11
votes
Accepted
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
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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7
votes
Accepted
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 ...
- 1,537
7
votes
Accepted
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 ...
- 1,855
7
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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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 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 ...
6
votes
Accepted
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
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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5
votes
Accepted
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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5
votes
A question on synapses
According to this research paper by Lockary and Goodman, the resting membrane potential of C.Elegans is two fold because its a stepped resting potential of -70mV and -35mV. After an initial activation ...
- 1,186
5
votes
Accepted
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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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). ...
- 30.6k
5
votes
Accepted
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 ...
- 10.1k
5
votes
Accepted
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, ...
- 7,034
4
votes
What do the weights of an artificial neural network represent in biological neurons?
The weight matrix is typically considered to be a strength of connectivity metric between nodes in the parallel computronium model that neural networks are based on. That fact is fairly evident when ...
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4
votes
Differential equations in psychology
A large and notable area within psychology to which differential equations are central is dynamical systems theory. It is widely applied to cognitive science. Differential equations are used to ...
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4
votes
What are some credible conferences and journals in computational neuroscience?
Adding to what was already mentioned, there are several "Frontiers" journals:
Frontiers in Neuroscience
Frontiers in Neural Circuits
Frontiers in Computational Neuroscience
Frontiers in Synaptic ...
- 517
4
votes
Accepted
What extent is non linear dynamics and chaos helpful to study brain function?
Since this an active and relatively new area of research, nobody can tell you for certain where it will lead.
Whether it will "dead end" is perhaps the wrong way to think about it too. All lines of ...
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4
votes
How are the outputs of neurons encoded, if at all?
The concept of digital channels of information flow is a serial-processing biased view of information: it applies a lot to serial systems like computers (which are still serial even with multiple "...
- 7,034
4
votes
ML/Neuroscience: TensorFlow vs PyTorch vs Keras for bulding NN models of the nervous system?
If you're looking at computational models of actual neurons and biological neural networks, there are a number of tools out there which are specifically for the purpose. The most commonly used are:
...
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4
votes
Explaining mathematically why most people chose 7 when asked to chose a number between 1-10
This is a really fun problem! Intuitively, the numbers all have latent features (isEven, isPrime, etc), so they live in a richly structured space. So far so good, but the (typical) structure of that ...
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3
votes
What is a good example of a psychological theory that became formalized into neural and computational terms?
I have one particular area to offer as a potential example. Keep in mind that likely no formalization of psychological concepts has heretofore been comprehensive (and the utility of a comprehensive "...
- 301
3
votes
Can machines really create anything new?
This is actual a pretty old and often debated question. It is called "Lady Lovelace's Objection" and first appeared in Alan Turing's seminal paper "Computing Machinery and Intelligence".
Below is my ...
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3
votes
what is the "trial-averaged neural response function"?
ρ(t) in Equation 1.1 cannot be summed and averaged because the idealized spikes are infinitesimally narrow and the chance of two spikes from different trials occurring at the same time t is zero.
In ...
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3
votes
What is the role of Chloride (Cl- ions) in membrane potential?
Short answer
Mostly Cl- is disregarded in calculations of the resting membrane potential and action potential voltage changes, because it is less important for the neural membrane characteristics than ...
- 20.5k
3
votes
Accepted
What is the role of Chloride (Cl- ions) in membrane potential?
In normal neurons, Chloride's reversal potential is near the resting potential for the neuron and also happens to be near the leak conductance reversal potential for the neuron. While not exactly the ...
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3
votes
Accepted
Can anyone see what is wrong with this implementation of the Pinsky-Rinzel model in Brian2?
If anyone ever finds this and has the same problem: The original paper has a flaw in the paper:
...
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3
votes
How can machine possibly possess consciousness if computation is a human idea?
Short answer: This is formally known as the hard problem of consciousness - if you can figure it out, then you'll probably win a Nobel Prize:
The hard problem of consciousness is the problem of ...
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3
votes
Accepted
What is "Predictive Reverse Engineering" and how can it be used for understanding brain structure?
I am unfamiliar with the term "Predictive Reverse Engineering" but your question seemed very interesting. Informally speaking, "Predictive Reverse Engineering" seems to denote trying to reverse ...
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