For questions about mathematical and computational neuroscience.

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1answer
24 views

Determining the position of the calcium ion in the three dimensional space

Is it possible to determine the position of a single calcium ion or its population in the context of a three dimensional space with relatively good time frequency, say 1 Hz, taking into account ...
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0answers
108 views

How can I test whether Dorsal Raphe Nucleus(DRN) activity at night is related to variations in mood?

I'm reading this paper, which discusses Serotonin activity in the Dorsal Ralphe Nucleus(DRN), and even includes some mathematical models of how serotonin is released and reabsorbed. The paper states ...
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0answers
77 views

For binary (spike train) signals, take FFT of signal or autocorrelation of signal?

I want to characterize a binary time-series signal x (derived from neuron action potential data) in the frequency domain. Should I use the FFT of the original signal x, or the power spectrum (FFT of ...
4
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0answers
188 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" ...
3
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0answers
19 views

What's the relation between BCM and Oja's learning rule?

A software I'm using has implemented two unsupervised learning algorithms, Oja's and Bienenstock, Cooper, Munro's (BCM) learning rule. I understand that they are two very different algorithms for ...
3
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0answers
23 views

Where do spatial dimensions enter in single compartment neuronal models?

I am trying to understand how the length and diameter of a compartment are specified. For example, in the Hodgkin–Huxley model, we only have conductances specified in $\rm mS/cm^2$. How do you specify ...
3
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0answers
28 views

Grating orientation & frequency which induces highest gamma

I am doing some research on perception and gamma activity in V1 area. To check some of my results I need to find an experimental result, from which I would know which orientations and frequencies of ...
2
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0answers
27 views

How do mammals explore state spaces in reinforcement learning tasks?

Reinforcement learning is the act of learning how to preform a task given punishment and reward. A "state-space" is the space of choices in a context. When performing a reinforcement learning task, is ...
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0answers
13 views

What is the most unified functional model of the hippocampus?

There are many different incremental models of the hippocampus and it's role in learning as shown by a quick search. However, have there been any efforts to combine these various models into a single ...
2
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0answers
13 views

What's the difference between divisive and soft normalization?

I know that recursive neural integrators (let me know if I need to clarify this term) can be considers soft normalizers, since their feedback loop means that any stimulus eventually saturates the ...
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0answers
33 views

How to compute weights and bias for a McCulloch-Pitts neuron?

I am trying to learn how to manipulate McCulloch-Pitts neurons in order to determine their weights and bias based off of inputs. In this example I have inputs: x, y, z ∈ {−1,1} The neuron's output ...
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0answers
16 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 ...
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0answers
207 views

How much information does the somatosensory system produce?

Are there any approximations of how many bits of information human somatosensory system produces? Especially mechano-receptors as measured in average number of bits per area of skin per second? I've ...
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0answers
5 views

What are some good references for preprocessing and analysis of the P300 response from EEG data in Python?

I have just started to work on problems in neuroscience on my own. I sought to analyze the P300 response from EEG data because I was trying to understand a Kaggle.com challenge that used it. I found ...
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0answers
17 views

Is it necessary to read signals and systems before statistical signal processing/ detection theory

For one who is interested in computational neuroscience and brain computer interface, in university curriculum (e.g. BCCN Berlin), it requires a course in statistical signal processing / signal ...
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0answers
13 views

A simple derivation of the generalization bounds for the classical perceptron model

I'm basically referring to the great work of Elizabeth Gardner in this matter. I find that her work is often overlooked in the field of neuroscience, arguably because it is too difficult to understand ...
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0answers
13 views

Do studies exist that can map specimens of neocortex to the functions they perform(ed) in vivo?

Much brain research has proposed that the brain (the neocortex, esp.) is set up in areas - an area for faces, an area for language, etc.. The experiments typically go 1) damage an area 2) observe ...
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36 views

Research on computational models of physiological mechanisms in affective neuroscience at a biochemical level

As computational neuroscience has the mainstream on single neuron/network modelling for biochemical aspect, and computational modelling of physiological mechanism of hippocampus for analytic study of ...
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0answers
25 views

Differences between the many versions of neuromorphic hardware

There is a ton of neuromorhpic hardware being pumped out these days. Off the top of my head, I can name IBM (BlueGene and TrueNorth), Qualcomm, Neurogrid, Brainstorm (Neurogrid 2.0), Spinnaker, ...
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0answers
19 views

Structure for General Intelligence

I've just read Dan Rasmussen's paper on general intelligence and I was wondering what other approaches for complex, scalable and adaptable learning have been tried in the past? This question's scope ...
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0answers
66 views

What is the possibility that research in neuroscience can lead to a new kind of mathematics?

The mathematics of astrophysics is far more complicated. That scientists say the brain is the most complex organ we know. So will mathematics evolve to tackle such complexity? Or does the required ...
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0answers
13 views

What approaches has there been to resolving the “symbol grounding problem”?

The symbol grounding problem can be summarized as the problem of defining a mapping between dogs-in-the-world and the concept of dog in your head. What approaches have been used in cognitive models to ...