For questions about the function and structure of both biological and artificial neural networks (ANNs), and for the applications of ANNs to modeling in cognitive science.

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What do the weights of an artificial neural network represent in biological neurons?

In artificial neural networks the connections between neurons are a assigned numbers called "weights" or "parameters". As new data is fed into the neural net, these weights change. This is how the ...
3
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0answers
28 views

Why do we train the threshold as a weight in neural networks?

Why do we train the threshold as a weight? I understand the process of how to do it (the bias and augmented weight vector) but do not get the importance or practical applications of doing so.
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0answers
36 views

What exactly is an astroglial calcium wave?

There are quite a few conflicting reports as to what stimulates them, how they propagate, whether they communicate intercellularly, and what they look like. The only consistent information I can ...
3
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2answers
56 views

Hebbian Learning - Understanding Simultaneous Firing

Im beginning to write a neural network simulator in Java and thinking of Hebbian Learning but Im stuck at one thing: What causes two neurons to fire at the same interval while only one of them is ...
8
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1answer
65 views

Does an action potential abolish an excitatory postsynaptic potential?

From some sources, I've read that excitatory postsynaptic potentials (EPSPs) decay over time, which would imply that they aren't abolished by action potentials. However, other sources seem to indicate ...
8
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1answer
63 views

Does a recent general review of recurrent neural networks exist?

Does anyone know of a comparatively recent paper reviewing the literature on psychological applications of recurrent neural networks? I'm looking for a paper which provides a general overview of the ...
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1answer
42 views

Is the weight of neural inputs in the human brain as central as it is for neurons in an artifical neural network?

As an example of an artificial neural net (ANN), a neural processing unit (NPU) is able to encode previous (learned) information by storing a weighted resistance for each input. Since ANN's are ...
6
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1answer
79 views

How does the brain break down visual information for processing? What “channels” is visual input broken into?

Some time ago I remember reading about how the human brain breaks down visual information into a number of individual "channels". For example, one channel might focus on edges and lines, another ...
3
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0answers
19 views

What is the equivalent of a Hamming network in the NEF?

After doing a bit of research, I'm somewhat convinced that Hamming networks are networks that classify, but only put out a single result, as opposed to other networks which output multiple results. In ...
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0answers
19 views

A simple derivation of the generalization bounds for the classical perceptron model

I'm basically referring to the great work of Elizabeth Gardner in this matter. I find that her work is often overlooked in the field of neuroscience, arguably because it is too difficult to understand ...
4
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2answers
131 views

Why is it so difficult to use a “true mirror” as a mirror

This Youtube video shows what a "true mirror" is: https://www.youtube.com/watch?v=ZSxCZCy5Wsk In short, when you look into a true mirror you look at yourself (among other things) as you really are, ...
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2answers
133 views

How is the biological accuracy of ANNs typically measured?

I am referring to the computational neuroscience side of neural network research that focuses on biological accuracy. I've read references to improving biological realism (using say spiking neurons ...
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2answers
71 views

Reference request in Circuit and Signals for Computational Neuroscience

In the area of computational neuroscience, there are basic theories from electric circuits and signal processing to be applied. For background study, which reference will be more suitable ? ...
0
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1answer
35 views

What is an example of a learning machine that achieves zero variance?

I'm attempting to find an example of a learning machine/neural network that achieves zero variance, but I am having a hard time finding an example anywhere. Variance is defined as the generalization ...
2
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2answers
81 views

How many action potentials from presynaptic neurons would be required to make a postsynaptic neuron fire?

I am looking for a rough estimation of the number of action potentials from other neurons required to cause a neuron to fire? I read here that a potential of ~ -55mv must be reached before an action ...
5
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1answer
50 views

What's the functional difference between the NEF and normal ANNs?

