NeuroGPU
NeuroGPU is software that reduces computation time required for compartmental modeling and model optimization by leveraging the parallel processing of GPUs. It's is open source, and seamlessly interfaces with the NEURON simulation environment, enabling utilization of existing model databases. It really shines when trying to optimize models to best recapitulate experimental data, as this process lends itself well to parallelization.
Software developed by Roy Ben-Shalom, Ph.D. and his team of URAP Students.
Classification of Layer 5 pyramidal neurons in mouse prefrontal cortex
The Bender lab found that D1R-, D2R-, and D3R-expressing pyramidal neurons in L5 mPFC can be distinguished by electrophysiological properties (Clarkson et al. 2017). Here, we provide the necessary code for other labs to replicate this classification with their own recordings, assuming that they match recording conditions (e.g. calcium buffer, stimulus parameters, etc - see README as well as Clarkson et al., 2017 methods for details). All code written by Becky Clarkson.
Deconvolution-based event detection for spontaneous synaptic events
This is a direct port of Pernía-Andrade et al's event detection protocols into our Igor Pro-based aquisition software. It is, bar none, the best event detection algorithm we've ever used for minis. Like anything in ephys, garbage-in, garbage-out. But if you can get your baseline noise down to the 2 pA range, picking out 2.5 pA minis is trivial. Provided here as an example of what one could do in their own analysis software. All code written by Ken Burke.
Visualization tool for SCN2A variants
This is a visualization tool to allow one to identify where within the NaV1.2 channel a particular variant lies. The 4th transmembrane voltage sensor is in light blue in each domain. The ion selectivity filter is comprised of the 4 black dots (DEKA). See our TINS article for more detail about the structure of this channel and associated channelopathies. Code written by Sindy Law.
