We describe a protocol to monitor changes in the afferent neuron activity during motor commands in a model vertebrate hair cell system.
Sensory systems gather cues essential for directing behavior, but animals must decipher what information is biologically relevant. Locomotion generates reafferent cues that animals must disentangle from relevant sensory cues of the surrounding environment. For example, when a fish swims, flow generated from body undulations is detected by the mechanoreceptive neuromasts, comprising hair cells, that compose the lateral line system. The hair cells then transmit fluid motion information from the sensor to the brain via the sensory afferent neurons. Concurrently, corollary discharge of the motor command is relayed to hair cells to prevent sensory overload. Accounting for the inhibitory effect of predictive motor signals during locomotion is, therefore, critical when evaluating the sensitivity of the lateral line system. We have developed an in vivo electrophysiological approach to simultaneously monitor posterior lateral line afferent neuron and ventral motor root activity in zebrafish larvae (4-7 days post fertilization) that can last for several hours. Extracellular recordings of afferent neurons are achieved using the loose patch clamp technique, which can detect activity from single or multiple neurons. Ventral root recordings are performed through the skin with glass electrodes to detect motor neuron activity. Our experimental protocol provides the potential to monitor endogenous or evoked changes in sensory input across motor behaviors in an intact, behaving vertebrate.
Afferent neurons of mechanosensory systems transmit information from hair cells to the brain during hearing and balance. Electrophysiology can reveal the sensitivity of afferent neurons through direct recordings. While whole cell patching from hair cells can be challenging, recording from downstream afferent neurons is easier and allows assessment of action potentials in response to controlled stimulations1,2,3. Stimulating hair cells lead to their deflection, which modifies mechanosensory structures, thus triggering an increase in action potentials (spikes) in afferent neurons4,5,6. In the absence of external stimuli, afferent neurons also spike spontaneously due to glutamate leak from the hair cells on to afferent post-synaptic terminals7,8, and have been shown to contribute toward maintaining sensitivity9,10. Patch clamp recording of afferent activity enables observation of hair cell sensitivity and signal dynamics that are not possible using techniques with lower temporal resolution, such as in microphonics11,12 or functional calcium imaging13,14,15. The following protocol will allow the recording of afferent activity concurrent with motor commands to reveal instantaneous changes in hair cell sensitivity.
Zebrafish (Danio rerio) use hair cells contained in neuromasts that compose the lateral line system to detect water movement relative to their body, which is translated into neural signals essential for navigation16,17,18, predator avoidance, prey capture19,20, and schooling21. Water flow can also be self-generated by the motions of swimming22,23,24, respiration22,25,26, and feeding27. These behaviors comprise repetitive movements that can fatigue hair cells and impair sensing. Therefore, it is critical that the lateral line system differentiates between external (exafferent) and self-generated (reafferent) flow stimuli. A corollary discharge attenuates self-generated flow signals during locomotion in zebrafish. This inhibitory predictive motor signal is relayed via descending neurons to the sensory receptors to modify the input or interrupt the processing of the reafferent feedback28,29. Seminal work contributing to our early understanding of this feedforward system relied on in vitro preparations where the connectivity and endogenous activity of the neural circuit were not maintained28,30,31,32,33,34,35. This protocol describes an approach to preserving an intact neural circuit where endogenous feedback dynamics are maintained thus enabling better understanding of the corollary discharge in vivo.
The protocol outlined here describes how to monitor posterior lateral line afferent neuron and motor neuron activity simultaneously in larval zebrafish. Characterizing afferent signal dynamics before, during, and after motor commands provides insights into real-time, endogenous feedback from the central nervous system that modulates hair cell sensitivity during locomotion. This protocol outlines what materials will need to be prepared prior to experiments and then describes how to paralyze and prepare zebrafish larvae. The protocol will describe how to establish a stable loose patch recording of afferent neurons and extracellular ventral root (VR) recordings of motor neurons. Representative data that can be obtained using this protocol are presented from an exemplar individual and analysis was performed on multiple replicates of the experimental protocol. Pre-processing of data is performed using custom written scripts in MATLAB. Overall, this in vivo experimental paradigm is poised to provide a better understanding of sensory feedback during locomotion in a model vertebrate hair cell system.
