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15

There is no better way to describe brain activity than brain waves! :) There are newer ways to analyze and think about brain waves, though. Usually you will find these under literature on neuronal oscillations. Good aspects of thinking about brain activity using brain waves: Brain waves are directly related to neural activity. They are an electric or ...


13

Short answer Brain waves are not electromagnetic waves. Long answer Measured brain activity, as you already mentioned, is the result of individual neurons firing. The activity exists, in fact, of two parts. First of all, there are the action potentials (APs). APs are current flow within a neuron from one end to the other. The magnitude of these APs (and ...


12

This very much depends on what, exactly, you're trying to do. EEG measurements tend to be extremely reliable, but the inferences one may draw on mental state are not necessarily so. EEG-driven BCI overwhelmingly relies on machine learning to correctly classify signals into a finite number of categories and act upon them. Typically, you'll do something ...


12

Yes and no. Source estimation has been utilized in electrical engineering for decades, but is becoming more and more prevalent in the EEG realm, especially in light of efforts to register EEG readings with concurrent fMRI studies. Basically, given a set of EEG (or even MEG, magnetoencephalographic) measurements, can we "invert" them to find the individual ...


12

Antoine Tremblay has just released an advanced analysis toolbox: http://onlinelibrary.wiley.com/doi/10.1111/psyp.12299/abstract It's missing about half the features on your list, although fundamentally, spectral density is a simple task and LORETA is a stand-alone package anyways (although similar approaches, e.g. general CSD estimation, are implemented in ...


12

The OpenEEG project has some information for building your own EEG system. Instructables has a "simple" EEG circuit you can build. Note that this is going to be somewhat costly and time consuming because you are dealing with tiny voltages and high impedances. OpenBCI has some hardware for sale (still expensive but not as bad as research-grade equipment) and ...


11

In short: we know that eye-blinks are reflected frontally in the EEG data and we use that knowledge to identify which components reflect for example eye-blinks. It would not make sense to identify a component related to eye-blinks on the back of the head - there would be something wrong with your data. What ICA does is (data driven) estimate a number of ...


11

The source I have quoted below gives an example of the following stenographic image:- Is this perception a particular trick that my eye performs or is it processing the visual data in an alternative way? Stereograms can be viewed as three-dimensional images by providing two side-by-side views of a three-dimensional scene, rendered from slightly ...


11

Short answer Brainwaves are typically associated with the electroencephalogram, which is a signal mainly composed of potential differences generated in the superficial layers of the brain. Potential differences represent electric fields and do not represent electromagnetic (EM) radiation. EM radiation is build up of packets of energy (photons). EM radiation ...


10

Steven J. Luck's "An Introduction to the Event-Related Potential Technique" is a great beginner's book on EEG. It's basic but not too simple, and it goes into the structure of the signals as well as into issues on experimental design.


9

Programs/packages for EEG analysis There are decent MatLab toolboxes with good tutorials for for the analysis of EEG data. The EEGLAB toolbox (tutorial) can be operated by both GUI and command-line (and script). The fieldtrip toolbox (tutorial) is mainly operated by command line / script. Of course there are also (commercial) software packages for EEG ...


8

A study by D’Zmura et al. (2009) in which two syllables were spoken in imagination showed that imagined speech information was present in EEG alpha, beta and theta bands. The beta band (13-18 Hz) proved most informative. The most informative electrodes were located mainly near the top of the head (vertex) where electromyographic artifacts had least influence....


7

As often in this area, the problem seems to be entirely created by confusions about definitions and terminology and the difficulties resulting from the use of common-sense concepts like “surprise” in scientific theories. One answer would be “Why not?” Basically you seem to object to the definition of surprise used by some theorists but definitions are ...


7

I'm surprised that no one has mentioned spiking activity. The spatial and temporal resolutions are phenomenal. The technology to record action potentials simultaneously from many neurons over many cortical areas is growing. Much of theoretical neuroscience deals with how those patterns of spiking convey information. As with the other answers, I will add ...


7

I use the FieldTrip toolbox in Matlab to analyze my own modified auditory MMN experiment :) But I use MEG, so I don't have that many software options. The toolbox is very powerful but it has a steep learning curve and I would recommend it only if you already have both Matlab and EEG data analysis experience. I don't analyze my data in the classical MMN way ...


