlite files, each increasing in content and size. It is recommended that you download the database files directly from our API or contact us for other options.



(~170 MB)


(~7 GB)


(>160 GB)

experiment metadata

tissue source, experimental conditions

chemical / electrical connections

connection probability

cell properties

transgenic class, layer, morphology, intrinsic physiology

per-connection average properties

strength, kinetics, dynamics,

averaged synaptic responses,

electrical connection properties

per-connection synaptic release models

quantal release parameters,

short-term plasticity

per-stimulus response properties

curve fits to individual synaptic responses


per-stimulus spike properties

timing and measurements of individual presynaptic spikes


stimulus / recording metadata


per-stimulus response data

time-series data for every presynaptic spike and corresponding postsynaptic recording