All animal care and experiments were performed in accordance with protocols approved by the University of Florida's Institutional Animal Care and Use Committee.
1. Preparation of materials for electrophysiological recordings
2. Solution preparation
3. Preparation of larvae for electrophysiological recordings
4. Ventral root recording
5. Afferent neuron recording
6. Data acquisition
7. Euthanasia
8. Pre-processing and data-analysis
NOTE: Data pre-processing and analysis will require a basic understanding of command line coding.
After zebrafish larvae are properly immobilized and the posterior lateral line afferent ganglion and VR recording is achieved, activity in both afferent and motor neurons can be measured simultaneously. Recording channels are displayed using gap-free recording protocols (step 1.4) for continuous monitoring of afferent and VR activity. In real-time, decreases in spontaneous afferent spike rate can be observed concurrent with VR activity indicative of fictive swim bouts (Figure 1E). We found that best results and accurate spike detection were products of recordings that achieved a signal-to-noise ratio of at least 0.5. Custom written pre-processing scripts generate plots to assist in visualization of afferent and VR spike detection. Spontaneous afferent spikes are identified using a combination of spike parameters such as threshold, minimum duration (0.01 ms), and minimum inter-spike interval (ISI; 1 ms). Increasing negative pressure while establishing the recording often yields signal detection from multiple afferent units at once. Filtering by amplitude allows for distinguishing between signal dynamics of independent afferents. Isolating signals can be achieved by adjusting the lower-bound and upper-bound detection variables in the pre-processing script (Figure 2A). Aggressive suction to achieve multi-unit recordings can lead to unstable recordings, mechanical noise, degradation of afferent health, and ultimately a loss of signal. Therefore, it is important to slowly dial back suction to atmospheric pressure once the desired signal is achieved. Ventral root spike detection follows identical parameters to afferent spike detection but requires additional inputs to define distinct fictive swim bouts. Bursts within a motor command are defined by VR activity with a minimum of two spikes within 0.1 ms of each other and lasted a minimum of 5 ms. All swim bouts are then delineated by a minimum of three bursts with inter-burst intervals of <200 ms (Figure 2B).
Afferent activity is difficult to interpret when looking at a recording in its entirety. Pre-processing scripts will overlay sections of afferent activity centered on a well-defined period of interest, in this case, the onset of a swim bout (n = 33, Figure 2C) to assist in visualizing trends in signal dynamics. Instantaneous afferent activity is calculated using a moving average filter and a 100 ms sampling window. Mean spontaneous activity shows dramatic changes in response to the onset of motor activity (Figure 2C). To better dissect and analyze afferent activity, periods before and after the swim are set to match the time interval of the corresponding swim bout. In the pre-processing script and representative analyzed results these periods are termed "pre-swim" and "post-swim". Pre-swim, swim, and post-swim spike rates were calculated by taking the number of spikes within the respective period over its duration. The precision of estimates for each individual is partly a function of the number of swims, so we analyzed variable relationships using weighted regressions, with individual weights equal to the square root of the number of swims.
