For questions about mathematical and computational neuroscience.

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25
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3answers
16k views

Why would the brain flip the images perceived by your eyes?

The following is a common scientific statement, which you don't have to google long for to find: The eye views images upside-down in the manner of a camera lens, but our brains reinterpret this ...
4
votes
1answer
32 views

Does Spaun's serial memory exhibit proactive interference and serial searching

Xuan Choo recentely created a model of serial working memory for Spaun. Does this model of working memory exhibit the effects of proactive interference (as well as changing data types yielding freedom ...
8
votes
4answers
606 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 ...
0
votes
0answers
10 views

Are there cognitive models that distinguish semantic and episodic memory?

From various amnesia cases it has been shown that semantic and episodic memories reside in different parts of the brain. Are there any cognitive models that distinguish these two types of memories? If ...
5
votes
1answer
33 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 ...
2
votes
1answer
36 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 ...
3
votes
0answers
10 views

Are there theories on how vocabularies for the Semantic Pointer Architecture are created?

The semantic pointer architecture is a vector symbolic architecture where high-dimensional sparse vectors represent concepts. These concepts can be mathematical, linguistic or sensory. In all of the ...
2
votes
0answers
14 views

How can Semantic Pointer Architecture be used to capture dynamical systems?

Most uses of SPA I've seen seem to be representing static systems, such as recognizing digits, categorizing images, rapid variable creation and planning a path for writing those digits back out. Can ...
3
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0answers
17 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 ...
1
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0answers
21 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 ...
1
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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 ...
1
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0answers
14 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 ...
0
votes
1answer
10 views

Benefits of using more complicated neuron models in NEF models

The NEF allows you to use almost any neuron model as long as it has an equation for it's activity and it's spikes in some way. Usually, a simple leaky-integrate-fire (LIF) neuron model is used, but ...
4
votes
2answers
84 views

Why is it so difficult to use a “true mirror” as a mirror

This Youtube video shows what a "true mirror" is: https://www.youtube.com/watch?v=ZSxCZCy5Wsk In short, when you look into a true mirror you look at yourself (among other things) as you really are, ...
8
votes
4answers
286 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 ...
3
votes
2answers
25 views

What aspects of ACT-R are not contained within Spaun?

ACT-R was the first big cognitive model and excels at modelling human behavioral data quite accurately. Spaun, which is the world's largest functional brain model, took a lot of ACT-R's insights and ...
3
votes
0answers
34 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 ...
3
votes
1answer
60 views

What are presynaptic puncta?

What are presynaptic puncta? And what makes them different from presynaptic terminals?
1
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0answers
37 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 ...
14
votes
7answers
2k views

Difference between parallel processing done by human brain and by computers

I am asking a question regarding parallel processing as done by billions of Neurons inside our brain and parallel processing done by our computers in a cluster for example or even on a Graphics ...
6
votes
3answers
133 views

Research groups in Computer Science which study Computational Neuroscience

I am currently applying to graduate programs in Computer Science in the United States for admission next fall. I am particularly interested in the convergence of Computer Science and Computational ...
23
votes
2answers
1k views

What are current neuronal explanations and models of 'consciousness'?

I would like to understand more about consciousness from a neuroscientific perspective. I have a limited understanding of it in the philosophical/psychological sense through lectures. Although it is ...
7
votes
2answers
93 views

How does masking work?

Masking occurs when the delay between the target and the mask is less than a threshhold (say 50 milliseconds). If sensory data passes from lower to higher visual cortices/processing regions as in a ...
5
votes
1answer
44 views

What's the functional difference between the NEF and normal ANNs?

Aside from obvious biological plausibility, from a computational standpoint, what's the motivation of using the Neural Engineering Framework (NEF) instead of Artificial Neural Networks (ANNs) for ...
10
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2answers
175 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 ...
3
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1answer
26 views

How does hPES compare to the learning rates of ANNs?

