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Catalog
ASAP is committed to accelerating the pace of discovery and informing a path to a cure for Parkinson’s disease through collaboration, research-enabling resources, and data sharing. We’ve created this catalog to showcase the research outputs and tools developed by ASAP-funded programs.
Code
surmeierlab/EZT2022SA: EZTNotebooks
This repository contains five Jupyter Notebooks (Python 3.0) created or modified for specific use with action potential analysis for the Zampese, et.al. 2022 Science Advances paper.
Teams
Code
Day2023 R code and analysis
Datasets for all figures 1-8 in: GABAergic regulation of striatal spiny projection neuron excitability depends upon their activity state.
Image is taken from Fig 1B inset and illustrates RiboTag-eGFP in SPNs of the striatum.
Teams
Code
RectiPy software package
Recurrent neural network training in Python (RectiPy) is a software package developed by Richard Gast that allows for lightweight implementations of recurrent neural networks (RNNs) based on ordinary or delayed differential equations. Here, the team provides a tool that allows for the implementation of biologically informed spiking neural networks and optimizes the parameters of these networks via gradient descent.
Teams
Code
State-dependent GABAergic regulation of striatal spiny projection neuron excitability: NEURON + Python model of striatal projection neurons
This repository contains a NEURON + Python model of striatal projection neurons (or SPNs) designed to simulate the interaction between GABAergic and glutamatergic synaptic inputs.
Teams
Code
Richert/Heterogeneous_SNNs: v1.0.0: Scripts to replicate the results of Gast et al. PNAS 2024
This release includes configuration files and scripts to replicate the main results presented in Gast et al. PNAS 2024, including Python scripts for the simulation, bifurcation analysis, and training of networks of Izhikevich neurons with heterogeneous spike thresholds.
Teams