Questions tagged [computational-modeling]

For questions about modeling processes from cognitive and neurobiological theories via algorithms and computer simulations, and also about confirming experimental results with theoretical/statistical constructs.

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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 ...
Artem Kaznatcheev's user avatar
27 votes
3 answers
4k views

What are some of the drawbacks to probabilistic models of cognition?

Probabilistic approaches to modelling cognition are increasing in popularity and being encouraged within the field (Chater, Tanenbaum, & Yuille, 2006). What are some of the arguments against or ...
Vielle's user avatar
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23 votes
2 answers
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Applications of computational learning theory in the cognitive sciences

Computational learning theory (CoLT) is a branch of theoretical computer science associated with the mathematical analysis of machine learning. A lot of the early ideas of the field take inspiration ...
Artem Kaznatcheev's user avatar
21 votes
2 answers
3k views

Why does neuroplasticity decrease in adults?

Although adult brains are malleable and even undergo limited neuorgenesis, the extent of the neuroplasticiy is much lower than in children. This is most obvious in language acquisition, and recovery ...
Artem Kaznatcheev's user avatar
19 votes
3 answers
6k views

Is back-prop biologically plausible?

One of the common criticisms of Deep Learning is it's training algorithms, back-propagation of error (back-prop), has no biologically plausible implementation, despite evidence of something like it ...
Seanny123's user avatar
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17 votes
1 answer
2k 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 ...
Artem Kaznatcheev's user avatar
16 votes
3 answers
939 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 ...
Douglas S. Stones's user avatar
15 votes
2 answers
444 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 ...
shanusmagnus's user avatar
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15 votes
1 answer
806 views

Biological plausibility of bayesian models of cognition

Inspired by this question: What are some of the drawbacks to probabilistic models of cognition? I would like to know more about the biological plausibility of Bayesian models of cognition. Is there ...
zachguo's user avatar
  • 253
15 votes
1 answer
640 views

How does the brain calculate velocity?

How does the human brain calculate velocities? For example, when crossing a road and seeing a car coming towards you, how does the brain actually compute the rough velocity of the vehicle and your own ...
AAM's user avatar
  • 409
15 votes
1 answer
332 views

Computational models of early learning in children

What are currently used biologically plausible computational models/frameworks of early learning in children? Personally, I have used cascade correlation neural nets to model pronoun acquisition in ...
Artem Kaznatcheev's user avatar
14 votes
4 answers
2k views

Why is training better when following an easy-to-difficult schedule?

As suggested in the answer to this question, experimental results show that training is most effective when it follows an easy-to-difficult schedule. What theories and specifically computational ...
Ofri Raviv's user avatar
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14 votes
1 answer
322 views

How do humans control saccades?

I've gathered the standard rational for a visual system utilizing saccades from perception textbooks: the neural cost of processing an entire scene at a high level of detail would be prohibitive, but ...
zergylord's user avatar
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14 votes
2 answers
953 views

The computer model of the brain

I am a computer programmer or computer engineer, and am interested in comparing the brain to a classical computer in some way. How well does this comparison hold up? This is a general introduction ...
Arnon Weinberg's user avatar
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14 votes
3 answers
2k 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 ...
Xingdong Zuo's user avatar
13 votes
2 answers
521 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 ...
Arnon Weinberg's user avatar
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13 votes
1 answer
290 views

What explains variability in the mean firing rate across biological neurons?

Biological neurons have a trade-off between high information transfer (high firing rate) and energy conservation (low firing rate). One would suspect that the maximization of this function has a ...
Kyler B's user avatar
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12 votes
2 answers
560 views

Are there any modern mechanistic theories of motivation?