Aside from obvious biological plausibility, from a computational standpoint, what's the motivation of using the Neural Engineering Framework (NEF) instead of Artificial Neural Networks (ANNs) for ...
2
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0answers
71 views

Differences between the many versions of neuromorphic hardware [closed]

There is a ton of neuromorhpic hardware being pumped out these days. Off the top of my head, I can name IBM (BlueGene and TrueNorth), Qualcomm, Neurogrid, Brainstorm (Neurogrid 2.0), Spinnaker, ...
5
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0answers
65 views

What functions does the brain perform to recognize a familiar object unconsciously?

Let's say a person's brain experiences how a vehicle/object looks for the very 1st time. It would require lot of attention/focus/processing to analyse the object, extract features and train its neural ...
8
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1answer
119 views

Spiking Neural Network Simulation: Measuring and Classifying Bump Attractor States

I am currently working with Spiking Neural Networks and multi-(meta)-stable attractor states. What I observe in my simulations are 'bump' attractors that appear, disappear, and may wander around. ...
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2answers
30 views

Are there any programmes to identify modular “NeuroBricks”?

In synthetic biology, an organization called the BioBricks Foundation tries to identify modular biological components that are amenable to engineering design, and publishes them in the Registry of ...
3
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2answers
3k views

What is the difference between biological and artificial neural networks?

I read that neural networks are of two types: a) Biological neural networks b) Artificial neural networks (or ANN) I read, "Neural Networks are models of biological neural structures," and the ...
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2answers
234 views

How distantly related are research in computational neuroscience and neural networks/machine learning?

If one is more interested in understanding how algorithms in the biological brain solve problems (theoretically, particularly the mathematical aspect), and possibly in building brain-inspired ...
10
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3answers
168 views

What kinds of information can (and cannot) be extracted from connectome?

Several scientific projects are trying to map the connectome, such as The Human Connectome Project. The connectomes of other organisms, such as C. elegans, have been mapped already. Having an ...
10
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1answer
75 views

Why do long range axons in mammals travel in white matter tracts?

I am curious to know as to why long range, myelinated axons prefer to convene and form white matter tracts, rather than simply reach its target in an arbitrary fashion. Is there some kind of ...
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1answer
43 views

Why do I get smaller accuracy when I use 80% of training sets using HMAX model?

I am trying to compute the accuracy of the HMAX model. I am using the Face category (containing 435 images) from the Caltech101 database. I split it into $x$ ...
3
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1answer
172 views

What causes a muscle to be unsteady?

I have noticed for myself that sometimes, certain muscles may become unsteady. Here are three examples: Sometimes it is more difficult to hold my hand still in the air. Another example is how my ...
4
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1answer
82 views

What does a cortical column do?

The Blue Brain project led by Henry Markram focused on simulating cortical columns under the idea they form basic processing units of the brain/cognitive function. What does a cortical column do? I ...
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1answer
143 views

Is it truly necessary to upgrade Tononi's criteria of consciousness in the Integrated Information theory?

I am referring specifically to a very recent paper by Max Tegmark. In this paper he proposes 3 more criteria (independence, dynamics, and utility principle) in addition to Tononi's original criteria ...
5
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1answer
175 views

Computational model of biological object recognition

The human brain can achieve a remarkable ability to recognize visual patterns in an Invariant, selective and fast manner. The human visual system is quite powerful. It has an exquisite selectivity ...
5
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1answer
177 views

When a person starts to scratch, why does this often start others to scratch?

Often, when a person starts scratching and complains of being itchy, whether they suggest there might be a bug biting them (for example fleas, head lice, mites) another person with them will start to ...
5
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0answers
38 views

What kind of feed-back scheme is there for a back-propagation feed-forward ANN for self-learning of touching a coordinate with robot arm?

I'm a beginner in this topic and are learning how to build an artificial neural network and different types of training associated with them. Right now, I'm trying to figure out self learning. For ...
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2answers
178 views

As for future mind control/reading technology, can humans fight it?

As of recent times, rats have communicated through wireless brain implants, from across the globe. Also, recent fMRI technologies have allowed prediction of movements (or intention), and the ...
3
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2answers
138 views

Why neural architecture is not hardwired for N-dimensional vision but hardwired for abstract math?

