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
93 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
21 views

How well are neurotransmitters used in SPA?

How much does the SPAUN and the Semantic Pointer Architecture (SPA) that was used to build it take neurotransmitters into account? In the book How to Build a Brain, various inhibitory and excitatory ...
3
votes
1answer
20 views

How well does the NEF capture neuronal heterogeneity?

From what I understand of the Neurogical Engineering Framework (NEF), groups of neurons are used to compute functions. However, I'm not clear if these calculations take into account neurons of ...
2
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0answers
19 views

What is the most unified functional model of the hippocampus?

There are many different incremental models of the hippocampus and it's role in learning as shown by a quick search. However, have there been any efforts to combine these various models into a single ...
-1
votes
1answer
54 views

Prerequisite Request: Neurorobotics [closed]

For the newly emerging field, Neurorobotics. Can one list several highly recommended prerequisite courses prior to entering this field ? Except for classical machine learning, computational ...
5
votes
0answers
42 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 ...
10
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2answers
472 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 ...
6
votes
3answers
169 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 ...
8
votes
1answer
162 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
1answer
61 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 ...
9
votes
1answer
144 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
votes
2answers
66 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
174 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
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0answers
173 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 ...
7
votes
1answer
62 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 ...
1
vote
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 $x$ ...
7
votes
1answer
50 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
votes
0answers
17 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 ...
4
votes
1answer
455 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
82 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
60 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 ...
6
votes
2answers
139 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 ...
12
votes
2answers
280 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 ...
5
votes
1answer
257 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 ...
12
votes
1answer
254 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 ...
4
votes
0answers
251 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" ...
6
votes
1answer
90 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 ...
7
votes
2answers
141 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 ...
11
votes
3answers
214 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 ...
5
votes
3answers
139 views

Are there any cognitive models for visual navigation?

I've seen a few neuroscience accounts of visual navigation and many A.I. projects, but no psychologically plausible accounts that actually solve the computational problem (i.e. produce a working ...
3
votes
0answers
75 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 ...
11
votes
4answers
483 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 ...
-1
votes
1answer
60 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 ...
2
votes
2answers
580 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 ...
5
votes
0answers
85 views

What are the most well-understood vocal animal languages? [closed]

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 ...
4
votes
1answer
118 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 ...
4
votes
2answers
318 views

What skills are required to build simulations of the human brain? [closed]

I want to build a system that has the ability to gather data from the internet in order to build a cognitive model of the human brain. The model should be able to answer the questions required by a ...
-3
votes
1answer
179 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 ...
24
votes
3answers
2k 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 ...
19
votes
2answers
1k 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 ...
8
votes
1answer
172 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 ...
28
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 ...
14
votes
1answer
268 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 ...
15
votes
2answers
582 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 ...
15
votes
3answers
529 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 ...
7
votes
1answer
108 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 ...
5
votes
1answer
717 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 ...
7
votes
1answer
133 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, ...
10
votes
1answer
1k 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 ...
10
votes
5answers
350 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 ...