I remember hearing about the old 'drive' theory of motivation in Psych 101, and despite continuing my cognitive science education for another 4 years, that's the last theory of motivation I've heard ...
zergylord's user avatar
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12 votes
3 answers
287 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 ...
zergylord's user avatar
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12 votes
1 answer
3k 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 ...
Peter Helfer's user avatar
11 votes
1 answer
576 views

Importance of Neural Synchrony to Cognition

Is there a consensus on whether computation using Neural Synchrony is reasonable or not? In "How to Build a Brain", Chris Eliasmisth cites Yuko Munakata and R. C. O'Reilly as saying that "the ...
Seanny123's user avatar
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11 votes
2 answers
276 views

Computational Model Linking Neural Activity to Behavior

A big question in neuroscience is how neural activity represents knowledge. We can use modelling to explore how different levels of neural activity- subthreshold currents, action potentials, local ...
mac389's user avatar
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10 votes
5 answers
481 views

Visual search: complexity of positive vs negative search tasks

Thinking about experiments where participants perform visual search tasks, I remember hearing in a Cog Psych lecture that if the instructions of the task were of the form "find the element that has ...
Roly's user avatar
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10 votes
4 answers
3k views

What are the mathematical models of memory?

Are there mathematical models of memory in humans or animals? I want to know how neuroscientists use mathematics to describe memory in living creatures. How do neuroscientists model memory and show ...
MOON's user avatar
  • 221
10 votes
2 answers
311 views

How to computationally model the Wisconsin Card Sorting task?

The Wisconsin Card Sorting task is rather famous but appears to be quite difficult to model computationally. I work in RL and I am interested in how people learn the optimal strategy. I'm interested ...
user865's user avatar
  • 103
10 votes
2 answers
169 views

Criteria for evaluating cognitive systems

In the first chapter of the book "How to Build a Brain", Chris Eliasmith quickly establishes some criteria which he will use to evaluate Spaun, the cognitive system described in the book. He describes ...
Seanny123's user avatar
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10 votes
1 answer
172 views

Is cortical magnification in the visual system related to synaptic pruning, or is it a separate developmental or learning process?

I'm primarily interested in learning about current computational models that explain cortical magnification in the visual system. With this in mind, my specific questions are: (1) Is this phenomenon ...
Joebevo's user avatar
  • 449
9 votes
3 answers
6k views

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 ...
Alex Ryan's user avatar
  • 485
9 votes
4 answers
4k views

How to read a neuron tuning curve graph?

I'm working through the tutorial of section 2.4 of "How to Build a Brain" and I've encountered this graph of a neuron tuning curve. I understand the Y axis is the firing rate of the neuron, that each ...
Seanny123's user avatar
  • 8,853
9 votes
1 answer
218 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 ...
Amir's user avatar
  • 141
8 votes
2 answers
3k views

Differential equations in psychology [duplicate]

I am wondering (and searching with no success) if there are any examples of differential equations in psychology? I mean, no tutorial explaining what is differenetial equations or even partial ...
Lil'Lobster's user avatar
8 votes
2 answers
110 views

Biologically plausible cognitive model of Wisconsin card sorting task

As discussed previously, there are a wide range of models that have been applied to the Wisconsin card sorting task. However, which one is most biologically plausible? That is, uses a realistic model ...
Seanny123's user avatar
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8 votes
2 answers
170 views

Any models that act using both streams of visual processing?

The Two-Stream Hypothesis, where object properties are processed independently from spatial information, remains the most well established theory of visual processing. However, it concerns me that ...
zergylord's user avatar
  • 2,404
8 votes
2 answers
496 views

What is the difference between spike-triggered averaging and reverse correlation?

I'm interested in the difference between spike-triggered averaging and reverse correlation. In some papers (i.e., Schwartz, Odelia, et al) I see the term 'Spike Triggered Averaging'. In others, (ie ...
DankMasterDan's user avatar
8 votes
1 answer
25k views

Explaining mathematically why most people chose 7 when asked to chose a number between 1-10

Last day, I watched a video at ‘Numberphile’ which made a strange demand. According to the video, if you ask people to randomly pick any one integer between 1 and 10 (both inclusive), people are more ...
user57048's user avatar
  • 181
8 votes
1 answer
82 views

What are biologically plausible ways to model binocular disparity?

