Frequency response properties of primary afferent neurons in the posterior lateral line system of larval zebrafish

Abstract

The ability of fishes to detect water flow with the neuromasts of their lateral line system depends on the physiology of afferent neurons as well as the hydrodynamic environment. Using larval zebrafish (Danio rerio), we measured the basic response properties of primary afferent neurons to mechanical deflections of individual superficial neuromasts. We used two types of stimulation protocols. First, we used sine wave stimulation to characterize the response properties of the afferent neurons. The average frequency-response curve was flat across stimulation frequencies between 0 and 100 Hz, matching the filtering properties of a displacement detector. Spike rate increased asymptotically with frequency, and phase locking was maximal between 10 and 60 Hz. Second, we used pulse train stimulation to analyze the maximum spike rate capabilities. We found that afferent neurons could generate up to 80 spikes/s and could follow a pulse train stimulation rate of up to 40 pulses/s in a reliable and precise manner. Both sine wave and pulse stimulation protocols indicate that an afferent neuron can maintain their evoked activity for longer durations at low stimulation frequencies than at high frequencies. We found one type of afferent neuron based on spontaneous activity patterns and discovered a correlation between the level of spontaneous and evoked activity. Overall, our results establish the baseline response properties of lateral line primary afferent neurons in larval zebrafish, which is a crucial step in understanding how vertebrate mechanoreceptive systems sense and subsequently process information from the environment.

Keywords: afferent neuron; electrophysiology; frequency response; lateral line; pulse stimulus; zebrafish.

Fig. 1.

A: setup to record the response of a posterior lateral line afferent neuron to single neuromast deflections. B: extracellular loose-patch recordings reveal the response characteristics of single afferents to sinusoidal or pulse stimulations applied to individual neuromasts. C: additional pulse stimulations were performed to confirm that the activity patterns of extracellular recordings matched those of intracellular recordings.

Fig. 2.

A: example of spontaneous activity of an afferent neuron (i.e., in the absence of neuromast deflection), as revealed by an extracellular loose patch recording. B: distribution of interspike intervals (ISIs) for the example shown in A shows that the falling part of the distribution follows a single exponential decay rate, which indicates that the pattern of spontaneous firing behaved like a Poisson process. C: ISI return maps, where ISI_n (n is an index) is plotted against the preceding ISI_n−1, shows that spontaneous spiking had no bursting firing patterns or other well-defined temporal structure.

Fig. 3.

Response of afferent neurons to three sinusoidal neuromast stimulation frequencies. For each frequency, the stimulus is shown with an example of an afferent recording, with the peristimulus time histogram above. A raster plot on top is shown for several repeated responses.

Fig. 4.

Response of afferent neurons to sine-wave stimulation across a range of frequencies. A: a log-log plot of response gain (spike rate × vector strength) as a function of stimulus frequency. The dashed line is a linear regression of the data for stimulation frequencies above 10 Hz. Note that the gain values are artificially depressed due to the residual spontaneous activity at stimulation frequencies below 10 Hz (gray region). B: evoked spike rate increases asymptotically as stimulation frequency increases, where the line is a fit of Eq. 1 (see methods). C: the ability to phase lock to the stimulus, as measured by vector strength, is highest at midrange frequencies (solid line). Dashed lines show examples of afferent neurons that display a low-pass filter and a high-pass filter (n = 1). D: a relatively linear increase in vector angle from 10 to 60 Hz (gray region) indicates that a constant time delay exists between the stimulus and the response.

Fig. 5.

Afferent spike rate can decrease over time, depending on the stimulus frequency. A: an example of a typical afferent response illustrating the decrease in spike rate over the course of 7-s-long stimulation. B: linear regressions show that at a low stimulation frequency (2 Hz), a low spike rate is maintained throughout the stimulus duration. At higher stimulation frequencies (30 and 60 Hz), spike rates, which are initially higher in comparison, generally decrease over time. C: the slopes of spike rate change over time, measured from the curves in B, depend critically on stimulation frequency. Spike rate slope shows a decreasing trend within an intermediate range of frequencies (gray region).

