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Questions tagged [neuroscience]

A field of science that studies nervous systems. Use [neuroimaging] tag for questions about fMRI data analysis.

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Riemannian alignment has no effect

I am trying to implement a Brain-Computer Interface system that should be able to differentiate between rest and movement trials. I am using motor-related cortical potentials for movement detection. ...
sjaustirni's user avatar
3 votes
1 answer
69 views

SEM/regression: Identify better predictor

I have data from a longitudinal study, specifically MRI data and performance on a neuropsychological test at two time points. I would like to test whether the change in gray matter in Brain Region A ...
anonymoususer's user avatar
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Methods for comparing degree of structural coupling between two time series

I have two arrays, one representing an auditory stimulus and the other representing neural activity from auditory cortex. The auditory stimulus has known temporal and spectral structure. The neural ...
user90664's user avatar
5 votes
2 answers
428 views

Eye-Tracker - number of fixation metrics: how to handle zero values when performing statistical tests?

I collected data on fixation count metrics (also called number of fixations) via eye-tracker technology on a sample of 120 participants. The fixation count was calculated on certain AOIs (areas of ...
Ric87's user avatar
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Why is non-negative matrix factorization better than ICA in neuronal analysis

I've recently joined a neuroscience lab and am currently reading up on their pipeline to analyze 2-photon calcium imaging with single neuron resolution. The data consist of a movie where the pixel ...
Leo's user avatar
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1 vote
2 answers
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Which test to use to figure out if tumor excision percentage affects survival

I have a set of patients (n=27) that all died from a tumor. They all underwent surgery by the same surgeon. And all of them had their tumors removed by different percentages. They all received the ...
Bilal Bahadır Akbulut's user avatar
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14 views

How can I merge data from two different raters for the same dataset?

We're analyzing patient MRI sections of the brain for tumour volume. We do this manually, frame by frame, drawing the borders of the tumour. To ensure more accurate results, we have used two different ...
Bilal Bahadır Akbulut's user avatar
2 votes
0 answers
24 views

Predicting nested categorical variables from a set of continuous predictors

My dataset contains multiple continuous predictors (responses from n neurons) from which I would like to predict two categorical variables (A and B), where B is nested under A. A can take 8 different ...
Toghrul's user avatar
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Test if two dependent, unequal size samples are from the same distribution

I read Non-parametric test if two samples are drawn from the same distribution and have tried permutation test, KS test The issue is I have data of different sample size that are collected from the ...
Elder Gu's user avatar
1 vote
1 answer
40 views

Multiple Sclerosis: study design to beta test a software

I am a beta-tester of a software that is intended to help the radiologist to interpret MRI reading of Multiple Sclerosis (MS). MS is a disease that, over time, could lead to new lesions, expanding ...
KingBOB's user avatar
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Training a Neural Network on Two Interrelated Tasks

I'm working on a project where I'm interested in comparing the performance of a Neural Network to human performance on a multisensory perceptual task. The task is quite easy, but I'm more interested ...
Harry Julian's user avatar
0 votes
1 answer
151 views

Is it possible to run Spiking Neural Network (SNN) on the current von neumann architecture?

I am a new to Spiking Neural network (SNN). I read a couple of papers about it. Some of them highlighted that SNN is a kind of a hardware-dependent model that can efficiently work on neuromorphic ...
Amhs_11's user avatar
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1 answer
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What is 'Soft' normalization ? (not softmax)

While reading the neuroscience paper "Neural population dynamics during reaching" by Churchland et al. 2012, Nature, the authors mention using 'soft' normalization of their (biological) ...
pikabou's user avatar
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2 votes
2 answers
873 views

What is a "filter" and what does "filtering" mean in statistics/engineering/computer science?

I see the term "filter" in many neuroscience papers including those with heavy statistical content ("spatial filter", "temporal filter", etc.), as well as those with ...
Sia's user avatar
  • 139
2 votes
1 answer
902 views

Square root transformation of Poisson process. How $\small Var[\sqrt{P(\lambda)}] \approx \frac{1}{4}$

I am working on Kaggle Neural data challenge. I am trying to understand the transformation applied on the neural spiking data. A number of spikes given a stimulus are Poisson distributed as $$Y_i \...
Saranraj Nambusubramaniyan's user avatar
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0 answers
25 views

Generalised linear mixed effect model(gamer)

I have total of 230 subjects where each subject has 82 volume data of 82 brain region. Not all but many subjects have gone time point 1, time point 2 and time point 3 scans. So, this leads to total of ...
NepNeuro's user avatar
1 vote
0 answers
13 views

