For questions about mathematical and computational neuroscience.

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2
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2answers
32 views

Are there models of single neurons on slow timescales?

From what I've come across on the web, most models of single neurons seem to focus on the "fast timescale", where electrical signals are transmitted from one neuron to another. However, neurons are ...
1
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0answers
38 views

How long does the trace of a memory last in the brain?

With long-term plasticity one refers to the phenomen by which synapses are modified by neural activity and these modifications last for long times, a day perhaps of the order of days. This phenomenon ...
2
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1answer
19 views

Role of declarative memory in learning skill

In Neil Taatgen's paper on primitive information processing elements (PRIMs) he notes that as a result of saving the used PRIMs in declarative memory (which is fast) as opposed to procedural memory ...
3
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0answers
10 views

Relation between NEF and synchronous explanation of cognition

I'm having a hard time determining if synchrony (I'm talking about the type described in reference to the visual cortex as seen here and less about synaptic plasticity which also involves synchrony) ...
1
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0answers
17 views

How are Bayesian models implemented in the NEF?

One of the much documented problems of Bayesian approaches to cognitive modeling is that there isn't much of a neural grounding. The NEF can be used to compute probabilistic computations with ease ...
8
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1answer
65 views

Does an action potential abolish an excitatory postsynaptic potential?

From some sources, I've read that excitatory postsynaptic potentials (EPSPs) decay over time, which would imply that they aren't abolished by action potentials. However, other sources seem to indicate ...
8
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1answer
64 views

Does a recent general review of recurrent neural networks exist?

Does anyone know of a comparatively recent paper reviewing the literature on psychological applications of recurrent neural networks? I'm looking for a paper which provides a general overview of the ...
7
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2answers
88 views

What research has been done on brain-to-brain interfaces?

Is there an existing research area focusing on brain to brain interfaces? If so, what are some papers that have been published in this area?
2
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0answers
18 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 ...
4
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1answer
41 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 ...
3
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1answer
23 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
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0answers
46 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 ...
4
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0answers
38 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
39 views

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

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 ...
2
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0answers
19 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
22 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
19 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
133 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, ...
7
votes
2answers
63 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 ...
3
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0answers
40 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
122 views

What are presynaptic puncta?

What are presynaptic puncta? And what makes them different from presynaptic terminals?
2
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0answers
40 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 ...
6
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3answers
232 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 ...
7
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2answers
121 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 ...
3
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2answers
34 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 ...
2
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0answers
16 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
141 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
13 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. ...
3
votes
1answer
17 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
18 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 ...
2
votes
1answer
39 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
26 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 ...
4
votes
0answers
32 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 ...
1
vote
2answers
71 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 ? ...
0
votes
1answer
35 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
186 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
2answers
81 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 ...
1
vote
1answer
55 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 ...
5
votes
1answer
50 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 ...
2
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0answers
71 views

Differences between the many versions of neuromorphic hardware [closed]

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, ...
3
votes
2answers
56 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). ...
4
votes
0answers
28 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
155 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
34 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, ...
2
votes
5answers
1k 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 ...
-1
votes
1answer
51 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 ...
3
votes
1answer
34 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 ...
4
votes
0answers
31 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 ...
9
votes
1answer
113 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 ...
3
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1answer
52 views

Is there a research field which holds close connections between computational neuroscience and classical robotics

Is there a research field which holds close connections between computational neuroscience and classical robotics, particularly building corresponding robots to implement and test the theories from ...