Differences in afferent spike rates across the various periods of interest (pre-swim, swim, and post-swim) were tested by a two-way analysis of variance (ANOVA). Tukey's post-hoc test detected significant differences in spike rates between swimming spike rates and spike rates of both pre-swim (8.94 ± 0.2 Hz, relative decrease 57%) and post-swim (5.34 ± 0.2 Hz, relative decrease 40%) periods. The spike rate did not immediately return to the baseline given we also found that post-swim spike rate was lower than the pre-swim spike rate (Tukey post-hoc tests across groups, p < 0.001; Figure 3A). Linear models were used to detect relationships between relative spike rate and fictive swim parameters. Relative spike rate was calculated by taking the swim spike rate over the pre-swim spike rate. Fictive swim parameters included swim duration, swim frequency (i.e., number of bursts within a swim bout over the duration of the swim bout), and duty cycle (i.e., sum of the swim burst durations over the swim bout total duration). In our hands, the mean and variance of relative spike rate was correlated, so it was necessary for the data to be log transformed for analysis. Afferent spike rate was negatively correlated with swim duration meaning that the lateral line experiences greater inhibition during swims of longer duration (r2 = 0.186, F2,26 = 2.971, p = 0.045; Figure 3B). There was no correlation detected between relative spike rate and neither swim frequency nor duty cycle ((r2 = 0.099, F2,26 = 1.431, p = 0.231, and r2 = 0.047, F2,26 = 0.645, p = 0.932, respectively; Figure 3C,D). All analyses of variable relationships were weighted by the number of swims per individual and all the variables were then averaged by each individual (n = 29).
Figure 1: Simultaneous electrophysiological recording of posterior lateral line afferent neuron and ventral motor root activity. (A). Example of a loose-patch afferent (i) and ventral motor root (ii) recording electrodes. Scale bars represent 50 µm. (B) Larval zebrafish are paralyzed and pinned in four locations (cross symbols) to a Sylgard dish for recording stability. Bold crosses represent insertion points for pins. (C) The electrophysiology rig is mounted on a vibration-isolation table and consists of an upright fixed stage microscope on a motorized controller capable of 40x magnification. Dual current clamp and voltage clamp head stages are mounted on micromanipulators. (D) The myomeres of the body musculature are separated by myosepta that serve as recording landmarks for motor neuron arborizations. The ventral motor root electrode approaches the ventral body (left) and is centered and lowered on top of a myoseptum (arrowhead). Scale bar represents 50 µm. (E) Screen capture of electrophysiological recording in real-time allowing visualization of the spontaneous afferent activity (channel 1) and bursting ventral root activity indicative of fictive swim bout (channel 2). The Record and Play buttons are denoted with red arrows. (F) The posterior lateral line afferent ganglion (dashed line) lies just under the skin and can be identified by a tight cluster of afferent soma. The ganglion can be located by following the lateral line nerve past the cleithrum bone (arrowhead) to where it connects to the ganglion. Scale bar represents 30 µm. Please click here to view a larger version of this figure.
Figure 2: Pre-processing figure outputs visualize accurate spike detection. (A) Extracellular, loose-patch recording of posterior lateral line afferent neurons. Discrete spikes (labeled with red dots) are detected with a minimum inter-spike interval of 1 ms. Baseline noise and activity from other units are filtered out by thresholding to only include spike amplitudes within 50% of the maximum. (B) Ventral motor root recording (VR) of fictive swim bouts reveal voluntary motor commands throughout the duration of the recording. VR spikes (red dots) are detected using a similar threshold filter and then binned into a single swim bout (green) by detecting a burst of activity within 200 ms of one another (see insert; scale bar represents 200 ms). Spikes detected outside the defined swim bout do not occur within the inter-spike interval of stereotyped burst activity and are therefore excluded. (C) Mean spontaneous afferent spike rate centered on the onset of each swim bout (time = 0 s) illustrating spike rate before, during, and after swimming. Error bars represent ± SEM. Please click here to view a larger version of this figure.
Figure 3: Quantification of afferent activity before, during, and after fictive swimming. (A) Afferent spike rate is significantly reduced during swimming and this effect persists even afterwards. Statistically similar groupings are denoted by a and b. (B) Longer swim duration is correlated to decreased afferent spike rate. (C–D) Swim frequency and swim duty cycle show no correlation to afferent spike rate. All values represent mean ± SEM. Outlying individuals with low statistical weight were omitted. Please click here to view a larger version of this figure.
