Neural Connections and Brain Function Quiz

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What is a limitation of a perceptron model?

It requires extensive computational power

It is not suitable for classification tasks

It cannot learn complex patterns

It can only solve linearly separable problems (correct)

In the context of the text, who is described as an expert in Financial Markets and Algorithmic Trading Analytics?

Watanabe

Dr. Anand Jayaraman (correct)

Marc Chagall

Vincent van Gogh

What does the text suggest is the best learning system known to us?

Logistic regression model

Linear regression model

Simple perceptron model

Biological neural system (correct)

What animal was able to discriminate between paintings by Van Gogh and Chagall with 95% accuracy?

Pigeons Signup and view all the answers

What do mice in the text have the ability to memorize?

Mazes Signup and view all the answers

Which unit is considered fundamental in biological neural networks?

Neurons Signup and view all the answers

What is used to overcome the limitations of a perceptron model?

Multi-layer perceptron Signup and view all the answers

What is the key idea behind Hebbian Learning?

Strengthening synapses that are used more Signup and view all the answers

In the context of machine learning, what is the primary focus in determining synaptic strength?

Finding the optimal weights consistent with the given data Signup and view all the answers

What characteristics does a Perceptron model capture?

Input, Weights, Bias, Dot Product Signup and view all the answers

Why are Perceptrons considered brittle?

Their sensitivity to small changes in input data Signup and view all the answers

How does a Perceptron make decisions?

By weighing up evidence from inputs Signup and view all the answers

What method is used to train a Perceptron effectively?

Changing weights to minimize error Signup and view all the answers

What is the relationship between a neuron's input and its weights in the Perceptron model?

z = w ∙ x models the weighted sum of inputs Signup and view all the answers

What triggers the release of neurotransmitter substances at the synapse?

Spikes travelling along the axon of the pre-synaptic neuron Signup and view all the answers

According to Donald Hebb, how does a synapse get strengthened?

By releasing more neurotransmitter Signup and view all the answers

In computational neurons, what determines the input to the next neuron based on synaptic strength?

Strength of the synaptic connections Signup and view all the answers

What happens when the strength of a synaptic connection is weak?

Results in weaker paths through the network Signup and view all the answers

Which component influences one neuron on another and is learnt by feedback or observation?

Synaptic strengths Signup and view all the answers

How does Donald Hebb describe the learning process in neural networks?

By applying larger weights to connections that are used more Signup and view all the answers

What determines whether a synapse gets stronger or weaker according to Hebbian learning?

The frequency of use of the synapse Signup and view all the answers

What triggers the action potential in post-synaptic neurons?

Integration of excitatory and inhibitory signals Signup and view all the answers

What is the purpose of using a different activation function in a Sigmoid Neuron?

To ensure a smooth output transition from 0 to 1. Signup and view all the answers

In logistic regression, what do weight coefficients (W) represent?

Features or attributes of the data. Signup and view all the answers

How is the probability of a vehicle being fitted with a manual transmission estimated in logistic regression using the MTcars dataset?

By fitting a single logistic regression unit on the dataset. Signup and view all the answers

What is the purpose of using the sigmoid function in artificial neural models like the Perceptron?

To introduce non-linearity in the model. Signup and view all the answers

Which component of an artificial neural model estimates the probability of a binary outcome in logistic regression?

Activation function. Signup and view all the answers

What does a small change in weight result in for a Sigmoid Neuron's output?

A smooth change in output. Signup and view all the answers

How are weight coefficients determined in logistic regression for a classification task?

Learned from the dataset during training. Signup and view all the answers

In an artificial neural model, what does the sigmoid function output when z is large and positive?

~ 1 Signup and view all the answers