Biotechnology and Biomedical Engineering
AMRITA VISHWA VIDYAPEETHAM
Introduction
This lab provides a platform for EEG data analysis and visualization for understanding the correlations of neural activity through electroencephalography data. Experiments designed in this lab help student communities to acquire expertise on fundamental tools that were necessary to describe, analyze and process common biological signals. With the recent trends of interest from computational neuroscience research, the experimental strategies were featured with models of neurons to understand general properties of neural networks and to graphically visualize how biological neurons work with computational efficiency. The lab focuses on an open-source signal analysis platform that can also be extended by students from across the internet.
To describe, analyze and process common biological signals.
Processing EEG signals and specific events to analyze and classify event-driven variations with specific focus on underlying neural activity.
To study basics of neuron models for understanding precise spiking behaviors, similar to the biological neurons.
To understand the computational basics of neural properties that drive network dynamics in large scale computational models.
To study how single neuron can be scaled to replicate a network activity with different synaptic connections with neuron models.
Processing EEG signals and specific events to analyze and classify event-driven variations with specific focus on underlying neural activity.
To study basics of neuron models for understanding precise spiking behaviors, similar to the biological neurons.
To understand the computational basics of neural properties that drive network dynamics in large scale computational models.
To study how single neuron can be scaled to replicate a network activity with different synaptic connections with neuron models.
No reference books available.