Single Unit Spiking
Single Unit Spiking - Related Videos
08:48
Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
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Cited by 1 •
2012
Understanding the function of the vertebrate central nervous system requires recordings from many neurons because cortical function arises on the level of populations of neurons. Here we describe an optical method to record suprathreshold neural activity with single-cell and single-spike resolution, dithered random-access scanning. This method records somatic fluorescence calcium signals from up to 100 neurons with high temporal resolution. A maximum-likelihood algorithm deconvolves the...
11:00
Single-unit In vivo Recordings from the Optic Chiasm of Rat
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Cited by 3 •
2010
Retinal ganglion cells transmit visual information from the eye to the brain with sequences of action potentials. Here, we demonstrate how to record the action potentials of single ganglion cells in vivo from anesthetized rats.
12:32
Retrograde Fluorescent Labeling Allows for Targeted Extracellular Single-unit Recording from Identified Neurons In vivo
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Cited by 14 •
2013
Retrograde transport of fluorescent dye labels a sub-population of neurons based on anatomical projection. Labeled axons can be visually targeted in vivo, permitting extracellular recording from identified axons. This technique facilitates recording when neurons cannot be labeled through genetic manipulation or are difficult to isolate using 'blind' in vivo approaches.
02:19
Triggering a Closed-Loop Stimulation by Neuron Spiking Activity
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2025
This video demonstrates the operation of closed-loop stimulation in a rat with a surgically implanted device to record neural activity. Neuronal signals are first recorded and analyzed. Template waveforms are then uploaded, and parameters are defined to trigger closed-loop stimulation.
08:29
Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo
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Cited by 23 •
2014
An approach is presented for determining structures of viral membrane glycoprotein complexes using a combination of electron cryo-tomography and sub-tomogram averaging with the computational package Jsubtomo.
FAQs
Fine electrodes capture extracellular voltage fluctuations produced near the recording site rather than directly measuring a neuron's internal state. The resulting waveform has characteristic features that can be compared with background activity and signals from neighboring cells. This electrical separation allows analysis to focus on one neuron's firing events within a more complex neural recording.
Spike sorting separates waveform events that may arise from different neurons or from background activity. Signal-processing methods examine the characteristic features of recorded waveforms so that events associated with one neuron can be distinguished from nearby signals. This step is essential for assigning firing patterns and timing to the appropriate cellular source.
Signal processing converts complex extracellular voltage recordings into identifiable spike events by emphasizing waveform characteristics and separating activity from neighboring cells or background signals. The processed data provide a more precise basis for examining when a neuron fires and how its activity changes during an experiment. Without this separation, cellular responses could be difficult to interpret.
Analysis of individual firing events can reveal firing patterns, precise timing, and changes in activity associated with stimuli. Researchers can use these features to examine how neural signals represent information and how neurons participate in circuit function. The value lies not only in detecting activity, but also in relating its temporal organization to experimental conditions.
A basic workflow uses fine electrodes to record extracellular voltage fluctuations, followed by signal processing to identify waveform events. Spike-sorting methods then distinguish the characteristic waveform of one neuron from background activity and neighboring cells. Researchers can analyze the resulting event times and patterns to evaluate neural responses and circuit behavior.
Researchers compare the timing and pattern of detected spikes with the stimuli presented during an experiment. This comparison can show whether a neuron's activity changes in relation to a stimulus and can help characterize the temporal structure of that response. Such measurements support investigations of neural coding and the way circuits process information.
Single-neuron firing patterns provide detailed neural signals that engineers can evaluate as potential inputs for bioelectronic systems. In brain-computer interfaces and neural prostheses, these recordings help assess how neuronal activity can be translated into engineered control signals. They also support system development and evaluation by linking measured neural responses with intended device functions.