Questions tagged [neurons]

For questions about all aspects of a biological or artificial neuron.

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3
votes
2answers
105 views

How do layers in an artificial neural network transform inputs to outputs?

To me, most ANN/RNN related articles don't tell me actually how the network is implemented. I know that in the ANN you'll have multiple neurons, activation function, weights, etc. But, how do you, ...
4
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2answers
129 views

Neural Network with varying inputs (for a game ai)

I want to create a simple game which basically consists of 2d circles shooting smaller circles at each other (to make hitbox detection easier for the start). My goal is to create an ai which adapts ...
3
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1answer
35 views

Can a neuron have both a bias and a threshold?

I have not seen a neuron that uses both a bias and a threshold. Why is this?
0
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2answers
65 views

What determines the values of weights in a neural network?

I am trying to understand how weights are actually gotten. What is generating them in a neural network? What is the algorithm that gives them certain values?
2
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1answer
57 views

Is input normalization built-in into mammals sensory neurons?

The spectrum of human sensory inputs seems to fall within certain ranges suggesting normalization is built-in into biological NNs? It also adapts to circumstantial conditions, e.g. people living in a ...
3
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2answers
112 views

How do biological neurons weights get initialized?

When trying to map artificial neuronal models to biological facts it was not possible to find an answer regarding the biological justification of randomly initializing the weights. Perhaps this is ...
1
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0answers
16 views

Since there are different types of neurons in adjacent positions in the brain's arrays, should heterogeneous layers be developed?

Below is a taxonomy of neurons. Some of these types occur in different locations in the brain, but there are adjacent neurons of varying types with clearly functional type diversity in many parts of ...
1
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1answer
38 views

Neurological interpretation of LSTMs

I am searching for an Interpretation of LSTMs and recurrent neural Networks within Cognitive Neuroscience. Is there a mechanism in the human brain, that works analog to LSTMs? How does Long-term ...
1
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1answer
78 views

Maximum number of neurons in a layer given number of neurons in previous layer

Consider an extremely complicated feed-forward neural network training example but with no need of computational efficiency or limiting of processing time. What is the maximum number of hidden ...
14
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2answers
175 views

Are Modular Neural Networks more effective than large, monolithic networks at any tasks?

Modular/Multiple Neural networks (MNNs) revolve around training smaller, independent networks that can feed into each other or another higher network. In principle, the hierarchical organization ...
1
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0answers
43 views

How does the degree of neuronal realism affect computing in a deep learning scenario?

Neurons can be simulated using different models that vary in the degree of biophysical realism. When designing an artificial neuronal network, I am interested in the consequences of choosing a degree ...
8
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3answers
124 views

Is there research that employs realistic models of neurons?

Is there research that employs realistic models of neurons? Usually, the model of a neuron for a neural network is quite simple as opposed to the realistic neuron, which involves hundreds of proteins ...
2
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3answers
574 views

Are AI algorithms capable of self-repair?

Do AI algorithms exist which are capable of healing themselves or regenerating a hurt area when they detect so? For example: In humans if a certain part of brain gets hurt or removed, neighbouring ...
6
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3answers
282 views

How to model inhibitory synapses in the artificial neuron? [Biological inspiration]

In the brain some synapses are stimulating and some inhibiting. ReLu erases that property to only stimulating once, since in the brain inhibition doesn't mean 0 output, but more precisely - negative ...
4
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1answer
1k views

Do we know what the units of neural networks will do before we train them?

I apologize if this is a repeated question or if this is too simple. I was learning about back-propagation and looking at the algorithm there is no particular 'partiality' given to any unit. What I ...
7
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3answers
658 views

What makes animal brain so special?

So this is an introductory question. Whenever I read any book about Neural Nets or Machine Learning, their introductory chapter says that we haven't been able to replicate the brain's power due to its ...
3
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1answer
114 views

Spiking Neural Network Resources

I'm very interested in writing a Spiking Neural Network engine (SNN) from scratch, but I can't find the basic information I need to get started. For example, I've seen pictures of the individual ...
5
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1answer
235 views

Is the neuron adequately comprehended?

It is possible that the signal handling of a neuron is outside the engineering comprehension of the most astute of human brains, even after the relationships of inputs to outputs are statistically ...
1
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1answer
198 views

Comments on my proposed “Jitter” neuron

I have an application of neural networks (standard MLP architecture) where I want to forecast a tanh output (ranging from -1 to +1) with about 1500 input features in ~700 samples. Each sample ...
6
votes
1answer
312 views

How many nodes/hidden layers are required to solve a classification problem where the boundary is a sinusoidal function?

A single neuron is capable of forming a decision boundary between linearly seperable data. Is there any intuition as to how many, and in what configuration, would be necessary to correctly approximate ...
6
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5answers
4k views

When will the number of neurons in AI systems equal the human brain?

Based on fitting to historical data and extrapolation, when is it expected that the number of neurons in AI systems will equal those of the human brain? I'm interested in a possible direct ...
5
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1answer
205 views

What is the calcium equivalent role in neural networks

I understand that neural networks model biological neurons. Each node in the network represents a neuron cell and the connections between nodes represent the connections between cells. As in nature, ...
28
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4answers
881 views

How to find the optimal number of neurons per layer?

When you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?