Search Results for "model-builder"

mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). Toolbox Paper: http://dx.doi.org/10.3389/fnhum.2016.00604 Methods Paper: https://doi.org/10.3389/fnins.2021.705621

...The software combines deconvolution for detection, and variable length template matching approaches for screening out false positive events. Eventer also includes a machine learning-based approach allowing users to train a model to implement their ‘expert’ selection criteria across data sets without bias. Sharing models allows users to implement consistent analysis procedures. The software is coded in MATLAB, but has been compiled as standalone applications for Windows, Mac and Linux. Please visit the official Eventer website for more info https://eventerneuro.netlify.app/ While the paper is in preparation, please cite as; Winchester, G., Liu, S., Steele, O.G., Aziz, W. and Penn, A.C. (2020) Eventer. ...

MCTC4BMI (Multimodal Compressed Sensing and Tensor Decomposition for Brain-Machine Interfaces) is a MATLAB toolbox designed to process and analyze EEG data. It applies compressed sensing and tensor decomposition techniques to improve brain-machine interface (BMI) performance.

BPL (Bayesian Program Learning) is a MATLAB implementation of the Bayesian Program Learning framework for one-shot concept learning (especially on handwritten characters). The approach treats each concept (e.g. a character) as being generated by a probabilistic program (motor primitives, strokes, spatial relationships), and inference proceeds by fitting those generative programs to a single example, generalizing to new examples, and generating new exemplars. The repository contains code for...

Implementation of duration high-order hidden Markov model (DHO-HMM) in Matlab with application in speech recognition.

MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab.

An implementation of a new proposed model of smoothly spiking neural networks + a fully analytical gradient descent algorithm.