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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28
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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 ...
24
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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
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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 ...
17
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3answers
2k 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 ...
15
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3answers
540 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 ...
15
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2answers
597 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 ...
14
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1answer
273 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 ...
13
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1answer
264 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 ...
13
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1answer
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 ...
12
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2answers
287 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 ...
12
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1answer
234 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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4answers
495 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 ...
11
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1answer
251 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 ...
11
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2answers
193 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 ...
11
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3answers
217 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 ...
10
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5answers
352 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
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2answers
209 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 ...
10
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1answer
284 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 ...
10
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2answers
153 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 ...
10
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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
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2answers
537 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 ...
9
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1answer
145 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 ...
9
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4answers
931 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 ...
8
votes
4answers
947 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 ...
8
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2answers
81 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 ...
8
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1answer
177 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 ...
8
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1answer
168 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. ...
8
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0answers
51 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 ...
7
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3answers
140 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 ...
7
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2answers
78 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 ...
7
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2answers
142 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 ...
7
votes
1answer
109 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
54 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 ...
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 ...
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, ...
7
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0answers
51 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 ...
6
votes
3answers
170 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 ...
6
votes
1answer
69 views

How to interpret neuron spiking models one comes across in literature?

Background I'm in high school currently conducting research (obviously it is relatively rudimentary compared to what is being done in the labs, etc.) in computational neuroscience. I'm dealing with ...
6
votes
1answer
341 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? ...
6
votes
2answers
60 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 ...
6
votes
2answers
150 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 ...
6
votes
1answer
91 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 ...
6
votes
1answer
110 views

What are the practical uses of ontologies?

I have read many papers and books about ontologies, and I am trying to figure out that how they are used in a real project. For example, how can the ontology for a soccer player robot can be defined ...
6
votes
1answer
54 views

EPSP/IPSP amplitude values?

I'm working with a Hodgkin-Huxley model that receives synaptic inputs from presynaptic neurons. If it receives a spike from an excitatory presynaptic neuron, the voltage of my HH neuron inceases by an ...
5
votes
3answers
146 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 ...
5
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3answers
141 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 model)...
5
votes
3answers
171 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 ...
5
votes
1answer
61 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
votes
1answer
38 views

What models/mechanisms exist for the brain to chain movements together?

Motor Sequence Learning is the study of the cognitive ability to chain various motor sequences together. The most intuitive example of this is learning to play a sequence of notes on a piano. ...
5
votes
1answer
53 views

A question on synapses

we are looking into running simulations of the nervous system of C. Elegans. It is believed by most people that the worm's nervous system encodes information through graded potentials and/or plateau ...