Oscillatory Activity
Oscillatory Activity - Related Videos
07:28
Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity
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Cited by 8 •
2017
Psychophysical methods such as the QUEST estimation procedure can efficiently yield robust estimates of the stimulation intensity at which nonpainful sensations transition into painful sensations. By stimulating repeatedly at the threshold intensity, the variability in rating responses can directly be attributed to perceptual classifications in subsequent analyses.
11:26
Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
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Cited by 7 •
2014
Cerebral perfusion is maintained across a range of pressures via cerebral autoregulation. However, characterizing autoregulation requires prominent pressure fluctuations at regulated frequencies. The described protocol will show how oscillatory lower body negative pressure can generate pressure fluctuations to provide data for projection pursuit regression for quantification of the autoregulatory curve.
07:56
Preparation of Liquid Crystal Networks for Macroscopic Oscillatory Motion Induced by Light
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Cited by 11 •
2017
The goal of the protocol is to create liquid crystalline polymer films that can mechanically oscillate under continuous light irradiation. We describe in great detail the conception of free-standing films, from the liquid crystal alignment method to the photo-actuation. The experimental protocol applied to prepare this material is broadly applicable.
06:07
Studying Large Amplitude Oscillatory Shear Response of Soft Materials
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Cited by 14 •
2019
We present a detailed protocol outlining how to perform nonlinear oscillatory shear rheology on soft materials, and how to run the SPP-LAOS analysis to understand the responses as a sequence of physical processes.
08:32
Assembly and Characterization of an External Driver for the Generation of Sub-Kilohertz Oscillatory Flow in Microchannels
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2022
The protocol demonstrates a convenient method to produce harmonic oscillatory flow from 10-1000 Hz in microchannels. This is performed by interfacing a computer-controlled speaker diaphragm to the microchannel in a modular manner.
FAQs
Oscillatory activity emerges when three influences interact: intrinsic membrane properties of neurons, synaptic excitation and inhibition, and recurrent connections within a network. Membrane properties shape how individual neurons respond over time, while excitatory and inhibitory inputs regulate network fluctuations. Recurrent communication can coordinate those responses, allowing rhythmic patterns to appear across connected neurons and brain regions.
Frequency bands organize oscillatory activity by the rate at which fluctuations occur. Theta, alpha, beta, and gamma are characteristic bands that give researchers a way to describe and compare rhythmic activity. Examining these bands can support studies of sleep, sensory processing, attention, learning, and communication between brain regions.
Timing and strength capture different features of a rhythm. Timing concerns when fluctuations occur relative to one another or across activity being compared, while strength describes how pronounced the measured pattern is. Considering both helps researchers characterize changes more precisely and assess whether altered activity may provide insight into neurological disorders.
EEG and local field potentials provide ways to measure neural rhythms. By examining signals from these methods, researchers can characterize oscillatory activity through its frequency, timing, and strength. They can then relate those measurements to sleep, sensory processing, attention, learning, and communication between brain regions.
It can help researchers examine how rhythmic neural patterns relate to sleep, sensory processing, attention, learning, and communication between brain regions. These applications connect cellular and network mechanisms with broader experimental questions about how neural systems coordinate their activity. Comparing rhythms across these settings can reveal which aspects of brain function vary with context.
Changes in timing or strength can provide measurable features for examining altered neural dynamics in neurological disorders. Investigators can compare these features across conditions to ask whether activity differs between patterns. The same observations may also help guide experimental interventions, linking measurement of brain rhythms with attempts to modify neural function.