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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....


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Short answer The peak polarity of an EEG is arbitrary. Background Positive and negative in an EEG measure is arbitrary. If you measure the EEG between two electrodes and you flip the wires, the polarity of the signal will reverse too. Only when standard EEG montages are used, in which the active and reference electrodes are strictly defined, then signal ...


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Biological signals are analogues and hence continuous. Early EEG systems simply recorded the analogue signals and displayed it as a continuous signal graphically as wiggly lines written by little pens on a roll of paper (Fig. 1). Only after analogue-to-digital converters became available, could EEG signals and the likes be digitally sampled. Fig. 1. ...


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Your recording necessarily has noise. That's a property of any physical apparatus, and you are recording the activity of noisy neurons. The other property of noise is that, by definition, it will average out. So don't do anything about that. 100Hz is quite a low frequency. Artifacts (e.g. blinks, but I doubt you would have that in sleeping subjects) would ...


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Short practical answer for a signal to be properly sampled, it has to be done [at] the Nyquist sampling rate Up front: sampling at the Nyquist frequency is the bare minimum rate to reproduce the frequency of the input signal. Dependent on your demands, I would advise to go at least 2 times that, if not more, to reproduce amplitude and shape of the signal....


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How you analyse your data depends a bit on how you did your time-frequency decomposition. If you're using a fast Fourier transform, you will likely cut out the temporal window of interest prior to analysis, and your power estimate will be a single value (per subject and/or condition) within this time window. For example, alpha wave desynchronisation is ...


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TL;DR: We don't know whether the brain really uses predictive coding or not. But neurally computing an error signal on a small scale is possible (see below). Predictive coding is an hypothesis for a putative signal-processing mechanism used in vertebrate brains. As things stand presently (2017), mapping the hypothesis of predictive coding onto known neural ...


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I provided an answer to a similar question here that limitedly deals with the role of biological prediction errors. Here's an excerpt of that answer: ...to answer this properly, we must first make it clear that there are potentially dozens, hundreds, or an arbitrarily high number of other "prediction error types" in use by the brain. Here are just a few ...


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According to a review by Croft & Barry (2000), a number of possible methods exist to prevent, or reject ocular artifacts in the EEG; Prevention/reduction of artifact instances Recording with eyes closed - A very effective method, but eye closure alters the EEG, e.g., it increases alpha band activity; Let subjects fixate on a target - Method reduces ...


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Decidels are ratios in log scale. Usually the ratio of powers (in the physical sense). Powers sum up, but not dB. For example, a sound source at 70dB SPL means its power is approximately 3200 times higher than the reference sound source of dB SPL. If you have 2 sound sources both at 70dB, their power add up but their total sound pressure is going to be only ...


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The MRI signal is a small electrical current induced in the receiver coil by the precession of magnetization during resonance, i.e., a manifestation of Faraday's Law of Induction, wherein a changing magnetic field induces a voltage in a nearby conductor. The BOLD response often used in fMRI measures the hemodynamic response, i.e., the relative levels of ...


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The EEG signature of eye blinks is typically visible for about 200ms of data. When you want to move a window of 50 to 200 samples, I assume that your sampling frequency is 1000Hz (you should specify this in your next question). A classical feature for eye blink detection is the peak-to-peak amplitude, which is the absolute difference of the maximum ...


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Depending on whom you ask, you get both answers. That's mostly dependent on the denoising algorithm. If you're using an adaption of GST, you are segmenting first with an n-1 overlap. If you're using S3P I'd recommend not segmenting, since (in my experience) there is a slight difference, with unsegmented data having slightly closer results to Fernandez and ...


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For the unipolar configuration, why can't we just use Earth ground as our reference instead of having a reference electrode or performing an average of measurements on all the electrodes? The ground has a different function than the reference. The reference is the electrode that the voltage is recorded against; a voltage is a potential difference so you ...


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Here is the 10 KHz signal (the maximum frequency of the signal is 10 KHz): Now, if we sample the signal at 5 KHz and 10 KHz, the signal will look like as shown below (the brown points): It is clear that we can't get any useful information from the sampled signal. Now, to get some information about the signal, Nyquist said that we must sample the signal ...


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To add to the answer provided by @AliceD, pure digital waveforms are square waveforms as they represent steps between 1s and 0s and are therefore not continuous. Analogue waveforms are not. They are smooth continuous waves and can represent many voltage points at each millisecond, microsecond or nanosecond between the peaks and troughs. Outputs from ADCs (...


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You already seem to be making the difference between a point of focus, versus "things in the back of ones mind". I think that's quite apt. Different authors have come up with different theories about this subject. I think it's a difficult question but I'll just give my hunch, supported by a (very) few papers that supports that view. Note, that there's a ...


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Short answer As far as I can see - no you can't. Background In EEG systems, unipolar signals are measurements against a distant reference electrode, for example Fpz (Fig. 1). So suppose I have recorded unipolar EEG signals, say O1 and O2 against Fps, then I can obtain a bipolar measurement offline by subtracting O1-O2 (source: Biopac). However, if you ...


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Thank you for your interesting question! Generally, there are three types of methods to process your EEG time-series data: Time domain methods (e.g., regression, statistical analysis on your EEG time-series data, etc.) Frequency domain methods (e.g., Fourier Transform) Time-frequency domain methods (e.g., Short-Time Fourier Transform, Wavelet Transform, ...


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"High-density EEG" refers to the number of electrodes in the array. Typically, any EEG rig with more than 64 electrodes is considered to be high-density electroencephalography.


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ASSR analysis is based on the fact that the electrophysiological responses are time locked with the stimulus repetition rate. There is not one possible method of analysis. Generally spoken, ASSR analysis occurs in the spectral domain, and specifically the frequency of the stimulus repetition rate is analyzed, as well as its harmonics. For example, if the ...


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