Brain Activity Monitoring
Brain Activity Monitoring - Related Videos
10:07
Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks
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Cited by 162 •
2015
Monitoring brain activity outside the lab without physical constraints presents methodological challenges. A fiberless, wearable functional Near Infrared Spectroscopy (fNIRS) system was used to measure brain activity during an ecological prospective memory task. It was demonstrated that this system could be used to monitor brain activity during non-lab based experiments.
05:15
Monitoring Seizure-Induced Neural Electrical Activity in Brain Slices Using Microelectrode Arrays
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2025
This protocol involves using a microelectrode array (MEA) to record electrical activity in a brain slice exposed to a seizure-inducing drug. The procedure includes positioning the brain slice in an MEA recording chamber, applying electrical stimulation to induce artificial seizures, and analyzing the resulting signals.
09:30
Measurement of Larval Activity in the Drosophila Activity Monitor
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Cited by 10 •
2015
This report describes a method for measuring Drosophila larval activity using the TriKinetics Drosophila Activity Monitor. The device employs infrared beams to detect movements of up to 16 individual animals. Data can be analyzed to represent motion parameters including rates and the positions of the animals within the assay chambers.
09:55
Monitoring Acupuncture Effects on Human Brain by fMRI
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Cited by 82 •
2010
FMRI and physiological monitoring is used to study the effects of Acupuncture on the central and peripheral nervous systems. Acupuncture mobilizes a limbic-paralimbic-neocortical network, with great overlap with the default mode network, to modulate neurological activity, possibly related to its autonomic effect in the peripheral nervous system.
05:20
Drosophila Activity Monitor (DAM): A Method to Measure Locomotor Activity in Flies
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2023
This video describes the Drosophila activity monitor (DAM) system used to track locomotor activity. Researchers use activity data collected from the DAM to study circadian rhythms in fruit flies. The featured protocol clip shows how to load flies in the device and record activity data for circadian experiments.
FAQs
EEG records voltage fluctuations at the scalp that arise from synchronized neuronal activity. The measured pattern therefore reflects coordinated changes in neural circuit function rather than a direct readout of every individual neuron. Comparing these signals across behavioral or biological conditions can help relate circuit activity to behavior, sleep, learning, or disease.
fMRI tracks blood-oxygen-level-dependent changes associated with local metabolism. This provides a hemodynamic perspective that complements EEG measurements of electrical activity. By examining where these metabolic patterns vary under different conditions, researchers can connect local responses with sensory processing, behavior, learning, sleep, or disease-related changes in brain function.
Electrical and hemodynamic measurements describe different aspects of neural function. EEG reflects voltage fluctuations produced by synchronized activity, whereas fMRI indicates blood-oxygen-level-dependent changes associated with local metabolism. Comparing their activity patterns can provide complementary evidence about how neural circuits function and how those patterns relate to behavior, sensory processing, or disease.
Researchers compare activity patterns across conditions to identify changes associated with a behavior, sensory experience, sleep state, learning process, or disease. The relevant measurement may come from electrical or hemodynamic signals, depending on the method. This comparison-based approach helps link observed brain changes with biological function rather than treating a signal in isolation.
Brain activity monitoring is useful when researchers need to relate neural-circuit function to behavior, sensory processing, sleep, learning, or disease. Measurements collected over time can reveal how activity patterns change across biological conditions. In this way, the methods support investigations of normal brain function as well as disruptions associated with neurological disorders.
Comparing brain activity patterns can reveal disruptions linked to neurological disorders and support the development of diagnostic methods. The same evidence can inform research on treatments and brain-computer interfaces. Its value comes from connecting measurable electrical or metabolic changes with brain function, creating a biological basis for studying disease and developing related applications.