Tagged Questions

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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6
votes
1answer
54 views

How does masking work?

Masking occurs when the delay between the target and the mask is less than a threshhold (say 50 milliseconds). If sensory data passes from lower to higher visual cortices/processing regions as in a ...
1
vote
2answers
50 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
votes
1answer
29 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 ...
0
votes
1answer
34 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
votes
1answer
38 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 ...
1
vote
0answers
19 views

Differences between the many versions of neuromorphic hardware

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, ...
4
votes
0answers
40 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
votes
1answer
57 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. ...
3
votes
2answers
28 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
votes
2answers
84 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 ...
10
votes
2answers
109 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
votes
3answers
145 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 ...
9
votes
1answer
70 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 ...
1
vote
1answer
40 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
votes
1answer
112 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
votes
1answer
70 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 ...
1
vote
1answer
127 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
votes
1answer
127 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
votes
1answer
118 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 ...
4
votes
0answers
33 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 ...
0
votes
2answers
147 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
votes
2answers
123 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 ...
10
votes
3answers
190 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
votes
1answer
67 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
votes
1answer
76 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
votes
1answer
150 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 ...
13
votes
5answers
2k 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 ...
2
votes
0answers
140 views

Does this neural network model exist?

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 ...
6
votes
1answer
140 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
votes
1answer
100 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 ...
7
votes
1answer
131 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 ...
10
votes
3answers
388 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 ...
8
votes
0answers
351 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 ...
9
votes
1answer
631 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
votes
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
votes
2answers
139 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 ...
9
votes
1answer
276 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
votes
1answer
253 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 ...
10
votes
2answers
250 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 ...
15
votes
2answers
303 views

How are newly created neurons recruited into existing networks?

As far as I understand, the basics of neurogenesis (abstracted down to the level that makes sense to a computer scientist) is as follows: Neural progenitor cells differentiate into new neurons that ...
22
votes
2answers
716 views

What is an effective metric of complexity for an Artificial Neural Network?

After asking the question What is the most complex neural network... I realized I don't really have a good metric of "complexity" in a general sense. The simplest measure would likely be count of ...
9
votes
1answer
526 views

What is the most complex artificial neural network created to date?

A few years ago I wrote a research paper for college on neural networks. At the time IBM's Blue Brain was the clear winner. Some rumor went around that they were close to emulating a brain the ...
11
votes
2answers
709 views

What can we learn from the neural networks of C.elegans to understand human brains?

Recently I am reading some works about Caenorhabditis Elegans. A C.elegans has 302 neurons and we already know the function and connection of every one of their neurons so that we can exactly ...
22
votes
2answers
1k views

Neural networks with biologically plausible accounts of neurogenesis

One of the reasons artificial neural net algorithms like cascade correlation (pdf) have been generating interest is because they start with a minimal topology (just input and output unit) and recruit ...
10
votes
1answer
217 views

Are there any connectionist models that integrate reinforcement and fully supervised learning?

I've been working on modeling some phenomena involving real-time control in an environment with inherent rewards (specifically, playing a 'pong'-like game), and it's increasingly looking like ...