Waveform Recording
Waveform Recording - Related Videos
06:01
Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R
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Cited by 1 •
2022
This article describes the semi-automated measurement of the amplitudes and latencies of the first five peaks and troughs in the auditory brainstem response waveform. An additional routine compiles and annotates the data into a spreadsheet for experimenter analysis. These free computer routines are executed using the open-source statistical package R.
01:07
Effective Value of a Periodic Waveform
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2024
The concept of effective value, the root mean square (RMS) value, is crucial in understanding electrical circuits and power delivery. This idea emerges from the necessity to measure the effectiveness of a voltage or current source in supplying power to a resistive load. The effective value of a periodic current represents the direct current (DC) that conveys the same average power to a resistor as the periodic current itself. This concept is crucial when assessing AC circuits. To determine the...
05:11
High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
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2025
This study improves electromagnetic flowmeter accuracy by optimizing excitation waveforms, applying multi-stage filtering, and using Complex Programmable Logic Device (CPLD)-based rectification. A novel waveform-based empty pipe detection method enhances reliability. Experiments show 0.1% accuracy within 0.1-15 m/s, validating industrial applicability.
10:31
A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
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Cited by 8 •
2017
The article shows how to use the program SpikeSorter to detect and sort spikes in extracellular recordings made with multi-electrode arrays.
08:59
Multichannel Extracellular Recording in Freely Moving Mice
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Cited by 1 •
2023
The protocol describes the methodology of extracellular recording in the motor cortex (MC) to reveal extracellular electrophysiological properties in freely moving conscious mice, as well as the data analysis of local field potentials (LFPs) and spikes, which is useful for evaluating the network neural activity underlying behaviors of interest.
FAQs
Timing indicates when neural events occur, while amplitude describes the size of the measured voltage fluctuation or current. Waveform shape adds information about how the signal changes through time. Examining these features together helps distinguish patterns associated with action potentials, synaptic signaling, oscillations, or sensory responses rather than treating the trace as a single undifferentiated measurement.
The recording configuration determines the scale of activity captured by the electrodes. Depending on that arrangement, a trace may reflect an individual neuron, a brain region, or a population of cells. This distinction is important when interpreting whether a waveform represents a localized cellular event or coordinated activity distributed across multiple neural elements.
These processing stages prepare biological signals for visualization and analysis. Amplification increases the measurable representation of voltage fluctuations or electrical currents, filtering modifies the recorded signal before interpretation, and digital sampling converts it into numerical data. Together, they support quantitative examination of waveform timing, amplitude, and shape while preserving a form suitable for displaying neural activity.
A typical workflow begins with electrodes detecting neural voltage fluctuations or electrical currents. The detected signal is then amplified, filtered, and converted into digital samples. Researchers can display the resulting trace and examine its timing, amplitude, and shape. This sequence links the original biological activity to quantitative measurements used for analyzing neural events and responses.
Waveform recording can be applied to action potentials, synaptic signaling, oscillations, and sensory responses. Researchers interpret the recorded traces by examining how these events differ in timing, amplitude, or shape. The method therefore supports questions about both discrete neural activity and broader patterns of signaling, depending on the recording configuration and the level of neural organization being studied.
Recorded neural traces provide measurements that can be compared with behavioral observations, disease-related questions, or experimental interventions. Changes in waveform timing, amplitude, or shape can serve as quantitative descriptions of altered neural dynamics. In this way, the technique helps investigators relate electrical activity from neurons, regions, or populations to functional outcomes and intervention effects.