Course10210510060 lectures
Computational Neuroscience
Prof. Sharba Bandyopadhyay · IIT Kharagpur
About
Computational Neuroscience is the fundamental subject to provide quantitative understanding of information processing by neurons in the brain. Questions on, how humans and other animals learn efficiently, create and recall memories, make decisions among many others can be approached with the basic understanding of computation by neurons and its general principles. The course will include topics starting with the very basics of quantifying neuronal activity and modeling spiking by single neurons. Next the course dwells upon the general approaches used to understand representation of information by neurons and how such information may be readout for practical applications. Finally the course covers the computational modeling of implementing plasticity, the most important aspect of the brain, aiding in learning, memory and cognition.
Intended audience: Students interested in Neural and Cognitive Sciences and AI
Prerequisites: 1st year college Mathematics and Biology
Lectures
Week 1
- Lecture 01 : Neuron structure
- Lecture 02 : Networks of Neurons and Synapses
- Lecture 03 : Basic Structures in the Brain
- Lecture 04 : Systems of neural processing
- Lecture 05 : Methods of Recording Neural Activity
Week 2
- Lecture 06 : Membrane Potential and All or None Spike
- Lecture 07 : Patch Clamp Measurements
- Lecture 08 : Ion channels
- Lecture 09 : Current injection: Synapses
- Lecture 10 : Single Neuron Activity
Week 3
- Lecture 11 : Point and compartmental models of neurons
- Lecture 12 : Hodgkin Huxley Equations - I
- Lecture 13 : Hodgkin Huxley Equations – II
- Lecture 14 : Reducing the HHE and Moris-Lecar Equations (MLE)
- Lecture 15 : Properties of MLE
Week 4
- Lecture 16 : Phase Plane Analysis - I
- Lecture 17 : Phase Plane Analysis - II
- Lecture 18 : Phase Plane Analysis - III
- Lecture 19 : Analyzing HHE with Phase Plane Analysis -I
- Lecture 20 : Analyzing HHE with Phase Plane Analysis -II
Week 5
- Lecture 21 : Random variables and random process
- Lecture 22 : Spike train statistics and response measure
- Lecture 23 : Receptive fields and models of receptive fields
- Lecture 24 : Stimulus to Response mapping(Coding) - I
- Lecture 25 : Stimulus to Response mapping(Coding) - II
Week 6
- Lecture 26: Stimulus to Response Mapping(Coding) - III
- Lecture 27: Response to Stimulus Mapping (Decoding)
- Lecture 28: Basics of Information Theory - I
- Lecture 29: Basics of Information Theory - II
- Lecture 30: Maximally Informative Dimensions
Week 7
- Lecture 31 : Intro to Discrimination based methods
- Lecture 32 : Kullback Leibler Distance
- Lecture 33 : Measuring Spike Train Distances - I
- Lecture 34 : Measuring Spike Train Distances - II
- Lecture 35 : Signal and Noise Correlations
Week 8
- Lecture 36: Statistical Methods in Discrimination
- Lecture 37: Single Cell Decoding - I: Two Alternative Forced Choice task in Monkeys
- Lecture 38: Single Cell Decoding - II: Using ROC Curves for discrimination
- Lecture 39: Single Cell Encoding - I: Operant Conditioning Task in Ferrets
- Lecture 40: Single Cell Encoding - II: Learning in avoidance and approach methods in Ferrets
Week 9
- Lecture 41: Plasticity - Synaptic Transmission and Synaptic Strength
- Lecture 42: Ways of modification of Synaptic Strength
- Lecture 43: Type of Plasticity
- Lecture 44: Short Term Plasticity - I
- Lecture 45: Short Term Plasticity - II
Week 10
- Lecture 46 : Long Term Plasticity
- Lecture 47 : Spike Time Dependent Plasticity
- Lecture 48 : Hebbian Plasticity
- Lecture 49 : BCM Rule
- Lecture 50 : Synaptic Normalization
Week 11
- Lecture 51 : Adaptation
- Lecture 52 : Models of Short Term Plasticity
- Lecture 53 : Attention - I
- Lecture 54 : Attention - II
- Lecture 55 : Developmental Cicuits
Week 12
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Kharagpur
- Department
- Biotechnology
- Teacher
- Prof. Sharba Bandyopadhyay
- Level
- Undergraduate
- Language
- English
- Subjects
- Biology
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed