Brain-­Computer Interfacing: An Introduction - Rajesh P. N. Rao  ## Metadata - Author: **Rajesh P. N. Rao** - Full Title: Brain-­Computer Interfacing: An Introduction - Category: #articles - URL: https://readwise.io/reader/document_raw_content/72559370 ## Highlights - For example, eye movements, eye blinks, eye- brow movements, talking, chewing, and head movements can all cause large artifacts in the EEG signal. ([View Highlight](https://read.readwise.io/read/01h62wx47r76g0s459jagg3kjs)) - Alpha waves (or the alpha rhythm) are electrical fluctuations in the range 8–13 Hz and can be measured in EEG from the occipital region in awake persons when they are relaxed or their eyes are closed. A particular kind of alpha wave popular in BCI applications is known as the mu rhythm (8–12 Hz). It is found over sensorimotor areas in the absence of movement and is decreased or abolished when the subject performs a movement or imagines performing a movement. ([View Highlight](https://read.readwise.io/read/01h62x5czt5mjry0242rea2rqn)) - Beta waves (13–30 Hz) are detectable over the parietal and frontal lobes in a per- son who is alert and actively concentrating. ([View Highlight](https://read.readwise.io/read/01h62xcqqara93aa8rmq102amq)) - Delta waves have the frequency range of 0.5–4 Hz and are detectable in babies and during slow wave sleep in adults. ([View Highlight](https://read.readwise.io/read/01h62xczfynm7nsmw38dhdnvdn)) - Theta waves, with a frequency range of 4–8 Hz, are associated with drowsiness or “idling” in children and adults. ([View Highlight](https://read.readwise.io/read/01h62xdz6r5hs2rkv827w3qwtm)) - Gamma waves, in the frequency range 30–100 Hz or more, have been reported in tasks involving short-­term memory and multisensory inte- gration. ([View Highlight](https://read.readwise.io/read/01h62xe94mp28zsavr1ma4vmrn)) - High gamma activity (70 Hz and above) has also been recently reported for motor tasks and used in ECoG BCIs ( ([View Highlight](https://read.readwise.io/read/01h62xef45p0cyfn5yqg55gxcn)) - Magnetoencephalography (MEG) measures the magnetic fields produced by elec- trical activity in the brain using superconducting quantum interference devices ([View Highlight](https://read.readwise.io/read/01h62xgwfnfszyz2xdqskfctg4)) - MEG systems are con- siderably more expensive than EEG systems, bulky and not portable, and require a magnetically shielded room to prevent interference from external magnetic signals, including the earth’s own magnetic field. ([View Highlight](https://read.readwise.io/read/01h62xhq48dfa6ffg0dwwcs1r8)) - Functional magnetic resonance imaging (fMRI) indirectly measures neural activity in the brain by detecting changes in blood flow due to increased activation of neurons in particular brain areas during specific tasks. When neurons become active, they consume more oxygen, which is brought to the brain by the blood. Neural activity triggers a dilation of local capillaries, result- ing in an increased inflow of highly oxygenated blood that replaces oxygen-­depleted blood. ([View Highlight](https://read.readwise.io/read/01h62xnkkwzymxawwhxsq7nsdg)) - A major advantage of fMRI is that its spatial resolution, typically in the 1–3 mm range, is much higher than other noninvasive techniques such as EEG and MEG. However, its temporal resolution is poor. ([View Highlight](https://read.readwise.io/read/01h62xmmr9q1qrb6zvnxenxccs)) - Functional near infrared (fNIR) imaging (Figure 3.9B) is an optical technique for measuring changes in blood oxygenation level caused by increased neural activity in the brain. This type of imaging is based on detecting near-­infrared light absorbance of hemoglobin in the blood with and without oxygen. It thus provides an indirect window into ongoing brain activity in a manner similar to fMRI (see previous sec- tion). It is less cumbersome than fMRI, although it is more prone to noise and offers less spatial resolution. ([View Highlight](https://read.readwise.io/read/01h62xq7yb3m5ny7chrm796ws4)) - PET measures emissions from radioactively labeled, metabolically active chemicals that have been injected into the bloodstream for transportation to the brain. The labeled compound is called a radiotracer. Sensors in the PET scanner detect the radioactive compound as they make their way to various areas of the brain as a result of metabolic activity caused by brain activity. This infor- mation is used to generate two-­ or three-­dimensional images indicating the amount of brain activity. The most commonly used radiotracer is a labeled form of glucose. ([View Highlight](https://read.readwise.io/read/01h62xrm5pgyp67wbrv57sx7b3)) - extracellular stimulation typically activates a local population of neurons near the electrode rather than a single neuron. ([View Highlight](https://read.readwise.io/read/01h6brepqg8xen040e5fz67yrd)) - A semi-­invasive method for stimulating neurons in the brain is to use electrodes on the surface of the cortex as discussed above for electrocorticography (ECoG). ([View Highlight](https://read.readwise.io/read/01h5yz5fc8824n7zfjnzf2q5yb)) - For noninvasive approaches, there exist a wide range of feature extraction tech- niques based on frequency-­domain, time-­domain, or wavelet analysis, which can be used in conjunction with spatial filtering techniques to reduce dimensionality (PCA), separate sources from mixtures (ICA), or enhance discriminability between output classes (CSP). ([View Highlight](https://read.readwise.io/read/01h5yzsk6sr9ghwyxrz64zzjht)) - As we shall discuss in Chapter 7, some of the most impressive demonstrations of brain-­computer interfacing in animals have relied on using regression techniques to map population motor activity to appropriate control signals for prosthetic devices. ([View Highlight](https://read.readwise.io/read/01h78q3pe7mt25bycx28evfzfs)) - Similar to imagining movements, one can also ask a human subject to perform a cognitive task such as mental arithmetic or visualizing a face. If the cognitive tasks are sufficiently distinct, the brain areas that are activated will also be different, and the resulting brain activation, measured for example using EEG, can be discriminated using a classifier trained on an initial data set collected from the subject. Each cognitive task is mapped to one control signal (e.g., performing mental arithmetic is mapped to moving the cursor up, etc.). The approach thus relies strongly on being able to reliably discriminate the activity patterns for different cognitive tasks, making the choice of the cognitive tasks an important and tricky experimental design decision. ([View Highlight](https://read.readwise.io/read/01h78q8z9eqvqq3hsm5xb6spge)) - the P300 (or P3) signal observed in EEG recordings, so named because it is a positive deflection in the EEG signal that occurs approximately 300 milliseconds after a stimulus. The P300 is an example of an “event-­related potential” (ERP) or “evoked potential” (EP) – it is evoked by the occurrence of a rare or unpredictable stimulus such as a flashing bar at a location being attended to by the subject. It is generally observed most strongly over the parietal lobe, although some components also originate in the temporal and frontal lobes. ([View Highlight](https://read.readwise.io/read/01h7fkhkcam9qd865tqhnd1knw)) - The N100 (or N1) is a negative going potential that occurs approximately 100 ms after an unpredictable stimulus and is typically distributed over the frontal and central regions of the head. It is usually followed by a positive wave (known as the P200), resulting in the “N100-­P200 complex.” The N100 occurs for example in response to a sudden, loud noise, but not if the sound is created by the subject. ([View Highlight](https://read.readwise.io/read/01h7fkyvx26mry1s1cq4reyqhf))