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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3
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1answer
27 views

How does the frequency of a visual stimulus affect the steady-state visually evoked potential?

I want to make a project for EEG signal processing, and in my research I found the concept of SSVEP, which means that if you have a stimulus with low frequency applied to the eye, the electrical ...
2
votes
1answer
18 views

How does hPES compare to the learning rates of ANNs?

The primary learning mechanism of artificial neural networks (ANN) is back-propagation, which is not biologically plausible. Trevor Berkolay created an alternative to this learning with the ...
0
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0answers
8 views

What approaches has there been to resolving the “symbol grounding problem”?

The symbol grounding problem can be summarized as the problem of defining a mapping between dogs-in-the-world and the concept of dog in your head. What approaches have been used in cognitive models to ...
6
votes
1answer
62 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 ...
0
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2answers
32 views

Knowledge in what fields is necessary to develop an EEG brain-computer interface?

I am a computer science student, and as part of my project, I would like to develop a system that changes the TV channel, increases its volume, etc. by just the thought of it. My primary investigation ...
2
votes
1answer
32 views

Is EEG brain-computer interface reliable?

I am a computer science student [assume I have very little knowledge of the biological part of EEG]. I recently came across the topic EEG and was pretty interested in it. As far as I know, we get an ...
4
votes
0answers
33 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 ...
9
votes
1answer
83 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 ...
4
votes
1answer
53 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 ...
5
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1answer
30 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 ...
2
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0answers
15 views

How to compare tasks completed by neural architectures objectively?

When I first saw this video of Spaun and the tasks it can complete (solving the Towers of Hanoi problem, completing the Raven matrices), I was really impressed, but then I realized I didn't really ...
5
votes
1answer
22 views

What are the 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 ...
2
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1answer
36 views

Relation between Nengo, SPA and NEF with respect to other Neural Models

I'm working through How to Build a Brain and I keep getting confused on the relation between Nengo, the Semantic Pointer Architecture (SPA) and the Neurological Engineering Framework (NEF). Are there ...
3
votes
1answer
121 views

What is the difference between computational neuroscience, theoretical neuroscience, and neuroinformatics (if there is one)?

In particular, theoretical and computational neuroscience seem to be synonymous with each other. Neuroinformatics at least seems to deal somewhat more with solving things numerically and the usage and ...
1
vote
1answer
27 views

Overview of Pitts & McCullough (1943) “A logical calculus of the ideas immanent in nervous activity”

Is there a good tutorial or simplified overview of the paper, 'Logical calculus for nervous activity' (McCullough & Pitts, 1943)? Reference McCullough, W. S., & Pitts, W. (1943). A logical ...
5
votes
1answer
45 views

Are there any agent based cognitive models that are inspired by complex systems studies of ant colonies and economies?

I think that certain aspects of ant colony behavior seem almost like economic decision-making in behavior. There are also links between ant colony optimization and features of the brain like selective ...
7
votes
3answers
342 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 ...
1
vote
1answer
39 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 $x$ ...
5
votes
1answer
84 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? ...
7
votes
2answers
66 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 ...
0
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0answers
22 views

What is the most biologically plausible model of the retina?

Perhaps, retina is one of the most well studied and well understood parts of the brain. Are there any full models of the retina that would mimic the firing of the ganglion cells based on the input ...
5
votes
1answer
97 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 ...
11
votes
1answer
163 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 ...
6
votes
2answers
99 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 ...
7
votes
1answer
50 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 ...
4
votes
0answers
139 views

Is “Biophysics of Computation” still a good book?

To begin with, I hope this is the right place to ask - if not, please don't be too mad about it :) Currently I'm studying mathematics (2nd year) and I think I'm pretty into neuroscience. To "test" ...
5
votes
1answer
71 views

How can one estimate the excitability or mood of general public on a specific day?

I'm interested if there are publicly available tools or resources that can be used to gauge the overall activity/excitability or mood of general public for a specific day. For example, yesterday I ...
5
votes
2answers
126 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 ...
10
votes
3answers
186 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 ...
3
votes
0answers
68 views

Predicting the Duration of Future Events

I am interested in the question of how people use/integrate previous experiences with instances of tasks or events to make predictions about the duration of future instances of tasks/events. To ...
-1
votes
1answer
59 views

Practical Use For a Neuroimager [closed]

You may be aware that neuro-imagers have become much cheaper and many are available with a SDK. I think this will open up a huge gateway for much more intimate human interfaces. However, I am stumped ...
3
votes
0answers
73 views

What are the most well-understood vocal animal languages?

There are many examples of animal language that involve vocal pattens or "grammar". For example, there is the the Bee dance, bird songs, whale songs, dogs. Bird vocalization includes both bird calls ...
2
votes
2answers
254 views

How to adjust SSE or RMSE for the number of free parameters in the model?

How do I adjust SSE (sum of squared errors) or RMSE (root-mean-square errors) for the number of free parameters in the model? Is there an "adjusted" RMSD metric similar to the adjusted r-squared ...
4
votes
1answer
87 views

Does the Hodgkin-Huxley Model take into account the action of the ion pumps (e.g., Na-K-ATPase)?

After the firing of a neuron, the sodium and potassium concentration differences vanish. It requires some time for cell to actively transport the ions in and out to re-establish the balance. Does ...
9
votes
1answer
144 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 ...
7
votes
1answer
111 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, ...
7
votes
1answer
99 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
126 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
375 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
313 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 ...
6
votes
2answers
143 views

How to computationally model the Wisconsin Card Sorting task? [closed]

The Wisconsin Card Sorting task is rather famous but appears to be quite difficult to model computationally. To respond to @Artem's question, I work in RL and I am interested in how people learn the ...
-4
votes
1answer
166 views

Using natural language processing for traffic monitoring from video

I am stuck trying to learn how to use video processing as explained in the linked papers in the area of human behavior detection or traffic surveillance (any kind of monitoring activity). In ...
16
votes
2answers
701 views

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 ...
10
votes
5answers
308 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 ...
9
votes
1answer
575 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 ...
9
votes
1answer
186 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 ...
11
votes
2answers
474 views

Biological plausibility of bayesian models of cognition

Inspired by this question: What are drawbacks to probabilistic models of cognition? I would like to know more about the biological plausibility of Bayesian models of cognition. Is there any neural ...
22
votes
3answers
1k 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 ...
4
votes
1answer
233 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
247 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 ...