12 votes

Is EEG brain-computer interface reliable?

This very much depends on what, exactly, you're trying to do. EEG measurements tend to be extremely reliable, but the inferences one may draw on mental state are not necessarily so. EEG-driven BCI ...
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11 votes
Accepted

Importance of Neural Synchrony to Cognition

As you have already hinted at, the issue is controversial. I could leave it at that and say "no, there is no consensus", and it would be a true answer, but it wouldn't be satisfying, wouldn't it? ...
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  • 2,414
9 votes
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Modern treatments of Alan Turing's B-type neural networks

To my knowledge, with respect to the context of the question, the first neural-like model of computations capable of learning – or, for that matter, computational model of neural processing and ...
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  • 745
9 votes
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Is back-prop biologically plausible?

Biological Plausibility of Back-Prop No, the algorithm of back-prop (BP) isn't biologically plausible. However, there are other means which involve propagating the error through multiple layers of ...
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  • 8,783
8 votes

Differential equations in psychology

The Hodgkin and Huxley model of neuronal firing is based on non-linear differential equations. A significant portion of research on sensation and perception is based on such models.
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  • 2,617
7 votes
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What is the difference between computational neuroscience, theoretical neuroscience, and neuroinformatics (if there is one)?

There is no difference between "computational neuroscience" and "theoretical neuroscience" in practice. The two are almost always used interchangeably. Neuroinformatics, like bioinformatics, is more ...
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7 votes

How to compare brain waves?

The field of study you should focus on is the one for which you have already identified in your paragraph above which is EEG based "brain-computer interface". EEG signals are compared by ...
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  • 349
7 votes

How is the biological accuracy of ANNs typically measured?

One way the biological plausibility of an artificial neural network could be assessed is to look at how much a neural network abstracts away from the behavior of real neurons. For instance, it is ...
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  • 5,418
7 votes
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How to interpret neuron spiking models one comes across in literature?

Read dayan and abbot "theoretical neuroscience" Learn differential equations Know the relationship between voltage, current, resistance and conductance Differential equations is absolutely essential ...
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  • 1,835
7 votes

What is the computational role of the cortical column?

Cortical columns are groups of neurons in the brain that are oriented perpendicularly to the cortical surface. Cells within a column respond to the same stimulus property (Fig. 1). For example, ...
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6 votes

How is the biological accuracy of ANNs typically measured?

Due to my newness to the field, I can only talk about comparisons of biological plausibility when discussing the Neural Engineering Framework (NEF) and functional modeling. What is missing from this ...
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  • 8,783
6 votes
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What do the weights of an artificial neural network represent in biological neurons?

The weights in an artificial neural network are an approximation of multiple processes combined that take place in biological neurons. Myelination plays a role, but not a major one. Weights in ...
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  • 1,487
6 votes
Accepted

Why Bayesian Cognitive Modeling?

Here's a quick answer from general background knowledge, not from any specific knowledge of "Bayesian Program Synthesis (BPS)" In general, Bayesian models can use strongly informed priors or diffuse "...
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6 votes
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The computer model of the brain

This question's reference to a classical computer refers to a "Turing Machine" style of computation, also known as a knowledge system, in which decisions and possible results are pre-...
5 votes

How to read a neuron tuning curve graph?

From the comments: I'm going to hazard a guess that these are neurons that are tuned to a particular direction in space and that the x-axis is the angle in multiples of π radians, particularly since ...
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5 votes
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Biologically plausible cognitive model of Wisconsin card sorting task

Amos (2000) and Monchi et al. (2000) use the similar approach of assigning each card attribute to a node and using mutual inhibition to choose the right one. Although their models are biologically ...
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  • 8,783
5 votes

Are there working computational frameworks for human behavior and personality?

Cognitive Architectures The description most closely matches the concept of a cognitive architecture. Whereas I would say most empirical cognitive science focuses on isolating cognitive functions or ...
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5 votes
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Publicly Available NEURON models

A repository of publicly available NEURON models can be found on ModelDB by filtering for Models that contain the Modeling Application: NEURON.
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  • 8,783
5 votes

What is a good example of a psychological theory that became formalized into neural and computational terms?

Check out all of the videos in this playlist https://www.youtube.com/watch?v=lrppe54fixc&list=PL1hKzFfV5qJlVTjD8XWzyiaHxBZZ7iWs9&index=3 The particular video I linked gives the example of the ...
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  • 1,835
5 votes

How often are complex networks and graph theory useful in computational neuroscience?

In my opinion as a computational neuroscience researcher, graph theory has not made major inroads into computational neuroscience because we don't have good evidence for what graphs characterise ...
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5 votes
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Are ACT-R and Spaun the state of the art in cognitive science computational models?

There are TONS of other Cognitive Models being researched. Specifically, see this giant comprehensive list of Cognitive Models [1]. Given such a wide array of models, it might be more helpful to focus ...
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  • 8,783
5 votes

What are good introductory books on mathematical psychology?

I also like https://bayesmodels.com/. I posted the question on twitter, you could check out the responses. Joachim Vandekerckhove suggested: Lewandowsky, S., & Farrell, S. (2010). ...
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5 votes
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Parallel arrangement of capacitor and resistor in leaky integrate-and-fire model

I see your confusion is caused by $u_{rest}$. Indeed that diagram is somewhat confusing because $u_{rest}$ is not the main source relative to which to consider the topology of the circuit. The main ...
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  • 9,895
5 votes
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Are there animals with only excitatory neurons?

Not in any well-studied animal; for example, C. elegans certainly has both excitatory and inhibitory neurons. Even in animals with very simple and poorly understood nervous systems (for example, ...
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  • 5,629
4 votes

How does the brain compute sound localisation without the equations?

The location of a sound is defined on three dimensions: distance, elevation, and azimuth. When the distance between a listener and a sound source is changed there is a change in the overall level as ...
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  • 2,617
4 votes

What are the mathematical models of memory?

If you have a physics background, you may be particularly interested in Sparse Distributed Memory, a model that provides a number of psychologically plausible characteristics, and is also ...
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  • 435
4 votes

Criteria for evaluating cognitive systems

Hofstadter provides a detailed set of criteria in Fluid Concepts and Creative Analogies. Some of his criteria that I do not see mentioned above concern the flow of information-processing: whether or ...
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  • 435
4 votes

How distantly related are research in computational neuroscience and neural networks/machine learning?

Computational neuroscience and neural networks are both studied on this MSc at the University of Sussex. When I took the course in 2004/5, the Neural Networks module was compulsory, and the ...
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4 votes
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What aspects of ACT-R are not contained within Spaun?

Both ACT-R and Spaun are modular, and could be extended to include capabilities of each other. Comparing the functionalities of the two architectures by a simple checklist is not the most appropriate ...
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