I figure there is a vast body of literature on stereovision, both neurophysiological and computational studies. Computer Vision also provides some algorithmic insight on implementing binocular ...
compephys's user avatar
  • 316
8 votes
1 answer
331 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. ...
SmCaterpillar's user avatar
8 votes
1 answer
151 views

Judgments of similarity between samples of writing

I was thinking last night about the possibility of an experiment that investigates the factors contributing to peoples' judgments of 'stylistic similarity' between two samples of writing. For example, ...
Mynah's user avatar
  • 81
8 votes
0 answers
500 views

Non-computational models of cognition

There is a question on this site that asks a somewhat related question, whether there are non-physical models for cognition. However, that question still assumes a computational paradigm for the non-...
yters's user avatar
  • 537
7 votes
3 answers
307 views

How does the brain compute sound localisation without the equations?

What sort of computations are used for localising sound with the ears, and how does the brain compute the time difference between sounds reaching each ear? I am interested in the specific mechanisms ...
AAM's user avatar
  • 409
7 votes
1 answer
920 views

Cosyne vs CNS conferences for Computational Neuroscience?

While Googling, I noticed there are 2 conferences for computational neuroscience: Cosyne and CNS. My questions are: 1) What are these conferences' differences in terms of material & impact/size? ...
DankMasterDan's user avatar
7 votes
1 answer
176 views

What is "Predictive Reverse Engineering" and how can it be used for understanding brain structure?

Here is a quotation from the paper Markram et al., Introducing the Human Brain Project : New informatics and modeling approaches are making it possible to reverse engineer the detailed structure ...
Lior's user avatar
  • 143
7 votes
2 answers
834 views

For binary (spike train) signals, take FFT of signal or autocorrelation of signal?

I want to characterize a binary time-series signal x (derived from neuron action potential data) in the frequency domain. Should I use the FFT of the original signal x, or the power spectrum (FFT of ...
DankMasterDan's user avatar
7 votes
1 answer
127 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 these ...
Artem Kaznatcheev's user avatar
7 votes
1 answer
159 views

Increasing pitch perception of the same auditory stimuli

I was trying to work up a small clip of repeating beep sounds I recorded from a mobile game. This series of sounds, when played, gave an unmistakable perception of increasing pitch with every ...
stochastic13's user avatar
7 votes
1 answer
94 views

Common components of other cognitive architectures and the Semantic Pointer Architecture

In the papers I've read about it, the Semantic Pointer Architecture (SPA) embodied in Spaun is said to be more biologically plausible than many other proposed architectures such as the Neural ...
Seanny123's user avatar
  • 8,853
7 votes
1 answer
161 views

What's the relation between BCM and Oja's learning rule?

A software I'm using has implemented two unsupervised learning algorithms, Oja's and Bienenstock, Cooper, Munro's (BCM) learning rule. I understand that they are two very different algorithms for ...
Seanny123's user avatar
  • 8,853
6 votes
4 answers
1k views

What are good introductory books on mathematical psychology?

I have a background in physics and has enough knowledge in Fourier analysis, group & representation theory, projective geometry, complexity theory, and dynamical systems theory. What introductory ...
Ooker's user avatar
  • 1,771
6 votes
3 answers
194 views

Is there a complete cortico-cortical connectivity map based on a useful partitioning of the cortex?

I have something like Brodmann Areas in mind, but any complete list of cortex regions would do. I'm primarily interested in human brains here. Ultimately I'd like enough information to be able to ...
Andrew McKnight's user avatar
6 votes
2 answers
126 views

What is a good example of a psychological theory that became formalized into neural and computational terms?

As far as I see it the goal of cognitive sciences is to find a description of mental processes in terms of neural computations that can be eventually formalized by a mathematical theory to generate ...
mvdoc's user avatar
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