GeNN is a GPU enhanced Neuronal Network simulation environment supporting multiple frontends and backends. Spiking neural network models can be specified directly in Python or C++ or through interfaces to Brian 2, SpineCreator (SpineML), or PyNN.
This is a diffusion-weighted MRI processing Matlab toolbox (including binaries), which can be used to: • Compute the Q-Ball Imaging Orientation Distribution Function in Constant Solid Angle (CSA-ODF) (Aganj et al, MRM 2010).
Neuroimaging researchers require a diverse collection of bespoke command-line and graphical tools to analyse data and answer research questions. Installing and maintaining a neuroimaging software setup is challenging and often results in un-reproducible environments.
Understanding of how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education.
Clinica is a software platform for clinical research studies involving patients with neurological and psychiatric diseases and the acquisition of multimodal data (neuroimaging, clinical and cognitive evaluations, genetics…), most often with longitudinal follow-up.
A whole-cortex macaque structural connectome constructed from a combination of axonal tract-tracing and diffusion-weighted imaging data. Created for modeling brain dynamics using TheVirtualBrain (thevirtualbrain.org) platform. A detailed description and example usage can be found in the paper here: https://www.
World Wide Series Seminar Kilosort is a software package for identifying neurons and their spikes in extracellular electrophysiology, a process known as “spike sorting”. Kilosort has been primarily developed and tested on the Neuropixels 1.
World Wide Series Seminar Suite2P is a very modular imaging processing pipeline written in Python which allows you to perform registration of raw data movies, automatic cell detection, extraction of calcium traces and infers spike times.
The BigPint package can help examine any large multivariate dataset. However, we note that the example datasets and example code in this package consider RNA-sequencing datasets. If you are using this software for RNA-sequencing data, then it can help you confirm that the variability between your treatment groups is larger than that between your replicates and determine how various normalization techniques in popular RNA-sequencing analysis packages (such as edgeR, DESeq2, and limma) affect your dataset.
Extracellular microelectrodes frequently record neural activity from more than one neuron in the vicinity of the electrode. The process of labeling each recorded spike waveform with the identity of its source neuron is called spike sorting and is often approached from an abstracted statistical perspective.