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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7
votes
2answers
139 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
205 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
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 ...
-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 ...
5
votes
0answers
82 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 ...
2
votes
2answers
459 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
105 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 ...
10
votes
2answers
179 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
128 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
104 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 ...
8
votes
1answer
159 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 ...
14
votes
3answers
468 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 ...
13
votes
1answer
1k 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 ...
10
votes
2answers
190 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 ...
-4
votes
1answer
174 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 ...
19
votes
2answers
922 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
336 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 ...
10
votes
1answer
829 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 ...
12
votes
1answer
221 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 ...
14
votes
2answers
548 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 ...
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 ...
4
votes
1answer
320 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 ...
12
votes
2answers
267 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 ...
11
votes
1answer
232 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
140 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 ...
4
votes
2answers
311 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
403 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 ...
16
votes
3answers
1k 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 ...
13
votes
1answer
260 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 ...
25
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 ...
5
votes
3answers
136 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 ...
10
votes
1answer
269 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 ...