7

I've used the Zeo (http://www.myzeo.com/sleep/). It seems to work pretty well. It tracks which stage of sleep you are using a very basic EEG. There are some details on how it operates here: http://radar.oreilly.com/2009/10/how-the-zeo-sleep-device-works.html As I said, I've used it in the past and from what I can tell, it seems to be pretty accurate, ...


7

Do you mean evoked potentials, or event-related potentials, or just straight-up EEG? The general way to distinguish between the two is that EEG will tell you about state (aroused, asleep, etc) where evoked or event-related potentials will tell you about operations (processing sound/language/etc); evoked or event-related potentials also generally require ...


7

The field of study you should focus on is the one for which you have already identified in your paragraph above which is EEG based "brain-computer interface". EEG signals are compared by their "features". Each of the signal you have provided above have different features. These features can be mean, variance, frequency, kurtosis, skewness of each of the ...


7

I'm only going to attempt to answer a small part of your question: how does glial activation affect the blood oxygen level-dependent (BOLD) response measured by fMRI? Schulz et al. (2012) were able to investigate the role of glial signaling on fMRI activity by simultaneously measuring neuronal responses with invasive optical imaging and fMRI. They found ...


7

Based on your comments I interpret your question as: "(1) What is the definition of the signal-to-noise-ratio (SNR) and (2) how do I determine the SNR for event-related potential (ERP) amplitudes in an EEG signal?". (1) Signal-to-noise-ratio (SNR) is a term often encountered in electrophysiology (e.g. EEG) and signal processing and can be loosely defined ...


7

They are ordered based on when they were discovered/named (as pointed about by Ana's comment). Alpha and beta waves were among the first signals observed in EEG data. From Wikipedia: Alpha waves were discovered by German neurologist Hans Berger, most famous for his invention of the EEG. Alpha waves were among the first waves documented by Berger, along ...


7

EEG research all started with Hans Berger, who in 1929 reported that brain activity could be recorded by measuring electrical activity on the scalp. Although the notion of ‘brain waves’ that were found by Berger was controversial, over the years many researchers replicated the results, which led to the acceptance of EEG as a real phenomenon. Neurons Before ...


6

http://sccn.ucsd.edu/eeglab/ http://chronux.org are two libraries with tons of functions for analyzing eeg and emg data


6

Bearing in mind the fact that I can't prove a negative, I'm going to say "No, it's not (yet) possible". Flow is rather loosely defined (e.g. "merging of action and awareness"), so coming up with hard measures is a challenge in and of itself -- even without bringing electrophysiology into the equasion. As a Positive Psychology concept, it belongs to the ...


6

Yes they do. That is to say, light conditions do not generally affect alpha waves, only the eyelids do (and other factors). This has led to alpha waves being interpreted as reflecting an active inhibitory process in the visual cortex (relaxation) rather than a reduction of stimulus (resting). The following image is from an Israeli study published in 2013 ...


6

You should consider using subject-specific alpha channels and frequency ranges. There are differences between individuals in alpha peak frequency. Also the placement of the EEG cap as well as small differences in orientations of cortex can affect which channels pick up perceptual activity. One way to do this would be to record data from the subject with ...


6

If "brain waves" produce a time-varying electric potential as shown on the EEG, then as far as I know electromagnetic waves are present. I was taught that you cannot have a time varying electric potential without creating an electromagnetic wave. You can try browsing wiki explanation https://en.wikipedia.org/wiki/Maxwell%27s_equations, but the main idea is ...


5

We were looking for an EEG device few years ago. The commercial offers were between 20,000 EUR for a 32 passive electrode to 50,000 EUR for an 64/128 active electrode. This included everything except the computers - some offers were without off-line data processing software. I never considered the EEG systems that were not mentioned in the method section of ...


5

Also. Appraisal theory argues that a cognitive mechanism assesses the meaning of a situation before initiating an emotion. It does not argue that this mechanism operates consciously, so demonstrating that it doesn't doesn't impinge on the validity of appraisal theory at all. Mismatch negativity may be part of the process leading to surprise, but noting ...


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