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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0answers
18 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 ...
1
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0answers
11 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
11 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
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1answer
13 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 ...
1
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1answer
14 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
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1answer
80 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
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1answer
26 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
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1answer
42 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 ...
5
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1answer
226 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
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1answer
37 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
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1answer
67 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
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2answers
60 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 ...
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0answers
20 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 ...
4
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1answer
73 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 ...
10
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1answer
152 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
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2answers
93 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 ...
5
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0answers
30 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
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0answers
118 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" ...
4
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1answer
65 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
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2answers
124 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
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3answers
181 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
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0answers
64 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
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1answer
58 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
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0answers
70 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
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2answers
220 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
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1answer
85 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
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1answer
141 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
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1answer
106 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
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1answer
95 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
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1answer
121 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
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3answers
362 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
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0answers
289 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
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2answers
139 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
162 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 ...
14
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2answers
670 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
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5answers
303 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
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1answer
503 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
181 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
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2answers
457 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 ...
21
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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
218 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
235 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 ...
10
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1answer
202 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 ...
4
votes
3answers
136 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 ...
2
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2answers
268 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 ...
11
votes
4answers
277 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 ...
14
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3answers
919 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 ...
12
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1answer
238 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 ...
21
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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 ...
4
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3answers
120 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 ...