Neural coding Flashcards
(65 cards)
What is encoding? simple answer
For a given stimulus, you want to know what the response is. This is stochastic. P(r|s)
What is decoding? simple answer
For a given response, you want to know what the stimulus was. P(s|r)
How can neurons encode information?
In their firing rates, the timing of their spikes, the combined firing patters of many cells
What are 3 types of encoding?
rate encoding, temporal encoding, phase encoding
What are 4 types of decoding?
classifiers, template based decoding, bayesian decoding, regression
What is rate code?
how much a neuron is firing in response to a stimulus
What is temporal code?
Precise timing of individual spikes
What is synchrony code?
Timing of spikes in relation to eachother
What are tuning curves?
type of rate code. On the x-axis the stimulus paramter and on the y-axis is the firing rate,
What is positive about having multiple cells? Looking at population code
The more cells you have the more things you can distinguish, there is more robustness to noise and more neuronal variability
what does stochastic mean?
random
Why is decoding from single cells problematic?
if the cell is participating in a population ccode instead.
when we fire with 30 Hertx, we cant really say if it was -20 or + 20 degrees. Because its a bell curve.
What does training of a decoder mean?
the decoder learns to associate between the stimuli and the response
What are Classifiers?
wants to make a decision boudary/ seperating hyperplane, and uses that to make a decision
- it finds the best line/hyperplane to seperate classes to make predictions.
1: train the decoders: put labels on every response associated with a stimulus. find the best line between the data
2: predict the label for the new data points according to the position relative to the decision boundary
What is template-based decoding?
Making a template by calculating the average activity to each stimulus. when there is a new vector you look how similar it is to each template. the highest correlation coefficient is the prediction.
you need to find maximum correlation coefficient
1: train the decoder. put labels on every response associated with stimulus
step 2: make themplate by calculating the average for each stimulus
step 3: calculate correlation coefficient between test population vector and each templatehat
is the pearson correlation?
normalizes the covariance with the standard deviations
Bayesion decoding?
uses bayes theorem to maximisze the posterior or likelihood
regression?
predicts continous data
How can you predict the position of an animal in a box
by stakcing tuning curves. you look at each point what the expected activity is. the stack of tuning curves is your reference population vector
P(s)
what is the probability that the stimulus is s
P(r)
what is the probability that the repsonse is r
p(r|s)
if we know what the stimulus is, what is the probability that the response is r?
Formula of Bayes theorem
P(r|s) P(s)
____________ = P(s|r)
P(r)
Posterior in bayes theorem
p(s|r). we have a dog who is happy, what is the probability that the stimulus is that he got a present?