Fluctuations in the HH Model

The Hodgkin Huxley Model describes the voltage that flows through a membrane of a nerve cell - this voltage is subject to arbitrary fluctuations that result from the stochastic closing and opening of ...
Calculator123's user avatar
1 vote
0 answers
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Regression on unevenly distributed high dimensional dataset

I have a very high dimensional (20K+ hand engineered features) biological dataset to predict a single continuous output variable (such as a mental state exam scores for a dementia patient). The output ...
user254813's user avatar
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177 views

How to perform machine learning on data with many trials on individual subjects

I have an EEG dataset. The data are epoched around an event of interest and are of the form channels x timepoints x trials. There are many of these types of datasets for several subjects. Because ...
statHacker's user avatar
2 votes
1 answer
69 views

Updating Prediction Errors in Gradient Ascent (Friston's Free-energy)

Background In Rafal Bogacz's tutorial on the free-energy framework for modelling perception and learning, section 2.3 we have: $$\dot{\phi} = \frac{\partial F}{\partial\phi} = \varepsilon_u g'(\phi) ...
Izhaki's user avatar
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1 vote
0 answers
132 views

Feedback Neural Network

I'm looking for a Neural Network has feedback weights. Feedback weights are connections between neurons from a layer to a previous layer. For instance: from the output layer to the input layer. I did ...
Dea Ead's user avatar
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1 answer
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How to find difference between data recorded for 1431 variables for X subjects, across 3 time points?

I am doing research using magnetoencephalography (MEG). I'm performing coherence analysis which, briefly, is a measure of neuronal synchronicity and functional connectivity. For each subject scanned ...
Abdullah Alshammaa's user avatar
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0 answers
26 views

How to test whether event A affects the frequency at which event B occurs

I conducted an experiment in which I measured the occurrence of some event A over time. I then intervened in the system, periodically introducing event B. I hypothesise that event B affects the ...
Ruairi O'Sullivan's user avatar
66 votes
12 answers
19k views

Why do neural networks need so many training examples to perform?

A human child at age 2 needs around 5 instances of a car to be able to identify it with reasonable accuracy regardless of color, make, etc. When my son was 2, he was able to identify trams and trains, ...
Marcin's user avatar
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0 answers
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biological basis for excluding values outside 3 standard deviations from the mean? [duplicate]

Is there any biological basis for excluding outliers in a dataset of blood cytokine levels (e.g. values outside 3 standard deviations from the mean for each cytokine) as measured by multiplex ...
Paul's user avatar
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0 votes
1 answer
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For EEG analysis, why is it more efficient to use the raw data than images of the data?

Data Science publications for EEG analysis like EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces use the raw EEG data (see: github vlawhern/arl-eegmodels ) rather than ...
user7468395's user avatar
0 votes
2 answers
234 views

Bonferroni correction and discussion of the results

In a study in which I analyze several biomarkers through logistic and linear regressions, should I discuss in the discussion of the paper the results with p <0.05 (they only have a nominal ...
Paul's user avatar
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1 vote
0 answers
54 views

Statistic analysis on dependent and simultaneously independent data

Let's assume that I have a datasheet looking like that: ...
Mary's user avatar
  • 21
49 votes
4 answers
7k views

Does correlation = 0.2 mean that there is an association "in only 1 in 5 people"?

In The Idiot Brain: A Neuroscientist Explains What Your Head is Really Up To, Dean Burnett wrote The correlation between height and intelligence is usually cited as being about $0.2$, meaning ...
Sitak's user avatar
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1 vote
1 answer
46 views

Couldn't ANN's be modeled on any part of the body (not just the brain)?

It's commonly said that ANN's are modeled after the brain, but as we know, neurons are also found elsewhere in the human body. So if someone was being provocative and said that ANN's could equally ...
COOLBEANS's user avatar
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3 votes
1 answer
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How to reverse factor analysis (FA) and reconstruct original variables?

I saw this interesting topic: How to reverse PCA and reconstruct original variables from several principal components? and a nice answer with a very useful example of Iris data in Matlab. I would like ...
floUDC's user avatar
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1 answer
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How to determine needed amount of random samples of whole population?