The experimental protocol described provides the potential to monitor endogenous changes in sensory input across motor behaviors in an intact, behaving vertebrate. Specifically, it details an in vivo approach to performing simultaneous extracellular recordings of lateral line afferent neurons and ventral motor roots in larval zebrafish. Spontaneous afferent activity has been previously characterized in zebrafish without consideration of potential concurrent motor activity1,2,39,40,41. Without monitoring the presence of motor activity with ventral root recordings, deciphering afferent activity will likely be underestimated due to the influence of efferent inhibition during, and even after, spontaneous swimming.
In vivo electrophysiological recordings are inherently challenging. In our experience, maintaining a healthy preparation is the single greatest factor to achieving successful, long-lasting recordings for afferent neurons and ventral motor roots. To do this, it is important to not only identify and monitor fast blood flow, but also recognize the texture of the skin and underlying musculature. We recommend observing several paralyzed larvae under a microscope before further handling to become familiar with the intrinsic blood flow and skin state of healthy larvae. A successful ventral root recording through the skin requires a smooth, healthy skin surface in order for the recording electrode to generate a tight seal. This approach circumvents traditional protocols37,42 that are invasive and time-consuming, which call for dissecting away the epithelium to expose the underlying musculature. An inconvenience of recording through the skin is the potential variability in time before signals are realized. Optimizing the magnitude and duration of applied negative pressure will decrease the time required to establish a signal and potentially improve the signal-to-noise ratio. Recordings from a healthy, active preparation should yield spontaneous afferent spike rates between 5-10 Hz with fictive swim bouts occurring every few seconds.
In addition to revealing motor activity state, ventral root recordings can serve as a proxy for monitoring efferent activity that discharges parallel to motor commands to attenuate lateral line activity30,31,32 as well as activity in homologous hair cell systems (e.g., the auditory and vestibular system35,43,44,45). Efferent neurons reside deep in the hindbrain, making electrophysiological recordings of them exceedingly challenging. Zebrafish are a model genetic system, and our electrophysiology protocol can be complemented by transgenic lines to powerfully investigate aspects of corollary discharge, hair cell sensitivity, excitotoxicity, and beyond.
The authors have nothing to disclose.
We gratefully acknowledge support from the National Institute of Health (DC010809), National Science Foundation (IOS1257150, 1856237), and the Whitney Laboratory for Marine Biosciences to J.C.L. We would like to thank past and present members of the Liao Lab for stimulating discussions.
100 mL beaker | PYREX | 1000 | resceptacle for etchant |
10x water immersion objective | Olympus | UMPLFLN10xW | low magnification for positioning larvae and recording electrode |
40x water immersion objective | Olympus | LUMPLFLN40XW | higher magnification for position electrode tip and establishing patch-clamp |
abfload.m | supplemental coding file | custom written MATLAB script for converting raw electrophysiology recordings to .mat files | |
AffVR_preprocess.m | supplemental coding file | custom written MATLAB script for preprocessing recording data | |
BNC coaxial cables | ThorLabs | 2249-C-12 | connecting amplifier and digitizer channels; require 4 |
borosilicate glass capillaries w/ filament | Warner Instruments | G150F-3 | inner diameter: 0.86, outer diameter: 1.50; capillary glass used to form recording electrodes |
burst_detect | supplemental coding file | custom written MATLAB function necessary to run AffVR_preprocess.m | |
computer | N/A | N/A | any computer should work |
DC Power Supply | Tenma | 72-420 | used for electrically etching dissection pins |
