How to detect Human Brain Activity using external devices?
The human brain is a complex organ, responsible for our thoughts, feelings, and actions. To understand how the brain works is one of the major challenges and goals of neuroscience, psychology, and medicine. Studying the brain is not easy, as it is hidden inside the skull and constantly changing.
How can we measure what is going on inside the brain, without opening it up or interfering with its function? In this blog post, we will explore three different methods that can detect human brain activity from the external devices: EEG, fMRI, and MEG. We will explain how these method works, what are its advantages and limitations, and what are some of the applications and findings that they have enabled.
Human Brain Activity – How it works
Human brain activity(s) are the result of electrical signals transmitted between the neurons in the brain. Neurons are specialized cells that can generate and receive electrical impulses. These impulses are triggered by chemical signals from other neurons or stimuli from the environment.
The electrical impulses travel along the neuron’s axon, a long extension that connects to other neurons through junctions called synapses. At the synapse, the electrical signal is converted into a chemical signal that can cross the gap between neurons and stimulate the next neuron. This process of electrical and chemical signaling enables the brain to perform various functions, such as perception, cognition, emotion, and action.
Brain Computing Interfaces (BCIs)
A Brain Computing Interfaces (BCIs) is a device that lets the human brain communicate with and control external software or hardware, such as a computer or robotic limb.
A BCI consists of three main components: a signal acquisition system, a signal processing system, and a signal output system.
The Signal Acquisition System records the brain activity using electrodes, which can be implanted inside the brain (invasive), placed on the surface of the brain (partially invasive), or attached to the scalp (non-invasive).
The Signal Processing System analyzes the brain signals and extracts the relevant features, such as the frequency, amplitude, or phase. The signal output system translates the features into commands or feedback, such as moving a cursor, typing a word, or stimulating the brain.
Electrical Activity of the Brain
To measure the electrical activity of the brain, scientists use different methods, such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). These methods are capable of revealing the patterns and locations of brain activity associated with different tasks, states, or disorders.
The electrical signals of the brain are not constant, but vary in frequency, amplitude, and phase. These variations reflect the different modes of information processing and communication in the brain. For example, low-frequency signals (such as delta and theta waves) are associated with sleep and relaxation, while high-frequency signals (such as gamma waves) are associated with attention and learning.
EEG – Measuring Electrical Activity with Electrodes
EEG stands for Electroencephalogram, which is a test that measures the electrical activity of your brain by using electrodes attached to your scalp, where it detects the changes in electric fields generated by the brain. This can help in detecting potential problems with brain cell communication, such as seizures, head injury, encephalitis, or stroke.
EEG can also monitor brain states over longer periods, such as engagement, motivation, or drowsiness. EEG has a very high temporal resolution, meaning that it can capture brain processes that occur very fast, such as the response to a visual or auditory stimulus. However, EEG also has a low spatial resolution, meaning that it cannot pinpoint the exact location of the brain activity, especially for deeper brain regions.
EEG is relatively cheap and easy to use, compared to other methods. It can be used in various settings, such as laboratories, clinics, or even at home. However, EEG also has some drawbacks, such as the susceptibility to noise and artifacts from muscle movements, eye blinks, or electrical devices.
fMRI – Measuring Blood Flow with Magnetic Fields
fMRI stands for Functional Magnetic Resonance Imaging, which is a type of MRI scan that can show which areas of your brain are most active by measuring changes in blood flow. It is mainly used for planning brain surgery and other procedures that might affect your brain function.
fMRI is another widely used method to measure brain activity. It uses a strong magnetic field to create images of the brain, based on the changes in blood flow associated with neural activity. The assumption is that when neurons are active, they need more oxygen, which is delivered by the blood.
fMRI has a very high spatial resolution, meaning that it can show the detailed structure and function of the brain, including the deep brain regions. However, it has a low temporal resolution, meaning that it cannot capture the fast changes in brain activity.
fMRI is particularly useful for studying the brain networks and regions involved in various cognitive processes, such as memory, language, or emotion. However, fMRI also has some limitations, such as the high cost and complexity of the equipment, the requirement for the participants to lie still in a noisy and confined space, and the low temporal resolution, meaning that it cannot capture the fast changes in brain activity.
MEG – Measuring Magnetic Fields with Sensor
MEG stands for magnetoencephalography, which is a method to measure brain activity by detecting the magnetic fields produced by the electrical currents in the brain. It uses sensors that are very sensitive to magnetic fields, called magnetometers, which are placed around the head of the person being studied.
MEG can show both the location and the timing of brain activity, with high accuracy and speed. It can be used to study various brain functions, such as perception, cognition, language, and motor control. However, MEG is also expensive, rare, and sensitive to external magnetic sources, which can interfere with the measurements.
MEG has both high temporal and spatial resolution, meaning that it can capture the fast and precise changes in brain activity. MEG also has some challenges, such as the high cost and rarity of the equipment, the sensitivity to external magnetic sources, and the difficulty of combining it with other methods, such as EEG or fMRI.
External devices can be used to detect human brain activity by measuring different physical properties, such as electric fields, blood flow, and magnetic fields. Human brain activity is the result of electrical signals transmitted between the neurons in the brain. These signals can be measured by various methods, such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG).
By using these methods, scientists can gain insights into the structure and function of the human brain, as well as the mechanisms and processes underlying various mental phenomena. However, there is still much to learn and improve, as the brain is a complex and dynamic system that is constantly changing and adapting. Therefore, future research should aim to combine and integrate different methods, as well as develop new and innovative ways to measure and understand human brain activity.