The primary learning mechanism of artificial neural networks (ANN) is back-propagation, which is not biologically plausible. Trevor Berkolay created an alternative to this learning with the ...
3
votes
1answer
55 views

Relation between Nengo, SPA and NEF with respect to other Neural Models

I'm working through How to Build a Brain and I keep getting confused on the relation between Nengo, the Semantic Pointer Architecture (SPA) and the Neurological Engineering Framework (NEF). Are there ...
3
votes
1answer
16 views

How well are neurotransmitters used in SPA?

How much does the SPAUN and the Semantic Pointer Architecture (SPA) that was used to build it take neurotransmitters into account? In the book How to Build a Brain, various inhibitory and excitatory ...
3
votes
1answer
16 views

How well does the NEF capture neuronal heterogeneity?

From what I understand of the Neurogical Engineering Framework (NEF), groups of neurons are used to compute functions. However, I'm not clear if these calculations take into account neurons of ...
1
vote
0answers
42 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, ...
2
votes
0answers
14 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 ...
4
votes
2answers
75 views

Measurement of phase difference between two signals using cross correlation vs. fourier transform

I am studying eeg signals with the aim of distinguishing between preictal and interictal epilepsy states based on the eeg signal. I have read some papers and one of the metrics used to distinguish ...
2
votes
1answer
12 views

How is memory accounted for in the NEF?

The Neurological Engineering Framework can be used to create systems that use memory in interesting ways. One system (Spaun) is able to memorize (and forget) lists much in the same way as humans do. ...
-1
votes
1answer
48 views

Prerequisite Request: Neurorobotics [closed]

For the newly emerging field, Neurorobotics. Can one list several highly recommended prerequisite courses prior to entering this field ? Except for classical machine learning, computational ...
1
vote
2answers
64 views

Reference request in Circuit and Signals for Computational Neuroscience

In the area of computational neuroscience, there are basic theories from electric circuits and signal processing to be applied. For background study, which reference will be more suitable ? ...
3
votes
0answers
18 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 ...
3
votes
0answers
21 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 ...
10
votes
2answers
162 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 ...
0
votes
1answer
33 views

What is an example of a learning machine that achieves zero variance?

I'm attempting to find an example of a learning machine/neural network that achieves zero variance, but I am having a hard time finding an example anywhere. Variance is defined as the generalization ...
4
votes
2answers
165 views

Why does a neuron choose to connect to another?

I have been reading about neuron creation, guidance cues and all sorts of highly complex mechanisms used to allow one neuron axon to extend or connect - but to what end? Why does one neuron end up ...
2
votes
1answer
157 views

Why does optogenetics not mean that perfect brain-computer interfaces are possible?

There have been multiple articles and videos circulating on the Internet claiming that optogenetics has made it possible to have perfect input/output to the brain from a computer. This is obviously ...
2
votes
5answers
519 views

Why do scientists say brains are faster than computers?

Supposing that neurons function similarly to transistors: A neuron able to fire $200$ times per second and transistors can be switched on and off more than $100,000,000,000$ times per second. Let's ...
0
votes
1answer
43 views

How many action potentials from presynaptic neurons would be required to make a postsynaptic neuron fire?

I am looking for a rough estimation of the number of action potentials from other neurons required to cause a neuron to fire? I read here that a potential of ~ -55mv must be reached before an action ...
2
votes
0answers
38 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 ...
6
votes
3answers
142 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 ...
3
votes
2answers
45 views

How do humans learn to combine tasks?

I've been reading about hierarchical learning (a variant of reinforcement learning from what I understand) and how it is shown to allow learning of a higher-level task (the main example is assembly). ...
1
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0answers
20 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 ...
4
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0answers
25 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 ...
2
votes
2answers
114 views

Diffrence between SSVEP and P300

I have read about SSVEP and P300 as different subjects. But its seems that they are related to each other. Is P300 a kind of SSVEP?
1
vote
1answer
30 views

What are the neurobiological factors associated with intelligence in animals?

For example, is there a well-defined relationship between "number of neurons in the cortex" and some measure of "intelligence" in animals? I'm familiar with the encephalization quotient - that is, ...