electrophysiology digitizer | Axon Instruments, Molecular Devices | Axon DigiData 1440A | enables acquisition of patch-clamp data |
filament | Sutter Instrument Company | FB255B | 2.5 mm box filament used in micropipette puller |
fine forceps | Fine Science Tools | Dumont #5 (0.05 x 0.02 mm) Item No. 11295-10 | used to manipulate larvae and insert pins |
fixed stage DIC microscope | Olympus | BX51WI | microscope used to visualize and establish patch-clamp recordings |
flexible, tapered pipette tip | Fisher Scientific | 02-707-169 | flexible tips enable insertion into recording electrode to dispense extracellular solution at the tip |
FluoroDish | World Precision Instruments Inc. | FD3510-100 | cover glass bottomed dish recording dish |
KimWipe | KimTech | 34155 | task wipe used for wicking away excess fluid from larvae |
Kwik-Gard | World Precision Instruments Inc. | 710172 | self-mixing sylgard elastomer |
MATLAB | MathWorks | R2020b | command line software for preprocessing data |
microelectrode amplifier | Axon Instruments, Molecular Devices | MultiClamp 700B | patch clamp amplifier for dual channel recordings |
microforge | Narishige | MF-830 microforge | to polish recording electrode |
micromanipulator control unit | Siskiyou | MC1000-eR/T | 4-axis dial coordinator for controlling micromanipulator |
micropipette puller | Sutter Instrument Company | Flaming/Brown P-97 | for pulling capillary glass into recording electrodes |
microscope control unit | Siskiyou | MC1000e | positions the microscope around the fixed stage and preparation |
motorized micromanipulator | Siskiyou | MX7600 | positions the headstage and attached recording electrode for patch-clamp recording |
MultiClamp Commander | Molecular Devices | 2.2.2 | downloadable from Axon MultiClamp 700B Commander download page |
optical air table | Newport Corporation | VH3036W-OPT | breadboard isolation table to float microscope and minimize vibrations during recordings |
pCLAMP | Molecular Devices | 10.7.0 | downloadable from Axon pCLAMP 10 Electrophysiology Data Acquisition & Analysis Software Download page |
permanent ink marker | Sharpie | order from amazon.com | for marking the leading edge side of the VR electrode to ensure proper orientation when inserting into pipette holder |
petri-dish | Falcon | 35-3001 | used to immerse larvae in paralytic |
pipette holder | Molecular Devices | 1-HL-U | hold recording electrode and connect to the headstage |
pneumatic transducer | Fluke Biomedical Instruments | DPM1B | for controlling recording electrode internal pressure |
potassium hydroxide | Sigma-Aldrich | 221473-25G | etchant for etching dissection pins |
silicone tubing | Tygon | 14-169-1A | tubing to connect pneumatic transducer to pipette holder |
spike_detect | supplemental coding file | custom written MATLAB function necessary to run AffVR_preprocess.m | |
stereomicroscope | Carl Zeiss | Stemi 2000-C | used to visualize pin tips and during preparation of larvae |
straight edge razor blade | Canopus | order from amazon.com | cuts the tungsten wire while making dissection pins |
swimbout_detect | supplemental coding file | custom written MATLAB function necessary to run AffVR_preprocess.m | |
syringe | Becton Dickinson Compoany | 309602 | filled with extracellular solution to inject into recording electrodes |
transfer pipette | Sigma-Aldrich | Z135003-500EA | single use, non-sterile pipette for transfering larvae |
tricaine methanesulfonate | Syndel | 12854 | pharmaceutical aneasthetic used to euthanize larvae with high dosage. |
tungsten wire | World Precision Instruments Inc. | 715500 | 0.002 inch, 50.8 μm diameter; used to make dissection pins |
vacuum filtration unit | Sigma-Aldrich | SCGVU11RE | single use, sterile, vacuum filtration units used to sterilize extracellular solution used for electrophysiology electrode ringer |
voltage-clamp current-clamp headstage | Molecular Devices | CV-7B | supplied with MultiClamp 700B amplifier used as left and right headstages |
α-bungarotoxin | ThermoFisher | B1601 | for immobilizing the larvae prior to recording |