Learn · Computational Neuroscience
Lecture 34 of 60Week 7
Lecture 34 : Measuring Spike Train Distances - II
Prof. Sharba Bandyopadhyay · IIT Kharagpur
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All the lectures
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Lecture 46 : Long Term Plasticity
- Lecture 47 : Spike Time Dependent Plasticity
- Lecture 48 : Hebbian Plasticity
- Lecture 49 : BCM Rule
- Lecture 50 : Synaptic Normalization
- Lecture 51 : Adaptation
- Lecture 52 : Models of Short Term Plasticity
- Lecture 53 : Attention - I
- Lecture 54 : Attention - II
- Lecture 55 : Developmental Cicuits
- Lecture 56 : Optimal Coding in Visual System
- Lecture 57 : Optimal Coding in Auditory System
- Lecture 58 : Optimal Coding of Deviant Stimuli in Development
- Lecture 59 : Spike Timing Dependent Plasticity - a theoretical Perspective
- Lecture 60 : Important Problems in Neuroscience