Enabling Event-driven Computation in Brain Dynamics
Brain is characterized by the discrete spiking events, which are the fundamental units of computation in the brain.
BrainEvent provides a set of data structures and algorithms for such event-driven computation, which can be used to
model the brain dynamics in a more efficient and biologically plausible way.
Particularly, it provides the following class to represent binary events in the brain:
EventArray: representing array with a vector/matrix of events.
Furthermore, it implements the following commonly used data structures for event-driven computation of the above class:
COO: a sparse matrix in COO format for sparse and event-driven computation.CSR: a sparse matrix in CSR format for sparse and event-driven computation.CSC: a sparse matrix in CSC format for sparse and event-driven computation.BlockCSR: a block sparse matrix in CSR format for sparse and event-driven computation.BlockELL: a block sparse matrix in ELL format for sparse and event-driven computation.JITC_CSR: a just-in-time connectivity sparse matrix in CSR format for sparse and event-driven computation.JITC_CSC: a just-in-time connectivity sparse matrix in CSC format for sparse and event-driven computation.FixedPreNumConn: a fixed number of pre-synaptic connections for sparse and event-driven computation.FixedPostNumConn: a fixed number of post-synaptic connections for sparse and event-driven computation.- ...
BrainEvent is fully compatible with physical units and unit-aware computations provided in BrainUnit.
Installation
You can install brainevent via pip:
pip install brainevent --upgrade
Documentation
The official documentation is hosted on Read the Docs: https://brainevent.readthedocs.io/
See also the brain modeling ecosystem
We are building the Brain Modeling ecosystem: https://brainmodeling.readthedocs.io/
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Metadata
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Release files for brainevent 0.0.1.post20250422
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