In The Theoretical Minimum, in lecture 1, Leonard Susskind says that you can only visualize 3 dimentional images. (see yourself). Therefore, he says, in order to deal with N dimensions, you need to ...
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3answers
205 views

Is there any recent work on modeling how we rapidly acquire new knowledge?

I work with neural network models of human cognition a lot, and one thing that bugs me about them is the timescale: they learn over thousands of trials whereas humans seem to learn after a couple ...
2
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1answer
69 views

Is the energy of an action potential divided among multiple axon terminals?

My understanding is that the bulk of an axon is myelinated, greatly adding to the efficiency of transmitting action potentials. However, the axon terminals are not myelinated. I'm wondering if the ...
5
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1answer
77 views

Structural descriptions of neuronal networks are important for understanding brain dysfunctions; which dysfunctions, in particular?

In a recent paper, we find this quote: The brain contains vast numbers of interconnected neurons that constitute anatomical and functional networks. Structural descriptions of neuronal network ...
10
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1answer
219 views

Is a Hopfield network with a continuous activation variable and a discrete time variable possible?

I've found plenty of resources on Hopfield networks that use either discrete variables for both activation level and time or continuous variables for both activation level and time. Is it possible to ...
14
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7answers
3k views

Difference between parallel processing done by human brain and by computers

I am asking a question regarding parallel processing as done by billions of Neurons inside our brain and parallel processing done by our computers in a cluster for example or even on a Graphics ...
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0answers
161 views

Does this neural network model exist? [closed]

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 ...
8
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1answer
148 views

Hebbian Learning Rule, Local or Global?

I just learned about the Hebbian Learning Rule. It essentially says "Neurons that fire together, wire together". I'm wondering if the learning rule is affected by the spatial distance of the two ...
7
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1answer
104 views

Can processing effort for sub-tasks in neural networks be measured?

I often heard statements like: 80% of your brain processing is computing the effect of gravity or, similarily: You only use 20% of your brain power My question isn't about the truth of ...
8
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1answer
159 views

How can STDP fit with reciprocal connectivity?

I have rather technical question regarding STDP dynamics. I am working on a neural network implementing an STDP learning algorithm, and have noticed that it is extremely anti-reciprocal. When two ...
14
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3answers
468 views

What are the key examples of the use of computational methods in the study of biological neural networks?

In an upcoming postdoc, I'm going to be looking through biological neural network data in the hopes of finding some interesting "patterns". I'm coming at this field from a mathematics/computer ...
13
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1answer
1k views

Modern treatments of Alan Turing's B-type neural networks

In the cognitive sciences Alan Turing is best known for launching AI with his Computing machinery and intelligence (1950). However, this was not his first contribution to the cognitive sciences, in ...
10
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1answer
828 views

Spurious attractors in Hopfield networks

A classic "Hopfield network" is a type of artificial neural network in which the units are bi-stable and fully interconnected by symmetrically weighted connections. In 1982, Hopfield showed that such ...
8
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1answer
115 views

What is the role of traveling waves in circuit formation during cortical development?

Propagating waves of activity have been characterized in various regions of the brain such as the visual cortex (Nauhaus et al., 2012). Recently they have been reported for the first time to occur ...
6
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2answers
152 views

Utility or software to visualize Neural Network?

I am using Octave to generate a Neural Network with a single hidden layer, and saving it as two CSV files. Is there a utility or software that will load the files and create an image, PDF or HTML ...
11
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1answer
329 views

How does neural spiking begin in the fetus?

I'm interested in modeling human brain spiking activity. How does the very first spiking activity begin in the fetus? I imagine all spiking activity is initiated by the senses and internal ...
4
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1answer
319 views

Computational differences between spiking neural networks and previous ANNs

This is an AI question regarding "3rd generation neural networks" - spiking neural networks (SNN). I hve been studying this concept online from various papers, mainly Maass (1997). I and am not ...
12
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2answers
267 views

References for biologically plausible models of knowledge representation?

I'm looking for references that deal with the issue of how various kinds of semantic knowledge are (or might be) represented neurally. Most of the discussion of this topic seems skewed by social ...