For questions about mathematical and computational neuroscience.

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3
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1answer
92 views

link between top-down (bottom-up) processing and cortex layers

What are the relations between top-down and bottom-up processings and the flows of information in the brain? For example, does top-down processing start from some layers and go to lower layers? If so ...
2
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0answers
9 views

What is the limitation of Biosocial Theory developed by Linehan?

Linehan's biosocial theory takes into consideration of the accumulation effect of a stress on individuals, which the Diathesis-stress model could not explain. A predisposition (diathesis) with stress ...
0
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1answer
9 views

Neuroanatomical mapping of production compilation

ACT-R and Spaun map their production rule system onto the the basal ganglia and thalamus. However, I haven't been able to find how ACT-R maps production rule compilation onto the basal ganglia or ...
3
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2answers
50 views

Color and shape arriving together in visual system

I know that in the visual cortex there are separate visual pathways for both color and shape. Do these separate pathways imply that human beings become consciously aware of these features separately ...
3
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1answer
22 views

Can anyone see what is wrong with this implementation of the Pinsky-Rinzel model in Brian2?

Not sure if this is the right place to ask this but I've been attempting to implement the Pinsky-Rinzel model in the Brian2 simulator. I'm basing my implementation off the original article here: http:/...
2
votes
1answer
199 views

How many possible states does a brain have?

Suppose I have a box, inside of which is a light which can be either on or off: it has exactly two states. Suppose I wanted to take some "snapshot" of the state of this device, and store all the ...
4
votes
1answer
73 views

Is semantic pointer architecture compatible with a predictive coding account of the brain?

Both SPA (Eliasmith et al.) and predictive coding (Friston, Clark, Rao, et al.) seem to have a lot of explanatory power. My understanding of SPA is probably rudimentary, but Eliasmith and others ...
4
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1answer
92 views

Interpretation & Actual Result of “10% of your brain” Myth

It is well known that the common myth that an individual only ever uses 10% of their brain is.. well, a myth. I had a question about a possible interpretation of this idea, and a follow-up question ...
5
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1answer
69 views

How does a human classify or cluster data?

Here, what I mean by DATA are text documents. I am going to do a research on text clustering algorithms by the help of artificial neural networks (ANNs). But first of all I need to know how our brain ...
5
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0answers
48 views

Why cerebellar input fibers use 2 ways to send a siganl to DCN?

Both groups of input fibers of cerebellum (mossy, climbing) start 2 pathways: 1) project directly to the deep nuclei 2) project to cerebellar cortex, which then (after some processing) sends ...
3
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0answers
15 views

SaccadeAngular velocity Matlab [closed]

I have the data for a monkey's eye position in a cartesian plane synced to the time. I can convert the numbers into polar form however I'm not too sure how to find the angular velocity at that point. ...
4
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1answer
34 views

Neurophysiological mappings of empathy

What biologically plausible models are there of empathy? I know there has been a significant amount of work in defining emotion on a neurophysiological basis using models (I'm currently reading this ...
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0answers
54 views

Is cortical magnification in the visual system related to synaptic pruning, or is it a separate developmental or learning process?

I'm primarily interested in learning about current computational models that explain cortical magnification in the visual system. With this in mind, my specific questions are: (1) Is this phenomenon ...
3
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2answers
44 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 ...
5
votes
1answer
185 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 ...
3
votes
1answer
26 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
15 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) ...
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0answers
27 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 (...
9
votes
1answer
73 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 ...
9
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1answer
81 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 ...
9
votes
2answers
122 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
28 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
votes
1answer
54 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
votes
1answer
34 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 ...
3
votes
1answer
92 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 (also called "completing a pattern") and planning a path for ...
9
votes
1answer
82 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 ...
3
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0answers
24 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 ...
0
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1answer
31 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 ...
5
votes
2answers
227 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
79 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
44 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 ...
4
votes
1answer
409 views

What are presynaptic puncta?

What are presynaptic puncta? And what makes them different from presynaptic terminals?
3
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0answers
44 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 ...
7
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3answers
392 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 ...
9
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2answers
185 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
votes
2answers
68 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
1answer
43 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 ...
5
votes
2answers
230 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
27 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
21 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
20 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
40 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
48 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 ...
5
votes
0answers
50 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
81 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
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1answer
40 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 ...
6
votes
2answers
277 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
107 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
76 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 ...