<p>I'm looking for a neural network model with specific characteristics. This model may not exist...</p>

<p>I need a network which doesn't use "layers" as traditional artificial neural networks do. Instead, I want [what I believe to be] a more biological model.</p>

<p>This model will house a large cluster of interconnected neurons, like the image below. A few neurons (at bottom of diagram) will receive input signals, and a cascade effect will cause successive, connected neurons to possibly fire depending on signal strength and connection weight. This is nothing new, but, there are no explicit layers...just more and more distant, indirect connections.</p>

<p>As you can see, I also have the network divided into sections (circles). Each circle represents a semantic domain (a linguistics concept) which is the core information surrounding a concept; essentially a semantic domain is a concept.</p>

<p>Connections between nodes within a section have higher weights than connections between nodes of different sections. So the nodes for "car" are more connected to one another than nodes connecting "English" to "car". Thus, when a neuron in a single section fires (is activated), it is likely that the entire (or most of) the section will also be activated.</p>

<p><strong>All in all, I need output patterns to be used as input for further output, and so on.</strong> A cascade effect is what I am after.</p>

<p>I hope this makes sense. Please ask for clarification where needed.</p>

<p>Are there any suitable models in existence that model what I've described, already?</p>

<p><img src="https://i.sstatic.net/78V2s.jpg" alt="enter image description here"></p>

CC BY-SA 3.0
2012-11-14T23:53:53.940Z
it's not really clear to me what the goal of this neural network is, what the distinction between "layer" and the circles in your diagram, or why this is "more biological". If you are interested in neural networks of semantic cognition, there are several. Perhaps you could start here: http://psych.stanford.edu/~jlm/papers/McCRogers03.pdf
Jeff
CC BY-SA 3.0
2012-11-15T00:45:07.013Z
Awesome, I'll have a look. The goal of this network is to translate a word from English to Spanish. It does so by separating storage of words from concepts. The concept of a car is used by both English and Spanish. Given that we start in English and want to end with Spanish, the network will find the Spanish word corresponding to the car concept.
Chad Johnson
CC BY-SA 3.0
2012-11-15T01:08:56.857Z
ah interesting! keep in mind there is a lot of literature on bilingualism and translation out there; there is at least some evidence to suggest translating does *not* need to activate semantic features (perhaps two lexical nodes are joined at the lemma level).
Jeff
CC BY-SA 3.0
2012-11-15T18:58:33.173Z
Ah, so you're saying there is evidence that when translating, we need to think of the meaning behind a given concept...we just access the concept itself (essentially a reference to the concept) and then we just find linked words?
Chad Johnson
CC BY-SA 3.0
2012-11-15T19:01:05.710Z
yes, basically. most models of spoken word production posit at least 3 levels: semantic features, lemma, and phonemes. if words of different language share the same lemma (this is debated), then translating a word may involve going up only one level, from phonemes to lemma, and then back down to the phonemes of another language, without accessing the semantic features of a word
Jeff
CC BY-SA 3.0
2012-11-15T19:07:49.063Z
Awesome. I would think lemmas are semi-shared across languages. For example, English speakers and Spanish speakers generally possess concepts of automobiles, cats, and airplanes, and so those speaking both English and Spanish probably reuse these lemmas. However, a tribal man may not possess these concepts, but, each of these things could be explained using one or more sentences. This is where the difficulty comes in: translating  when there are only similar or non-existent lemmas in the target language.
Chad Johnson
CC BY-SA 3.0
2012-11-15T19:18:28.413Z
yes, i agree lemmas are probably shared, but that is an empirical question. and yes, translating a word from a language in which no suitable word exists in the target language probably does rely on different processes, but this is relatively rare
Jeff
CC BY-SA 3.0
2013-09-09T14:17:32.253Z
This is a naive view of translation. Translation is much, much more complicated than a 1 to 1 mapping between words... even though the economic stakes are huge, we are still very, very far from machine translation. (Douglas Hofstadter has written some interesting books on the difficulty of translation, if you are interested).
Timothée Behra
CC BY-SA 3.0
2015-03-28T11:30:02.850Z
I'm voting to close this because the question as written is both too broad and lacks important context.
Christian Hummeluhr
<neural-network><artificial-intelligence>
Does this neural network model exist?
Chad Johnson
# Does this neural network model exist?