I wrote an algorithm that categorizes a large set of electrophysiological data, way more than I could go through per hand (think over 10.000 cells). I want to take randomly drawn sample cells out of ...
Olaf Bunk's user avatar
2 votes
0 answers
194 views

Finding time intervals where two groups of time series are significantly different

I have two sets of time series, let's call them $C$ and $D$. Assume that $C$ ($D$) has $n$ ($m$) samples (each sample is a time-series of length $T$). I want to assess if there are periods of time ...
gota's user avatar
  • 143
1 vote
1 answer
107 views

Cross-fertilization of neural network/machine learning theory and R&D in physiology

Clearly, the development of neural networks has been based, at least initially, on those occurring in actual animals, human or otherwise. Conversely, how have neural-network or machine-learning models/...
Tom Copeland's user avatar
1 vote
1 answer
2k views

Comparing results of unsupervised clustering to a known classification

Disclaimer: I'm looking for a bit of help as I'm only a simple neuroscientist and even working out what to google in this area is a tricky prospect. Here goes: I have a set of data (3d positions in ...
secondlevel's user avatar
8 votes
1 answer
196 views

Meaning of low power in neuroscience after combining results of many meta-analyses (Button et al 2013)

In a 2013 review article in Nature Neuroscience, Button et al. Power failure: why small sample size undermines the reliability of neuroscience, it was stated that: the average statistical power of ...
arkiaamu's user avatar
  • 765
3 votes
0 answers
201 views

May outliers represent significant values?

Each element of a 56x1 vector represents the functional association between two brain networks. I want to assess which of these 56 values are significant. One way to deal with this is to use an ...
smndpln's user avatar
  • 472
6 votes
2 answers
908 views

To what extent are convolutional neural networks inspired by biology?

I have read in several places that convolutional neural networks were biologically inspired. In what ways do CNNs mirror biology, and in what ways don't they? Is there a more biologically plausible ...
Ari Herman's user avatar
0 votes
1 answer
72 views

How predict time series B given A; predict time series transform?

Assume a unidirectional circuit that transforms information. If one records the activity from the middle and end of the circuit they will end up with two times series. My goal is to predict the ...
K. W. Cooper's user avatar
1 vote
1 answer
66 views

Machine Learning application to neuroscientific data

I have the following question, and it is (for me) an open research question. I really don't have a feeling if it is a difficult question or a trivial one, getting a better feeling for approaches I ...
Pugl's user avatar
  • 1,511
1 vote
1 answer
236 views

What is a d-prime experiment

I am reading about Roc curves and have encountered the term ""D-prime experiment" does anyone know what it is?
user135172's user avatar
5 votes
1 answer
376 views

Linear model: only the whole model significant?

This is the result of a linear model (MatLab, LinearModel.fit): ...
smndpln's user avatar
  • 472
4 votes
1 answer
2k views

Correlation with repeated measures

For each of my 20 subjects, I have: physiological parameter: brain activity (y1) at time T1; physiological parameter: brain activity (y2) at time T2; behavioral parameter: reaction time (X); I want ...
smndpln's user avatar
  • 472
10 votes
3 answers
2k views

Bootstrap to test differences between correlation coefficients

I have two correlation coefficients ($r_1$ and $r_2$), obtained within the same sample (20 subjects). My aim is to test it they are significantly different. $r_1$ is the correlation between a ...
smndpln's user avatar
  • 472
3 votes
1 answer
234 views

Approximating Bernoulli distributions as Poisson distributions in analysis of neural data

I'm reading Analysis of Neural Data, by Kass et al (2014), where Kass argues that spike trains can be viewed as point processes (in chapter 19). Furthermore, he goes on to convert spike trains (that ...
harisf's user avatar
  • 259
1 vote
1 answer
299 views

Tests for comparing correlation values. The winner is?

The question is relatively simple, but trivial. I have data divided by one fixed effect (Emotion, with 2 conditions: A and B), and I have a covariate, for each of my 20 subjects. My aim is to 1) ...
smndpln's user avatar
  • 472
3 votes
0 answers
566 views

Is Fisher's z transformation necessary when comparing the variances of correlation coefficients?

I am working on functional connectivity between brain regions, where functional connectivity is represented by the Pearson correlation coefficient between the time series (fMRI) of brain regions. I am ...
Samira's user avatar
  • 31
0 votes
0 answers
103 views

Classifying spikes as excitatory or inhibitory based on their shape

I have two classes of spike, namely, excitatory spikes and inhibitory spikes. In the figure you can see their shapes. I want to classify my spikes based on these two shapes. The shape in the figure ...
Mina's user avatar
  • 169
4 votes
1 answer
96 views

Reliability of single case reports vs group inference

In his paper "Ten ironic rules for non-statistical reviewers", Karl Friston includes the following tongue-in-cheek response of a fictional author to a reviewer who complains about the sample size ...
z8080's user avatar
  • 2,382
1 vote
0 answers
181 views

Neuroimaging in SPM & GIFT - Regressor Convolution and fitting a GLM to ICA data

I have two kind of disparate questions. I am attempting to replicate the following paper: http://www.sciencedirect.com/science/article/pii/S1053811916300428 I am using SPM to perform preprocessing ...
chainhomelow's user avatar