Overview

This course is a system, design-oriented course aimed to provide exposure to Neuroscience and its importance in the real world. Neuroscience and Neuro- Instrumentation are popular research areas and this course is an introduction to both. The emphasis is on Electro-physiology with an introduction to standard Biological Stimulators and signal conditioning circuits. Expected course outcomes:
• Introduction to EEG and Event-Related Potentials (ERPs).
• Introduction to Brain-Computer Interface (BCI) and its applications.
• Applications using ERPs to screen for disorders of Cognition.
• Introduction to ERP stimulators and signal conditioning circuits.
• Demonstration of EEGLab and ERPLab for EEG and ERP signal processing

Syllabus

Introductory Neuroscience & Neuro-Instrumentation Intro.
01 - Cellular (Microscopic) Structure of the Central Nervous System (CNS).
02 Anatomical (Macroscopic) structure of the CNS.
03 Introduction to Cleanroom and IC Fabrication Techniques.
04 Introduction to EEG applications for Hearing Loss.
05 Electrophysiological Recordings.
06 Neocortical Circuits.
07 The resting Membrane Potential.
08 Applications of MEMS Fabrication Technologies.
09 Fundamentals of biopotentials and applications.
10 Fundamentals of EEG and applications.
11 The Action Potential (1).
12 The Action Potential (2).
13 Axonology, Neuronal Biophysics (1).
14 Axonology, Neuronal Biophysics (2).
15 Experimental Setup for EEG Recording.
16 Introduction to Cleanroom Protocols and Demonstration of Gowning Procedure.
17 Electromagnetic Stimulation of the Brain (1).
18 Electromagnetic Stimulation of the Brain (2).
19 Introduction to Event Related Potentials.
20 Introduction to 3D Printing.
21 3D Printing: Applications and Demonstrations.
22 Introduction to Event Related Potentials (2).
23 Different Event Related Potentials.
24 Different Event Related Potentials (2).
25 Introduction to Silicone Wafer Processing Techniques.
26 Basics of Silicone Dioxide: Oxidation, Characterization and Applications.
27 Inverse Problem, EEG source localization.
28 Inverse Problem, EEG source localization (2).
29 Introduction to Brain Computer Interfaces.
30 Signal Conditioning Circuit for EEG Bioamplifiers.
31 Basics of BCI Experimentation: Introdcution BCI Applications.
32 Different Brain Computer Interfaces.
33 Introduction to EEGLAB, ERPLAB and AEP Demonstration.
34 Introduction to EEGLAB, ERPLAB and AEP Demonstration (2).
35 Introduction to Photolithography.
36 Basics of BCI Experimentation: Stimuli Generation and Insertion.
37 MMN Demonstration with EEGLAB and ERPLAB (1).
38 MMN Demonstration with EEGLAB and ERPLAB (2).
39 Introduction to Photolithography (2).
40 Basics of Instrumentation Amplifier and Online Simulation.
41 Basics of BCI Experimentation: Experimental Setup and Biopotential Acquisition.
42 P300 Demonstration with EEGLAB/ERPLAB (1).
43 P300 Demonstration with EEGLAB/ERPLAB (2).
44 Wavelet Analysis with VEP (1).
45 Details of Lithography, E-beam Lithography and Mask Aligner.
46 Basics of BCI Experimentation: Signal Acquisition using MATLAB (EEGLAB).
47 Wavelet Analysis with VEP (2).
48 Demonstration: Resting Membrane Potential.
49 Demonstration: Membrane Time Constant (τ).
50 Photoresist (SU-8) and soft lithography.
51 Physical Vapour Deposition: Thermal Evaporation.
52 Introduction to Epilepsy and Classification.
53 Epileptogenisis.
54 Demonstration: Membrane Length Constant (λ).
55 Demonstration: Action Potential.
56 Demonstration: Voltage Clamp.
57 Demonstration: Synaptic Potentials & Current.
58 Physical Vapour Deposition: E-beam Evaporation.
59 Physical Vapour Deposition: Sputtering.
60 Recent Trends: Epilepsy Classification using EEG data.
61 Demonstration: Wireless EEG with dry electrodes.
62 Basics of EEG, ERP and acquisition.
63 Phtotolithography with example.
64 Stress Tissue Analysis using COMSOL Multiphysics.
65 Recent Trends: Microelectrode Arrays and Deep Brain Stimulation.