Fig. 6.

Response of afferent neurons to pulse stimulation across a range of frequencies. A: a raster plot (left) of the afferent response to low-frequency stimulation (3 pulses/s) is shown for repeated trials, with the stimulus pattern (dots) shown below. An example of an afferent trace (right) illustrates how each stimulus pulse can elicit a spike. Note that nonevoked spikes are also present. B: at 30 pulses/s, afferents generally spike to each stimulus pulse throughout the stimulus duration. C: at 60 pulses/s, spikes also follow pulses with a one-to-one pattern, but only for the initial portion of the stimulus. Spikes start to fail shortly after the initiation of the spike train.

Fig. 7.

Measurements of spike rate and vector strength for afferent responses to pulse stimuli. A: solid line indicates fitted values for Eq. 1, showing that spike rate increases asymptotically with pulse rate. Dashed line represents the 1:1 ratio of spikes to pulses. Values that fall below this line indicate that, for the given pulse rate, each pulse does not elicit a spike response. Thus the intersection between the solid and dashed line sets the maximum pulse rate for which our definition of reliability in maintained (gray arrow). Gray circle represents the maximum spike rate observed. B: vector strength of the response (using the initial spike, see methods) across pulse rates, where the gray circle represents the minimum vector strength observed. All values are means ± SE. Equations are described in the methods.

Fig. 8.

Measurements of change in maximum spike rate and vector strength over the portion of the pulse train stimulation duration. A: an afferent response to pulse stimulation can be characterized by 1) the maximum spike rate (black line), and 2) the maximum pulse rate for which an afferent can generate at least one spike for each pulse (gray line). The inset graph illustrates how the maximum spike rate (black circle) and maximum pulse rate (gray arrow) values were calculated. Both values decrease over time, represented as a percentage portion from the start of the stimulus, where 0% is the start of the stimulus and 100% is the end of the stimulus. B: the minimum vector strength (black line) and maximum pulse rate at which an afferent response is highly synchronized with the pulse train (vs. >0.9, gray line) does not show the consistent pattern of decrease seen in A. The inset graph illustrates how the minimum vector strength (black circle) and maximum pulse rate (gray arrow) values were calculated. The lines connecting the data points are for illustrative purposes.

Fig. 9.

Correlation between spontaneous and evoked afferent activity. A: the best frequency of an afferent neuron (e.g., highest vector strength) in response to sinusoidal stimulation is correlated to its spontaneous spike rate. B: the maximum spike rate of an afferent neuron, as determined by pulse stimulation, increases with spontaneous spike rate. C: the correlation coefficient (r) between spontaneous activity and maximum spike rate (solid line) generally increases with time over the course of the stimulus, while the P value of the correlation (dashed line) decreases such that the relationship is significant only after the first 20% of the stimulus has been applied. D: the correlation (r) between spontaneous activity and reliability (e.g., maximum pulse rate that an afferent could reliably follow, solid line) is only significant between 20 and 80% of the portion of the stimulus (dashed line, P < 0.05). The lines connecting the data points are for illustrative purposes.

Fig. 10.

Comparing the effect of direct stimulation to indirect stimulation on the neuromast. A: indirect neuromast stimulation, in which a sinusoidal motion must be transmitted through the fluid medium before influencing the neuromast, results in a lower evoked spike rate (solid line) compared with direct mechanical stimulation of the neuromast (dashed line). B: vector strength differs during indirect (solid line) vs. direct (dashed line) stimulation. C: when neuromasts are directly stimulated, most afferent neurons exhibited low best frequencies. D: when neuromasts are indirectly stimulated, the same cells shifted to higher best frequencies. E: simultaneous tracking of the stimulation pipette and hair cell bundle of a single neuromast, showing the displacement of hair cell bundle (gray trace) in response to the rostrocaudal (r-c) displacement of the stimulation pipette (black trace) at three frequencies. F: the deflection amplitude of the hair cell bundle increases with stimulation frequency (P < 0.05, Wilcoxon rank-sum test).