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lab-descriptor.json
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lab-descriptor.json
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{
"broadArea": {
"name": "Biotechnology and Biomedical Engineering",
"link": "https://www.vlab.co.in/broad-area-biotechnology-and-biomedical-engineering",
"code": "BIO"
},
"lab": "Biosignal Processing and Analysis Lab",
"lab_display_name": "Biosignal Processing and Analysis Lab",
"deployLab": true,
"phase": 3,
"collegeName": "AMRT",
"baseUrl": "bpa-au.vlabs.ac.in",
"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.",
"experiments": [
{
"name": "Bio signal import and channel analysis",
"short-name": "channel-analysis",
"repo": "https://github.com/virtual-labs/exp-channel-analysis-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Time Frequency Analysis of Bio signals",
"short-name": "analysis-biosignals",
"repo": "https://github.com/virtual-labs/exp-analysis-biosignals-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Point processes and models",
"short-name": "point-processes",
"repo": "https://github.com/virtual-labs/exp-point-processes-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Analysis of biosignal activity and artifacts",
"short-name": "biosignal-activity-artifacts",
"repo": "https://github.com/virtual-labs/exp-biosignal-activity-artifacts-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Filtering and removal of artifacts in Biosignals",
"short-name": "artifacts-biosignals",
"repo": "https://github.com/virtual-labs/exp-artifacts-biosignals-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Power spectrum calculations using different windows",
"short-name": "power-spectrum-calculations",
"repo": "https://github.com/virtual-labs/exp-power-spectrum-calculations-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Study the changes in the PSDs by varying window width",
"short-name": "study-psds",
"repo": "https://github.com/virtual-labs/exp-study-psds-au",
"tag": "v1.0.1",
"deploy": true
},
{
"name": "Temporal structure in EEG",
"short-name": "eeg",
"repo": "https://github.com/virtual-labs/exp-eeg-au",
"tag": "v1.0.4",
"deploy": true
},
{
"name": "Motor unit firing pattern",
"short-name": "firing-pattern",
"repo": "https://github.com/virtual-labs/exp-firing-pattern-au",
"tag": "v1.0.0",
"deploy": true
},
{
"name": "Modeling network activity as in biological circuits",
"short-name": "biological-circuits",
"repo": "https://github.com/virtual-labs/exp-biological-circuits-au",
"tag": "v1.0.0",
"deploy": true
},
{
"name": "Modeling synaptic network connectivity",
"short-name": "network-connectivity",
"repo": "https://github.com/virtual-labs/exp-network-connectivity-au",
"tag": "v1.0.2",
"deploy": true
},
{
"name": "Reconstructing averaged population response",
"short-name": "population-response",
"repo": "https://github.com/virtual-labs/exp-population-response-au",
"tag": "v1.0.0",
"deploy": true
}
],
"targetAudience": {
"UG": [
"B. Tech./ B.E in Biotechnology/Microbiology/Bioinformatics/Biomedical Science"
],
"PG": [
"MS/Ph. D. Beginners in Biotechnology/Microbiology/Bioinformatics/Biomedical Science"
]
},
"objective": "To describe, analyze and process common biological signals.<br/> Processing EEG signals and specific events to analyze and classify event-driven variations with specific focus on underlying neural activity.<br/> To study basics of neuron models for understanding precise spiking behaviors, similar to the biological neurons<br/> To understand the computational basics of neural properties that drive network dynamics in large scale computational models.<br/> To study how single neuron can be scaled to replicate a network activity with different synaptic connections with neuron models.",
"courseAlignment": {
"description": "The syllabi of this lab aligns to the following universities in India.",
"universities": [
"Anna University Tamil Nadu",
"Visvesvaraya Technological University Karnataka",
"Jawaharlal Nehru Technological University Telangana",
"University of Calicut Kerala",
"University of Kerala Senate House Campus Kerala"
]
},
"version": "v1.5.0",
"exp_name": "Reconstructing averaged population response",
"exp_short_name": "population-response",
"production": true,
"current_item": {
"item": "feedback",
"target": "feedback.html",
"label": "Feedback"
},
"menu": [
{
"item": "aim",
"target": "index.html",
"source": "aim.md",
"label": "Aim"
},
{
"item": "theory",
"target": "theory.html",
"source": "theory.md",
"label": "Theory"
},
{
"item": "pretest",
"target": "pretest.html",
"source": "pretest.js",
"label": "Pre Test"
},
{
"item": "procedure",
"target": "procedure.html",
"source": "procedure.md",
"label": "Procedure"
},
{
"item": "simulation",
"target": "simulation.html",
"label": "Simulation"
},
{
"item": "posttest",
"target": "posttest.html",
"source": "posttest.js",
"label": "Post Test"
},
{
"item": "references",
"target": "references.html",
"source": "references.md",
"label": "References"
},
{ "item": "feedback", "target": "feedback.html", "label": "Feedback" }
]
}