(Asked by: username_0 on 2012-11-14)

I'm looking for a neural network model with specific characteristics. This model may not exist...

I need a network which doesn't use "layers" as traditional artificial neural networks do. Instead, I want [what I believe to be] a more biological model.

This model will house a large cluster of interconnected neurons, like the image below. A few neurons (at bottom of diagram) will receive input signals, and a cascade effect will cause successive, connected neurons to possibly fire depending on signal strength and connection weight. This is nothing new, but, there are no explicit layers...just more and more distant, indirect connections.

As you can see, I also have the network divided into sections (circles). Each circle represents a semantic domain (a linguistics concept) which is the core information surrounding a concept; essentially a semantic domain is a concept.

Connections between nodes within a section have higher weights than connections between nodes of different sections. So the nodes for "car" are more connected to one another than nodes connecting "English" to "car". Thus, when a neuron in a single section fires (is activated), it is likely that the entire (or most of) the section will also be activated.

**All in all, I need output patterns to be used as input for further output, and so on.** A cascade effect is what I am after.

I hope this makes sense. Please ask for clarification where needed.

Are there any suitable models in existence that model what I've described, already?

![enter image description here](https://i.sstatic.net/78V2s.jpg)

**Tags:** neural-network, artificial-intelligence

> **Comments:**
> **username_1**: it's not really clear to me what the goal of this neural network is, what the distinction between "layer" and the circles in your diagram, or why this is "more biological". If you are interested in neural networks of semantic cognition, there are several. Perhaps you could start here: http://psych.stanford.edu/~jlm/papers/McCRogers03.pdf  
> **username_0**: Awesome, I'll have a look. The goal of this network is to translate a word from English to Spanish. It does so by separating storage of words from concepts. The concept of a car is used by both English and Spanish. Given that we start in English and want to end with Spanish, the network will find the Spanish word corresponding to the car concept.  
> **username_1**: ah interesting! keep in mind there is a lot of literature on bilingualism and translation out there; there is at least some evidence to suggest translating does *not* need to activate semantic features (perhaps two lexical nodes are joined at the lemma level).  
> **username_0**: Ah, so you're saying there is evidence that when translating, we need to think of the meaning behind a given concept...we just access the concept itself (essentially a reference to the concept) and then we just find linked words?  
> **username_1**: yes, basically. most models of spoken word production posit at least 3 levels: semantic features, lemma, and phonemes. if words of different language share the same lemma (this is debated), then translating a word may involve going up only one level, from phonemes to lemma, and then back down to the phonemes of another language, without accessing the semantic features of a word  
> **username_0**: Awesome. I would think lemmas are semi-shared across languages. For example, English speakers and Spanish speakers generally possess concepts of automobiles, cats, and airplanes, and so those speaking both English and Spanish probably reuse these lemmas. However, a tribal man may not possess these concepts, but, each of these things could be explained using one or more sentences. This is where the difficulty comes in: translating  when there are only similar or non-existent lemmas in the target language.  
> **username_1**: yes, i agree lemmas are probably shared, but that is an empirical question. and yes, translating a word from a language in which no suitable word exists in the target language probably does rely on different processes, but this is relatively rare  
> **username_2**: This is a naive view of translation. Translation is much, much more complicated than a 1 to 1 mapping between words... even though the economic stakes are huge, we are still very, very far from machine translation. (Douglas Hofstadter has written some interesting books on the difficulty of translation, if you are interested).  
> **username_3**: I'm voting to close this because the question as written is both too broad and lacks important context.  

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## 0 answers

